Metacogntion: Daring Your Students to Take Responsibility for Their Own Successes and Failures.

by Harrison Fisher

The Education Endowment Foundation in Britain claims that metacognitive styles of learning ‘have consistently high levels of impact, with pupils making an average of eight months’ additional progress’ (Education Endowment Foundation, 2016). This seems to be particularly the case with older pupils, e.g. those of university level, and particularly when used in a group setting, so learners can support each other. Metacognition refers to the process of reflecting on learning itself, as opposed to merely learning by rote or memorizing. Think about it, if you knew exactly what was hindering your learning, your learning experience would be more profound. Put simply, you would learn more!shutterstock_124813237

It is so important in metacognitive learning that students take responsibility for their own progress. However, to students, there can sometimes be a perception that the professor is solely responsible for their learning. Metacognition can help to shift this perception and empower students to take more responsibility by encouraging them to reflect on the learning process while making necessary adjustments to their learning methods.

Metacognition for students is about reflecting on the most appropriate methods of learning, using different methods as needed, and subsequently revising their learning process. If we are realistic, students’ performance and learning is measured by their final course mark. So, students are on a continuous path to decipher how different learning methods work for them, and which to apply given the expected assessment. The question that arises at this point is whether the traditional forms of assessment used in higher education allow students to improve their metacognition, and whether they are representative of the challenges that will arise for students once they enter the workforce. There has been a lot of research on the relative benefits of various forms of assessment, but to a certain extent they miss the point that this itself will depend on students’ metacognitive engagement, and effective strategies will depend on students reflecting on what works for them.

One of the key goals of education is preparing students for employment. It follows that professors should be exposing students to the broadest range of assessments, ones that are more indicative of the challenges that they will encounter in their chosen fields. This will lead to students who are more dynamic in how they approach given problems and tasks. For example, take the multiple-choice exam. Is this type of assessment representative of the metacognitive skills required to handle customer complaints? Are the metacognitive skills needed to answer short answer questions similar to the leadership and teamwork skills sought by top employers? The short answer is no! What employers do not want is a worker who can merely remember facts, or who can ace an exam. What they do want is a flexible employee who can solve problems, who can be proactive, who can realize what their weaknesses are through reflection and respond to them.

One strategy to broaden students’ learning and development could be to allow students to reflect on their own learning. This could include asking students to keep a reflective log of their progress, keeping track of what they found difficult, and, more importantly, why they found it difficult. In this way, students are not focused on the content, but on the process of learning. Students can as a result change this in future. For example, if students are given a choice of assessment task or methods, they can ask themselves ‘What works for me?’ and ‘Why is it that this works?’ Each student is an individual with very different strengths and weaknesses, and assessment methods should reflect this. In a global affairs class for example, you could ask your students ‘How will the British decision to leave the European Union impact North America, and how could this impact be minimized?’ To assess this question, you could allow your students freedom in the way in which they present their answers. Some of these might include recorded video oral presentations, essays, creative infographics, recorded Mp3’s, slide decks and so on. This will allow your students to play to their strengths, and to make progress more quickly.

In giving freedom to students as far as which medium they submit their work, you can empower the student to discover what works for them. In other words, if you as a tutor let them present their work in a format they choose (for example: an essay, a vlog, a newspaper report etc.) this will surely allow them to reflect on how they learn and how they wish to present their work, which will then enrich their understanding. For example, in the case of assessing through Vlog, students may have what Gardner (1983) in his theory of Multiple Intelligences called linguistic intelligence, in that they are good with words and verbalizing their thoughts. As a result, they may feel that a Vlog, which involves recording a video presentation, is a perfect way to present their learning, rather than the more traditional exam or essay.

Likewise, another useful strategy could be to allow students to talk to each other about how they learn best. What strategies do they use, and which is most effective for them? Why is this? How would they advise each other to proceed in order to be more successful? One of the most valuable ways to learn is from others, and this will allow your more successful or confident students to have a positive effect on others. This allows students to both take responsibility for their learning, but also will allow students to reflect upon methods that they never would have thought of without the help of their peers.

These are by no means the only strategies that could sharpen students’ metacognition, but they are effective, tried and tested methods. Too often, independent learning comes off as a gimmick, something that is said without having any real meaningful outcome. Metacognitive strategies can change this. In fact, one of the most influential names in the field of metacognition, John Flavell (1987), believed, being influenced by the developmental theories of Jean Piaget, that metacognition is the process that drives all learning and development. As a result, we as professionals would definitely be missing out by not using this knowledge in our practice.

This is why the responsibility for learning needs to rest on the shoulders of the student. Learning will be more profound and more lasting, and, though it is hard work, the pay-off will be huge. Go on, dare your students to take responsibility for their own learning by using metacognition to monitor their successes and failures.

 

References

Flavell, J. H. (1987) Speculation about the nature and development of metacognition. In F. Weinert & R. Kluwe (Eds.), Metacognition, motivation, and understanding (pp.21 – 29). Hillsdale, NJ: Lawrence Erlbaum.

Education Endownment Foundation. (2016). Meta-cognition and self-regulation. Education Endowment Foundation.

Gardner, H. (1983). Frames of Mind: The Theory of Multiple Intelligences.


Selecting a quantitative measure of metacognition  

by Dr. Jessica Santangelo, Hofstra University

If you are interested in metacognition and promoting the development of metacognitive skills, you may also be interested in measuring metacognition. But how does one assess a person’s metacognitive development?

Metacognitive development can be assessed via quantitative or qualitative measures. Quantitative measures include self-report measures, often using Likert-style survey instruments, while qualitative measures use coding of responses to open-ended prompts (e.g., Stanton 2015). While quantitative measures are generally easier and faster to score, a drawback is that self-report measures are not always accurate (Schunk 2008). Qualitative data can be more rich, providing deeper and more nuanced information, but is much more labor intensive and time consuming to analyze. Ideally, one uses a combination of quantitative and qualitative data to develop as complete a picture of metacognitive development as possible.

When I set out to assess the metacognitive development of 484 (!) students, I was overwhelmed by the number of quantitative tools available. The focus of the tools varies. Some tools attempt to assess metacognition directly while others assess factors or attributes associated with metacognition (e.g., study skills, self-regulated learning). Some are not explicitly intended to assess metacognition (e.g., LASSI), but are used by some authors as an indicator of metacognitive development (e.g., Downing et al 2007, 2011). Some have been through many iterations over the years (e.g., ASI, RASI, and ASSIST) while others remain relatively unchanged (e.g., MAI, MSLQ). Some are free while others have a per student fee. Some are longer (120 items, ILS) and others are shorter (18, RASI).

How does one choose the “best” quantitative tool? Unfortunately, there is no easy answer. It depends on the specific question being addressed and the amount of time and money available to administer the tool. I compiled a (non-comprehensive) list of tools I encountered in my search along with some information about each one to assist anyone looking for a quantitative measure of metacognitive development.

For my 484-student project, I chose to use the Metacognitive Awareness Inventory (MAI; Schraw and Dennison 1994) in combination with coding responses to open-ended prompts I created. I chose the MAI because it purports to measure metacognition directly (rather than being a study or learning skills inventory), is free, and is of moderate length (52 items). Others have found correlations between MAI results and other quantitative measures of student success (e.g., GPA and end of course grades), even suggesting using the MAI as a screening tool to identify students who could benefit from metacognition training (Young and Fry 2008). These characteristics  fit with the questions I was asking: Can we rapidly (and accurately) assess metacognitive development at the beginning of an introductory course? Does including explicit instruction and implicit practice with metacognitive skills in a course increase student metacognitive development?

While coding the open-ended responses is taking months to complete, it has revealed some clear and interesting patterns. In contrast, the quantitative data from the MAI, though gathered in about 5 minutes running scantron sheets through a machine, show no patterns at all. There does not appear to be any relationship between the quantitative MAI data and the qualitative data or any other measure of student success (GPA, exam and course grades, etc.). I’m not entirely surprised – metacognitive skills are unlikely to be wholly captured by a number generated by a 52-item self-report questionnaire. However, given the results of others (e.g., Sperling et al 2004, Young and Fry 2008) I was hopeful there would be at least some relationship between the quantitative and qualitative results.

This is not to say that rapid assessments via self-report questionnaires are worthless. It is simply a caution to not rely on these quantitative tools as one’s sole measure of metacognitive development. Indeed, I have colleagues who have had more “success” with tools other than the MAI (e.g, with the MSLQ), where success is defined as the quantitative tool reflecting similar patterns or trends as other, more time-consuming qualitative measures.

As with many things in science, there is no easy answer. My hope is that this compilation of available tools makes the choice of which one to use a little easier.

For more in-depth reading on measuring metacognition, I recommend:

Mogashana, D., J. M. Case, and D. Marshall. 2012. What do student learning inventories really measure? A critical analysis of students’ responses to the approaches to learning and studying inventory. Studies in Higher Education 37:783–792.

Schraw, G., and J. Impara, eds. 2000. Issues in the Measurement of Metacognition. Buros Institute of Mental Measurements, Lincoln, NE.

References

Downing, K., F. Ning, and K. Shin. 2011. Impact of problem‐based learning on student experience and metacognitive development. Multicultural Education & Technology Journal 5:55–69.

Downing, K., R. Ho, K. Shin, L. Vrijmoed, and E. Wong. 2007. Metacognitive development and moving away. Educational Studies 33:1–13.

Schraw, G., and R. S. Dennison. 1994. Assessing metacognitive awareness. Contemporary educational psychology 19:460–475.

Schunk, D. H. 2008. Metacognition, self-regulation, and self-regulated learning: research recommendations. Educational Psychology Review 20:463–467.

Sperling, R. A., B. C. Howard, R. Staley, and N. DuBois. 2004. Metacognition and self-regulated learning constructs. Educational Research and Evaluation 10:117–139.

Stanton, J. D., X. N. Neider, I. J. Gallegos, and N. C. Clark. 2015. Differences in metacognitive regulation in introductory biology students: when prompts are not enough. CBE-Life Sciences Education 14:ar15.

Young, A., and J. Fry. 2008. Metacognitive awareness and academic achievement in college students. Journal of the Scholarship of Teaching and Learning 8:1–10.

 


Do Your Questions Invite Metacognition?

By Arthur L. Costa and Bena Kallick, Co-founders, International Institute for Habits of Mind

Our ‘inner voice’ is what we use to reflect on what we do, how and why we behave in the way we do, how we critique ourselves and how we connect the knowledge, ideas, concepts and concept frameworks developed using each of our four learning systems. It is the voice that challenges us to strive further and the voice that condemns our foolishness.

Mark Treadwell, Learning: How the Brain Learns (2014)

One of a teacher’s most important practices is designing and posing questions.   Wise teachers pose questions consciously with deliberate intentions. They know that questions engage sometimes subtle and overt responses from students.   Questions are the powerful stimuli that evoke cognitive, behavioral and emotional responses in students. They initiate a journey in the mind. Indeed questions are the backbone of instruction. They must be employed with care (Costa & Kallick, 2008).

Building a Thinking Vocabulary

Because thinking words may not be used in students’ homes or in previous classrooms, thinking vocabulary may be a “foreign language” to them. They may not know how to perform the specific thinking skills that a given term implies. It is imperative, therefore, that students develop a vocabulary with which to express their metacognitive processes.

When adults speak usiing mindful language, using specific, cognitive terminology and instructing students in ways to perform certain skills, students are more inclined to be able to both name and use those skills. For example,

Instead of saying: Use Metacognitive language by saying:
“Let’s look at these two pictures.” “As you COMPARE these two pictures…”
“What do you think will happen when . . . ?” “What do you PREDICT will happen when . . . ?”
“How can you put those into groups?” “How might you CLASSIFY . . . ?”
“Let’s work this problem.” “Let’s ANALYZE this problem.”
“What do you think would have happened if… ?” “What do you SPECULATE would have happened if… ?”
“What did you think of this story?” “What CONCLUSIONS can you draw about this story?”
“How can you explain . . . ?” “What HYPOTHESES do you have that might explain . . . ?”
“How do you know that’s true?” “What EVIDENCE do you have to sup-port . . . ?”
“How else could you use this . . . ?” “How could you APPLY this . . . ?”
“Do you think that is the best alternative? “As you EVALUATE these alternatives….”

