Metacognition supports HIP undergraduate research

by Dr. John Draeger, SUNY Buffalo State

The Association of American Colleges and Universities (AAC&U) has identified a number of high-impact learning practices (e.g., undergraduate research, collaborative assignments, learning communities, service learning, study abroad, capstone seminars). Each of these learning practices involve a significant investment of student effort over time with multiple interactions between faculty and students about substantive matters as well as frequent,constructive feedback from faculty, and regular, structured processes for reflection and integration (Kuh 2008; Kilgo, Sheets & Pascarella 2015). This post offers some strategies for intentionally structuring undergraduate research experiences and building metacognition into the process. Subsequent posts will consider other high-impact practices (HIPs).

 Undergraduate research is a HIP because students ask the questions and set the research agenda. Inquiry-based projects, such as undergraduate research, promote student autonomy, self-direction, and teach students about the process (Healey & Jenkins 2009; Kilgo & Pascarella 2016). Without guidance, however, students can find themselves in a hot mess. After years of mentoring undergraduate research projects in philosophy, I’ve developed the following model to help keep students on track. Elements of this model may seem obvious and common practice. I don’t claim that it is novel, but I offer it as a distillation of some lessons that I’ve learned the hard way.

First, philosophers like to ask the big questions (and they should), but unless topics are reined in, student research can easily turn to sprawl and sloppy thinking. Thus, I talk with students about topic refinement early and often. I begin student meetings by asking them to give a one-minute “elevator pitch” for their topic. As the topic gets refined, the pitch becomes easier. En route to refining the topic and developing the elevator pitch, I ask a series of critical questions about the underlying conceptual issues. For example, if a student wants to consider what parents owe their children, I will push her to consider the nature of obligation (e.g., human rights, fairness, well-being, character, social roles) and concrete cases that may or may not fall within the scope of that obligation (e.g., providing food, a new bike, college tuition). Prodding them to consider the nature and scope of the obligation prompts them to consider the underlying philosophical substructure, which is what I believe philosophical inquiry is all about (Draeger 2014). However, once students begin making deep conceptual connections, it is easy for a topic to sprawl as students believe that each connected idea will need its own separate discussion. Metacognition encourages students to be aware of their own learning process (e.g., research) and make intentional adjustments based on that awareness. Encouraging students to be aware of the possibility topic sprawl can help them better evaluate whether their current thinking is moving away from the core issue or towards a better version of that core issue.

Second, all of us are standing on the shoulders of giants. It is good scholarship to acknowledge the original thinking efforts of others by using proper citation. However, the research experience should teach students more than to not plagiarize. Rather, undergraduate research allows students the opportunity to become co-inquirers within an existing scholarly conversation. Becoming familiar with the literature allows them to tap into long-standing debates and utilize conceptual distinctions developed by others. As students begin their research, each comes with their own background and dispositions. Some believe they need to read everything on a topic before they venture an opinion. Others are so eager to begin that they skip the literature review and soon find themselves lost without the resources found within the tradition. Metacognition can help students become aware of when they are reading too much or too little as well as point the way to adjustments in their process.

Third, many students struggle with how to find the relevant source material in philosophy. Even if they know how to use the library, they are often unfamiliar with idiosyncrasies of philosophy as a discipline. For this reason, I explicitly discuss how to go about doing library work (e.g., how to use library databases, how to conduct keyword searches, how to decide which articles seem promising), discuss reading strategies (e.g., how to read at different speeds to find articles most deserving attention, how to read identified articles more carefully, how to annotate a text with an eye towards research), and discuss note taking strategies (e.g., how to organize summaries, critical questions, conceptual applications, personal reflections). When undergraduate research is embedded in my course, we discuss these strategies in class. When undergraduate research takes the form of an independent project, I discuss these strategies one-on-one. In either case, I encourage students to practice becoming aware of what’s working, what’s not, and when they need to adjust their strategies.

Fourth, my undergraduate research students are required to keep a weekly journal. Students are asked to track pesky questions, troublesome counter-examples, and worrisome objections. Beyond their focus on content, however, students are also asked to focus on their own process, including a sketch of the library, reading, and writing strategies attempted as well as whether those strategies were successful. Journaling about these strategies is another way to encourage metacognitive awareness about the research process and locate opportunities for intentional self-regulation.

Undergraduate research can be a HIP (if implemented well) because it encourages students to learn about the research process on their own terms as well as producing their own research product. Metacognition helps monitor whether students are engaged in the sort of deep learning that makes undergraduate research a HIP.  Moreover, intentionally structuring metacognitive opportunities can encourage greater learner autonomy and help facilitate inquiry-based research long after undergraduate experiences have officially concluded. In this way, undergraduate research and metacognition can be highly-impactful because they support the skills necessary for lifelong learning.

References

Draeger, J. (posted July 11, 2014). Using metacognition to uncover the substructure of moral issues.” Retrieved from https://www.improvewithmetacognition.com.

Healey, M., & Jenkins, A. (2009). Developing undergraduate research and inquiry. York: HE Academy.

Kilgo, C. A., Sheets, J. K. E., & Pascarella, E. T. (2015). The link between high-impact practices and student learning: Some longitudinal evidence. Higher Education, 69(4), 509-525.

Kilgo, C. A., & Pascarella, E. T. (2016). Does independent research with a faculty member enhance four-year graduation and graduate/professional degree plans? Convergent results with different analytical methods. Higher Education, 71(4), 575-592.

Kuh, G. D. (2008). Excerpt from high-impact educational practices: What they are, who has access to them, and why they matter. Association of American Colleges and Universities.


Small Metacognition – Part II

By Jennifer A. McCabe, Ph.D., Goucher College

Just before the start of this spring semester, I decided to make a change in the structure of readings and discussions in my upper-level seminar course on Cognition, Teaching, and Learning. I had recently read James Lang’s (2016) book, Small Teaching: Everyday Lessons from the Science of Learning, and was inspired to include it in my class. Instead of jumping into a discussion of research articles, with a few popular press articles or book chapters included toward the end of the semester as examples of translational science writing, I flipped the order and instead started the course with three weeks reading, discussing, and applying the information from Lang’s book (syllabus available upon request).

book cover - James Lang's Small Teaching

As described in my previous blog post (Small Metacognition I) the premise of Small Teaching is that evidence-based, incremental shifts in how teachers structure and deliver educational experiences can have a large pay-off in terms of student learning and engagement. The book speaks to multiple aspects of teacher metacognition (knowing about (students’) knowing, thinking about (students’) thinking, and learning about (students’) learning), even though the term itself is never mentioned.

My students were assigned to read one Small Teaching chapter per class day. For each, they prepared ‘Reading Responses’ consisting of three short paragraphs – from the perspective of a student, an educator, and a cognitive psychologist. At the start of each class period, they completed a ‘Comprehension Check’ question meant to give them feedback on their own learning of the day’s readings. This was self-graded with a check-plus/check/check-minus system, and was low-stakes in that only effort and completion counted. I mostly led these class periods, administering the Comprehension Check, engaging them in some type of active learning activity relevant to the day’s topic, and facilitating a discussion of the reading based on their Reading Responses. This first portion of the class was designed to help them learn about effective teaching through Lang’s book, and also through modeling my own class design and delivery.

This became important because after we finished the nine book chapters, we then shifted into primary source readings of research articles related to applied memory and the Scholarship of Teaching and Learning. During each class period with an article assigned, two students took the role of Discussion Leader; using what they learned from Small Teaching, and in consultation with me ahead of time, they curated and led a class period that included a Comprehension Check question (which should be effective for learning based on findings from memory research on testing as described in Lang’s Retrieving chapter), an active learning exercise (known to be effective based on ideas from the Connecting chapter), and an interactive discussion (relevant to elaboration-based strategies described in the Self-Explaining chapter). Students engaged in conversation about how the current article related to their reading of Small Teaching earlier in the semester (which itself highlighted the usefulness of spacing and mixing of topics, as described in the Interleaving chapter).

During these student-led class periods, I essentially became a member of the class, participating in demonstrations and discussions as a contributor but not as a leader. The Discussion Leaders were empowered in their choices of how to make the class period effective and engaging for their peers. Following the class, I provided feedback to the groups, with a particular emphasis early in the semester on strategies for the next time they led the class. The Discussion Leader experience helped to develop their metacognition by thinking intentionally about the most effective learning experiences, and then how to design and deliver them. There were also times when they had to change teaching/learning strategies midstream, if something was not working well (another component of sophisticated metacognition).

In order to better understand the student experience of reading Small Teaching, which is not aimed at an undergraduate audience, and also to more directly connect to topics in metacognition, I gave the thirteen students in my class an optional free-response survey completed during our final class period. In the spirit of transparency, I had them read my Small Metacognition I blog post first, and explained my plan to write a follow-up post about the class experience with Lang’s book. Each decided whether or not to allow me to use their responses. Though I use names below, pseudonyms are used as needed to reflect my students’ preference.  (Students, if you’re reading this, thank you for contributing to this post!)

I first asked about the most important or memorable lessons from Small Teaching. Several mentioned specific topics or chapters that were impactful, namely retrieving, interleaving, practicing, motivating, growing, and expanding. Many wrote about using evidence to inform teaching in ways that are incremental rather than complete overhauls. For example, Elise wrote, “The current way courses are structured are pretty terrible for durable learning. In order to better structure courses, professors can implement small but impactful techniques to encourage better learning in class as well as guide students towards more empirically supported learning and study methods.” Though metacognition did not come up directly, several responses were related. Anna wrote, “The most important lesson is that learning is complex and that there are many factors at play in the classroom.” Megan commented that it is critical that “both parties (teacher and student) understand exactly why they are doing what they do to learn.” And Katherine noted, “It made me reflect on my own experience in academics and my growth as a learner.”

Next I asked in what ways they think that Small Teaching has (or will) changed the way you think or act in the world. Here students clearly referenced metacognitive development, with Addy saying it “introduced a more metacognitive approach in education to me,” and Samantha noting, “I now have this toolbox of ways I can implement effective strategies.” Noah said, “I feel I have a better understanding of how my mindset can affect my ability to learn.” Anna’s response captured multiple aspects of metacognition: “As a student, Small Teaching (and our larger course discussions) has already shifted the way I think about and articulate my learning experiences. I really think the metacognitive awareness of learning how to learn has helped me to think about the strategies I have used and would like to further implement in my future learning.” Two additional students commented on improved metacognitive awareness.

Finally students were asked whether they would recommend keeping Small Teaching as a core reading in this seminar course. Every student responded positively. They appreciated the book coming at the start of the class as a foundation for the research articles they would be reading, as a way to take an educator’s perspective on learning and memory research, and as an example of a translational piece (they created their own translational projects later in the semester).

I came away from this experience feeling pleased with my decision to incorporate Small Teaching into this class, and also feeling as though I myself had a significant learning (and metacognitive!) experience. Hopefully my students – most of whom were seniors, and some of whom will become teachers – will leave this course with a more sophisticated metacognitive perspective not only toward their own learning, but also toward purposeful and transparent design of educational experiences that effectively support others’ learning.

Recommended Reading

Lang, J. M. (2016). Small Teaching. San Francisco, CA: Jossey-Bass.


Supporting Student Self-Assessment with Knowledge Surveys

by Dr. Lauren Scharff, U. S. Air Force Academy*

In my earlier post this year, “Know Cubed” – How do students know if they know what they need to know?, I introduced three challenges for accurate student self-assessment. I also introduced the idea of incorporating knowledge surveys as a tool to support student self-assessment (an aspect of metacognitive learning) and promote metacognitive instruction. This post shares my first foray into the use of knowledge surveys.

What exactly are knowledge surveys? They are collections of questions that support student self-assessment of their course material understanding and related skills. Students complete the questions either at the beginning of the semester or prior to each unit of the course (pre), and then also immediately prior to exams (post-unit instruction). When answering the questions, students rate themselves on their ability to answer the question (similar to a confidence rating) rather than fully answering the question. The type of learning expectation is highlighted by including the Bloom’s level at the end of each question. Completion of knowledge surveys develops metacognitive awareness of learning and can help guide more efficient studying.

Example knowledge survey questions
Example knowledge survey questions

My motivation to include knowledge surveys in my course was a result of a presentation by Dr. Karl Wirth, who was invited to be the keynote speaker at the annual SoTL Forum we hold at my institution, the United States Air Force Academy. He shared compelling data and anecdotes about his incorporation of knowledge surveys into his geosciences course. His talk inspired several of us to try out knowledge surveys in our courses this spring.

So, after a semester, what do I think about knowledge surveys? How did my students respond?

In a nutshell, I am convinced that knowledge surveys enhanced student learning and promoted student metacognition about their learning. Their use provided additional opportunities to discuss the science of learning and helped focus learning efforts. But, there were also some important lessons learned that I will use to modify how I incorporate knowledge surveys in the future.

Evidence that knowledge surveys were beneficial:

My personal observations included the following, with increasing levels of each as the semester went on and students learned how to learn using the knowledge survey questions:

  • Students directly told me how much they liked and appreciated the knowledge survey questions. There is a lot of unfamiliar and challenging content in this upper-level course, so the knowledge survey questions served as an effective road map to help guide student learning efforts.
  • Students asked questions in class directly related to the knowledge survey questions (as well as other questions). Because I was clear about what I wanted them to learn, they were able to judge if they had solid understanding of those concepts and ask questions while we were discussing the topics.
  • Students came to office hours to ask questions, and were able to more clearly articulate what they did and did not understand prior to the exams when asking for further clarifications.
  • Students realized that they needed to study differently for the questions at different Bloom’s levels of learning. “Explain” questions required more than basic memorization of the terms related to those questions. I took class time to suggest and reinforce the use of more effective learning strategies and several students reported increasing success and the use of those strategies for other courses (yay!).
  • Overall, students became more accurate in assessing their understanding of the material prior to the exam. More specifically, when I compared the knowledge survey reports with actual exam performance, students progressively became more accurate across the semester. I think some of this increase in accuracy was due to the changes stated in points above.

