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.


How to Get the Most Out of Studying

Dr. Stephen Chew has put together a highly lauded series of short videos that share with students some powerful principles of effective learning, including metacognition. His goal was to create a resource that students can view whenever and as often as they want.

They include

  • Video 1: Beliefs That Make You Fail…Or Succeed
  • Video 2: What Students Should Understand About How People Learn
  • Video 3: Cognitive Principles for Optimizing Learning
  • Video 4: Putting the Principles for Optimizing Learning into Practice
  • Video 5: I Blew the Exam, Now What?

Links to the videos can be found here:

https://www.samford.edu/departments/academic-success-center/how-to-study

Dr. Chew also provides an overview handout that summarizes the purposes of the videos, gives guidance on how to use them, and outlines the main points within the videos:

https://www.samford.edu/departments/files/Academic_Success_Center/How-to-Study-Teaching_Resources.pdf


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.


Developing Metacognition with Student Learning Portfolios

In this IDEA paper #44, The Learning Portfolio: A Powerful Idea for Significant Learning, Dr. John Zubizarreta shares models and guidance for incorporating learning portfolios. He also makes powerful arguments regarding the ability of portfolios to engage students in meaningful reflection about their learning, which in turn will support a metacognitive development and life-long learning.

 


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.

———–

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.