As students hear these cognitive terms in everyday use and experience the cognitive processes that accompany these labels, they internalize the words and use them as part of their own  metacognitive vocabulary. Teachers will also want to give specific instruction and provide awareness of experiences so that students recognize and know the meaning of the terminology.

Invite metacognitive responses.

Teachers can deliberately invite students to become spectators of their own thinking by posing questions that invite a metacognitive response. Some questions invite a behavioral response, others can invite a thought-full response. Notice how behavioral questions can be transformed into questions that invite thinking:

Questions That Invite a Behavioral Response Questions That Invite Metacognitive Responses
“Why did you do that?” “What were you thinking when you did that?”
“What did the author mean when . . . ?” “What cues were you aware of?”
“What are your plans for . . . ?” “As you envision . . . what might be…..”
“When will you start . . . ?” “How will you decide when to start . . ?”
“Was that a good choice?” “What criteria did you have in mind to make that choice?”

If teachers pose questions that deliberately engage students’ cognitive processing, and let students know why the questions are being posed in this way, it is more likely that students will become aware of and engage their own metacognitive processes.

Making Internal Dialogue External

Students can become spectators of their own thinking when they are invited to monitor and make explicit the internal dialogue that accompanies their thinking.

They reveal their own thinking as they consider questions such as:

  • “What was going on in your head when……?”
  • “What were the benefits of……?”
  • “As you evaluate the effects of . . . ?”
  • “By what criteria are you judging…..?
  • “What will you be aware of next time?”
  • “What did you hear yourself saying inside your brain when you were tempted talk but your job was to listen?”

Keep Students Thinking About Their Thinking

While such questions will initiate students’ metacognitive journey, you will also want to sustain that momentum by:

Causing Students to Monitor their Accuracy

  • “How do you know you are right?”
  • “What other ways can you prove that you are correct?

Pausing and Clarifying but not Interrupting

  • “Explain what you mean when you said you ‘just figured it out'”.
  •  “When you said you started at the beginning, how did you know                                where to begin?”

Providing Data, Not Answers (As soon as you confirm that an answer is correct, there is no need to think further about it!)

  • “I think you heard it wrong; let me repeat the question………………”
  • “You need to check your addition.”

Resisting Making Value Judgments Or Agreeing With Students’                  Answers.

  • “So, your answer is 48. Who came up with a different answer?”
  • “That’s one possibility. Who solved it another way?”

Remaining Focused On Thinking Processes

  • “Tell us what strategies you used to solve the problem”
  • “What steps did you take in your solution?”
  • “What was going on inside your head as you solved the problem?”

Encouraging Persistence

  • “Success! You completed step one. Now you’re ready to forge ahead.”
  • “C’mon, you can do it” Try it again!”

Ultimately, the intent of all this is to have students monitor and pose their own questions that promote thinking in themselves and others. Questioning, monitoring and reflecting on our experiences are requisites for becoming a continuous, lifelong learner. When we teach students to think about their thinking, we help make the world a more thought-full place.

References

Costa, A & Kallick, B. (2008) Learning and Leading with Habits of Mind: 16 Characteristics for Success. Alexandria, VA: ASCD

Treadwell, M (2014) Learning: How the brain learns. www.MarkTreadwell.com/products


A Whole New Engineer: A Whole New Challenge

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

In 1973, cognitive psychologists Kahneman and Tversky (1973) wanted to present their study participants with a stereotypical description of engineers:

Jack is a 45-year old man. He is married and has four children. He is generally conservative, careful, and ambitious. He shows no interest in political and social issues and spends most of his free time on his many hobbies, which include home carpentry, sailing, and mathematical puzzles. (p. 241)

When asked if they thought Jack was an engineer, 90% of the participants thought he was.

Whatever stereotypes of engineers may persist to the present day (e.g., geek, introvert, asocial: http://www.thecreativeengineer.com/2008/12/16/a-few-engineering-myths/ ), various parts of the engineering community are trying to create “a whole new engineer” (Goldberg & Somerville, 2014). Cross-disciplinary centers have been established at universities, like iFoundry which was launched in 2008 at the University of Illinois, in order to prepare engineering students for working in the 21st century. One mandate was to promote “deep reflection and attention to the complex system in which engineering education is embedded” (https://ifoundry.illinois.edu/who-we-are/what-ifoundry ).

On a larger scale, the Franlin W. Olin College of Engineering admitted its first class in 2002 in order to implement a full-scale hands-on, project-based and design curriculum. Olin College provides students with funding for “passionate pursuits,” which are personal projects of academic value proposed by students https://en.wikipedia.org/wiki/Franklin_W._Olin_College_of_Engineering. STEM is being transformed to STEAM, where the addition of A represents Artful Thinking in the context of Science, Technology, Engineering, and Mathematics (Radziwell et al., 2015). To develop artful thinking a facilitator might present a painting and ask students: What do you see? What does it make you think? What is happening? Why do you think so? These questions help learners develop dispositions to observe, describe, question, reason, and reflect. The whole new engineer is becoming a whole lots of things, but is the new engineer becoming more metacognitive?

We know that engineering students can be metacognitive when solving textbook problems (Taraban, 2015). Indeed, by now there is an extensive corpus of research on students’ textbook problem-solving in introductory physics and other areas of STEM. Explaining the material to oneself with the knowledge that this will help one better understand it, or testing oneself with the knowledge that this will help one more reliably retrieve the information later, are examples of metacognitive processes and knowledge. Case and Marshall (1995) described a developmental pathway by which students transition towards deeper understanding of domain concepts and principles, which they labeled the conceptual deep approach to learning, and which is: “relating of learning tasks to their underlying concepts or theory” with the intention “to gain understanding while doing this” (p. 609). Basically, their suggestion is that over the course of development students recognize that a goal of learning is to understand the material more deeply, and that this recognition guides how they learn. Draeger (2015), and others, have suggested that this kind of monitoring of the effectiveness of learning strategies and regulating one’s behavior are characteristic of metacognitive thinking.

The current re-design of the traditional engineer involves sweeping changes, in the classroom, in the university, and in professional practice, and it aims to do this, in part, by infusing more reflection into engineering training and practice. So, what is a reflective practitioner, and are reflective practitioners metacognitive thinkers?

Schön (1987) suggested that reflective practitioners think carefully about what they are doing as they are doing it. Reflective practitioners assess and revise their existing practices and strive to develop more effective behaviors. They critically assess their behavior as a means to improving it. As Schön (1987) puts it, reflective practice is a “dialogue of thinking and doing through which I become more skillful” (p. 31). Schön maintained “that there is a core of artistry, an exercise of intelligence, and a kind of knowing inherent in professional practice, which we can only learn about by carefully studying the performance of extremely competent professionals” (Osterman, 1990, p. 133).

Through reflective practice we submit our behaviors to critical analysis, asking questions like these: What am I doing? What effect is it having? (Osterman, 1990). This very much reminds one of the distinction that Draeger (2015) made between metacognition and critical thinking. Specifically, one can be a critical thinker without being metacognitive. The two processes can overlap but are not identical. Simply, to be metacognitive, one would need to think about the reflective processing itself. Metacognitions would involve knowledge of the benefits of reflective practice, how it relates to self, and metacognitive processes related to monitoring and controlling the reflective practices. Imagine observing any expert – an expert teacher, an expert golfer, an expert acrobat – and striving to mimic that expertise through carefully observing and critiquing one’s own performance. That’s reflective practice. It’s about trying to get a job done in the best possible way. In a complementary fashion, metacognitive knowledge and processing involve intentionally and consciously monitoring and regulating those reflective practices.

In A Whole New Engineer (Goldberg & Somerville, 2014) the authors assert that

Here we are calling attention to the importance of the Whole New Engineer’s ability to do three things:

  • Notice and be aware of thoughts, feelings, and sensations.
  • Reflect and learn from experience.
  • Seek deeper peace, meaning, and purpose from noticing and reflection. (p. 114)

Goldberg and Somerville (2014) make a call to be more attentive and sensitive to surroundings, to notice and reflect, but not necessarily to be metacognitive in those contexts – they are not clear about the latter point. Thus, it may be safe to say that being metacognitive doesn’t automatically come through reflective practice, critical thinking, mindfulness, or artful thinking strategies. Metacognition represents a distinct type of knowledge and process that can potentially enhance the effects of the aforementioned. The whole new engineer can be a whole lot of things, but is not automatically a metacognitive engineer. Simply, an engineering student, or even a practicing engineer, can be good at certain design projects, for instance, and develop a critical eye for that work, but without necessarily developing metacognitive awareness around when to shift strategies or techniques in order to be more effective.

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/ .

Kahneman, D., & Tversky, A. (1973). On the psychology of prediction. Psychological Review, 80(4), 237-251. http://dx.doi.org/10.1037/h0034747

Osterman, K. F. (1990). Reflective practice: A new agenda for education. Education and Urban Society, 22(2), 133-152.

Radziwill, N. M., Benton, M. C., & Moellers, C. (2015). From STEM to STEAM: Reframing what it means to learn. The STEAM Journal, 2(1), Article 3.

Schön, D. (1987). Educating the reflective practitioner. How professionals think in action. London: Temple Smith.

Taraban, R. (2015). Metacognition in STEM courses: A developmental path. Retrieved from https://www.improvewithmetacognition.com/metacognition-in-stem-courses-a-developmental-path/


Fine-tuning Just-in-Time assignments to encourage metacognition

By John Draeger, SUNY Buffalo State

In two previous posts, I’ve argued that instructors can improve metacognition through Just-in-Time teaching (JiTT) assignments (Draeger, 2014; Draeger, 2015). Just-in-Time assignments require that students complete short assignments prior to class and instructors review those assignments before class begins (Novak, 1999). Students in my philosophy classes, for example, are required to answer several questions about the reading and submit those answers electronically the night before our class meets. I read their answers prior to the class session and use their responses to tailor class discussion. JiTT assignments have many benefits, including improving the likelihood that students will do the reading. For the last five semesters, I’ve been experimenting with ways to use JiTT assignments to help students improve their metacognition.

In my early attempts to incorporate metacognition into JiTT assignments, I asked asked a variety of questions: What is your reading strategy? Was the current reading more challenging than the last? How would you know if your strategy as effective? Student answers were often informative, but they tended to focus on the content of the reading. For example, students would report that they found certain sections of the reading to be especially confusing or they found that an author’s view rested on a spurious assumption. While helpful in adjusting class time to hone-in on the parts of the material most in need of discussion, these questions did not always prompt students to reflect on their individual learning process. Consequently, I have continued to tweak my JiTT questions in an attempt to focus student attention more explicitly on aspects of the learning process. As I work to fine-tune my JiTT assignments, I often think about my own attempts to become more aware of my teaching practice and then I can see parallels to the kind of metacognition that I seek to encourage in my students. (Scharff & Draeger, 2015). I have come to believe that building questions on metacognition into JiTT assignments have at least three broad benefits.

First, metacognitive questions serve as an easy conversation starter about the aims of learning. For example, I have asked students: What are your goals in this course? What are your goals for the week? How does last night’s reading fit into one of your goals for the week? Most students respond that they hope to understand the readings, remember the relevant information for the exam, and get good grades. These answers are unsurprising. However, such pedestrian responses give me an opportunity to revisit my goals for the course, namely my desire to help students learn to uncover philosophical substructure (Draeger, 2014). They also provide me with an opportunity to encourage them to think more carefully about what they hope to achieve. I encourage them to think about their own motivations (or lack of) and their reasons for engaging in course content. While I wouldn’t need their JiTT responses to talk about various learning goals, students seem to be more responsive to those conversations when I am responding to their own answers to pre-class assignments.  Such conversations have led me to ask new JiTT questions: How does this course fit into your degree program? What would you tell a parent about why this course is worth taking? How might this course might be relevant to your life 30 years from now? Students often report that my courses are irrelevant to their degree programs because my courses satisfy a general education requirement. This has led to fruitful conversations about the connection between their general education courses and their program of study, as well as how philosophy might figure into a student’s quest for employability and my desire to help them become lifelong learners.

Second, metacognitive questions prompt students to think about their learning processes. For example, I have asked students: What skills do you hope to develop this semester? How have your reading practices evolved as the semester has progressed? Are your annotation strategies effective? What is your strategy for revising papers? What is one thing you learned about the last round of revisions that you hope to carry through to the next round? Even though some student responses are less than illuminating and even when we don’t discuss their answers in class, students are still being prompted to think about their learning process multiple times a week. I have to believe that it reminds students that they need multiple learning strategies and they need to monitor their effectiveness. I have also seen student answers become more nuanced as the semester progresses. For example, students who reported being “confused by the reading” at the beginning of the semester often reported being “confused by” some particular feature of the reading (e.g., examples within the text, references to views not previously discussed) later in the semester.