Student feedback included the following:

  • End-of-semester feedback from students indicated that vast majority of them thought the knowledge surveys supported their learning, with half of them giving them the highest rating of “definitely supports learning, keep as is.”
  • Optional reflection feedback suggested development of learning skills related to the use of the knowledge surveys and perceived value for their use. The following quote was typical of many students:

At first, I was not sure how the knowledge surveys were going to help me. The first time I went through them I did not know many of the questions and I assumed they were things I was already supposed to know. However, after we went over their purpose in class my view of them changed. As I read through the readings, I focused on the portions that answered the knowledge survey questions. If I could not find an answer or felt like I did not accurately answer the question, I bolded that question and brought it up in class. Before the GR, I go back through a blank knowledge survey and try to answer each question by myself. I then use this to compare to the actual answers to see what I actually need to study. Before the first GR I did not do this. However, for the second GR I did and I did much better.

Other Observations and Lessons learned:

Although I am generally pleased with my first foray into incorporating knowledge surveys, I did learn some lessons and I will make some modifications next time.

  • The biggest lesson is that I need to take even more time to explain knowledge surveys, how students should use them to guide their learning, and how I use them as an instructor to tailor my teaching.

What did I do this past semester? I explained knowledge surveys on the syllabus and verbally at the beginning of the semester. I gave periodic general reminders and included a slide in each lesson’s PPT that listed the relevant knowledge survey questions. I gave points for completion of the knowledge surveys to increase the perception of their value. I also included instructions about how to use them at the start of each knowledge survey:

Knowledge survey instructions
Knowledge survey instructions

Despite all these efforts, feedback and performance indicated that many students really didn’t understand the purpose of knowledge surveys or take them seriously until after the first exam (and some even later than that). What will I do in the future? In addition to the above, I will make more explicit connections during the lesson and as students engage in learning activities and demonstrations. I will ask students to share how they would explain certain concepts using the results of their activities and the other data that were presented during the lesson. The latter will provide explicit examples of what would (or would not) be considered a complete answer for the “explain” questions in contrast to the “remember” questions.

  • The biggest student feedback suggestion for modification of the knowledge surveys pertained to the “pre” knowledge surveys given at the start of each unit. Students reported they didn’t know most of the answers and felt like completion of the pre knowledge surveys was less useful. As an instructor, those “pre” responses helped me get a pulse on their level or prior knowledge and use that to tailor my lessons. Thus, I need to better communicate my use of those “pre” results because no one likes to take time to do what they perceive is “busy work.”
  • I also learned that students created a shared GoogleDoc where they would insert answers to the knowledge survey questions. I am all for students helping each other learn, and I encourage them to quiz each other so they can talk out the answers rather than simply re-reading their notes. However, it became apparent when students came in for office hours that the shared “answers” to the questions were not always correct and were sometimes incomplete. This was especially true for the higher-level questions. I personally was not a member of the shared document, so I did not check their answers in that document. In the future, I will earlier and more explicitly encourage students to be aware of the type of learning being targeted and the type of responses needed for each level, and encourage them to critically evaluate the answers being entered into such a shared document.

In sum, as an avid supporter of metacognitive learning and metacognitive instruction, I believe that knowledge surveys are a great tool for supporting both student and faculty awareness of learning, the first step in metacognition. We then should use that awareness to make necessary adjustments to our efforts – the other half of a continuous cycle that leads to increased student success.

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* Disclaimer: The views expressed in this document are those of the author and do not reflect the official policy or position of the U. S. Air Force, Department of Defense, or the U. S. Govt.


Developing Affective Abilities through Metacognition Part 4: Exercising Academic Courage in Faculty Development

by Dr. Ed Nuhfer, California State Universities (retired)

Courage is a metacognitive quality that enables not having our actions limited or dictated by fear. Academic courage is a unique category of “moral courage.” Unlike physical acts of courage that occur in a brief time span, moral courage governs a day-to-day way of being and acting in practice, despite recognizing the forces that merit fear. Martin (2011) describes academic courage as perseverance through academic difficulty in the face of fear. The threatening environments of universities and the nature of courage that educators, particularly faculty developers, need in their professional practice are our focus here. With the notable exceptions of Palmer (2017) and Martin (2011), data-based studies of developed courage by teacher-scholars are nearly nonexistent.

“Fear” inevitably enters nearly all discussions about “courage.” While courage does not exist in the absence of fear, courage is a developed metacognitive capacity; fear is not. Acting with courage becomes possible when a person’s learning involves affective development along with intellectual and ethical development. (See the last blog in this series, Part 3.) Hannah, Sweeney, and Lester (in Pury and Lopez, 2011, pp 125-148) portray acts of courage as the products of a developed “Cognitive-Affective Processing System.” In brief, courage enlists a lot of brainpower.

Teachers have courage (image from http://tamaravrussell.com/2015/07/teachers-have-courage/)

Academic Courage versus Suicidal Tendency

Institutions of higher education produce unique threats, and several are increasing for faculty and faculty developers. The unifying theme for most fear in academia is the potential loss of career and livelihood. Because threatening faculty livelihoods for reasons other than incompetence or ethical violations is a detriment to society, tenure developed in the U. S. as a means to shield scholars from being intimidated and having their voices silenced. But tenure has not always worked perfectly. Tenure-track positions are vanishing as academic staff, with no prospects of tenure or its protections, now replace retiring tenured professors. Increased faculty vulnerability naturally accompanies increased apprehension and fear. People involved in threatening scholars’ livelihoods are politicians & regents boards, administrators, students, and colleagues.

Politicians in parts of the federal government, and a few states, now actively suppress or work to eliminate government researchers and college faculty who work on topics where investigations produce (or might produce) evidence that contradicts partisan advocacy. Political power now is wielded to weaken tenure and eliminate programs that produce knowledge that contradicts authoritarian positions and even university benefactors’ interests. Faculty can suffer reprisals for doing politically-charged scholarship. The World Wide Web and social media open today’s college faculty and students to unprecedented surveillance, so even work performed outside universities with scholarly journals or professional organizations produces risks. Sometimes, faculty can wonder whether every group on the campus has power over them. When faculty state that their careers “live and die by student ratings,” this discloses that they also fear their students. To some faculty, it seems that even students have supervisory power to take away faculty livelihoods. All of these sources of fear represent substantial threats. When a faculty member discloses fear, a developer must never think to trivialize or discount it. The reason for fear is likely real.

College faculty have responsibilities as teachers and scholars. In both, a responsibility provides an obligation to remain current about new knowledge, to add to the knowledge base, and not merely act as dispensers of knowledge. As new evidence validates the increased effectiveness of different instructional methods, teacher-scholars have obligations to maintain command of the current literature and to apply the best available knowledge to serve their students. Yet, doing so poses risks.

Introducing unfamiliar teaching structures to the classroom is not always received favorably by students or by colleagues. Striving to enact nontraditional instructional techniques carries risks of becoming unpopular by not satisfying students with teaching as they expected to be taught. Where the retention of livelihoods rests more on popularity with those who have the power to take livelihood away than on the quality of research achieved or the learning promoted, acting from fear of becoming unpopular has potential consequences.

A courageous action is not rash or suicidal; it recognizes and respects actual threats. The temptation to bulldoze ahead with “best practices” by believing that one has superior knowledge disrespects a genuine threat. Acting courageously respects the threat and works to understand it, but without giving into fear. Acting from courage requires more brainpower than does just giving up. Building capacity to enact academic courage involves a lot of work. A courageous approach may strive to find empathy for colleagues and students, seek awareness of the reasons for their dissatisfaction and will work to gain an understanding of what changes will be needed for those in opposition to begin to accept and support the most beneficial actions. A failed first attempt will serve to inform later efforts.

Face management as a Cultural Challenge to Courage

Face management seeks to advance oneself socially through associating and being seen with those who are popular and/ or influential. Face management is a way of life in many organizations. Its dark side appears when advancing self involves marginalizing those perceived as unpopular or just different. Faculty being ostracized can include those who are struggling to make changes and newcomers with new ideas, perhaps controversial to local established practices, who are striving to be accepted and valued. Stanford professor Robert I. Sutton referenced such face-managing actions as “kiss-up; slap-down,” and recognized that the behavior could render toxic the culture of an entire organization–a department, a college, and even an institution. Ostracism is something any individual should fear. Researchers at the University of British Columbia’s Sauder School of Business studied the impact of ostracism on employee health and morale and discovered that it can be even more harmful to one’s mental and physical well-being than harassment or other forms of bullying. For a faculty developer, supporting those ostracized entails risks of also becoming marginalized.

That’s a hazard in faculty development work because faculty development is a helping profession. A faculty developer’s responsibility is to support faculty who are in need of help, and they seldom are people who hold popularity or power. Anyone who aspires to be a faculty developer needs to realize that he/she will likely experience such a threat multiple times. Often, faculty in need are also being marginalized, struggling to succeed and sometimes suffering the consequences of being caught crossways in a toxic, unit-level culture of kiss-up-slap-down. Unfortunately, face-managing cultures are tolerated, even nurtured, in universities, perhaps because courage isn’t taught in college.

While the exercise of academic courage in faculty development requires knowledge and skills, both are external qualities. Acting with academic courage is different. It’s an internal capacity that infuses knowledge and skills with empathy and affect. Internal development is a ceaseless metacognitive reflection, and it is a LOT of work.

References

Martin, A. J. (2011) Courage in the Classroom: Exploring a New Framework Predicting Academic Performance and Engagement. School Psychology Quarterly 26 2 145-160.

Palmer, P. (2017) The Courage to Teach: Exploring the Inner Landscape of a Teacher’s Life. 20th Ed. San Francisco, CA: Wiley.

Pury, C. L. S., and S. Lopez, eds. (2011). The Psychology of Courage. Washington DC: American Psychological Association.


Practicing Metacognition on a Chatbot

by Roman Taraban, Ph.D., Texas Tech University

Cognition involves many kinds of processes. There is categorization, problem solving, decision making, and comprehension, among others. Metacognition may involve these processes, but is different from them. Metacognitive thinking is thinking about the processes themselves (Draeger, 2015). That is, thinking about the processes involved in categorization, comprehension, and so on, and how these processes relate to one’s information processing capabilities. John Flavell, who coined the term metacognition, suggested that metacognitive processing relates not only to the individual thinkers but to others as well: “Metacognitive knowledge is one’s stored knowledge or beliefs about oneself and others as cognitive agents, about tasks, about actions or strategies, and about how all these interact to affect the outcomes of any sort of intellectual enterprise” (Flavell, 1999, p. 906). Consideration of how thinking in another person informs one’s own metacognitive knowledge is seldom considered in discussions of metacognition. In this post, I relate how reflecting on how others process information, specifically, how machines process information, can inform a person’s understanding of how he or she processes information. The metacognitive processes of interest here are those related to language processing, and the specific machine processing relates to that of machine systems called chatbots.

Chatbots are computer programs that interact with a person auditorily or through text. They are designed to communicate as much as possible like humans, in order to convey a sense of natural language communication. Chatbots are typically developed for commercial purposes, to provide customer service, for instance, or information about products or places. You will find chatbots on websites for companies, organizations, and events.

Recently I taught a graduate seminar on psycholinguistics, which is concerned with language acquisition, production, and comprehension. I assigned students the task of building chatbots for an application that interested them, for instance, a chatbot that could inform a user of the movies currently playing around town and show times. After students had built their chatbots and demonstrated them to the class, I assigned a written take-home metacognitive activity in which students had to discuss some aspect of the nature of chatbot language, for example, ways in which chatbot language might reduce moral relativity, constrain language interactions, or homogenize language. Students essentially had to think about the language processing constraints in chatbots and how that might affect their language interactions.

Students built chatbots to do everything from helping a student choose colleges for graduate work, college courses, movies, and restaurants, to guiding workouts or choosing a football game to watch. In their subsequent metacognitive reflection assignment, students had plenty to say:

  • Chatbots are peculiar devices.
  • Chatbots do not process language as humans would.
  • Chatbots, because of their limited cognitive capabilities, cannot respond to novel stimuli in conversations and therefore cannot problem-solve or be socially engaging.
  • Chatbots have higher potential of providing logical, true and precise answers than humans.
  • The nature of chatbot language has positive characteristics that reinvent the notion of interaction, and negative characteristics that create many confusions and misinterpretations about the use of a language.

Using chatbots as a foil prompted students to consider the nature of their own language processes. As a few examples:

For example, human communication is not a mere string of words put together to make meaning, rather it employs many other resources which feed communication such as the extralinguistic, paralinguistic and metalinguistic cues in order to achieve successful communication. I think that chatbots cannot perform such complex task as efficiently as most people do.

Although chatbots may serve humans as they interact with them, I think they do so with a structured sort of language which is intended to perform very specific tasks. As human language is inherently relative and creative, I think chatbots need much improvement to sound like humans if we need them to interact more “naturally.” In terms of human language, a unique characteristic is the ability to process linguistic and non-linguistic inputs. As humans we can process such inputs with the help of our background knowledge, working memory and other brain functions. Our judgements are further constrained, shaped or developed by moral relativity, i.e. the philosophical standpoints given or attributed by the cultures and societies we belong.

The students’ reflections on chatbot language processing fit Flavell’s (1999) suggestion that metacognition includes beliefs about others as cognitive agents, that is, as intelligent communicative actors. Often, learning about metacognitive strategies may begin by observing others and implicitly mimicking their behaviors. For instance, as children we may notice someone writing down a phone number or looking up a phone number and we recognize and adopt these specific processes to manage information. Knowledge of the strategies becomes more explicit the first time we fail to apply the strategy and cannot remember a phone number. We observe classmates reviewing notes repetitively and self-testing and adopt these methods of regulating and monitoring study behaviors. We rarely, if ever, create objects like chatbots, as in the present case, and use the objects to reflect on others’ and our own metacognitive processes, as a learning process. However, as AI technology and products become more prevalent, there arise many natural opportunities to think about and compare machines’ processes to our own. Of course, to qualify as metacognitive thinking, reflections on man vs machine processing will have to go beyond superficial comments like “My Alexa is not too smart.” To be metacognitive, thinking has to be about the processes themselves, in the machine and in the person.

The theme of this post is to highlight how metacognition is not only about thinking about one’s own thinking, but also thinking about thinking in the entities – humans or machines – with whom we communicate. Building a chatbot gives students direct contact with the processes in the machine and a bridge to reflecting on their own processes by comparison. It forces students to reflect on strengths and limitations of both kinds of language. There are other instances where this type of metacognitive knowledge comes into play naturally. Take child-directed speech (a.k.a. motherese, baby talk), for instance. Caretakers adjust their intonation, vocabulary, and rhythm when speaking to infant siblings. They have a sense that an infant is processing language differently so they adjust their own processing to accommodate. Similarly, in the classroom or at a conference, we become aware (sometimes depressingly) that our message is not connecting and may try to make adjustments in speed, terminology, examples, etc. The difference between those situations and the present one is that there may not be a moment of deliberate metacognitive reflection – how is the other person processing information compared to how I am processing the information. Flavell reminds us that this, too, is metacognitive. Here I am suggesting that we can make those moments more deliberate, indeed, we can turn them into class assignments!

References

Draeger, J. (2015). Two forms of ‘thinking about thinking’: metacognition and critical thinking. Retrieved from https://www.improvewithmetacognition.com/two-forms-of-thinking-about-thinking-metacognition-and-critical-thinking/.

Flavell, J. H. (1979). Metacognition and cognitive monitoring: A new area of cognitive–developmental inquiry. American Psychologist, 34(10), 906-911. doi.org/10.1037/0003-066X.34.10.906


Where Should I Start With Metacognition?

by Patrick Cunningham, Rose-Hulman Institute of Technology

Have you ever had a student say something like this to you? “I know the material, I just couldn’t show you on the exam.” How do you respond?

I have heard such comments from students and I think it exemplifies two significant deficiencies.

First, students are over-reliant on rehearsal learning strategies. Rehearsal is drill-and-practice or repetitive practice aimed at memorization and pattern matching. Such practices lead to surface learning and shallow processing. Students know facts and can reproduce solutions to familiar problems, but struggle when the problem looks different. Further, when faced with real-world situations they are often not even able to identify the need for the material let alone apply it. Only knowing material by rote is insufficient for fluency with it. For example, I can memorize German vocabulary and grammar rules, but engaging someone from Germany in a real conversation requires much more than just knowing words and grammar.

Second, students are inaccurate in their self-assessments of their learning, which can lead to false confidence and poor learning choices (Ehrlinger & Shain 2014). Related to this, I have developed a response to our hypothetical student. I ask, “How do you know you know the material?” In reply, students commonly point to looking over notes, looking over homework, reworking examples or homework problems, or working old exams – rehearsal strategies. I often follow up by asking how they assessed their ability to apply the material in new situations. This often brings a mixture of surprise and confusion. I then try to help them discover that while they are familiar with the concepts, they are not fluent with them. Students commonly confuse familiarity with understanding. Marilla Svinicki (2004) calls this the Illusion of Comprehension, and others have called it the illusion of fluency. Continuing the language example, I could more accurately test my knowledge of German by attempting and practicing conversations in German rather than just doing flashcards on vocabulary and grammar rules. Unless we employ concrete, demonstrable, and objective measures of our understanding, we are prone to inaccurate self-assessment and overconfidence. And, yes, we and our students are susceptible to these maladies. We can learn about and improve ourselves as we help our students.

Addressing these two deficiencies can be a good place to start with metacognition. Metacognition is the knowledge and regulation of our thinking processes. Our knowledge of strategies for building deeper understanding and our awareness of being susceptible to the illusion of comprehension are components of metacognitive knowledge. Our ability to regulate our thinking (learning) and apply appropriate learning strategies is critically dependent on accurate self-assessment of our level of understanding and our learning processes, specifically, in metacognitive monitoring and evaluation. So how can we support our students’ metacognitive development in these areas?

To help our students know about and use a broader range of learning strategies, we can introduce them to new strategies and give them opportunities to practice them. To learn more deeply, we need to help students move beyond rehearsal strategies. Deeper learning requires expanding and connecting the things we know, and is facilitated by elaborative and organizational learning strategies. Elaboration strategies aid the integration of knowledge into our knowledge frameworks by adding detail, summarizing, and creating examples and analogies. Organizational strategies impose structure on material and help us describe relationships among its elements (Dembo & Seli 2013).

We can help our students elaborate their knowledge by asking them to: 1) explain their solutions or mistakes they find in a provided solution; 2) generate and solve “what-if” scenarios based on example problems (such as, “what if it changed from rolling without slipping to rolling with slipping”); and 3) create and solve problems involving specific course concepts. We can help our students discover the structure of material by asking them to: 1) create concept maps or mind maps (though you may first need to help them learn what these are and practice creating them); 2) annotate their notes from a prior day or earlier in the period; and 3) reorganize and summarize their notes. Using these strategies in class builds students’ familiarity with them and improves the likelihood of students employing them on their own. Such strategies help students achieve deeper learning, knowing material better and making it more accessible and useable in different situations (i.e., more transferable). For example, a student who achieved deeper learning in a system dynamics course will be more likely to recognize the applicability of a specific dynamic model to understand and design a viscosity experiment in an experiment design class.

To help our students engage in more accurate self-assessment we can aid their discovery of being susceptible to inaccurate self-perceptions and give them opportunities to practice strategies that provide concrete, demonstrable, and objective measures of learning. We can be creative in helping students recognize their propensity for inaccuracy. I use a story about an awkward conversation I had about the location of a youth hostel while travelling in Germany as an undergraduate student. I spent several minutes with my pocket dictionary figuring out how to ask the question, “Wissen Sie wo die Jugendherberge ist?” When the kind stranger responded, I discovered I was nowhere near fluent in German. It takes more than vocabulary and grammar to be conversant in the German language!

We can help our students practice more accurate self-assessment by asking them to: 1) engage in brief recall and review sessions (checking completeness and correctness of their recalled lists); 2) self-testing without supports (tracking the time elapsed and correctness of solution); 3) explaining solutions (noticing the coherence, correctness, and fluency of their responses); and 4) creating and solving problems based on specific concepts (again, noting correctness of their solution and the time elapsed). Each of these strategies creates observable and objective measures (examples noted in parentheses) capable of indicating level of understanding. When I have students do brief (1-2 minute) recall exercises in class, I have them note omissions and incorrect statements as they review their notes and compare with peers. These indicate concepts they do not know as well.

Our students are over-reliant on rehearsal learning strategies and struggle to accurately assess their learning. We can help our students transform their learning by engaging them with a broader suite of learning strategies and concrete and objective measures of learning. By starting here, we are helping our students develop transferable metacognitive skills and knowledge, capable of improving their learning now, in our class, and throughout their lives.

References

Ehrlinger, J., & Shain, E. A. (2014). How Accuracy in Students’ Self Perceptions Relates to Success in Learning. In V. A. Benassi, C. E. Overson, & C. M. Hakala (Eds.). Applying science of learning in education: Infusing psychological science into the curriculum. Retrieved from the Society for the Teaching of Psychology web site: http://teachpsych.org/ebooks/asle2014/index.php

Svinicki, M. (2004). Learning and motivation in the postsecondary classroom. San Francisco, CA: John Wiley & Sons.

Dembo, M. & Seli, H. (2013). Motivation and learning strategies for college success: A focus on self-regulated learning (4th ed.). New York, NY: Routledge.


Small Metacognition – Part I

By Dr. Jennifer A. McCabe, Goucher College

I recently read James Lang’s (2016) book, Small Teaching: Everyday Lessons from the Science of Learning, which is framed by the premise that incremental shifts in how teachers structure and deliver educational experiences can have a large pay-off in terms of student learning and engagement. Each recommendation is grounded in what we know works for learning from memory research, and each is implementable without significant additional resources, time, or grading. Though Lang does not explicitly frame his book around metacognition (in fact, the word is not mentioned!), much of it supports the development of teacher metacognition with regard to several core components: knowing about (students’) knowing, thinking about (students’) thinking, and learning about (students’) learning.

In this first post (Part I), I describe Small Teaching through a metacognitive lens to support the development of teachers’ metacognition about course design and implementation. In Part II, I will discuss my experience of incorporating this book into a senior seminar in Cognition, Teaching, and Learning.

Adding Small Steps leads to Big Changes

The first section of Small Teaching, entitled Knowledge, presents the idea that students do not necessarily know what strategies support durable and flexible learning. This gives teachers the opportunity (and responsibility) to structure experiences that support learning, even though these may feel harder, slower, or show smaller gains in the short term (i.e., desirable difficulties; see Yan et al., 2017 for a recent review). The Retrieving chapter discusses the testing effect, and the many ways teachers can encourage students to practice effortful retrieval of information from long-term memory. Predicting presents the value of pre-testing and predictive opportunities, which boost curiosity and aide subsequent learning. Interleaving discusses the spaced (or distributed) study principle, and the related strategy of interleaving (i.e., mixing instead of, or in addition to, blocking); these strategies help rectify the common metacognitive pitfall of forgetting we (and our students) forget. Student’s ability to produce knowledge at one point in time does not necessarily predict their future ability to remember. Incorporating frequent retrieval practice and cumulative assessments are concrete ways to counter-act the natural process of forgetting.

The second section is focused on Understanding, or deep comprehension. In Connecting, Lang discusses strategies to link and expand knowledge, including the intentional activation and use of students’ prior knowledge, use of explicit frameworks (e.g., outlines, concept maps), and writing exercises that support students in the challenging task of creating new connections. Practicing stresses the metacognitive component of knowing about (students’) knowing; that is, intentionally assessing cognitive skills needed for a large assignment, then making space for practice of those skills to scaffold toward successful assignment completion. Self-Explaining describes the strategy of having students explain what they are thinking and doing during a task – another example of a desirable difficulty.

The third and final section of Small Teaching is framed around Inspiration. This includes Motivating, focusing on the role of emotions in learning. Even teachers who have metacognitive knowledge about the basics of learning from a cognitive perspective, may have low awareness of the impact motivation has on learning, and the ways in which we can intentionally utilize students’ emotion (e.g., cultivating positive rapport, showing enthusiasm, using story-telling and narratives, and supporting the development of self-transcendent purpose). Growing helps teachers understand the value of a growth mindset as connected to student success, and how to create classrooms that model and reward growth. Finally, Expanding offers a discussion about “big teaching” – new frontiers for major shifts in how college courses are structured and offered.

Ultimately, the take-away message from Small Teaching is that relatively minor changes can bring big rewards in our classrooms. As an added bonus, many techniques give teachers tangible feedback about how students are progressing toward course learning goals. Viewing this book from a metacognitive framework encourages teachers to examine their own beliefs about learning, which can lead to an enlightening appraisal of why we make the decisions we do. Metacognitive questions abound: What is the learning goal here? How does the structure of this assignment get students to the learning goal? What cognitive processes am I expecting students to engage in (and how do I know they know how to do them)? Does this assignment have an explicitly stated purpose? Do my assessments engage cognitive processes that support durable and flexible learning? Am I being transparent in communicating the rationale for my pedagogical choices to my students? How are my own learning beliefs and biases influencing my students’ experience?

These “small” principles provide great opportunity, but also potential hazards. Teachers need to consider the line between desirable and undesirable difficulties, ensuring that the work we assign for students is difficult in a way that encourages effort in support of learning, and not in a way that overwhelms or otherwise detracts from learning. That is, paying mindful attention to the cognitive processes involved in coursework, and the ability of students to engage in them, is critical. An effective assessment will be challenging in the manner of engaging processes such as retrieval or elaboration that we know support learning. An undesirably difficult assessment will be challenging in a non-productive way. For example, to make students work harder, teachers may give repetitive busy-work that requires time and energy, but does not aid learning. Or consider assessments so difficult that learners do not have the cognitive (or metacognitive) scaffolding in place to engage effectively, even with great effort. Overly difficult assessments can result in feelings of anxiety, overwhelm, and even anger – all of which are counter-productive to learning. Enter the value of teacher metacognition: A teacher skilled in thinking about how learning works, and what their students know (along with skills they bring to the course), will be better able to navigate their assessments to keep them on the side of desirable difficulties.

In sum, metacognitive awareness and self-regulation are both key components to effective translation of memory principles into effective educational design. Lessons from Small Teaching connect to “small” adjustments toward increased metacognitive awareness in teachers. In Part II I will explain and reflect on my, and my students’, experience with Small Teaching in my seminar course.

Recommended Reading

Lang, J. M. (2016). Small Teaching. San Francisco, CA: Jossey-Bass.

Yan, V. X., Clark, C. M., & Bjork, R. A. (2017). Memory and metamemory considerations in the instruction of human beings revisited: Implications for optimizing online learning. In J. C. Horvath, J. Lodge, & J. A. C. Hattie (Eds.), From the Laboratory to the Classroom: Translating the Learning Sciences for Teachers (pp. 61-78). New York: Routledge.


“Know Cubed” – How do students know if they know what they need to know?

by Dr. Lauren Scharff, U. S. Air Force Academy*


Know Cubed

This simple but somewhat of a tongue-twister question takes us to several challenging aspects of teaching and learning that link to both student and instructor metacognition:

  1. How do students self-assess their understanding and abilities prior to assessments?
  2. Are students able to accurately know what they are expected to be able to demonstrate for an assessment?
  3. What can we as instructors reasonably do to be transparent regarding our learning expectations and to support student development of accurate self-assessment?

Generally speaking, humans ARE good at self-assessment, as long as the self-assessment activity/tool is well-aligned with the actual assessment activity/tool (e.g. see Nuhfer, 2015). However, there are many possible reasons why students may not accurately self-assess, and several of those are directly under our control as instructors.

Thus, I believe we should engage in metacognitive instruction by developing our awareness of common reasons that students may not accurately self-assess, what we might be doing that inadvertently leads to those pitfalls, and some means by which we can support more accurate student self-assessment. We should then intentionally use that awareness to adjust what we do. This combination of awareness and self-regulation provides the foundation for metacognitive instruction.