Third, regular metacognitive questions help me (as the instructor) develop a learning profile of my students both individually and collectively. For example, I have asked students: What type of learning is required in this course? What are their personal characteristics that help or hinder their learning? Interestingly, students rarely point to personal characteristics that helped their learning.  Further, many of the “hinder” answers tend to be predictable (e.g., I procrastinate, I have a busy schedule). However, other answers paint a picture of the individual learners in the seats in front of me. For example, some students report some version of “I am not a big reader outside of class and so long readings intimidate me” and quite a few talk about difficulties taking notes in a discussion class. These are not surprising observations, but it helps knowing which students are having which troubles (e.g., if someone asked me “choose the students that don’t like to read,” I would not always be able to correctly identify them). Likewise, some students offer some version of “I need entertaining examples because I get bored easily” while others report some version of “I am intellectually curious about most everything and I get distracted easily.” It is not surprising that students would be distracted, but the JiTT metacognition responses allow me to understand a little more about why particular students are struggling. This emerging profile helps me make course adjustments before, during, and after class.

There are many ways to encourage student metacognition. I am not suggesting that you adopt Just-in-Time techniques simply because they can encourage students to reflect on their learning process and facilitate conversation. I am doing JiTT assignments anyway. Fine-tuning my questions has been a way of using an existing teaching strategy to promote metacognition. Rather, I encourage you to think about how you might tweak your current teaching strategies to promote student metacognition. In my case, because students complete JiTT assignments multiple times a week and because I now include questions on metacognition within every JiTT assignment, students have many opportunities to reflect on their learning and to practice metacognition. The emerging picture of my students has also encouraged me (as the instructor) to be more metacognitive about my teaching process. While I need to continue fine-tuning my assignments, I am becoming ever more convinced that regular incorporation of activities that promote reflection on learning are a means by which to improve with metacognition.

References

Draeger, J. (2014a). “Just-in-Time for Metacognition.” Retrieved from https://www.improvewithmetacognition.com/just-in-time-for-metacognition.

Draeger, J. (2014b), “Using metacognition to uncover the substructure of moral issues.” Retrieved from https://www.improvewithmetacognition.com/using-metacognition-to-uncover-the-substructure-of-moral-issues

Draeger, J. (2015). “Using Just-in-Time assignments to promote metacognition.” Retrieved from https://www.improvewithmetacognition.com/using-just-in-time-assignments-to-promote-metacognition.

Novak, G., Patterson, E., Gavrin, A., & Christian, W. (1999). Just-in-time teaching: Blending active learning with web technology. Upper Saddle River, NJ: Prentice Hall.

Scharff, L. and Draeger, J. (2015). “Thinking about metacognitive instruction” National Teaching and Learning Forum 24 (5), 4-6.


Developing Mindfulness as a Metacognitive Skill

by Ed Nuhfer Retired Professor of Geology and Director of Faculty Development and Director of Educational Assessment, enuhfer@earthlink.net, 208-241-5029

A simple concept for enhancing learning is to engage more of the brain in more of the students. “Interactive-engagement,” “collaborative/cooperative learning,” “problem-based learning” and an entire series of active learning pedagogies use the concept to optimize learning. Research shows that active learning works. While frequently espoused as “student-centered learning,” advocates frequently use the active learning terms to promote particular kinds of pedagogy as “student-centered.”

However, active learning is neither the only way to enhance learning nor is it usually as student-centered as advocates claim. Whether the design occurs by the course instructor or with an involvement of a more recent profession of “learning designers,” the fact is that the emphasis is on pedagogy and on student learning. As such, they are more focused on student learning than were older traditional methods of content delivery, but the reach to proclaim most learning-centered pedagogies as student-centered leaves a bit of a gap. Metacognition is the factor missing to help close the gap needed to make learning-centered practices more student-centered.

While pedagogy focuses on teaching, mindfulness focuses on knowing of one’s present state of engagement. Mindfulness develops by the learner from within, and this makes it different from the learning developed through a process designed from without. Metacognition is very student centered, and mindfulness could be the most student-centered metacognitive skill of all.

Because mindfulness involves being aware in the present moment, it can engage more of the brain needed for awareness by enlisting the parts of the brain concurrently distracted by our usual “default mode.” Operating in default mode includes thinking of imagined conversations, playing music inside of one’s head, unproductive absorption in activities in which one is not presently engaged, or thinking of responses to a conversation while not attending fully to hearing it.

Mindfulness receives frequent mention as a method of stress management, particularly when it enlists the parts of the brain that would otherwise be engaging in worrying or in preparing an unneeded flight-or-fight reaction. The need to manage stress by today’s college students seems greater than before. However, its value to student success extends beyond managing stress to enhancing cognitive learning through improving concentration and increasing the ability to focus and to improve interpersonal communication by enhancing ability to listen.

Mindfulness has its roots in Zen meditation, which laypersons easily perceive as something esoteric, mystical, or even bordering on religion. In reality, mindfulness is none of these. It is simply the beneficial outcome of practice to develop metacognitive skill. It is simple to learn, and measurable improvements can occur in as little as six weeks.

For blog readers, an opportunity to develop mindfulness is fast approaching on September 19, 2016, when Australia’s Monash University again offers its free massive open online course (MOOC) in mindfulness. Rather than gurus dressed in costumes, the instructors are psychology professors Drs Craig Hassed and Richard Chambers, who occasionally appear in ties and sportcoats. The course is immensely practical, and the two professors are also authors of a highly rated book, Mindful Learning, which is likely of interest to all members of this particular metacognitive blogosphere. Perhaps we’ll see each other online in Australia!

**This blog contribution is a short derivation from “Mindfulness as a Metacognitive Skill: Educating in Fractal Patterns XLVII” by the author and forthcoming in National Teaching and Learning Forum V25 N5.


Using Metacognition to Develop College Faculty

By Charity S. Peak, Ph.D.

What does it take to become an exceptional college teacher? As many of us have learned, there’s much more to the art and science of teaching than merely knowing the content. Still, every year, several new faculty members begin teaching with the false assertion that solely learning more about their subject will lead to success in the classroom. Instead, metacognition about their development as a teacher could help propel them into their new roles with greater ease. Below is an appeal for new faculty to embrace metacognition about their instruction by understanding their developmental path with college teaching.

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Dear New Faculty,

Congratulations on starting your new role as a college teacher! You’ve worked hard to get to this point, spending years in class and writing that thesis or dissertation. Now you get to share all of that knowledge with aspiring students. Your passion will hopefully convert several of them into majoring in your discipline or even becoming your research prodigies. Your optimism is contagious and inspiring.

Despite the fact that you now hold an advanced degree, your learning is not over. In fact, the journey to becoming an effective teacher has just begun. Before you step into that classroom, take a strategic pause to become metacognitive about your teaching, not just your content. You must now design a course that is meaningful for your students. Sure, you can simply use the materials provided by the textbook publisher, especially those well-designed PowerPoint slides, but did you know college teaching requires so much more? Did you know there are developmental stages for becoming an effective college teacher?

Akerlind (2007) shares brilliant insights about progressing from a teacher-centered to a learner-centered approach. In order to focus on student learning, faculty need to become aware of how they are teaching and begin to adapt their instruction to best meet the needs of their students. In other words, effective college faculty engage in metacognition about their instruction through awareness of teaching strategies, reflection about their practice, and self-regulation of teaching methods based on student learning needs. To this end, Akerlind asserts that college teachers move through the following developmental stages:

Akerlind Teaching Development Stages
Akerlind Teaching Development Stages

If these stages hold true, what does this mean for you? As Akerlind shares, new teachers often expend most of their energies on understanding their disciplinary content really well. You may spend great effort reading the textbook and researching the topics as much as possible. In all likelihood, much of your class time will be spent lecturing or presenting information (perhaps using those textbook slides), a very teacher-centered style. In reality, if you take this approach, you may learn more than your students this year because you spent greater time and energy mastering the material than they did.

Over time, however, you may discover that students are not participating in class like you want, or you may notice dwindling attendance. Student evaluations might even reflect dissatisfaction with your teaching style. Don’t be dismayed; don’t give up. You will begin to shift into Akerlind’s next developmental stage by considering alternative methods for content delivery. You will move toward focusing on how to teach rather than what to teach, especially now that you feel more comfortable with the content of the course. During this stage, you will gain greater metacognition about your teaching.

Through trial and error, you will begin to explore and experiment with a variety of teaching strategies, increasing your toolbox of techniques from which to use. Trying these new strategies will not be sufficient, though. You will need to select evidence-based strategies drawn from the scholarship of teaching and learning (SoTL) literature, and you will need to reflect on how well the new methods worked (also called reflective practice). Through reflection, you will begin to see which teaching techniques fit your personal style and subject matter. You will also begin to seek feedback, particularly from students, about how well these new strategies are being received.

Ultimately, though, you will discover that student satisfaction and snazzy teaching techniques fall flat if your students aren’t learning from the course. As Akerlind claims, you will move into the final developmental stage by designing your instruction and curriculum to be singularly focused on learning outcomes. You will search for a balance between being liked as a teacher to challenging students to transform their thinking. You may even embrace this positive restlessness and seek continuous improvement with your teaching each semester.

So why should you care about these stages of college teaching development? Because perhaps seeing your teaching as a journey and not a fixed goal will help you to be patient with yourself as you try new techniques and begin to feel overwhelmed. Perhaps metacognition about your future development will help you to progress more quickly through these stages to focusing on student learning rather than your instruction style. Go ahead and acknowledge that your first semester or two may be focused heavily on understanding the content at hand, but over time, try to embrace metacognitive instruction by leveraging knowledge about teaching and intentional awareness in the classroom to move toward more sophisticated methods for delivering that content. Become reflective practitioners who care about student feedback and continuous improvement, but eventually shift your focus to improving student learning outcomes.

The journey to becoming an effective college teacher will not happen overnight, even with this new metacognition you have, but rest assured that it will be rewarding and meaningful. In Bain’s (2004) pivotal work, What the Best College Teachers Do, you will discover that it could take up to 10 years to become an effective faculty member. However, maintaining metacognition about these stages of development will likely put you on target sooner, working toward a learner-centered approach to teaching. Good luck!

Resources:

Akerlind, G.S. (2007). Constraints on academics’ potential for developing as a teacher. Studies in Higher Education, 32(1): 21-37. doi: 10.1080/03075070601099416

Bain, K. (2004). What the best college teachers do. Cambridge, MA: Harvard University Press.


Two-in-One: Using Metacognition to Improve Judgment for Citizenship

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

Higher education should prepare students for citizenship, yet this is a difficult task in this fractious political climate. Partisanship is at an all-time high in the United States and the electoral contest between Hillary Clinton and Donald Trump is unlikely to ease those tensions. The summer of 2016 has also been marked by polarized responses to videos of police brutality; #alllivesmatter and #blacklivesmatter share videos and display the structures of American society in starkly different terms. Students developing as citizens need habits of mind to help them evaluate the messy and propagandistic political world. Judging politically is a reflective, metacognitive process, not just aimed at political facts, but also values and ethical commitments, and in response to the pluralistic values of others. It is metacognitive because it requires a shift from one’s own reflections to the imagined reflections of others and a dialogue between these reflections. Here, I’ll discuss what is metacognitive about political judgment, give a (brief) nod to the work of Hannah Arendt, and offer some ideas for the classroom and remaining questions.

One difficulty in developing political judgment is our tendency to assign higher credibility to information that is easier for us to process, perhaps because we have heard it often, it fits into our ideology, or tells a familiar and coherent story (Schwartz, N. 2015). Thus information silos, as on social media where one may have many friends sharing the same stories or perspectives, can make metacognitive judgement difficult (Johnson et. all 2009). Political ideology can limit evaluation of information or policy positions, stopping the metacognitive process of thinking about our thinking about politics, and instead replacing it with the ease of confirmation bias.