Based on my observations and discussions with colleagues across the years, here are three common reasons students might not accurately self-assess along with some strategies instructors might take to support better student self-assessment:

  1. Lesson-to-Exam Misalignment – For example, classroom instruction and activities sometimes focus on basic concepts and definitions, while exams ask for evaluation and synthesis. Students may self-assess their competency based on what was presented in the lesson, but then feel surprised and perform poorly on the exam when they are asked to go beyond the lower level. Even if instructors “warn” students that they will need to engage in higher-level processing on the exams, if students haven’t been given the opportunity to experience what that means and practice it, those students may not accurately self-assess their preparedness for the exam. Instructors should analyze the levels and types of learning materials they present in class and require of students during formative learning activities (in-class activities, homework, quizzes). Then, they should align their exams to have similar levels of expectation. If they desire higher-level learning to be demonstrated on exams, they should redesign their learning activities to allow scaffolding, practice, and feedback with those higher-level expectations.
  2. Confusing Questions – Students often claim that questions on exams are confusing, even if they don’t seem to be confusing from the instructor’s perspective. Thus, students might actually be accurate in their self-assessment of their understanding of a topic, but then fail to demonstrate it because they were confused by the question or simply misread it. Test anxiety can add additional cognitive load and make it more likely for students to misread questions. Thus, instructors should review their questions to find ways to more clearly indicate what they expect in a response. For example, if there are two parts to the question, rather than having a long question, break it into part (a) and part (b). This symbolism clearly communicates that a good response should have two parts. It often can be difficult for the person writing the question to assess the clarity of their question because they know what they mean, so it seems obvious. (Instructors can also fall into this trap when reviewing test banks questions and the correct answer is clearly indicated. Once the answer is known, it seems obvious.) Being aware of these pitfalls and taking the time to critically analyze one’s test questions is a good way to engage in metacognitive instruction. Having a colleague from a different area of expertise read through the questions before finalizing them can also help catch some instances where clarity could be improved.
  3. Smooth Presentations – Instructors are experts, and they generally like to be perceived as such. Thus, it is far more common for instructors to present problem work-outs or other complex material in ways that make it look smooth and easy. That seems good, right? Actually, smooth presentations can mislead students into thinking that the material is easy and not prompt them to ask questions. Following a smooth presentation, students might then self-assess as understanding the material when really they would not be able to work out a problem on their own. Explicit step-by-step examples in textbooks also sometimes fool students into thinking they know how to workout problems if the assigned homework can be completed by following the examples. Instructors should consider verbalizing points of possible confusion that they know often catch students or sharing their own struggles as they learned the material in the past. As they work out problems in front of class, they could ask what worked, what didn’t, and what changes could be made in the problem-solving approach (or writing approach, or presentation of an argument, etc.). They should also emphasize to students that they will be better able to self-assess their preparation for an exam if they work out problems without the examples in front of them.

The above challenges for accurate student self-assessment and instructor strategies to address them are just a start to help us become metacognitive instructors and help students become more metacognitive learners. In my next post I will share with you my recent exploration into the use of Knowledge Surveys. This tool directly helps students develop more accurate self-assessment. Further, with direction and encouragement from the instructor, knowledge surveys can help students become metacognitive learners by using their awareness of their learning to guide their use of learning strategies.

There are many routes to becoming a metacognitive instructor, although all require intentionality in developing awareness of factors impacting student learning and using that awareness to self-regulate instructional efforts. It is a process with many options and possible strategies, where even small efforts can lead to big pay-offs in student learning and development.

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Nuhfer, E. (January 2015). Self-assessment and the Affective Quality of Metacognition: Part 2 of 2. Blog post on Improve with Metacognition, retrieved from https://www.improvewithmetacognition.com/self-assessment-and-the-affective-quality-of-metacognition-part-2-of-2/

* Disclaimer: The views expressed in this document are those of the author and do not reflect the official policy or position of the U. S. Air Force, Department of Defense, or the U. S. Govt.


Using Metacognition to Support Students with LD and their Transition to College

by Mary L. Hebert, PhD; Fairleigh Dickinson University, The Regional Center for Learning Disabilities

Launching as a new college student is one of the most significant transitions a young person experiences. With college comes not only the adjustment to a new school, but newly defined relationships and expectations with professors, higher-level classes, new levels of independence and expectations for managing academics, social, emotional and physical wellness, as well as increasing physical separation from family. Academic transitions can be particularly stressful for students with a learning disability, as well as for their parents. This post advocates that strong metacognitive skills are an asset for any student going through transitions, but particularly for a student with learning differences.

Metacognition is associated with self-awareness and application to one’s environment to assist with adaptation. For the student who is arriving on a college campus with a history of accommodations and either an Individualized Education Plan or a 504 Plan due to a learning disability, the transition can be a daunting one. Well-developed metacognition is a powerful asset in preparing a student with learning disabilities to transition successfully to college. These students’ confidence may be impacted due to their history of academic challenges and having been a part of a program of services that provided accommodations in high school. It is important for such students to evaluate several things including: will they or won’t they identify their LD as they enter college, will they opt to seek services or apply for accommodations, how comfortable do they feel about identifying their LD in a college setting, how much do they know about services and accommodations at the college level?

While confidence is a necessary and desirable quality, a student with a LD may be at risk of over confidence, which has the potential to interfere with quality metacognition. Stephen Chew of Samford University in Alabama discusses over confidence in regard to its negative impact on choices of behaviors related to learning (Lang, 2012). I suggest here that over-confidence can also negatively impact the metacognition of students, especially LD students, across that broader set of choices related to the transition to college. Metacognitive strategies are essentially strategies that provide a student with a heightened awareness of the skill sets they have that will support them toward their tasks at hand. Students with weak metacognitive skills may underestimate the degree of support or accommodations that might be appropriate to support their successful adjustment to college life. I have observed students who are new freshmen with long histories of academic, mental health, and other services decide upon entry to college that they no longer wish to utilize these services. It is worth pausing to ask, is this the best time to cease or decrease services? Strong metacognitive skills can assist the student to judge more accurately a plan of services that will suit their needs at this point of transition.

A useful metacognitive strategy in preparation for this transitional phase of their education is to give aspiring college students lower stakes experiences and opportunities to assess their own awareness about the mastery of skills necessary to adjust to college. This practice prior to performance is an effective strategy to apply to college readiness thinking, decision-making and planning skills. Parents, counselors, teachers and others involved in a student’s educational process can orchestrate purposeful metacognitive opportunities to give the student a chance to practice and reflect on experiences that will be key strategies for the transition to college life. For example, a student who may be expressing a desire not to identify their disability when they transition to college and therefore not seek accommodations may be given the chance to work without accommodations in high school to assess how they perform without certain accommodations such as extended time, a note taker, modified assignments, organizational and time management assistance etc. In a supportive manner the student can be questioned as to what this experience was like, and how it impacted their learning and performance.

Having students practice in the manner they will be required to perform becomes an indispensable metacognitive tool which can assist with the metacognitive skills to think about, evaluate, and acquire self-knowledge and awareness of what their strengths, needs, and challenges are so they can plan for their transition more realistically and therefore more effectively. The goal is that they will adjust more successfully to college expectations and demands. As a high school student, a certain set of skills and expectations have been developed to respond to academics, social and emotional and time management tasks. Transitioning to college requires a solid metacognitive evaluation of how these skills and expectations will or won’t transfer to college expectations and demands. Understanding one’s learning disability and its impact not only on academic performance, but also on life skills such as time management, social relationships, emotional regulation, and wellness needs becomes key in readiness for functioning successfully in a college setting.

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Lang, James M. (2012). Metacognition and Student Learning, Chronicle of Higher Education, Retrieved from https://www.chronicle.com/article/MetacognitionStudent/130327


Am I responsible for engaging my students in learning how to learn?

by Patrick Cunningham, Rose-Hulman Institute of Technology

I’m a mechanical engineering professor and since my first teaching experience in graduate school I’ve wanted my students to walk away from my classes with deep learning. Practically, I want my students to remember and appropriately apply key concepts in new and different situations, specifically while working on real engineering problems.

In my early years of teaching, I thought if I just used the right techniques, exceptional materials, the right assignments, or the right motivational contexts, then I would get students to deeper learning. However, I still found a disconnect between my pedagogy and student learning. Good pedagogy is important, but it isn’t enough.

On sabbatical 4 years ago, I sat in on a graduate-level cognitive processes course that helped explain this disconnect. It helped me realize student learning is principally determined by the student. What the student does with the information determines the quality of their learning. How they use it. How they apply it. How they practice it. How engaged they are with it. I can provide a context conducive to deeper learning, but I cannot build the foundational and rich knowledge frameworks within the students’ minds. Only the students can do this. In other words, while we, as educators, are important in the learning process, we are not the primary determinants of learning, students are. Students are responsible for their learning, but they don’t universally realize it.

So, how do we help students realize their responsibility for learning? It requires presenting explicit instruction on how learning really works, providing practice with effective approaches to learning, and giving constructive feedback on the learning process (Kaplan, et al. 2013). When left unchecked, flawed conceptions of the learning process at best are allowed to persist and at worst are reinforced. Even when we do not explicitly speak to the learning process with our students, we say something about it. For example, when our primary mode of instruction is walking students through example problems, we may reinforce the belief that learning is about memorizing the process rather than connecting concepts to different contexts and knowing when to apply one concept versus another concept. Sometimes we do speak to students about the learning process, but we offer vague and unhelpful advice, such as, “work more problems”, or “study harder”. Such advice doesn’t point students to specific strategies instrumental in building more interconnected knowledge frameworks (e.g., elaborative and organizational strategies) (Dembo & Seli 2013) and can reinforce surface-level memorization and pattern matching approaches.

Because our teaching doesn’t guarantee student learning, because we desire our students develop deep and meaningful learning, and since we always say something about the learning process (intentionally or not), we, as educators, are responsible for engaging our students in developing as learners. We should be explicitly engaging our students in learning about and regulating their learning processes, i.e., developing their metacognitive skills.

As I advocate for our responsibility to aid students’ in learning how to learn, some common reactions include:

  1. Don’t people figure out how to learn naturally?
  2. Shouldn’t students already do this on their own?
  3. I don’t know metacognition and the science of learning like I know my specialty area.

Don’t we figure out how to learn naturally? Yes, learning is a natural process, but, no, we do not naturally develop deep and efficient approaches to learning – anymore than we naturally develop the skill of a concert musician or any other highly refined practice. Shouldn’t students already do this on their own? Ideally, yes, but the reality is most students’ prior learning experiences have led to ingrained surface learning habits.

Prior learning experiences condition how we go about learning, along with contextual factors, such as the guidance of parents and teachers. In general, students think they are good at learning and don’t see a need to change their approaches. They continue to get good grades using memorization and pattern matching – often cramming for exams – while lacking long-term memory of concepts and the ability to transfer these concepts to real applications. As long as our courses allow students to get good grades (their measures of “success”) with surface learning habits, such views will persist. Deep learning includes memorizing, i.e., knowing, things, but such durable and transferable learning requires much more than just memorization. It takes effortful intellectual engagement with concepts, exploring connections and sorting out relationships between concepts, and accurate self-assessment. Such approaches can be learned, and a few students do. More can if we explicitly guide them. Our students are not lazy, rather they are misguided by prior experiences. Let’s guide them!

I don’t know metacognition and the science of learning like I know my specialty area. Yes, it is important to be knowledgeable and proficient with what we teach. While we have done much with the content in our specialties, we have limited training, if any, training on metacognition (the knowledge and regulation of our thinking/learning processes) and the science of learning. However, as educators trying to improve our craft, shouldn’t we also be students of learning? This can start small and continue as a career-long pursuit. We can always improve! You also likely know more than you think you do. Your self-selection into advanced studies and a college teaching career are not an accident. As part of the select group of academics, you are likely already metacognitively skilled, even if you don’t realize it. Start small, with one thing. Learn about it and practice or recognize it in your own life. For example, peruse a copy of Linda Nilson’s Creating Self-Regulated Learners or James Lang’s Small Teaching, or attend a teaching workshop that sparks your interest. Then, confidently share it with your students and engage them in it as you teach your content. Your authentic experience with it demonstrates its relevance and importance. Once you have become comfortable with this, add another element. Over time, you will build practical expertise about the learning process. Along the way you will likely learn about yourself and make sense of your past (and present) learning experiences. I did!

Need help? Look for my next post, “Where should I start with metacognition?”

Acknowledgements

This blog post is based upon metacognition research supported by the National Science Foundation under Grant Nos. 1433757, 1433645, & 1150384. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the author and do not necessarily reflect the views of the National Science Foundation. I also extend my gratitude to my collaborating researchers, Dr. Holly Matusovich and Ms. Sarah Williams, for their support and critical feedback.

References

Dembo, M. & Seli, H. (2013). Motivation and Learning Strategies for College Success: A Focus on Self-Regulated Learning (4th ed.). New York, NY: Routledge.

Kaplan, M., Silver, N., Lavaque-Manty, D., Meizlish, D. (Eds.). (2013). Using Reflection and Metacognition to Improve Student Learning. Sterling, VA: Stylus.


Developing Affective Abilities through Metacognition Part 3: Recognizing Parallel Development of Cognition and Affect

by Dr. Ed Nuhfer, California State Universities (retired)

In Part 1, we showed how the initial views of behavioral scientists toward metacognition and affect led for a time to a view of intellectual development as exclusively cognitive. In Part 2, we showed that established ways of knowing each rest on unique concepts, and gaining a working understanding of any way of knowing requires first becoming aware of its supporting concepts.

In Part 2, we used the way of knowing for reaching ethical decisions to illustrate the practical necessity of understanding the four components of ethics and their relationships to each other. There seems to be no profession in which thought and practice do not involve ethical decisions, so it seems no accident that William Perry chose the title: Forms of Ethical and Intellectual Development in the College Years for his landmark book describing how higher education, when successful, changes students’ abilities to think.

Major ways of knowing, obviously ethics but even heavily objective ways of knowing such as science or quantitative reasoning, require us to commit to decisions that resolve conflicts between what we feel we want to be correct with what new knowledge leads us toward knowing to be correct. When a conflict occurs between feeling and knowing, it often arises from life experiences that we have not critically examined but which new knowledge and/or newly acquired processes of critical examination force us to confront. For part 3, we examine the role of metacognition to help understand how intellectual progress causes us to feel in certain ways as we work to gain a college education.

About a decade ago, I discovered that the Bloom team’s Taxonomy of the Affective Domain mapped so well onto the Perry Model of Intellectual Development (Nuhfer, 2008) that it provided a much-needed map for empowering metacognitive reflection on both affect and cognition. The map, summarized in Figure 1, greatly clarified for me how to better promote metacognitive development in both students and faculty. I hope that readers will find this map equally useful.

The researchers’ named equivalent stages of development appear in Figure 1’s rows, and the affective feelings noted in the middle column were those that I deduced from examining the affective comments of students recorded in Perry’s book and other studies, made within the stages deduced through researchers’ longitudinal interviews. Longitudinal studies were the basis for the Perry stages and also for the studies that followed after Perry (see Journal of Adult Development, 2004).

Figure 1. Parallel development of intellectual and affective capacities through higher education (slightly modified from Nuhfer, 2008). Metacognition must engage with emotions (middle column) if it is to be effective in advancing adult intellectual development. Otherwise, metacognition becomes just an additional tool for increasing absorption of disciplinary content.

When students know that becoming educated involves passing through an established sequence of developmental stages, each with its own defining cognitive and affective traits, they have a map that they can use to discover their present location and to guide them toward what lies ahead on the path to gaining an education. Regarding metacognition’s description as “thinking about thinking,” awareness of the sequential stages with their accompanying emotions allows students to expect, reflect, and then resolve the discomforting affective feelings that arise. Trepidation and even some fear are normal, and they even can serve as important indicators of progress in cognitive growth.

Those who strive to become educated engage in a journey toward the highest Perry Stages of intellectual development through passing through the earlier stages. Achieving resolution of our reactive affective feelings that occur during these transitional stages is often an internal struggle. Metacognition, a reflective internal conversation with self about our thinking, seems indispensable to this growth.

Important Questions when Linking Bloom’s taxonomies and Perry’s stages

Bloom’s Taxonomy of the Cognitive Domain (see Scharff, 2017) is one of the best-known contributions to education, but experts debate the degree to which the Bloom cognitive levels are hierarchical, developmental products. In contrast, the developmental character of both the Perry model and the Taxonomy of the Affective Domain is generally accepted. That both address the sequential development of college students explains why the two map better onto one another than do even the two Bloom team’s taxonomies of the cognitive and affective domains.

The map provided by Figure 1 illuminates a possible deficiency of learning design in higher education. Educators consistently refer to Perry’s highest stages of intellectual development (7, 8 & 9 – see Figure 1) as the stages characterized by metacognitive reflection. The lower stages seldom receive that recognition, so why might that be? Is metacognition just not happening in the preceding stages? If so, why not?

If those who have actually engaged in metacognition throughout their intellectual development are just those few who develop metacognitive ability spontaneously on their own, this accounts for its scarcity in the earlier stages and how few achieve the highest stages. Because intellectual and affective development requires passage through a sequence of stages, we instructors can only increase the proportion of those who attain highest-stage reasoning abilities by infusing metacognitive skills into the earlier stages as a part of our instructional design. Such design would shift all students’ perceptions of gaining an education from absorbing content provided by teachers in classrooms toward developing abilities to understand content in concert with developing understanding of self.

Dangerous Passages

Two dangerous passages in the journey through the stages of intellectual development end the educational aspirations of many students to achieve a true education marked with a celebratory graduation. Figure 1 offers a map that reveals the dangerous passages of our journey, where impactful emotions can urge us to give up on our own development. These are places where metacognition informed by only a little research on adult development can provide valuable assistance.

Many lower-division undergraduate students fail to graduate by getting trapped at the lower Perry stages 2 and 3. Stage 2 students typically view the purpose of education as learning facts rather than as experiencing challenges that develop expanded capacities to think. Further, students in Stage 2 often learn that beliefs and childhood teachings that they revere are, upon examination, flawed and perhaps even untrue. This sends them to Stage 3 and the bankrupt belief that all conclusions and arguments are equally valid. From there, educators’ efforts to move students into higher stages of thinking bring forth students’ affective reactions of frustration and bewilderment. These negative feelings can negate students’ trust in teachers and raise students’ doubts about their own abilities. At this stage, gaining relief by giving up can seem an attractive choice.

Another passage takes a similar toll, but this one manifests later, where it produces attrition of nearly half of our brightest students who gained admission to graduate school to achieve doctorates. Most Baccalaureate graduates are only Stage 4 thinkers, and in graduate school, the barrier to completion is the required dissertation, which is a challenging, open-ended Stage 5 project. Stage 5 challenges cannot be addressed by the same approaches that brought much undergraduate success— demonstrating rote knowledge and ability to perform calculations that arrived at uniquely “right answers.” The transition into Perry’s Stage 5 brings proficiency to evaluate conflicting evidence and arrive, not at “right answers,” but at conclusions that are most reasonable after evaluating all of the relevant, conflicting knowledge currently available. This high-attrition passage, not surprisingly, comes again with strong emotions. Powerful negative feelings of personal inadequacy or “imposter syndrome” often accompany the efforts to advance out of Stage 4, and too many graduate students lose confidence and withdraw before they can make the transition. If these distressed students understood the nature of the situation they were in, they likely would persist, trusting that continued perseverance would bring the necessary punctuated transition to Stage 5. With this transition comes the confidence and awareness necessary to engage ambiguous problems, which include dissertations.

In blog column Part 4, we will look at developing the affective quality of academic courage, which allows one to persist through challenges that bring fear and erosion of confidence.

References

Gigerenzer, G. (2007) Gut Feelings: The Intelligence of the Unconscious. New York. Penguin.

Journal of Adult Development (2004) Special volume of nine papers on the Perry legacy of cognitive development. Journal of Adult Development (11, 2) 59-161 Germantown NY: Periodicals Service Co.

Nuhfer, E. B. (2008) The Feeling of Learning: Intellectual Development and the Affective Domain: Educating in Fractal Patterns XXV. National Teaching and Learning Forum 18 1 7-11.


In Remembrance of Dr. Gregg Schraw and Dr. Marty Carr

By Hillary Steiner, Ph.D., Kennesaw State University and Aaron S. Richmond, Ph. D., Metropolitan State University of Denver

In this first blog post of 2018 we remember two educational psychologists with interests in metacognition who recently passed away. Aaron Richmond and Hillary Steiner describe how their personal and professional interactions with these scholars influenced their own work.

From Aaron: In my career as an educational psychologist, I was more than lucky to work with Gregg—I was honored. On September 16th, 2016, Gregg passed away with his sweet wife Lori by his side. Gregg was a prolific researcher in metacognition and in other educational research fields. He published over 90 journal articles, 15 books, and 45 book chapters. He sat on several editorial boards including the Journal of Educational Psychology, Metacognition and Learning, Educational Psychology Review, etc. He was an active member of Division C (Learning and instruction) in the American Educational Research Association, and several other regional academic conferences such as Northern Rocky Mountain Educational Research Association (NRMERA).photo of Dr. Gregg SchrawYes, Gregg was a prolific scholar, however, his greatest gift was to his students and colleagues. One of my dear friends and fellow metacognitive researcher Rayne Sperling at Pennsylvania State University wrote, “Gregg’s confidence in me and steady, supportive guidance provided the self-efficacy boost I needed in order to believe in myself as a scholar with something to say. As co-chair of my dissertation, mentor throughout my career, and dear friend always, Gregg was a strong, positive force in my life. Now, my own doc students tell me I am a wonderful, supportive mentor, and I always tell them, “I am just doing what I was taught; mentoring as I was mentored.” Gregg taught me this too. His mentoring continues with the students he mentored (and there are a lot of us) who now have students of our own.” (McCrudden, 2016, p. 681).

I had followed Gregg’s career, seen him at conferences—in awe of course with a star-struck gaze and for me, Gregg was a research icon. He was a mega-god for which I was not worthy. However, when I first met Gregg at NRMERA in the fall of 2003, I was a dewy-eyed graduate student who had plucked up the courage to introduce myself to discuss metacognitive research. I quickly realized that yes—he was a research god, but more importantly he was a kind, generous, supportive, and inclusive person / human. He listened to my good ideas and listened to my half-cocked ideas that needed serious fine-tuning. After that fateful day in Jackson Hole, Wyoming I knew that I had gained a mentor of all things. Gregg supported me through my career in both research and teaching. We published together, and he was one of my advocates. He advanced my career like so many others. He doled out sound and sincere professional advice willingly. For example, Gregg, Fred Kuch, and I were working on some metacognition research together and my students were working quite hard and doing a great job on the project. Mind you, I am at a large state university with no graduate students so these were undergraduate students. Gregg was so impressed with one of my students (because of the mentorship he and his students had provided me which I had passed on to my students) he offered to write her a letter of recommendation for graduate school. I found this simple but powerful and impactful gesture to be astonishing and yet typical of Gregg’s passion for advancing high quality scholars in the field of metacognition and educational psychology. This was just one simple example of how Gregg went out of his way to help people and support their goals and pursuits.

In the end, Gregg didn’t have to be, but he was my mentor like so many others. Gregg am I indebted to you and you will truly be missed. The field of metacognition lost a great scholar, mentor, and friend.

From Hillary:

On July 30, 2017, the field of metacognition lost another great. Dr. Martha “Marty” Carr, Professor of Educational Psychology at the University of Georgia, passed away at the young age of 59. A prolific researcher who mentored countless students to become scholars in their own right, Marty combined her interests in metacognition, motivation, giftedness, and mathematics achievement to impact the field of educational psychology in a unique way, asking big questions about how children’s metacognitive strategies influence the gender differences that emerge in mathematics achievement, and how metacognition differs in gifted children.

photo of Dr. Marty Carr

Marty began her career in developmental psychology at the University of Notre Dame under the tutelage of John Borkowski, followed by a postdoctoral stint at the Max Planck Institute for Psychological Research in Germany, where she quickly made important contributions related to the influence of motivation and metacognition on children’s learning strategy development. After joining the faculty of the University of Georgia in 1989, where she remained for her entire career, she began to cultivate additional interests in giftedness and mathematics strategy development. These varied interests dovetailed throughout the years, as she wrote about metacognition in gifted children, motivational and self-regulatory components of underachievement, and metacognitive influences on gender differences in math. Marty’s work was known for its methodological rigor, its unique application of developmental models and methods to learning processes, and its applicability to the classroom. She was recognized in particular for groundbreaking work on the predictors and influential factors of gender differences in mathematics. Her contributions led to national recognition and leadership, including presidency of the American Psychological Association’s Educational Psychology Division (Division 15), presidency of the Women in Mathematics Education division of the National Council for Teachers in Mathematics, and numerous awards, including the American MENSA Education and Research Foundation Award for Excellence.

As my dissertation advisor in the early 2000’s, Marty was the first person to make me feel like a scholar. She recognized my interests in giftedness and cognitive development and provided the perfect combination of support and encouragement that helped me craft a line of research that continues to this day. And I am not alone. At her memorial service, several students commented on how much her mentorship had meant to them. According to student Kellie Templeman, “her skill in striking the balance between technical knowledge, compassionate guidance, and tireless work ethic was what separated her from any other professor I have worked with.” She promoted metacognition in her own students by asking them to reflect constantly on the “why” questions of their individual projects and to remain goal-driven. As another former student noted, Marty pushed us to “keep going, get busy, and keep writing,” learning from our mistakes as we went. Yet, as a devoted mother who had many outside interests, including marathon running and working with animals (especially cats and horses) Marty was also an excellent model of work-life balance.

When I attended the American Educational Research Association conference as a graduate student, Marty introduced me to Gregg Schraw, who was to be my assigned mentor for the week. I was starry-eyed at meeting such a great figure in my field, but later realized that others were equally starry-eyed to meet Marty. Marty and Gregg were truly giants in educational psychology whose contributions have transformed the way we think about metacognition. May we continue to honor their memory in our own work.

References

McCrudden, M. T. (2016). Remembering Gregg Schraw. Educational Psychology Review28(4), 673-690.

 


Boosting Metacognition through In-Class Assessments

By Jennifer A. McCabe, Goucher College

Five years ago, I radically changed the assessment format of my undergraduate Human Learning and Memory course, from a more traditional model with three big exams to a frequent low-stakes testing approach, which involved administering a short quiz to start most class periods (and nixing big exams). This choice came on the heels of a shift from a content-driven focus to an elaboration and integration emphasis in this course, and a shift from a textbook to five popular press books about learning and memory (syllabus available by request). I decided that the assessments should more intentionally reflect a central goal for the course that students would come to class each day prepared to actively engage with and discuss the assigned material. When I first made this change, I gave little explicit thought to metacognitive development in my students; as I describe in this blog post, along the way I tweaked the way the quizzes were framed and administered to more transparently support metacognition.

The first iteration of the daily low-stakes assessment was described as a “KCA Quiz,” designed to assess (and improve) students’ Knowledge, Connection, and Application (“KCA”) of course topics and readings. At the start of most class periods, students had about 10 minutes to complete a 5-item open-book and open-notes quiz, which could include factual questions, connection questions, application questions, and thought/opinion questions. These would mainly focus on the reading assignment for the current day, but could also draw from prior assigned readings/topics. Students were expected to bring all their notes and books to class each day in hard copy (no electronics allowed), for reference. After collecting the quizzes, we discussed the answers as a large group, and then the quizzes were graded on a scale of 0 (absence) to 1 (0 or 1 correct) to 2 (2 or 3 correct) to a maximum of 3 (4 or 5 correct).

Certainly some elements of this assessment strategy had the potential to impact metacognition. For one, there was a consequence for lack of preparation if students could not find the answers in time. Also, receiving immediate feedback in class about whether their answers were correct should have given them insight into their learning. Yet, given what we now know about the power of retrieval practice (i.e., the testing effect; see recommended reading below), namely the inherent memory and metacognitive benefits, I was dissatisfied with the low (or no) expectation that students would retrieve the information from memory without using external sources. Therefore, I worked toward developing a modified version of “KCA Quizzes” that would better support retrieval practice and metacognition, yet preserve the low-stakes and frequent-testing components.