Yet, if there is a way out of the political echo chamber, it seems likely to involve reflection and the ability to notice and evaluate that reflection. Indeed, Chick, Karnahan and Caris (2009) found that metacognitive reflection that was sensitive to emotion and affect helped students understand and respond to racism by providing distance to examine their own emotional responses. Mezirow (2003) frames this as “learning that transforms problematic frames of reference—sets of fixed assumptions and expectations (habits of mind, meaning perspectives, mindsets)—to make them more inclusive, discriminating, open, reflective, and emotionally able to change” (58). He links this transformative learning to Jurgen Habermas’ discourse ethics, arguing that the goal of adult education is to prepare citizens for the critical reflective work both of collective problem solving and deliberative discourse.

Habermas’ discourse ethics are not the only approach to understanding how citizens develop politically in a plural world; indeed, one alternative theorist of political discourse and action is Hannah Arendt (1906-1975). Arendt, political theorist, wrote popular books on totalitarianism, political action and American politics and controversially covered the Eichmann trials, during which she developed her famous idea of “the banality of evil.” Slightly less well known is her unique work on political judgment, as she died before completing it. However, she provides a unique framework for thinking through reflective judgment as a mental “two-in-one.”

Arendt (1989) adapts Kantian aesthetic judgment to the political and social world, exploring how to evaluate new phenomenon when one does not have an existing concept or category under which it can be explained. The solution is a redefined common sense” which, for Arendt, is “the intuitive feeling for worldliness” that allows us to share the world with pluralistic others (Schwartz 2015). Arendt’s common sense is not community norms— agreeing with those who post on our Facebook wall—although it is formed in part by the “company we keep” both in books and in person, in discourse with whom we form our ideas of what common standards of judgment are.

This orienting common sense requires metacognitive consideration of both our individual perspectives and those of pluralistic others. These positions are often in dynamic tension with each other, producing cognitive dissonance. The faculty of imagination allows us to move, mentally, outside ourselves to consider the status of others, although she is well-aware we are still always ourselves. Imagining the perspectives of others as well as our own is “enlarged mentality;” it does not replace the partial view we have from our own subject position, nor is it a universal “view from nowhere.” Instead, it allows us to reason via internal dialogue which, in the unfinished The Life of the Mind, she calls this the “two-in-one” of thinking.

Developing Arendtian metacognitive reflective judgment is a difficult task, given the barriers to imagination. However, consider the question of how to respond to a video, like that taken of Philando Castile, where a person is killed by police. After our immediate reaction and interpretation, we can improve this judgment by considering the perspectives of others, not as an additive process, but as an exercise in enlarged mentality, playing the positions off each other. As Arendt notes, our judgments are not “universally valid” because they cannot “extend further than those others in whose place the judging person has put himself” (Beiner et. all 2001). But certainly an attempt to think from the position others prompts us to consider the sources of our judgments and gather information on the perspectives of those others—it demands that we think through police brutality from a non-binary perspective, as the two-in-one is really many and one.

Arendt’s notion of the “two-in-one” is useful for framing the importance of student practices of self-dialogue and reflection prior to or even instead of deliberative contestation in the classroom. We might practice skills and reflective activities, building up to full-scale deliberation (Stephens et all. 2013), or include reflective practice in unexpected places, like law school (Casey). We can also adapt what we know about changing deeply held beliefs to prompt better reflection on standpoints and our thinking. Framing new information in non-challenging language or affirming student self-worth can help with their consideration of identity challenging ideas (Hardisy, Johnson, & Weber, 2010). My students often write on a big question prior to class, and then engage various materials that relate to this big question, and then revisit and revise their paper as a dialogue with several of these perspectives. We also often do “think-alouds” in class with a partner or small group to discuss which voices are present in our internal dialogue and how they relate to our world in common.

There are still deep ethical and epistemological questions about Arendt’s reflective judgment; for example, can we reason from the imagined position of others if our knowledge of their perspective is lacking? Arendt herself was harshly, and I think rightly, criticized for her lack of such knowledge when she critiqued the actions of the NAACP and black families at Little Rock in 1957. Perhaps meta-cognition about the pluralistic political world requires diverse knowledge about the actual viewpoints of others—knowledge often lacking in the racially and politically segregated U.S. If we want prepare our students for citizenship, we need to challenge them to “go visiting” the viewpoints of others and provide the resource t make this possible. Although political divisions and ideologies make two-in-one thinking difficult, cultivating a metacognitive process for political judgment is worthy educational goal.

References

Arendt, Hannah, and Ronald Beiner. (1989). Lectures on Kant’s political philosophy. Chicago: University of Chicago Press.

Beiner, Ronald, Hannah Arendt, Stanley Cavell, Charles Larmore, Onora O’Neill, George Kateb, Robert J. Dostal et al. Judgment, imagination, and politics: Themes from Kant and Arendt. Rowman & Littlefield Publishers, 2001.

Casey, Timothy. 2014. Reflective Practice in Legal Education: The Stages of Reflection. Clinical Law Review 20:317.

Chick, Nancy L.; Karis, Terri; and Kernahan, Cyndi. (2009) “Learning from Their Own Learning: How Metacognitive and Meta-affective Reflections Enhance Learning in Race-Related Courses,” International Journal for the Scholarship of Teaching and

Learning: Vol. 3: No. 1, Article 16. Available at: http://digitalcommons.georgiasouthern.edu/ij-sotl/vol3/iss1/16

Hardisty, D. J., Johnson,E.J., & Weber, E.U.   (2010). A Dirty Word or a Dirty World? Attribute Framing, Political Affiliation, and Query Theory. Psychological Science, 21, 86-92.

Johnson, T. J., Bichard, S. L., & Zhang, W. (2009). Communication communities or “cyberghettos?’’: A path analysis model examining factors that explain selective exposure to blogs. Journal of Computer-Mediated Communication, 15, 60–82

Mezirow, Jack. “Transformative learning as discourse.” Journal of transformative education 1, no. 1 (2003): 58-63.

Murray, T., Stephens, L., Woolf, B. P., Wing, L., Xu, X., & Shrikant, N. (2013). Supporting Social Deliberative Skills Online: The Effects of Reflective Scaffolding Tools. In A. A.

Ozok & P. Zaphiris (Eds.),Online Communities and Social Computing (pp. 313–322). Springer Berlin Heidelberg. Retrieved from http://link.springer.com/chapter/10.1007/978-3-642-39371-6_36

Schwarz, N. (2015). Metacognition. In M. Mikulincer, PR Shaver, E. Borgida, & J. A. Bargh (Eds.), APA Handbook of Personality and Social Psychology: Attitudes and Social Cognition (pp. 203-229). Washington, DC: APA.”

Schwartz, J. P. (2015). To choose one’s company: Arendt, Kant, and the Political Sixth Sense. European Journal of Political Theory, 1474885115613700. http://doi.org/10.1177/1474885115613700


Hitting the Metacognitive Target with Learning Objectives

by Guy A. Boysen, McKednree University (gaboysen@mckednree.edu)

Imagine that you and your colleagues have just retired to the pub for a well-deserved pint at the end of a long week of work in the knowledge factory. After a few refreshing sidartps, you hear the challenge of “Darts!” Rather than playing the usual game of Cricket or 301, the challenger proposes a new competition but does not bother to share the rules. So, you lob darts at random, sometimes hearing “Nice shot!” and other times “Too bad, mate!” Without a clear target to aim for, however, there is no way for you to improve your performance. You lose, and the next round is on you.

If that sounds frustrating, imagine how students feel when they don’t know what to aim for in their efforts at learning – that is, how they feel in classes without clear learning objectives. Learning objectives refer to statements of what students should be able to do after an educational experience. High-quality learning objectives are clear, measurable, and focused on student outcomes rather than instructional methods (Boysen, 2012). Consider these examples.

  • Students in Spanish will be able to ask grammatical questions to solicit various forms of information from Spanish speakers.
  • Students who complete library training will be able to identify peer-reviewed journal articles using the EBSCO database.
  • Students in Statistics will be able to compute means and standard deviations using hand calculations.
  • Readers of this blog will be able to describe the relation between learning objectives and metacognition.

In a straightforward way, learning objectives let students know what they need to know – this is an essential tool for the metacognitive skill of being able to self-assess progress toward educational goals.

Just as you will never win at darts without knowing where to aim, students cannot intentionally evaluate where they are in the learning process without objectives. For example, students in Spanish who are unaware of the learning objective to ask various grammatical questions might mistakenly believe that they are muy bueno with “¿Que pasa?” as their only query. In contrast, students who are aware of the learning objective can more effectively use metacognition by self-assessing their ability to do things like ask for food, directions, the time, or an add/drop slip. Although research is needed to determine if there is a direct link between learning objectives and metacognition, there is longstanding evidence that providing students with learning objectives leads to increased learning (Duell, 1974; Rothkopf & Kaplan, 1972).

Learning objectives clearly have potential as metacognitive tools for helping students assess their own learning, so how do the best college teachers use them? Well, according to An Evidence-Based Guide for College and University Teaching: Developing the Model Teacher (Richmond, Boysen, & Gurung, 2016), there are two fundamental questions that model teachers can say “Yes!” to with regard to learning objectives.

  • Do you “articulate specific, measurable learning objectives in your syllabi or other course documents?” (p. 197)

Model teachers know that, for every one of their readings, activities, tests, and papers, students can determine the learning objective and use it to consider whether or not they are achieving the intended goal. The syllabus is an especially important metacognitive tool. It is the place to introduce students to the concepts of metacognition and learning objectives. In fact, you can even use it to establish learning objectives about the development of metacognition itself (see here for more on metacognitive syllabi; Richmond, 2015).

  • Do you “provide constructive feedback to students is that is related to their achievement of learning objectives?” (p. 197)

Model teachers recognize that students may be unskilled and unaware (Taraban, 2016), so they frequently offer opportunities for objective evaluation. Evaluations such as quizzes, tests, and rubric scores help to keep students’ self-assessment of learning grounded in reality (see Was, 2014 and Taraban, 2014 for more on feedback). For example, students may be 100% confident in their ability to ask questions in Spanish – that is until an oral examination. Struggling to stammer out a modest “¿Que hora es?” and nothing else should lead students to a clearer awareness of their current abilities.

In summary, don’t let your students lob random intellectual darts at mysterious learning targets. Be a model teacher by providing them with clear learning objectives and feedback on their success so that they can hone their metacognitive skills!

References

Boysen, G. A. (2012). A guide to writing learning objectives for teachers of psychology. Society for the Teaching of Psychology Office of Teaching Resources in Psychology Online. Retrieved from https://legacy.berea.edu/academic-assessment/files/2015/02/Guide-to-Writing-Learning-Objectives-for-Teachers-of-Psychology-Boysen-2012.pdf

Duell, O. P. (1974). Effect of type of objective, level of test questions, and the judged importance of tested materials upon posttest performance. Journal of Educational Psychology, 66, 225–323.

Richmond, A. S. (2015, March 6th). The metacognitive syllabus. Retrieved from https://www.improvewithmetacognition.com/metacognitive-syllabus/

Richmond, A. S., Boysen, G. A., Gurung, R. A. R. (2016). An evidence-based guide for college and university teaching: Developing the model teacher. Routledge.

Rothkopf, E. Z., & Kaplan, R. (1972). Exploration of the effect of density and specificity of instructional objectives on learning from text. Journal of Educational Psychology, 63, 295–302.

Taraban, R. (2014, December 10th). Mind the feedback gap. Retrieved from https://www.improvewithmetacognition.com/mind-the-feedback-gap/

Taraban, R. (2016, April 1st). Unskilled and unaware: A metacognitive bias. Retrieved from https://www.improvewithmetacognition.com/unskilled-unaware-metacognitive-bias/

Was, C. (2014, August 28th). Testing improves knowledge monitoring. Retrieved from https://www.improvewithmetacognition.com/testing-improves-knowledge-monitoring/


Hypercorrection: Overcoming overconfidence with metacognition

by Jason Lodge, Melbourne Centre for the Study of Higher Education, University of Melbourne

Confidence is generally seen as a positive attribute to have in 21st Century Western society. Confidence contributes to higher self-esteem, self-reported happiness. It apparently makes someone more attractive and leads to better career outcomes. With such strong evidence suggesting the benefits of confidence, it is no wonder that building confidence has become a major focus within many sectors, particularly in professional development and education.

Despite the evidence for the benefits of confidence, it has a dark side that is overconfidence. There are many occasions where it is problematic to overinflate our skills or abilities. Learning is one of the most obvious examples. According to the (in)famous Dunning-Kruger effect, unskilled learners are often unaware that they are in fact unskilled. The issue here is that those who are low in knowledge of an area are often ignorant to how much they don’t know about the area.