Starting in Fall 2016, I made several changes to this component of the course. First, I started calling them “KCA Assessments” instead of “KCA Quizzes.” Previously, I would get some complaints – in person and on course evaluations – about the pressure and stress of having a quiz every day. Simply shifting the language from “quiz” to “assessment” completely eliminated those complaints. I think that being “assessed” rather than “quizzed” activates a different schema for the students – perhaps representing a metacognitive shift from a performance focus to more of a learning focus.

This is particularly striking given that along with the name change, I made the assessments more challenging. Now they are a hybrid of closed- and open-books/notes, with a unique metacognitive twist. Students start by dividing their paper into left and right columns. For the first five minutes, they answer the five questions from memory (closed-book) in the left column. Then, I announce they can open their books and notes, and anything they want to add or modify about their answers is written in the right column. They know that I grade their answers (using the same generous scale described above) based only on whether they got them correct through the combination of closed- and open-notes. Yet using the left-right column method, they are forced not only to spend time effortfully retrieving the information (or even just trying – which as we discuss in class, still benefits memory), but also have a clear record of how easily and accurately they could arrive at correct answers from long-term memory, without consulting external sources. This supports metacognition by building students’ explicit awareness of their level of learning, which can then be used to guide their further learning behaviors. I encourage them to strive to be able to answer all the questions in the left column, but the pressure of testing is relieved by the back-up plan to consult course materials.

Recently, I administered a brief anonymous feedback survey about the KCA Assessments. Of the 21 students who responded in a class of 25, 86% agreed or strongly agreed that the assessments “improved my metacognition – that is, they helped me think and know more about my own learning and memory.” When asked an open-ended question about which aspect(s) of the assessments supported metacognition, 65% identified the closed/open-book hybrid approach, with comments such as:

“You couldn’t be convinced you know something if you couldn’t get it during the closed- book portion.”

“Helped me see what I actually remembered and what I needed help with or didn’t encode or couldn’t retrieve.”

“This allowed me to use my own memory to remember answers and gave me an idea of what I need to focus on more for when I read for the next class.”

“Having the closed then open note format really obviously shows what you processed more deeply than others.”

Other answers described the focus on deeper processing and application to real-life issues, learning to be more interactive and engaged with course reading assignments, getting immediate feedback after the assessments, and the reduced-pressure grading scale. The majority (90%) probably or definitely “would recommend keeping the KCA Assessments for future classes.”

The current iteration of this in-class assessment strategy grew from my own metacognitive insight as an instructor, with regard to balancing student learning, engagement, and incentives for examining and potentially changing learning strategies. Based on observing student performance, and on student feedback on course evaluations and from this survey, this approach is palatable (even enjoyable) for students, encourages deep and elaborative reading, supports durable memory for course material, and – at least by way of self-report – boosts metacognition in undergraduates.

Recommended Reading

Putnam, A. L., Sungkhasettee, V. W., & Roediger, H. L. (2016). Optimizing learning in college: Tips from cognitive psychology. Perspectives on Psychological Science, 11, 652-660. doi: 10.1177/1745691616645770

Roediger, H. L., & Pyc, M. A. (2012). Inexpensive techniques to improve education: Applying cognitive psychology to enhance educational practice. Journal of Applied Research in Memory and Cognition, 1, 242-248. http://dx.doi.org/10.1016/j.jarmac.2012.09.002


Introducing Metacognition to Students

by Hillary Steiner, Ph.D., Kennesaw State University

The students in my first-year seminar were engaged in a small group activity, which had spread outside of the classroom into the hallways. It was my first semester teaching this seminar, and we were approaching midterm. “Adam,” a good student who normally acted as a leader during group activities, sat alone, trying to stifle tears. He seemed grateful that I cared to ask what was wrong, but doubtful that I could help. His story was one I’d heard before. After years of straight As in science classes, he was encountering his first failures in an important chemistry course that was a gateway course to his major. His plan was to drop the course and rethink the career plans he’d first made as a child. Could I explain why “studying like crazy” wasn’t working? His chemistry professor couldn’t. While I had introduced good study strategies to the students a few weeks prior, this touching conversation caused me to rethink the way I approached the topic. Drawing on my background in educational psychology, I came to two conclusions: 1) I needed to make sure students understood the why behind study strategies so they’d be better prepared to implement them, and 2) I needed to reach out to other faculty to encourage the application of these strategies in the context of content-area courses. Since that time, I’ve written about these activities for a faculty audience (Steiner, 2014; 2016; Steiner, Dean, Foote, & Goldfine, 2013; 2016) and changed the way I approached metacognition.

Lately there seems to be a buzz about metacognition at my institution. Dr. Saundra McGuire, Director Emerita of the Center for Academic Success at Louisiana State University and author of a popular book on the topic (McGuire, 2015), visited our campus recently to speak about the importance of metacognition. Unlike me, who first learned of metacognition in my graduate training, McGuire discovered metacognition from outside educational psychology. As a chemistry professor, she saw the powerful ways her students’ learning was transformed when they used metacognitive strategies. Inspired by her campus visit, many faculty began requesting more information about how they could use metacognition in their own classes. At our teaching and learning center where I currently serve as a faculty fellow, my colleagues and I responded by offering more workshops and consultations on how to put the concept into practice. In these interactions, most faculty easily grasped metacognition, understood its importance, and were able to generate some strategies for their courses. However, what they needed was a quick and easy way to promote the idea to students—a concise primer for how (and why!) to become a metacognitive college student. I realized that such a document could also serve as a jumping-off point for discussion with my own students.

The handout was developed with this in mind. Keeping in mind students’ motivations for using such a document, I kept the language brief, encouraging, and jargon-free. I did not include scholarly references, but I did include a short list of resources students could access for further reading. My intent was to provide students enough of an explanation and rationale for metacognition that they’d have sufficient motivation to put the suggested strategies to use in an authentic context. Many faculty with whom I’ve worked feel they lack adequate time to introduce metacognition in their content-area courses. However, while first-year seminars and learning-to-learn classes offer a great opportunity to talk at length about metacognition, students especially benefit when content-area faculty encourage it in their individual disciplines. I am hopeful that this handout can serve as a resource for time-strapped faculty to distribute to their students who, like Adam, are searching for that life hack that will help them succeed in college.

References

McGuire, S. Y. (2015). Teach students how to learn: Strategies you can incorporate into any course to improve student metacognition, study skills, and motivation. Sterling, VA: Stylus.

Steiner, H. H. (2014). Teaching principles from cognitive psychology in the first-year seminar. E-Source for College Transitions, 11, 14-16.

Steiner, H. H. (2016). The strategy project: Promoting self-regulated learning through an authentic assignment. International Journal of Teaching and Learning in Higher Education, 28, 271-282.

Steiner, H.H., Dean, M. L., Foote, S. M., & Goldfine, R. A. (2013). Applying TLC (a targeted learning community) to transform teaching and learning in science. Learning Communities Research and Practice, 1(3), Article 5.

Steiner, H. H., Dean, M. L., Foote, S. M, & Goldfine, R.A. (2016). The targeted learning community: A comprehensive approach to promoting the success of first-year students in general chemistry. In L. C. Schmidt & J. Graziano (Eds.), Building synergy for high-impact educational initiatives: First-year seminars and learning communities. Columbia, SC: National Resource Center.


It shouldn’t be Top Secret – Bloom’s Taxonomy

By Lauren Scharff, Ph.D.,  U. S. Air Force Academy *

Across the past year or so I have been reminded several times of the following fact: Most students are not aware of Bloom’s Taxonomy, and even if they are aware, they have no clue how or why their awareness of it might benefit them and their learning. Most instructors have heard of at least one version of Bloom’s Taxonomy, and some keep it in mind when designing learning activities and assessments.  But, rarely do instructors even mention it to their students.

Why don’t instructors share Bloom’s Taxonomy with their students? Is it a top secret, for instructors only? No! In fact, awareness and use of Bloom’s taxonomy can support metacognitive learning, so students should be let in on the “secret.”

What were the key experiences that led me to this strong stance? Let me share….

In May of 2016, I was fortunate to attend a keynote by Dr. Saundra McGuire at High Point University. In her keynote address and in her book, Teach Students How to Learn (2015), McGuire shared stories of interactions with students as they became aware of Bloom’s Taxonomy and applied it to their learning. She also shared data showing how this coupled with a variety of other metacognitive strategies lead to large increases in student academic success. Her work served as the first “ah ha” moment for me, and I realized that I needed to start more explicitly discussing Bloom’s Taxonomy with my students.

An additional way to highlight Bloom’s Taxonomy and support student metacognitive learning was shared this past October (2017) when Dr. Karl Wirth led a workshop as part of our 9th Annual Scholarship of Teaching and Learning (SoTL) Forum at the U. S. Air Force Academy. In his workshop he shared examples of knowledge surveys along with data supporting their use as a powerful learning tool. Knowledge surveys are collections of questions that support student self-assessment of their knowledge, understanding, and skills. When answering the questions, students rate themselves on their ability to answer the question (similar to a confidence rating) rather than fully answering the question. Research shows that most students are able to accurately self-assess (confidence ratings correlate strongly with actual performance; Nuhfer, Fleisher, Cogan, & Gaze, 2017). However, most students do not take the time to carefully self-assess their knowledge and abilities without formal guidance and encouragement to do so. In order to be effective, knowledge surveys need to ask targeted / granular questions rather than global questions. Importantly, knowledge survey questions can span the full range of Bloom’s Taxonomy, and Dr. Wirth incorporates best practices by taking the time to explain Bloom’s Taxonomy to his students and explicitly share how his knowledge survey questions target different levels.

Sharing Bloom’s Taxonomy in our classes is a great first step, but ultimately, we hope that students use the taxonomy on their own, applying it to assignments across all their courses. However, just telling them about the taxonomy or explaining how aspects of our course tap into different levels of the taxonomy may not be enough to support their use of the taxonomy beyond our classrooms. In response to this need, and as part of an ongoing Scholarship of Teaching and Learning (SoTL) project at my institution, one of my student co-investigators (Leslie Perez, graduated May 2017), created a workshop handout that walks students through a series of questions that help them apply Bloom’s as a guide for their learning and academic efforts. This handout was also printed in a larger, poster format and is now displayed in the student dorms and the library. Students use the handout by starting in the middle and asking themselves questions about their assignments. Based on their answers, the walk through a path that helps them determine what level of Bloom’s Taxonomy they likely need to target for that assignment. It should help them become more explicitly aware of the learning expectations for their various assignments and support their informed selection of learning strategies, i.e. help them engage in metacognitive learning.

Figure 1. Snapshot of the handout we use to guide students in applying Bloom’s Taxonomy to their learning.  (full-sized version here)

As someone who is a strong proponent of metacognitive learning, I have become increasingly convinced that instructors should more often and more explicitly share this taxonomy, and perhaps even more importantly, share how it can be applied by students to raise their awareness of learning expectations for different assignments and guide their choice of learning strategies. I hope this post motivates instructors to share Bloom’s Taxonomy (and other science of learning information) with their students. Feel welcome to use the handout we created.

————

McGuire, S. (2015). Teach Students How to Learn. Stylus Publishing, LLC, Sterling, VA.

Nuhfer, E., Fleisher, S., Cogan, C., Wirth, K., & Gaze, E. (2017). How random noise and a graphical convention subverted behavioral scientists’explanations of self-assessment data: Numeracy underlies better alternatives. Numeracy, 10(1), Article 4. DOI: http://dx.doi.org/10.5038/1936-4660.10.1.4

* Disclaimer: The views expressed in this document are those of the author and do not reflect the official policy or position of the U. S. Air Force, Department of Defense, or the U. S. Govt.


Contemplating Contemplative Pedagogy

by Alison Staudinger, Ph.D., University of Wisconsin – Green Bay

Like many trained in the academy, I am skeptical of “woo”– practices with trappings of scientific import, but lacking empirical evidence. This is despite my recognition that science has always been suffused by power and social hierarchy in the very framing of its questions. In my pedagogical life, this means it has taken me a long time to warm up to “mindfulness,” a powerful, relatively recent trend in education. Mindfulness is sometimes touted as the solution to many serious problems— lack of emotional constraint, student stress and even faculty burnout. Some might wonder if its popularity doesn’t merely adjust us to the difficulties of life in late capitalism, which in the classroom often appear through long days of emotional labor. But, of course, there are branches of mindfulness associated with nearly every culture and major religion on the globe, many with complex histories and practices that have clearly been important for humans long before our fears of robot overlords emerged. Still, I tend towards asking many of my students to come into more contact with the world, not less, as I feared that meditation or the like might do. Contemplation might be good for self-care, I thought— or working through one’s own “shadow self,” just like therapy, but the justice-oriented classroom requires the tools of critique and conflict. Or does it?

My above assumptions were powerfully challenged at the The Center for Contemplative Mind’s Summer Session on Contemplative Learning in August of 2017, where I spent a week exploring the “tree” of contemplative pedagogy and practice, and did more coloring and dancing than at any other academic experience to date. I want to share three important concepts that might be useful for integrating a mindful approach to metacognition into your life or classroom. Ed Nufer has already written on the focus on the “present” that mindfulness brings, and Chris Was asked us to reconsider the relationship between mindfulness and metacognition. It is my hope that these three concepts are a tiny contribution to that reconsideration, and counter the idea that mindfulness practitioners seek to move beyond the self, rather than reflect on their learning.

First, presenter Kakali Bhattacharya shared how mindfulness helps her flourish in the often hostile institutional spaces of academia. Bhattacharya uses the image of a cup overflowing, saying that you must give to others from the overflow and thus must keep your cup full. For her, mindfulness as a method of self-care was coupled with a commitment to “post-oppositional” thinking and politics. Post-oppositionality requires rejecting existing narratives that frame struggles as Machichean battles between good and evil, a move that is difficult in our partisan times. However, this ability to recognize non-absolutes in a political sense may bear dividends in an intellectual one. Drawing on this, I replaced an assignment that had students debate two contrasting positions with one where they tried to reimagine the problem, offer a variety of solutions, or response from a position of intellectual humility about their own stance. While our in-class process was messy, their ultimate papers on the topic were creative and veered away from the same two arguments I’m used to reading.