Overconfidence is particularly problematic for students when considering how important it is to make relatively accurate estimates about how they are progressing. For example, if a student is overconfident about their progress, they may decide to stop reviewing or revising a topic prematurely. If students have a difficulty in accurately self-evaluating their learning it can lead them to being underprepared to use the knowledge, for example in an exam or when they need it in practice.

Being wrong can be good

One of the main problems with overconfidence is that students can fail to correct misconceptions or realise that they are wrong. Being wrong or failing has been long seen as negative educational outcomes.

Recent research on productive failure (e.g. Kapur, 2015) has shown, however, that being wrong and coming to realise it is a powerful learning experience. As opposed to more traditional notions of error-free learning, researchers are now starting to understand how important it is for learners to make mistakes. One of the necessary conditions for errors to be effective learning experiences though is that students need to realise they are making them. This is a problem when students are overconfident because they fail to see themselves failing.

There is a silver lining to overconfidence when it comes to making mistakes though. Research on a process called hypercorrection demonstrates that when learners are highly confident but wrong, if the misconception can be corrected, they have a much more effective learning experience (Butterfield & Metcalfe, 2001). In other words, overconfident students who realise that they are wrong about something tend to be surprised and that surprise means they are more likely to learn from the experience.

How metacognition helps with overconfidence

While hypercorrection has potential for helping students overcome misconceptions and achieve conceptual change, it doesn’t happen automatically. One of the main prerequisites is that students need to have enough awareness to realise that they are wrong. The balance between confidence and overconfidence is therefore precarious. It is helpful for students to feel confident that they can manage to learn new concepts, particularly complex and difficult concepts. Confidence helps students to persist when learning becomes difficult and challenging. However, students can have this confidence without necessarily engaging in careful reflective processing. In other words, confidence is not necessarily related to students being able to accurately monitoring their progress.

On the other hand though, it can be easy for students to feel confident in their knowledge of certain misconceptions. This is particularly so if the misconceptions are intuitive and based on real world experience. It is common to have misconceptions about physics and psychology for example because students have vast experience in the physical and social world. This experience gives them intuitive conceptions about the world that are reinforced over time. Some of these conceptions are wrong but their experience gives students high levels of confidence that they are right. Often careful observation or deliberate instructional design is required to shift students’ thinking about these conceptions.

Metacognition is critical in allowing students to monitor and detect when they are making errors or have incorrect conceptions. With misconceptions in particular, students can continue to believe false information if they don’t address the process at which they arrive at a conclusion. Often, overcoming a misconception requires dealing with the cognitive disequilibrium that comes from attempting to overwrite an intuitive conception of the world with a more sophisticated scientific conception.

For example, intuitively a heavy object like a bowling ball and light object like a feather will fall at different rates but, when observing both being dropped simultaneously, they fall at the same rate. The observation causes disequilibrium between the intuitive notion and the more sophisticated understanding of force and gravity encapsulated by Newton’s second law. Generally, overcoming this kind of disequilibrium requires students to shift strategies or approaches to understanding the concept to redress the faulty logic they relied on to arrive at the initial misconception. So in this example, they need to develop a higher-level conception of gravity that requires shifting from intuitive notions. Recognising the need for this shift only comes through metacognitive monitoring and effective error detection.

So metacognition is often necessary for correcting misconceptions and is particularly effective when students are confident about what they think they know and have the realisation that they are wrong. Overconfidence can therefore be managed through enhanced metacognition.

The research on confidence and hypercorrection suggests that it is good for students to be confident about what they think they know as long as they are prepared to recognise when they are wrong. This requires an ability to be able to detect errors and, more broadly, calibrate their perceived progress against their actual progress. While teachers can help with this to a degree through feedback and scaffolding, it is vital that students develop metacognition so that they can monitor when they are wrong or when they are not progressing as they should be. If they can, then there is every chance that the learning experience can be more powerful as a result.

References

Butterfield, B., & Metcalfe, J. (2001). Errors committed with high confidence are hypercorrected. Journal of Experimental Psychology. Learning, Memory, and Cognition, 27(6), 1491–1494. DOI: 10.1037/0278-7393.27.6.1491

Kapur, M. (2015). Learning from productive failure. Learning: Research and Practice, 1(1), 51–65. DOI: 10.1080/23735082.2015.1002195


When & Where to Teach Metacognitive Skills to College Students

Aaron S. Richmond, Ph.D.
Metropolitan State University of Denver

In past blogs, I’ve written about topics that focus on the relationship between academic procrastination and metacognition (Richmond, 2016), or different instructional methods to increase your student’s metacognition (Richmond 2015a, 2015b), or even how to use metacognitive theory to improve teaching practices (Richmond, 2014). However, during my morning coffee the other day I was reading a 2016 article in Metacognition in Learning by Foster, Was, Dunlosky, and Isaacson (yes, I am a geek like that). Studying the importance of repeated assessment and feedback, Foster and colleagues found that over the course of a semester sophomore and junior level education psychology students who were tested 13 separate times and provided feedback remained highly overconfident in their knowledge of the material. As many other researchers have concluded, severe overconfidence erodes accurate self-regulation and self-monitoring which can have a severe detrimental effect on student learning. After finishing my coffee, I thought about the potential long-term and pervasive impacts the lack of metacognition these students had and it dawned on me that in IwM we have not discussed when and where metacognitive skills should be taught in the college curriculum. Thus, I choose to focus this blog on potential suggestions/strategies on when and where to introduce teaching metacognitive skills in the college classroom.

When Should We Teach Metacognitive Skills?
First and foremost, as college and university teachers, we need to acknowledge that our students do not come to us from a vacuum and that they already have many developed, albeit sometimes erroneous and ineffective, metacognitive skills. Considering this fact, we need to adapt our metacognitive instruction on an individual student level to best teach our students. Now, to the question: When should we teach metacognitive skills? The answer is—of course ASAP! As one of the goals to metacognitive skills is to transfer across academic domains, introducing it during the first semester of college is imperative.

One of the most notable early interventions for metacognitive skills was done by Ken Kiewra at the University of Nebraska. Kiewra created a class “Academic Success” taught at the sophomore level using his Selection, Organization, Association, and Regulation (SOAR) model (Jairam & Kiewra, 2009). Jairam and Kiewra had modest effects of increasing student learning (e.g., recalling facts and associating relevant information among zoology terms) via these metacognitive skills. However, there are a few areas in which this approach to teaching metacognitive skills can be improved. First, this is not a class that all students were required to take (only education students). Thus, all other academic disciplines could benefit from this class (see more on this below). Second, most of the students who took this course were at the sophomore and junior college level. This course should be a first semester course for all students, rather than midway through the college career.

The final note regarding when we should teach metacognitive skills almost negates or precludes the initial question. That is, the ‘when’ is immediately, but immediately doesn’t mean or suggest once. Rather, metacognitive skills should be taught continuously throughout the college career with increasingly more advanced and effective memory and learning strategies. Just as a student would take an introductory course to a major, why not have a beginner, intermediate, and advanced metacognitive skills course?

Where Should Metacognitive Skills Be Taught?
Obviously, those at IwM, and presumably our readers, would quickly answer this question: EVERYWHERE! That is, metacognitive skills should be taught across the college curriculum. However, there are some academics who believe (a) our students have already learned effective learning strategies (Jairam & Kiewra, 2009), and (b) that metacognitive skills are not part of their curriculum. In response to the first belief, many of our incoming college and university students do not have effective metacognitive skills so it is important that we teach these skills in all different types of academic domains (Jairam & Kiewra, 2009). In response to the second belief, metacognition should be taught across all academic domains. This includes mathematics, philosophy, chemistry, nursing, psychology, anthropology. I will go so far as to suggest that metacognitive skills are tantamount to reading skills as it pertains to the learning process and should be incorporated throughout the curriculum. But herein lies the rub. I have yet to find a current model or research example of infusing metacognitive skill training across the curriculum. For example, in general studies education, why not have a metacognitive student learning objective that cuts across all academic domains. Or in a first-year-success program that is often taught in teams, why not incorporate metacognitive skill training via thematic instruction (e.g., various academic disciplines are asked to center their instruction around a similar topic) among several introductory level classes. That is, teach metacognition in General Psychology, Speech 101, Biology 101, etc. by using a threaded theme (e.g., racism) that requires teachers to teach metacognitive skills to help learn a particular topic. In the end, it is clear that all students in all disciplines could benefit from metacognitive skill training, yet researchers nor teachers have tackled these specific issues.

There Are Always More Questions Than Answers.
I’ve done it again, I’ve written a blog that touches on what I believe to be an important issue in metacognition and higher education that needs far more research. As such, I must wrap up this blog (as I always do) with a few questions/challenges/inspirational ideas.

  1. Should metacognition, learning strategies, etc. be taught throughout the curriculum?
    1. If so, how?
  2. If not, should they be taught in a self-contained introduction to college course?
    1. Should all college students to be required to take this course?
  3. What other models of introducing and teaching metacognitive skills are there that may be more effective than a self-contained course vs. a thematic curriculum approach?
  4. Once students have been introduced to metacognitive skills, what is the best method for continuing education of metacognitive skills?

References
Foster, N. L., Was, C. A., Dunlosky, J., & Isaacson, R. M. (2016). Even after thirteen class exams, students are still overconfident: The role of memory for past exam performance in student predictions. Metacognition and Learning, 1-19. doi:10.1007/s11409-016-9158-6

Jairam, D., & Kiewra, K. A. (2009). An investigation of the SOAR study method. Journal of Advanced Academics, 20(4), 602-629.

Richmond, A. S. (2016, February 16th). Are academic procrastinators metacognitively deprived?. Retrieved from https://www.improvewithmetacognition.com/are-academic-procrastinators-metacognitively-deprived/

Richmond, A. S. (2015a, November 5th). A minute a day keeps the metacognitive doctor away. Retrieved from https://www.improvewithmetacognition.com/a-minute-a-day-keeps-the-metacognitive-doctor-away/

Richmond, A. S. (2015b, July 20th). How do you increase your students metacognition?. Retrieved from https://www.improvewithmetacognition.com/how-do-you-increase-your-students-metacognition/

Richmond, S. (2014, August 28th). Meta-teaching: Improve your teaching while improving your student’s metacognition. Retrieved from https://www.improvewithmetacognition.com/meta-teaching-improve-your-teaching-while-improving-students-metacognition/


Don’t “Just Do It” – Think First

by Roman Taraban, PHD, Texas Tech University

“Just Do It” has been a great slogan for selling athletic equipment and has also spawned some humorous spinoffs, like Bart Simpson’s “Can’t someone else just do it?” And is it not how we sometimes solve problems: “Don’t think, just do it?” Although just doing it (or getting someone else to do it) may have some visceral appeal, models for teaching argue against just doing it when it comes to solving problems.

One of the most influential problem-solving models is Polya’s (1957) 4-step model: i) understand the problem, ii) develop a plan, iii) carry out the plan, and iv) look back. On this model, solvers don’t “do it” until the 3rd step. What is really striking about this model is that it is mostly about critical thinking and metacognitive processing. The principles of understanding the problem, planning one’s approach to solving the problem, and reflecting on the solution after “doing it,” all require critical thinking and metacognition (Draeger, 2015). STEM disciplines have generally embraced the Polya model, suggesting that commitments to metacognitive thinking by researchers and instructors are widespread and well-entrenched. Two disciplines will be considered here to make that point: mathematics and engineering.

In a research study in mathematics, Carlson and Bloom (2005) collected and analyzed the problem solving behaviors of twelve expert mathematicians. The data showed that the mathematicians engaged in metacognitive behaviors and decisions that were organized within a general problem-solving framework consisting of Orienting, Planning, Executing, and Checking. One of the phases, Executing, is where one “does it” – the others are more metacognitive. Researchers have developed comparable models for problem-solving in engineering. These models preface equation-crunching with understanding the problem and planning a solution, and follow up with reflection on the solution. This is exemplified in the six-step McMaster model: Engage, Define the Stated Problem, Explore, Plan, Do It, and Look Back (Woods et al., 1997).

In spite of teachers’ best intentions, might students still just do it? Certainly! An alternative to metacognitive planning before doing, and monitoring, regulating, and reflecting, is to apply a purely rote strategy (Garofalo & Lester, 1985), also termed a “plug and chug” method (Maloney, 2011). Plug and chug in physics and engineering involves a mental search for equations that will solve the problem, but with little conceptual understanding of the nature of the problem, little strategic decision-making, and little metacognitive self-reflection and regulation of the solution process. In disciplines not involving equations, various matching and cut-and-paste strategies could qualify as plug-and-chug. James Stice, a distinguished professor in chemical engineering, described part of his own engineering training (Stice, 1999) that suggests how plug-and-chug may come about:

“When I was an undergraduate student, many of my professors would derive an equation during lecture, and then would proceed to work an example problem. They would outline the situation, invoke the equation, plug in the numbers and arrive at a solution. What they did always seemed very logical and straightforward, I’d get it all down in my notes, and I’d leave the class feeling that I had understood what they had done. Later I often was chagrined to find that I couldn’t work a very similar problem for homework.” (p. 1)

Much of the motivation for research on how experts solve problems, like Carlson and Bloom (2005), has led to developing didactic models for the classroom, like the six-step McMaster model (Woods et al., 1997) in engineering: Engage, Define the Stated Problem, Explore, Plan, Do It, and Look Back. These didactic models have been developed largely in response to the absence of metacognitive thinking among students.

Although teaching methods could account for some of the absence of metacognitive thinking in beginning students, domain-specific knowledge may also be a factor. Few would disagree that domain-specific knowledge plays a key role in successful problem solving. Indeed, Carlson and Bloom attributed the expertise of their mathematicians, in part, to “a large reservoir of well-connected knowledge, heuristics, and facts” (p. 45). Can a novice student readily access domain-related facts, organize information within the problem, muse, imagine, and conjecture over possible strategies, apply heuristics, and effectively monitor progress? Of course not. Obviously, the absence of domain-specific knowledge in beginning students enables and motivates the teaching of domain-specific knowledge. But I would like to argue that the absence of domain-specific knowledge also enables and motivates teaching students metacognitive processes. This may seem illogical, but it’s not. The point is that an absence of domain-specific knowledge provides instructors with a great opportunity to teach the domain-specific knowledge but also how to think about thinking about that knowledge, that is, how to be metacognitive while learning facts and procedures.

Getting students to “Think, then Do It” will require more than working examples for them on the blackboard in order to convey domain-specific knowledge. Instead, within a framework like that provided by Carlson and Bloom, the metacognitive processes at each step of solving the problem should also be modeled. Some students may show metacognitive behaviors early on, and all successful students will eventually catch on. However, to truly be a pedagogical principle, it needs to be part of the learning situation. A model of metacognitive instruction (Scharff, 2015) for the student could be guided by the work on scaffolding metacognitive processes proposed in the seminal work of Brown and Palinscar (1982). The point is to take the domain-specific knowledge that you are trying to convey and to model and scaffold it to students along with the metacognitive decisions and control that go with expert problem solving, and to do it early on in instruction. It is worth mentioning that James Stice, who was taught to plug and chug, became a follower and proponent of the six-step McMaster model as professor of chemical engineering.

There is an old Jack Benny joke. Jack Benny was a comedian known for being a cheapskate. One night a thug stopped him – “Don’t make a move bud, your money or your life.” After a long pause, the thug, clearly annoyed, repeated – “Look bud, I said….Your money or your life.” Jack Benny: “I’m thinking it over.” Just to be fair, sometimes we should just Do It and not think too much about it. When it comes to teaching and learning, though, thinking about thinking is better.

References

Brown, A. L., & Palinscar, A. S. (1982). Inducing strategic learning from texts by means of informed, self-control training. Tech Report No. 262. Urbana: University of Illinois Center for the Study of Reading.

Carlson, M. P., & Bloom, I. (2005). The cyclic nature of problem solving: An emergent multidimensional problem-solving framework. Educational Studies in Mathematics, 58, 45-75.

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/ .

Garofalo, J., & Lester Jr., F. K. (1985). Metacognition, cognitive monitoring, and mathematical performance. Journal for Research in Mathematics Education, 16(3), 163-176.

Maloney, D. P. (2011). An overview of physics education research on problem solving. Getting Started in PER..Reviews in PER vol. 2. College Park, MD: American Association of Physics Teachers. http://opus.ipfw.edu/physics_facpubs/49

Polya, G. (1957). How to solve it. Princeton, NJ: Princeton University Press.

Scharff, Lauren (2015). “What do we mean by ‘metacognitive instruction?” Retrieved from https://www.improvewithmetacognition.com/what-do-we-mean-by-metacognitive-instruction/

Stice, J. (1999). Teaching problem solving. In Teachers and students – A sourcebook (Section 4). University of Texas at Austin: Center for Teaching Effectiveness. Retrieved from

http://www.utexas.edu/academic/cte/sourcebook/teaching3.pdf

Woods, D. R., Hrymak, A. N., Marshall, R. R., Wood, P. E., Crowe, C. M., Hoffman, T. W., Wright, J. D., Taylor, P. A., Woodhouse, K. A., & Bouchard C. G. (1997). Developing problem solving skills: The McMaster problem solving program. Journal of Engineering Education, 86(2), 75–91.


How to train reflection-in-action?

by Dr. Dominique Verpoorten, Lecturer (Learning Sciences), IFRES-University of Liège, Belgium

In this post, I’d like to introduce the notion of « reflection amplifier » in relationship with the notion of “reflection-in-action”.

Common sense tells us that reflection lies somewhere around the notion of learning and thinking. People learn as a result of reflecting. Reflection is practised in order to consider an object in more detail (Amulya, 2004).

Objects about which reflection can be amplified are innumerable. One can boost thinking on life, space, love, germs, fossils, butterflies or any content topic. This post addresses one specific topic of reflection: oneself as a learner.

Taking learning as an object of reflection is assumed to be an essential factor of expert learners (Ertmer & Newby, 1996). Reflective practice in formal learning contexts is supposed to gradually increase learners’ awareness of what helps and hampers a consistent orchestration of the various dimensions of their learning processes.

There are a number of methods that are held to encourage reflection on learning. These include learning diaries, portfolios, discussions of learning strategies, use of video and observers in a learning context, etc. These highly valuable approaches address post-practice reflection or what Schön (1983) refers to as “reflection on action”, that is a thinking episode taking place after the event and re-evaluating it so as to gain insight for improvement in the future.

But what about the training of “reflection in action”? Here come the reflection amplifiers (RAs). They present as deliberate, well-considered, and structured opportunities for students to examine and evaluate aspects of their learning experience as they occur. Unlike post-practice introspection assignments (portfolios, learning blogs…), RAs are nested in the study material and offered to individuals during learning activities. In the temporal flow of learning, their contiguity to student’s doings commits them to reflection-in-action more than to reflection on action, though Schön’s (1983) distinction is relative: even a reflection that takes place “in-action” bears on a pre-existing context. But in the case of a RA the interval is supposed to be a matter of seconds or minutes rather than hours. A typical feature of RAs is that they focus learners’ instant reflection on aspects of the learning experience they are currently committed to. RAs therefore present as brief, structured and repeated reflection affordances, interspersed in the learning material and activated during its internalization. These built-in opportunities for reflection are purposed to offer stop-and-think episodes in the course of learning. Examples of reflections amplifiers assigned to students in the course of their learning could be:

  • Rate your current mastery of the study material
  •  Give the degree of confidence you have in the correctness of your answer
  •  For one minute, evoke mentally the content at hand
  •  Give an estimation of your feeling of learning
  •  Write down a question that the teacher could ask on this topic

The word “amplifier” is used intentionally to convey the idea that enacting such affordances for reflection in the course of learning expands the mental context of the task at hand and discloses aspects of it that would otherwise be left untouched.

Reflection amplifiers have in common that they are harnessed to a first-order learning assignment. They serve it but are not confused with it due to their brevity and their meta-learning dimension. Reflection amplifiers are intended to support students at examining aspects of their learning experience in the moment of learning. They induce regular mental tinglings for evaluating “what is going on” (Salmon & al. 2007) and for nurturing internal feedback (Butler & Winne, 1995). They invite learners to think about what they are doing while they are doing it. Through establishing a practice of reflection during learning, RAs provide students with an opportunity to develop a habit of and a positive attitude towards thinking about learning.
By providing students with deliberate and structured opportunities to examine and evaluate their own learning while this learning unfolds, RAs instantiate a form of “split screen teaching” (Claxton, 2006), that consists in maintaining a dual focus on the content of the lesson and the learning dispositions and processes that are in play. Do you practice split screen teaching by sometimes providing reflection amplifiers to your students? What do they look like?

References

Amulya, J. (2004). What is Reflective Practice? Cambridge, MA: MIT – Center for Reflective Practice.

Butler, D. L., & Winne, P. H. (1995). Feedback and Self-Regulated Learning: A Theoretical Synthesis. Review of Educational Research, 65(3), 245-281.

Claxton, G. (2006, September). Expanding the capacity to learn: a new end for education? Opening keynote address presented at the British Educational Research Association Annual Conference, University of Warwick, UK.

Ertmer, P. A., & Newby, T. J. (1996). The expert learner: Strategic, self-regulated, and reflective. Instructional Science, 24(1), 1-24.
Georghiades, P. (2004). From the general to the situated: three decades of metacognition. International Journal of Science Education, 26(3), 365-383.

Salmon, P., Stanton, N., Jenkins, D., Walker, G., Young, M., & Aujla, A. (2007). What Really Is Going on? Review, Critique and Extension of Situation Awareness Theory. Engineering Psychology and Cognitive Ergonomics, 4562, 407-416.

Schön, D. (1983). The Reflective Practitioner: How professionals think in action. London: Temple Smith.

More about RAs:

http://orbi.ulg.ac.be/handle/2268/186755

http://orbi.ulg.ac.be/handle/2268/151345

http://orbi.ulg.ac.be/handle/2268/169931

http://orbi.ulg.ac.be/handle/2268/156417

http://orbi.ulg.ac.be/handle/2268/151799,

http://orbi.ulg.ac.be/handle/2268/151374


The Challenge of Deep Learning in the Age of LearnSmart Course Systems (Part 2)

A few months ago, I shared Part 1 of this post. In it I presented the claim that, “If there are ways for students to spend less time per course and still “be successful,” they will find the ways to do so. Unfortunately, their efficient choices may short-change their long-term, deep learning.” I linked this claim to some challenges that I foresaw with respect to two aspects of the online text chosen for the core course I was teaching: 1) the pre-highlighted LearnSmart text, and 2) the metacognition-focused LearnSmart quizzing feature. This feature required students to not only answer the quiz question, but also report their confidence in the correctness of that response. (See Part 1 for details to explain my concerns. Several other posts on this site also discuss confidence ratings as a metacognition tool. See references below.) My stated plan was to “regularly check in with the students, have class discussions aimed at bringing their choices about their learning behaviors into their conscious awareness, and positively reinforcing their positive self-regulation of deep-learning behaviors.” 

This post, Part 2, will share my reflections on how things turned out, along with a summary of some feedback from my students.

With respect to my actions, I did the following in order to increase student awareness of their learning choices and the impact of those choices. Twice early in the semester I took class time to explicitly discuss the possible learning shortcuts students might be tempted to take when reading the chapters (e.g. only reading the highlighted text) and when completing the LearnSmart pre-class quizzes (see Part 1 for details). I shared some alternate completion options that would likely enhance their learning and long-term retention of the material (e.g. reading the full text without highlights and using the online annotation features). Additionally, I took time to share other general learning / studying strategies that have been shown through research to support better learning. These ways of learning were repeatedly reinforced throughout the semester (and linked to content material when applicable, such as when we discussed human learning and memory).

Did these efforts impact student behaviors and choices of learning strategies? Although I cannot directly answer that question, I can share some insights based on some LearnSmart data, course performance, and reflections shared by the students.