The second concept, closely related to post-oppositionality, is “negative capability,” an idea taken from John Keats’ correspondence but now popular in psychology and business. Negative capacity names the ability to tolerate uncertainty, or, as Keats says, to be “capable of being in uncertainties, mysteries, doubts, without any irritable reach after fact and reason……”. (Cite Research). This might seem initially a strange concept to link to metacognition— it seems initially to involve not thinking about thinking, or, rather, willingly allowing yourself to think two contradictory things or to dwell in a lack of knowledge or understanding. For Keats, this is a process of imagination preferable to that of thinking, in the technical sense. Keats, as a Romantic, is generally understood as a critic of reason and fan of feeling. His poetic practice involves inhabiting the minds of his characters and even objects; he wrote that he could imagine a billiard ball enjoying “its own roundness, smoothness, volubility and the rapidity of its motion.” Cultivating these spaces of flow, or negative capability, might increase our ability to also reflect on our own learning and thinking, even as we, in those moments, refrain from committing to them or even to our own identity. Certainly an exercise to explore this idea would be easy to devise— although actually inhabiting an object is harder to do. In a class on ecology, imagining oneself as a plant and perhaps writing from that perspective might open up new vistas but also encourage negative capacity as a tendency of mind.

My mindfulness experience also left me wondering about the costs of integrating some of these practices into student learning shorn of their embeddedness into spiritual or cultural traditions, which brings me to the third concept— of avoiding treating mindfulness as a mere means to an end. Meditation is central to buddhism, but also to a variety of indigenous spiritual practices, and I wondered if they would work without this framework. Were they turned into, as one presenter worried, “McMindfulness” practices? One person I met was passionate about the notion that in meditation there is “No path, no wisdom, no gain” — a radical de-instrumentalization of the practice. To fully understand this saying would take a great deal of meditation, but I began to recognize throughout the week that the focus on the inward development that can occur in mindful practice was, paradoxically, likely to bear more fruit if not linked to specific goals or learning objectives from the outside. This realization was very hard to think about integrating in my classrooms— as each day is driven by specific goals linked to broader course objectives. My challenge for this year is to develop the negative capacity I need in order to engage in some of these practices with my students non-instrumentally while also recognizing the benefits research has shown for improving learning, happiness and health. And, I may need a commitment to post-oppositionality to navigate barriers to “woo” in some academic cultures.


Developing Affective Abilities through Metacognition Part 2: Going Granular

Ed Nuhfer, California State Universities- retired

In Part 1, we noted that the highest stages of thinking are not merely cognitive, but they require cognitive knowledge and skills with the addition of metacognitive reflection involving affect. We also promised to present some ways to help students increase the capacity for reaching these highest levels of thinking through using metacognition to understand and develop affective reasoning.

Granular components make up a whole shape

This contributed post, Part 2, has three components. The first recognizes that understanding a way of knowing can take two forms, global and granular. The second provides research-based evidence that gaining an understanding of a metadiscipline’s way of knowing (e.g., science) by gaining awareness of the essential interconnections (granular approach) that constitute the metadiscipline is more effective than trying initially to understand the metadiscipline through considering it as a whole (global approach). The third introduces an example of a heavily affective way of knowing—ethics— and its interconnected components.

  1. From describing to understanding

The popular definition of metacognition as “thinking about thinking” invites a universal response: “OK. So, now what do we think about?” No individual invented or discovered any complex way of knowing, such as science or ethics. Instead, these ways of knowing developed over a long time through the collective contributions of many workers. Over centuries, added insights made awareness of new concepts possible, and better understanding allowed an improved global articulation of each specific way of knowing.

In a few years of college education, we strive to produce understanding of bodies of knowledge that took centuries to develop. We believe that an effective sequence of gaining understanding of a metadiscipline usually recapitulates the historical order of its development. This parallel process for understanding a complex way of knowing involves first becoming aware of the essential interconnected concepts. Afterwards, scholars have increased capacity for constructing their global understanding of a way of knowing by learning how each concept contributes to the reasoning process that characterizes that way of knowing. To aid teaching and assessments of major ways of knowing, it is valuable to distinguish how global and granular queries elicit different ways of thinking and understanding.

Global approaches to understanding address complex issues with a single question. Examples are “How do you treat others ethically?” and “How well do you understand science?”

Granular approaches to thinking address the interconnected concepts that enable specific ways of knowing. For example, the Science Literacy Concept Inventory (SLCI) (Nuhfer et al. 2016a) is a granular instrument. It addresses a dozen interconnected concepts that science rests upon through twenty-five multiple-choice challenges. The composite score on all twenty-five items provides the measure of competence to answer the global challenge of “How well do you understand science as a way of knowing?” It achieves this measure without either directly asking participants the global question or asking them to name any of the specific concepts.

An example query from the SLCI follows. 

  1. Which of the following statements presents a hypothesis that science can now easily resolve? 
  1.  Warts can be cured by holding quartz crystals on them daily for a week.
  2. A classmate sitting in the room can see the auras of other students.
  3. Radio City Music Hall in New York is haunted by several spirits.
  4. People with chronic illnesses have them as punishment for past misdeeds.

The query tests for a granular understanding of science as a way of knowing the physical world through testable hypotheses. The query seeks to see if a student can recognize which of the statements is testable and addresses the physical world. All four options present possible hypotheses, but only one option offers a testable hypothesis and addresses physical phenomena. Note that the query tests for understanding, not for a memorized definition of “hypothesis” or “science.” Answers to twenty-five such questions that address a dozen concepts give a highly reliable assessment of understanding science as a way of knowing.

Now comes the rub. Experts can perform effective metacognition of their understanding in direct response to a single complex global question because their understanding has already assimilated the essential granular concepts that underlie science. Their knowing “what to think about” now comes intuitively from long experience. Novices (students) who directly try to address a global question about a complex issue don’t yet have the experiences that enable experts to respond quickly by unconsciously incorporating the most essential granular concepts in their informed response.

Novices need to methodically consider each of the granular concepts as checkpoints before they can reach a well-informed response. With practice in doing so over time, they can internalize the concepts and intuitively employ them more holistically. An early start in recognizing that granular-to-global-understanding process helps to achieve internalizing earlier in one’s career or education. Without instruction, the process will not begin until a challenge makes the need for the skill apparent, and an inept response can prove costly if the challenge involves a high-stakes decision.

  1. Granular disclosure deepens understanding quickly — the evidence from science

As noted, experts have the advantage of experience. However, their traditional educational experiences rarely included metacognitive reflection, so few of our current experts had the privilege of early understanding that might have resulted from undergraduate instruction on how to achieve an understanding of an ambiguous problem through metacognitive reflection on the most relevant underlying checkpoints of a relevant way of knowing. Many experts achieved this only after high-stakes challenges forced them to adopt more appropriate thinking.

If instructors explicitly engaged in relevant metacognitive instruction, might we be able to produce better future experts than exist now? Research says “yes” by showing that minds gain an increased global understanding of science simply from responding to a granular spectrum of queries that address the interconnected concepts that underlie science (Nuhfer et al., 2016b; 2017).

These research measures started with a global query that honestly disclosed the nature of the SLCI and asked students to estimate their anticipated scores. Our current dataset consists of 1576 participants, and the correlation between their estimates from this initial global self-assessment and their actual test scores was r = .28.

Following the global query, participants completed the SLCI knowledge survey. Knowledge surveys are granular self-assessment instruments that direct students to reflect metacognitively on the interconnected, granular components underlying a comprehensive topic. The SLCI contains 25 test items. For this research, participants first rate their competency on each item and then they answer all the questions. The correlation between the cumulative self-assessment on all 25 items on the entire knowledge survey and participants’ demonstrated competence from their score on the SLCI was r = .6. On later postdicted global queries (recorded after taking the knowledge survey and after taking the Inventory), the correlations between the global self-assessed scores and the actual SLCI scores all remained high at between r = .5 and r = .6.

These results offer a valuable insight: students knew no more content about science after taking the knowledge survey than they did before taking it because no instruction or study was involved. However, taking a knowledge survey provided a granular disclosure of what they must “think about” and conveyed a significantly better understanding of the complexity of the global query than did a detailed global description of the query. Improved metacognitive understanding of the challenge relative to one’s immediate competency is not the same thing as improved content knowledge. Rather, the former clarifies to the learner the specific content learning that one needs to get to improve his or her overall competency.

 When we decide to teach a complex way of knowing, conveying an understanding of what the knowing involves (i.e., conveying the granular concepts) will contribute to success. Further, metacognitive exercises are more effective than hearing the key points in lectures, because metacognitive reflection is focused interactive engagement with the problem. The focused conversation with self that is the hallmark of metacognition enlists sufficient parts of the brain to build understanding. Listening alone engages relatively little of the brain’s neural network and produces little understanding that can be retained. Metacognitive exercises will be most effective if we build students’ competence through taking a granular approach from the very start. We want to direct our students to think about and internalize the checkpoints rather than to try to answer the global question directly from unexamined feelings.

  1. From science to ethics

Science focuses on cognitive thinking that uses testable evidence. Instructors are most familiar with developing such thinking, which lies within Perry’s stages 4, 5 and 6. Developing highest level thinking abilities, (stages 7, 8 and 9) requires additional components that allow us to go beyond constructing strong, defendable arguments and enter the realm of using our results for making decisions and acting on them. These highest levels of thinking are metacognitive and affective. Reaching them requires that we develop an awareness of how our own affective feelings are an influence on our decisions, and it further requires that we develop capacity for empathy so that we truly understand how our actions impact others.

Like science, ethics constitutes a complex way of knowing, but the latter is a way of knowing that involves more affect. We treat one another ethically because we feel that we should do so, even when competing feelings and pragmatic arguments may exist to do otherwise in our perceived self-interests. Thus, an understanding of ethics requires understanding a different set of interconnected concepts.

The four granular ethical principles or concepts are, beneficence – “do good;” nonmaleficence – “do no harm;” justice – “treat equals as equals,” and autonomy – “respect others’ control over their own lives.” These provide our checkpoints for granular understanding.

To help readers initiate a global understanding of an ethical decision as experienced through a granular approach, I’ve included a short module exercise with this blog entry. Open it; read it. The text is less than 900 words. Afterwards, confront a few of the reflective exercises at the end of the module.

In Part 3, we can pick up our discussion with deeper exploration of the role of affect and metacognition in making ethical decision. Afterwards, we can explore the role of metacognition in other affective dimensions of thinking.


Tackling your “Laundry” List through Metacognitive Goal Setting

by Tara Beziat at Auburn University at Montgomery

On almost every to-do list I make these days is the word “Laundry.” With two kiddos and a husband who is an avid exerciser, our laundry quickly piles up. Recently, when I told my husband I had everything washed, I paused and thought about my goal of getting the laundry done. I can never actually get it all done. The goal is too broad and it is not time bound. I paused again and thought here I go again being metacognitive: I have goals; I am monitoring them and seeing if I meet them; I realized I needed to make adjustments. In going through this metacognitive process at home, I realized there were applications in my classroom too. I needed to help my students reframe their goals of “reading the textbook or “studying” and build better plans to reach them.

Backwards Planning

The first thing we need to do with goal setting is to build better plans to reach those goals, which research suggests could involve working backwards from the end state of those goals, (Jooyoung, Lu & Hedgock; 2017). It seems that when we have distant goals that involve many tasks, like a comprehensive exam, mid-term project or final presentation, a variety of issues come into play. Inadvertently, obstacles or “speed bumps” slow down our momentum towards the end goal and leave us discouraged. By starting with the end goal (e.g. comprehensive exam) and working backwards to the present time, we often anticipate these potential hurdles. This type planning also leads to the creation of sub-goals. The relatively immediacy of these sub-goals and then the completion of them leads to greater motivation in meeting the final goal.

What this means in my course is that I need to help students develop a timeline, so they see all of the tasks and activities they need to do to reach their end goals. As we develop this timeline, we will work backwards. As we chart out the plan for success, we can acknowledge potential hurdles that may require them to take more time with one task or even shift their preparation. If a large project is due the Monday after the Iron Bowl, a significant event here in Alabama, they may need to consider when they can work on the project prior to that game. By forecasting these “speed bumps,” and planning out the steps in reverse to reach their ultimate goals.

Set Specific Goals

Schunk (1990) identified specificity as one of the keys in goal setting. When we set specific goals, we can better gauge the amount of time and effort it will take to complete this goal. Specificity also allows for better monitoring, a key component in being metacognitive, and can lead to increased self-efficacy as one meets these goals. So students’ goals of “doing well in the course” or “studying harder” are not specific enough and need to be adjusted. To do well in the course, students need to consider what does this actually mean and what sub-tasks are involved to reach this goal. For example, they need to consider what they need to get on the various quizzes and assignments in the course if they want to have an A. This leads to a discussion about preparing for class, allocating study time and allocating time to assignments for the course. All of these can go on this timeline where we work backwards.

Time-Bound Goals

The proximity of the goal plays a key factor in our motivation (Schunk, 1990). Goals that are proximal are more motivating than distal goals. This again goes back to why it is important to plan backwards. It allows us to set up intermediate proximal goals during the semester so we can reach the distal goals. Students (and even professors) often say they are going to study in the afternoons or they are going to read over the weekend. Invariably, “speed bumps” occur and the studying and reading are pushed aside. By blocking out time in your schedule, just like you block out time to attend class, with start times and end times you are more likely to devoted your undivided attention to the task. Dr. Paul Pacheco-Vega provides great advice about planning and how to set up your calendar to get your tasks done. He even shows how to adjust your schedule for when those speed bumps occur. The key is to set aside time in your calendar but also to be aware of that life may just throw you a curve.