With respect to the LearnSmart application that quizzed students at the end of each chapter, one type of data I was able to retrieve was the overall percent of time that student LearnSmart quiz question responses fell into the following correctness and confidence categories (a metacognition-related evaluation):

  1. Students answered correctly and indicated confidence that they would answer correctly
  2. Students answered correctly but indicated that they were not confident of the correctness of their response
  3. Students answered incorrectly and knew they didn’t know the answer
  4. Students answered incorrectly but reported confidence in giving the correct answer

I examined how the percentage of time student responses fell in each category correlated with two course performance measures (final exam grade and overall course grades). Category 1 (correct and confident) and Category 3 (incorrect and knew it) both showed essentially a zero relationship with performance. There was a small positive relationship between being correct but not certain (Category 2). Category 2 responses might prompt more attention to the topic and ultimately lead to better learning. The strongest correlations (negative direction) occurred for Category 4, which was the category about which I was most concerned with respect to student learning and metacognition. There are two reasons students might have responses in that category. They could be prioritizing time efficiency over learning because they were intentionally always indicating they were confident (so that if they got lucky and answered correctly, the question would count toward the required number that they had to answer both correctly and with confidence; if they indicated low confidence, then the question would not count toward the required number they had to complete for the chapter). Alternately, Category 4 responses could be due to students being erroneous with respect their own state of understanding, suggesting poor metacognitive awareness and a likelihood to perform poorly on exams despite “studying hard.” Although there was no way for me to determine which of these two causes were underlying the student responses in this category, the negative relationship clearly indicated that those who had more such responses performed worse on the comprehensive final exam and in the course at large.

I also asked my students to share some verbal and written reflections regarding their choices of learning behaviors. These reflections didn’t explicitly address their reasons for indicating high or low confidence for the pre-class quizzes. However, they did address their choices with respect to reading only the highlighted versus the full chapter text. Despite the conversations at the beginning of the semester stressing that exam material included the full text and that their learning would be more complete if they read the full text, almost half the class reported only reading the highlighted text (or shifting from full to highlighted). These students indicated that their choice was primarily due to perceived time constraints and the fact that the pre-class LearnSmart quizzes focused on the highlighted material so students could be successful on the pre-class assignment without reading the full text. More positively, a couple students did shift to reading the full text because they saw the negative impact of only reading the highlighted text on their exam grades. Beyond the LearnSmart behaviors, several students reported increasing use (even in other courses) of the general learning / study strategies we discussed in class (e.g. working with a partner to discuss and quiz each other on the material), and some of them even shard these strategies with friends!

So, what are my take-aways?

Although this should surprise no one who has studied operant conditioning, the biggest take-away for me is that for almost half my students the immediate reinforcement of being able to more quickly complete the pre-class LearnSmart quiz was the most powerful driver of their behavior, despite explicit in-class discussion and their own acknowledgement that it hurt their performance on the later exams. When asked what they might do differently if they could redo the semester, several of these students indicated that they would tell themselves to read the full text. But, I have to wonder if this level of awareness would actually drive their self-regulatory behaviors due the unavoidable perceptions of time constraints and the immediate reinforcement of “good” performance on the pre-class LearnSmart quizzes. Unfortunately, at this point, instructors do not have control over the questions asked in the LearnSmart quizzes, so that particular (unwanted) reinforcement factor is unavoidable if you use those quizzes. A second take-away is that explicit discussion of high-efficacy learning strategies can lead to their adoption. These strategies were relatively independent from the LearnSmart quiz requirement for the course, so there was no conflict with those behaviors. Although the reinforcement was less immediate, students reported positive results from using the strategies, which motivated them to keep using them and to share them with friends. Personally, I believe that the multiple times that we discussed these general learning strategies also helped because they increased student awareness of them and their efficacy (awareness being an important first step in metacognition).

————

Some prior blog posts related to Confidence Ratings and Metacognition

Effects of Strategy Training and Incentives on Students’ Performance, Confidence, and Calibration, by Aaron Richmond October 2014

Quantifying Metacognition — Some Numeracy behind Self-Assessment Measures, by Ed Nuhfer, January 2016

The Importance of Teaching Effective Self-Assessment, by Stephen Chew, Feb 2016

Unskilled and Unaware: A Metacognitive Bias, by John R. Schumacher, Eevin Akers, and Roman Taraban, April 2016


Using Metacognition to select and apply appropriate teaching strategies

by John Draeger (SUNY Buffalo State) & Lauren Scharff (U. S. Air Force Academy)

Metacognition was a recurring theme at the recent Speaking SoTL (Scholarship of Teaching and Learning) conference at Highpoint university. Invited speaker Saundra McGuire, for one, argued that metacognition is the key to teaching students how to learn. Stacy Lipowski, for another, argued for the importance of metacognitive self-monitoring through the regular testing of students. We argued for the importance of metacognitive instruction (i.e. the use of reflective awareness and self-regulation to make intentional and timely adjustments to teaching a specific  individual or group of students) as a tool for selecting and implementing teaching strategies. This post will share a synopsis of our presentation from the conference.

We started with the assumption that many instructors would like to make use of evidence-based strategies to improve student learning, but they are often faced with the challenge of how to decide among the many available options. We suggested that metacognitive instruction provides a solution. Building blocks for metacognitive instruction include 1) consideration of student characteristics, context, and learning goals, 2) consideration of instructional strategies and how those align with the student characteristics, context, and learning goals, and 3) ongoing feedback, adjustment and refinement as the course progresses (Scharff & Draeger, 2015).

Suppose, for example, that you’re teaching a lower-level core course in your discipline with approximately 35 students where the course goals include the 1) acquisition of broad content and 2) application of this content to new contexts (e.g., current events, personal situations, other course content areas). Students enrolled in the course typically have a variety of backgrounds and ability levels. Moreover, they don’t always see the relevance of the course and they are not always motivated to complete assignments. As many of us know, these core courses are both a staple of undergraduate education and a challenge to teach.

Scholarly teachers (Richlin, 2001) consult the literature to find tools for addressing the challenges just described. Because of the recent growth of SoTL work, they will find many instructional choices to choose from. Let’s consider four choices. First, Just-in-Time teaching strategies ask students to engage course material prior to class and relay those responses to their instructor (e.g., select problem sets or focused writing). Instructors then use student responses to tailor the lesson for the day (Novak, Patterson, & Gavrin, 1999; Simkins & Maier, 2004; Scharff, Rolf, Novotny, & Lee, 2013). In courses where Just-in-Time teaching strategies are used, students are more likely to read before class and take ownership over their own learning. Second, Team-Based Learning (TBL) strategies also engage students in some pre-class preparation, and then during class, students engage in active learning through a specific sequence of individual work, group work, and immediate feedback to close the learning loop (Michaelsen & Sweet, 2011). TBL has been shown to shift course goals from knowing to applying and create a more balanced responsibility for learning between faculty and students (with students taking on more responsibility). Third, concept maps provide visual representations of important connections (often hierarchical connections) between important concepts. They can help students visualize connections between important course concepts (Davies, 2010), but they require some prior understanding of the concepts being mapped. Fourth, mind mapping also leads to visual representations of related concepts, but the process is more free-form and creative, and often requires less prior knowledge. It encourages exploration of relationships and is more similar to brainstorming.

Any of these three tools might be good instructional choices for the course described above. But how is an instructor supposed to choose?

Drawing inspiration from Tanner (2012) who shared questions to prompt metacognitive learning strategies for students, we recommend that instructors ask themselves a series of questions aligned with each of our proposed building blocks to prompt their own metacognitive awareness and self-regulation (Scharff & Draeger, 2015). For example, instructors should consider the type of learning (both content and skills) they hope their students will achieve for a given course, as well as their own level of level of preparedness and time / resources available for incorporating that particular type of teaching strategy.

In the course described above, any of the four instructional strategies might help with the broad acquisition of content, and depending upon how they are implemented, some of them might promote student application of the material to new contexts. For example, while concept maps can facilitate meaningful learning their often hierarchical structure may not allow for the flexibility associated with making connections to personal context and current events. In contrast, the flexibility of mind-mapping might serve well to promote generation of examples for application, but it would be less ideal to support content acquisition. Team-Based-Learning can promote active learning and facilitate the application of knowledge to personal contexts and current events, but it requires the instructor to have high familiarity with the course and the ability to be very flexible during class as students are given greater responsibility (which may be problematic with lower-level students who are not motivated to be in the course).   Just-in-Time-Teaching can promote both content acquisition and application if both are addressed in the pre-class questions. During class, the instructor should show some flexibility by tailoring the lesson to best reach students based on their responses to the pre-class questions, but overall, the lesson is much more traditional in its organization and expectations for student engagement than with TBL. Under these circumstances, it might be that Just-in-Time strategies offer the best prospect for teaching broad content to students with varying backgrounds and ability levels.

While the mindful choice of instructional strategies is important, we believe that instructors should also remain mindful in-the-moment as they implement strategies. Questions they might ask themselves include:

  • What are you doing to “check in” with your learners to ensure progress towards daily and weekly course objectives?
  • What are signs of success (or not) of the use of the strategy?
  • How can you  adjust the technique to better meet your student needs?
  • Are your students motivated and confident, or are they bored or overwhelmed and frustrated? Are your students being given enough time to practice new skills?
  • If learning is not where it needs to be or student affect is not supportive of learning, what are alternate strategies?
  • Are you prepared to shift to them? If not, then why not?

These prompts can help instructors adjust and refine their implementation of the chosen instructional strategy in a timely manner.

If, for example, Just-in-Time assignments reveal that students are understanding core concepts but having difficulty applying them, then the instructor could tweak Just-in-time assignments by more explicitly requiring application examples. These could then be discussed in class. Alternatively, the instructor might keep the Just-in-Time questions focused on content, but start to use mind mapping during class in order to promote a variety of examples of application.  In either case, it is essential that instructors are explicitly and intentionally considering whether the instructor choice is working as part of an ongoing cycle of awareness and self-regulation. Moreover, we believe that as instructors cultivate their ability to engage in metacognitive instruction, they will be better prepared to make in-the-moment adjustments during their lessons because they will be more “tuned-in” to the needs of individual learners and they will be more aware of available teaching strategies.

While not a magic bullet, we believe that metacognitive instruction can help instructors decide which instructional strategy best fits a particular pedagogical situation and it can help instructors adjust and refine those techniques as the need arises.

References

Davies, M. (2011). Concept mapping, mind mapping and argument mapping: what are the differences and do they matter? Higher education, 62(3), 279-301.

Michaelsen, L. K., & Sweet, M. (2011). Team‐based learning. New directions for teaching and learning,(128), 41-51.

Novak, G., Patterson, E., Gavrin, A., & Christian, W. (1999). Just-in-time teaching:

Blending active learning with web technology. Upper Saddle River, NJ: Prentice Hall.

Richlin, L. (2001). Scholarly teaching and the scholarship of teaching. New directions for teaching and learning, 2001(86), 57-68.

Scharff, L. and Draeger, J. (2015). “Thinking about metacognitive instruction” National Teaching and Learning Forum 24 (5), 4-6.

Scharff, L., Rolf, J. Novotny, S. and Lee, R. (2011). “Factors impacting completion of pre-class assignments (JiTT) in Physics, Math, and Behavioral Sciences.” In C. Rust (ed.), Improving Student Learning: Improving Student Learning Global Theories and Local Practices: Institutional, Disciplinary and Cultural Variations. Oxford Brookes University, UK.

Simkins, S. & Maier, M. (2009). Just-in-time teaching: Across the disciplines, across the

academy. Stylus Publishing, LLC.

Tanner, K. D. (2012). Promoting student metacognition. CBE-Life Sciences Education, 11(2), 113-120.


Meaningful Reflections for Improving Student Learning

by Ashley Welsh, Postdoctoral Teaching & Learning Fellow, Vantage College

I am a course coordinator and instructor for a science communication course (SCIE 113) for first-year science students. SCIE 113 focuses on writing, argumentation and communication in science and is part of the curriculum for an enriched, first-year experience program for international, English Language Learners. Throughout the term, students provide feedback on their peers’ writing in both face-to-face and online environments. The process of providing and receiving feedback is an important skill for students, however many students do not receive explicit instruction on how to provide or use constructive feedback (Mulder, Pearce, & Baik, 2014). In order to better understand my students’ experience with peer review, I conducted a research project to explore how their use and perceptions of peer review in their writing developed over the course of the term.

Many of the data collection methods I used to assess students’ perceptions and use of peer review in SCIE 113 this past term incorporated acts of reflection. These included in-class peer review worksheets and written reflections, small and large group discussions, an end-of-term survey about peer review, and my own researcher reflections. Periodically throughout the semester, I paired up the students and they engaged in peer review of one another’s writing. They each had a worksheet that asked them to comment on what their partner did well and how that person could improve their writing. During this activity, my teaching assistant and I interacted with the pairs and answered any potential questions. Afterwards, students independently completed written reflections about the usefulness of the peer review activity and their concerns about giving and receiving feedback. Before the class finished, we discussed students’ responses and concerns as a whole group. Students’ worksheets and written reflections, as well as classroom observations, offered insight into how my pedagogy mapped to their use of and reflections about peer review.