By helping my students reframe their goals and build a backwards timeline of how to accomplish their goals, I increase the chances of my students not only being successful in my course but also in their future courses. I am also helping them become more metacognitive. They are learning metacognitive strategies related to setting goals and monitoring and evaluating their progress toward this goal. As an added benefit this approach may lead to higher self-efficacy and increased learning.

Metacognitive strategies are not just for the classroom or academic environment, they have helped me improve my laundry process too! I have set better goals for my chore of doing laundry. I start with the end goal, to have all of the laundry washed and put away by Monday morning. The “laundry” is limited to the clothes in the hampers on Friday. I then set out to complete one load of laundry on Friday, Saturday and Sunday and then I put it away on Monday. This plans leaves lots of room for the numerous unforeseen hurdles in rearing two children under two.

Jooyoung, P., Lu, F., Hedgcock, W. (2017). Forward and Backward Planning and Goal Pursuit. Psychological Science. DOI:10.1177/0956797617715510

Schunk, D. H. (1990). Goal Setting and Self-Efficacy During Self-Regulated Learning. Educational Psychologist, 25(1), 71-86


Fundamental concepts and bottlenecks as guides to metacognitive instruction

by John Draeger, SUNY Buffalo State

In an earlier post, Lauren Scharff and I argued that metacognition can help instructors select and apply appropriate teaching strategies (Draeger & Scharff, 2016). More specifically, we argued that metacognition encourages instructors to consider the particulars of each learning environment (e.g., student background, learning goals, classroom culture) and we offered a series of question prompts to guide the conversation (e.g., what are you doing to check-in with students? What strategy adjustments might you make?). This post extends that work by offering two additional conceptual anchors to ground discussion, namely fundamental concepts and bottlenecks.

First, fundamental concepts can serve as a conceptual anchor for metacognitive instruction. Gerald Nosich describes fundamental and powerful concepts as those “core ideas used to organize other ideas and unlock important questions, insights, and discoveries” (Nosich, 2012). When designing a course, fundamental concepts guide my decisions regarding how much to cover and how much time to devote to a particular topic. As I am making choices, I ask myself “how does this material help students better understand the fundamental concept of the course?” In assessment, I want my assignments to align with the most important aspects of the course and fundamental concepts articulate those important features. And in class instruction, fundamental concepts guide class conversation and provide a mechanism for refocusing peripheral lines of questioning. Therefore, if metacognitive instruction encourages me to be intentional about my learning objectives and student progress towards achieving them, then fundamental concepts serve as a constant reminder to me (and my students) of what is most important.

By way of illustration, the concept of justice is fundamental concept to my upper division course in philosophy of law. The course readings are roughly subdivided into theoretical discussions that articulate particular philosophical conceptions of justice (e.g., procedural, moral) and applications in the law (e.g., landmark United States Supreme court cases). The theories illuminate elements in the court cases and the cases provide illustrations of the theoretical features. Without explicit reference to a fundamental concept, the course can seem like an endless list of court cases with each case, and each detail of each case, seeming as important as all the others. Through an explicit focus on the fundamental concept, however, the course is organized around a conceptual web with justice at the center and theories and cases emanating out in order of importance (e.g., theories can articulate conceptions of justice and cases can be organized according to those conceptions). As someone aspiring to practice metacognitive instruction, I regularly check-in with students and make adjustments based on class discussion. When students seem to be “in the weeds,” I can use the concept of justice (and our various conceptions of it) as a way to refocus the conversation on what is most important to the course. We can then build back the details of the theories and the cases. Further, some students relish the details of cases, but they are less inclined to consider how the cases illustrate the theories that we’ve been reading. Again, the concept of justice allows me to reframe class conversation and build back the structural details of the course (e.g., theories of justice, court cases). Finally, I make adjustments in my preparation between class sessions based on my informal assessment of student understanding in relation to the fundamental concept. In this way, fundamental concepts work in conjunction with my efforts to be a metacognitive instructor.

A second type of conceptual anchor for metacognitive instruction can be found by considering the bottlenecks of a given course. Middendorf and Pace (2004) describe course bottlenecks as aspects of the course (concepts/skills) that are both essential to the course and places where students consistently struggle. Students in my philosophy of law courses, for example, often confuse descriptive claims (how things are) with normative claims (how things should be). This confusion can cause students to be frustrated by class discussion and flummoxed by written assignments. For example, students in the grips of this confusion tend to focus on the fact that the U.S. Supreme Court reached a decision by a 5-4 margin without considering that it can (or perhaps even should have been otherwise). They reason that if the court ruled this way, then that’s the end of the story (descriptive claim about how the law is). These students tend not to consider whether the court might have been mistaken in their ruling (a normative question). Even if these students memorize court rulings and the rationale for those decisions, they have not yet engaged with the normative underpinnings of the course (e.g., whether a particular ruling is just). As someone trying to practice metacognitive instruction, I need to monitor student progress and make necessary adjustments. Bottlenecks (e.g., student struggles with normative questions) give me a predictable place to check-in and refocus student attention.

Moreover, given that the fact I can anticipate that students are likely to struggle with normative questions (the bottleneck of the course), I am more intentional about course design, instruction, and feedback on assessment. For example, I intentionally begin the course with Martin Luther King Jr.’s “Letter from a Birmingham Jail” because King’s argument makes it clear that there is such a thing as an unjust law. We then follow up by considering a number of landmark cases early in the semester, such as Plessy v. Ferguson and Brown v. Board of Education. In the former, the court supported the “separate but equal” doctrine. In the latter, they rejected it. We talk about what made the Plessy unjust and why Brown readdresses that injustice. This launches into more theoretical discussions about the types of reasoning offered in those decisions and how they are related to the fundamental concept of justice. By considering these cases, students have early illustrations of a just and unjust law (normative claims). This exercise becomes a touchstone for later in the semester when students struggle with the descriptive and normative distinction. Because metacognitive instruction demands that I regularly check-in, I am tuned into the fact that students are often stuck in the normative bottleneck . When this happens, we can revisit our conversations about King, Plessy and Brown. Moreover, if this teaching strategy doesn’t work, then I know that I need to choose another strategy. Student understanding will be stymied unless I can help them overcome predictable confusions. Clearing the bottleneck, therefore, can open up learning opportunities, but clearing the bottleneck only happens if I am aware of student difficulties and willing to make changes (i.e. metacognitive instruction).

This post has built on the thought that metacognitive instruction can help instructors choose appropriate instructional strategies. In particular, fundamental concepts can help instructors be intentional and explicit about what is most important about their courses. Likewise, locating consistent sources of student difficulty can help frame where and how instructional energies can be best spent. In short, both fundamental concepts and bottlenecks ground metacognitive instruction by providing anchor points and guiding instructors towards promising teaching strategies.

References

Draeger, J. & Scharff, L. (2016). “Using Metacognition to select and apply appropriate teaching strategies.”Retrieved from https://www.improvewithmetacognition.com/using-metacognition-select-apply-appropriate-teaching-strategies/

Middendorf, J., & Pace, D. (2004). Decoding the disciplines: A model for helping students learn disciplinary ways of thinking. New directions for teaching and learning, 2004(98), 1-12.

Nosich, G. (2012) Learning to think things through: A guide to critical thinking across the disciplines. Saddle River, N.J.: Prentice Hall.


Developing Affective Abilities through Metacognition: Part 1

by Ed Nuhfer, PhD, California State Universities (retired)

Roman Taraban launched such an important topic for our blog on July 20 with “Hate-Inspired Webforums, PTSD, and Metacognition” that it is surely worth extending his discussion further.

Roman noted that groups develop recognizable vocabularies (discourse) and manners of speaking for set purposes. The purpose of developed vocabulary and manner of speech of hate groups is to enlist support and then empower and activate those with dispositions toward bias and bigotry. Activation in hate groups includes intimidation, shaming, shunning, and physical violence. Affect is the ultimate origin of discourse because the desire to promote such discourse is an affective feeling. Like cognitive thinking and psychomotor activity, affect is essential to human life and function. However, affect can guide us to act in ways that are ineffective, toxic, or destructive.

Learning and education are the processes through which we support and advance civilization. The purpose of civilization may be to elevate effective, beneficial actions and to minimize deleterious ones. Through learning and education, we develop frameworks of reasoning and processes for developing beneficial proficiencies. Examples of a psychomotor framework would be a process through which one learns to hunt for food, play a musical instrument, or to produce a painting. Examples of cognitive frameworks would be the logic of language and the use of testing and verification as a way of knowing through which we understand the physical world. An example of an affective framework is ethics—the way of knowing through which we evaluate the nature of feelings that are directing (or attempting to direct), our choices and decisions through which we act.

It is relatively easy to assess when psychomotor efforts are effective and successful. It is more difficult to see how language presents a fallacious argument or when an accepted cognitive perception about the physical world constitutes a misconception. It is most difficult to determine whether an affective feeling is likely to direct us to actions that are beneficial and healthy or toxic and perverse. We observe our affective state through metacognition, which is a purposefully directed internal awareness. Metacognition has an ineffable quality. In contrast, physical action and cognitive reasoning are easier to assess through their immediate products.

The history of education seems marked by an initial focus on the development of effective psychomotor skills needed for survival, technology, and simple arts. Later educational efforts offered an emphasis on written language, literature, increasingly sophisticated arts, and science. We finally are arriving at a time in Western education when an acceptance is dawning that becoming educated should proceed beyond cognitive and psychomotor development to understanding ourselves and our affective traits. This pattern seems inevitable because it is recapitulated on a smaller scale in our development as individuals.

If we are lucky, we start life acquiring the skills needed for our survival and further development. If we are particularly fortunate, we progress to gaining valid knowledge, valuable skills, and capacity for understanding and appreciating the social and natural realms in which we live. Finally, if we are uncommonly privileged through fortune, we can develop wisdom that promotes our living in an expanded awareness of our reality and increased capacity for nurturing and caring well for our natural world and others around us.

Given the progression outlined above, we should expect that metacognition will be our students’ most challenging and least-developed capacity for learning and becoming educated. As educators, we should also expect struggle and resistance, both individually and collectively, against the legitimacy of affective development efforts and metacognition as essential to becoming educated. We have already seen such resistance to these advances.

In hindsight, it now appears that Benjamin Bloom and his team of educators who worked in the 1950s and 60s seemed decades ahead of their contemporaries by recognizing the indispensable importance of the affective domain to the process of becoming educated. The Bloom team’s contribution on affect took many years before its importance was realized. At the time Bloom published his taxonomy of the cognitive domain, he was producing a second volume on the taxonomy of the affective domain (and still later, the psychomotor domain), the established behavioral sciences were focused solely on cognition. These sciences ridiculed affect, dismissed metacognition (see Dunlosky and Metcalf, 2009) and treated both as nonsense that obstructed objective reasoning and cognitive thinking. Bloom’s first volume on the cognitive domain became the most-cited educational reference in history, but the second volume on the affective domain fell into such obscurity that few college professors even know that it existed. The academic realm so de-legitimatized affective feelings that researchers from the 1960s into the early 1990s were actually afraid to study or write about emotions (see Damasio, 1999).

William Perry’s 1960s landmark work (Perry, 1999) was contemporary with Bloom’s research. Perry presented his discovery of distinct stages of adult intellectual development that he derived from analysis of language patterns (discourse) that manifested during interviews that Perry held over several years with groups of students. This longitudinal study found that students changed their thinking and reasoning process during years of becoming educated. Moreover, the interviews revealed that the highest stages went beyond cognitive thinking by incorporating and regulating metacognitive awareness of one’s affective inclinations. This discovery of the nature of highest-level reasoning arrived with awkward timing, given the regard by scholars for affect and emotions. In Perry’s entire book, reference to “affect” occurs only once (in a brief footnote on page 49) and to “emotions” only once (on p. 140). “Feeling” / “feelings” appear thirty-nine times, but mostly in the quotations of statements made by students during interviews. Perry seemed unable to write openly about these aspects, so the three chapters on his three highest stages are conspicuously brief. Today, a close reading of these chapters indicates that he had probably also discovered the development of emotional intelligence in his interviews, but he seems to have understood the dangers that any emphasis on emotion might pose to his larger discovery.

Another landmark book (King and Kitchener, 1992) that followed Perry’s interview approach refused to venture even that far. These authors restricted their investigation of higher intellectual stages to purely cognitive reasoning. However, by 2004 (Journal of Adult Development, 2004) a synthesis revealed that many investigations and classification schemes that followed Perry all mapped to each other and were essentially describing the same stages.

Bloom’s Taxonomy of the Affective Domain seems to map even better onto the Perry stages than it does to Bloom’s Taxonomy of the Cognitive Domain, (see Nuhfer, 2008) indicating that building affective capacity is indeed a developmental process. Thus, well-designed higher education curricula can build it, providing instructors design the curricula to produce the highest levels of thinking.

As an added benefit, development of metacognitive awareness is probably the best way to curtail the influence of “hate groups,” whether these be minor cults or mainstream establishment organizations. People with metacognitive awareness can perceive when their affect is getting involved from external attempts to direct their abilities toward beneficent or maleficent ends. In part 2, we’ll consider how teaching any discipline presents an opportunity to push thinking to highest levels through using metacognitive awareness to reflect on ethics, respect, courage, and gratitude.

References

Damasio, A. (1999). The Feeling of What Happens: Body and Emotion in the Making of Consciousness. New York: Harcourt.

Dunlosky, J. and Metcalf, J. (2009). Metacognition. Thousand Oaks, CA: Sage.

Journal of Adult Development (2004). Special volume of nine papers on the Perry legacy of cognitive development. Journal of Adult Development (11, 2) 59-161 Germantown NY: Periodicals Service Co.

King, P. M., and Kitchener, K. S. (1994). Developing Reflective Judgment. San Francisco, CA: Jossey-Bass.

Nuhfer, E. B. (2008). The feeling of learning: Intellectual development and the affective domain: Educating in fractal patterns XXVI. National Teaching and Learning Forum, 18 (1) 7-11.

Perry, W. G. Jr. (1999). Forms of Ethical and Intellectual Development in the College Years. San Francisco, CA: Jossey-Bass (a reprint of the original 1968 work with minor updating).