As of late, I have been more deliberate with designing pedagogy and activities that offer students the time and space to reflect and record their strengths and weaknesses as learners. The term reflection, is often used when discussing metacognition. As Weinert (1987) describes, metacognition involves second-order cognitions such as thoughts about thoughts or the reflections of one’s actions. With respect to metacognitive regulation, Zohar and Barzilai (2013) highlight that an individual can heighten their awareness of their strengths/weaknesses and evaluate their progress via reflection. This reflection process also plays a key role in metacognition-focused data collection as most methods require students to reflect upon how their knowledge and skills influence their learning. Providing survey responses, answering interview questions, and writing in a journal require a student to appraise their personal development and experience as a learner through reflection (Kalman, 2007; Aktruk & Sahin, 2011).

While the act of reflection is an important component of metacognition and metacognitive research, its use in the classroom also presents its own set of challenges. As educators and researchers, we must be wary of not overusing the term so that it remains meaningful to students. We must also be cautious with how often we ask students to reflect. An extensive case study by Baird and Mitchell (1987) revealed that students become fatigued if they are asked to reflect upon their learning experiences too often. Furthermore, we hope these acts of reflection will help students to meaningfully evaluate their learning, but there is no guarantee that students will move beyond simplistic or surface responses. To address these challenges in my own classroom, I attempted to design activities and assessments that favoured “not only student participation and autonomy, but also their taking responsibility for their own learning” (Planas Lladó et al., p. 593).

While I am still in the midst of analyzing my data, I noticed over the course of the semester that students became increasingly willing to complete the reflections about peer review and their writing. At the beginning of the term, students wrote rather simplistic and short responses, but by the end of the term, students’ responses contained more depth and clarity. I was surprised that students were not fatigued by or reluctant to complete the weekly reflections and discussions about peer review and that this process became part of the norm of the classroom. Students also became faster with completing their written responses, which was promising given that they were all English Language Learners. As per John Draeger (personal communication, April 27, 2016), students’ practice with these activities appears to have helped them build the stamina and muscles required for successful and meaningful outcomes. It was rewarding to observe that within class discussions and their reflections, students became better aware of their strengths and weaknesses as reviewers and writers (self-monitoring) and often talked or wrote about how they could improve their skills (self-regulation).

Based on my preliminary analysis, it seems that tying the reflection questions explicitly to the peer review process allowed for increasingly meaningful and metacognitive student responses. The inclusion of this research project within my class served as an impetus for me to carefully consider and question how my pedagogy was linked to students’ perceptions and ability to reflect upon their learning experience. I am also curious as to how I can assist students with realizing that this process of reflection can improve their skills not only in my course, but also in their education (and dare I say life). This research project has served as an impetus for me to continue to explore how I can better support students to become more metacognitive about their learning in higher education.

References

Akturk, A. O., & Sahin, I. (2011). Literature review on metacognition and its measurement. Procedia Social and Behavioral Sciences, 15, 3731-3736.

Baird, J. R., & Mitchell, I. J. (1987). Improving the quality of teaching and learning. Melbourne, Victoria: Monash University Press.

Kalman, C. S. (2007). Successful science and engineering teaching in colleges and universities. Bolton, Massachusetts: Anker Publishing Company, Inc.

Mulder, R.A., Pearce, J.M., & Baik, C. (2014). Peer review in higher education: Student perceptions before and after participation. Active Learning in Higher Education, 15(2), 157-171.

Planas Lladó, A., Feliu Soley, L., Fraguell Sansbelló, R.M., Arbat Pujolras, G., Pujol Planella, J., Roura-Pascual, N., Suñol Martínez, J.J., & Montoro Moreno, L. (2014). Student perceptions of peer assessment: An interdisciplinary study. Assessment & Evaluation in Higher Education, 39(5), 592-610.

Weinert, F. E. (1987). Introduction and overview: Metacognition and motivation as determinants of effective learning and understanding. In F. E. Weinert & R. H. Kluwe (Eds.), Metacognition, motivation, and understanding (pp. 1-16). Hillsdale, New Jersey: Lawrence Erlbaum Associates, Inc.

Zohar, A., & Barzilai, S. (2013). A review of research on metacognition in science education: Current and future directions. Studies in Science Education, 49(2), 121-169.


Distributed Metacognition: Insights from Machine Learning and Human Distraction

by Philip Beaman, Ph.D., University of Reading, UK

Following the success of Google’s AlphaGo programme in competition with a human expert over five games, a result previously considered beyond the capabilities of mere machines (https://deepmind.com/alpha-go), there has been much interest in machine learning. Broadly speaking, machine learning comes in two forms: supervised learning (where the machine is trained by means of examples and errors it makes are corrected) or unsupervised learning (where there is no error signal to indicate previous failures). AlphaGo, as it happens, used supervised learning based upon examples of human expert-level games and it is this type of learning which looks very much like meta-cognition, even though the meta-cognitive monitoring and correction of the machine’s performance is external to the system itself, although not necessarily to the machine which is running the system. For example: an artificial neural network (perhaps of the kind which underpins AlphaGo) is trained to output Y when presented with X by means of a programme which stores training examples – and calculates the error signal from the neural network’s first attempts – outside the neural network software itself but on the same hardware. This is of interest because it illustrates the fluid boundary between a cognitive system (the neural network implemented on computer hardware) and its environment (other programmes running on the same hardware to support the neural network) and demonstrates that metacognition, like first-order cognition, is often a form of situated activity. Here, the monitoring and the basis for correction of performance is (like all supervised learning) external to the learning system itself.

In contrast, when psychologists talk about metacognition, we tend to assume that all the processing is going on internally (in the head), whereas in fact it is usually only partly in the head and partly in the world. This is not news to educationalists or to technologists: learners are encouraged to make effective use of external aids which help manage work and thought, but external aids to cognition are often overlooked by psychological theories and investigations. This was not always the case. In the book “Plans and the Structure of Behaviour” which introduced the term “working memory” to psychology, Miller, Galantner and Pribram (1960) spoke of working memory as being a “special state or place” used to track the execution of plans where the place could be in the frontal lobes of the brain (a prescient suggestion for the time!) or “on a sheet of paper”. This concept that was originally defined wholly functionally has, in subsequent years, morphed into a cognitive structure with a specific locus, or loci, of neural activity (e.g., Baddeley, 2007; D’Esposito, 2007; Henson, 2001; Smith, 2000).

We have come across the issue of distributed metacognition in our own work on auditory distraction. For many years, our lab (along with several others) collected and reported data on the disruptive effects of noise on human cognition and performance. We carefully delineated the types of noise which cause distraction and the tasks which were most sensitive to distraction but – at least until recently – neither we nor (so far as we know) anyone else gave any thought to meta-cognitive strategies which might be employed to reduce distraction outside the laboratory setting. Our experiments all involved standardized presentation schedules of material for later recall and imposed environmental noise (usually over headphones) which participants were told to ignore but which they could not avoid. The results of recent studies which both asked participants for their judgments of learning (JoLs) concerning the material and gave them the opportunity to control their own learning or recall strategy (e.g., Beaman, Hanczakowski & Jones, 2014) are of considerable interest. Theoretically, one of three things might happen: meta-cognition might not influence ability to resist distraction in any way, meta-cognitive control strategies might ameliorate the effects of distraction, or meta-cognition might itself be affected by distraction potentially escalating the disruptive effects. For now, let’s focus on the meta-cognitive monitoring judgments since these need to be reasonably accurate in order for people to have any idea that distraction is happening and that counter-measures might be necessary.

One thing we found was that people’s judgments of their own learning was fairly well-calibrated, with judgements of recall in the quiet and noise conditions mirroring the actual memory data. This is not a surprise because earlier studies, including one by Ellermeier and Zimmer (1997) also showed that , when asked to judge their confidence in their memory, people are aware of when noise is likely to detract from their learning. What is of interest, though, is where this insight comes from. No feedback was given after the memory test (i.e., in neural network terms this was not supervised learning) so it isn’t that participants were able to compare their memory performance in the various conditions to the correct answers. Ellermeier and Zimmer (1997) included in their study a measure of participants’ confidence in their abilities before they ever took the test and this measure was less well calibrated with actual performance so this successful metacognitive monitoring does seem to be dependent upon recent experience with these particular distractors and the particular memory test used, rather than being drawn from general knowledge or past experience. What then is the source of the information used to monitor memory accuracy (and hence the effects of auditory distraction on memory)? In our studies, the same participants experienced learning trials in noise and in quiet in the same sessions and the lists of items they were required to try and recall were always of the same set length and recalled by means of entering into a physical device (either writing or typing responses). Meta-cognitive monitoring, in other words, could be achieved in many of our experiments by learning the approximate length of the list to be recalled and comparing the physical record of number of items recalled with this learned number on a trial-by-trial basis. This kind of meta-cognitive monitoring is very much distributed because it relies upon the physical record of the number of items recalled on each trial to make the appropriate comparison. Is there any evidence that something like this is actually happening? An (as yet unpublished) experiment of ours provides a tantalising hint: If you ask people to write down the words they recall but give one group a standard pen to do so and another group a pen which is filled with invisible ink (so both groups are writing their recall, but only one is able to see the results) then it appears that monitoring is impaired in the latter case – suggesting (perhaps) that meta-cognition under distraction benefits from distributing some of the relevant knowledge away from the head and into the world.

References:

Baddeley, A. D. (2007). Working memory, thought and action. Oxford: Oxford University Press.

Beaman, C. P., Hanczakowski, M., & Jones, D. M. (2014). The effects of distraction on metacognition and metacognition on distraction: Evidence from recognition memory. Frontiers in Psychology, 5, 439.

D’Esposito, M. (2007) From cognitive to neural models of working memory. Philosophical Transactions of the Royal Society B: Biological Sciences, 362, 761-772.

Ellermeier, W. & Zimmer, K. (1997). Individual differences in susceptibility to the “irrelevant sound effect” Journal of the Acoustical Society of America, 102, 2191-2199.

Henson, R. N. A. (2001). Neural working memory. In: J. Andrade (Ed.) Working memory in perspective. Hove: Psychology Press.

Miller, G. A., Galanter, E. & Pribram, K. H. (1960). Plans and the structure of behavior. New York: Holt.

Smith, E. E. (2000). Neural bases of human working memory. Current Directions in Psychological Science, 9, 45-49.


Learning to Write and Writing to Learn: The Intersection of Rhetoric and Metacognition

by Amy Ratto Parks, Ph.D., University of Montana

If I had to choose the frustration most commonly expressed by students about writing it is this: the rules are always changing. They say, “every teacher wants something different” and because of that belief, many of them approach writing with feelings ranging from nervous anxiety to sheer dread. It is true that any single teacher will have his or her own specific expectations and biases, but most often, what students perceive as a “rule change” has to do with different disciplinary expectations. I argue that metacognition can help students anticipate and negotiate these shifting disciplinary expectations in writing courses.

Let’s look at an example. As we approach the end of spring semester, one single student on your campus might hold in her hand three assignments for final writing projects in three different classes: literature, psychology, and geology. All three assignments might require research, synthesis of ideas, and analysis – and all might be 6-8 pages in length. If you put yourself in the student’s place for a moment, it is easy to see how she might think, “Great! I can write the same kind of paper on three different topics.” That doesn’t sound terribly unreasonable. However, each of the teachers in these classes will actually be expecting some very different things in their papers: acceptable sources of research, citation style and formatting, use of the first person or passive voice (“I conducted research” versus “research was conducted”), and the kinds of analysis are very different in these three fields. Indeed, if we compared three papers from these disciplines we would see and hear writing that appeared to have almost nothing in common.

So what is a student to do? Or, how can we help students anticipate and navigate these differences? The fields of writing studies and metacognition have some answers for us. Although the two disciplines are not commonly brought together, a close examination of the overlap in their most basic concepts can offer teachers (and students) some very useful ways to understand the disciplinary differences between writing assignments.

Rhetorical constructs are at the intersection of the fields of writing studies and metacognition because they offer us the most clear illustration of the overlap between the way metacognitive theorists and writing researchers conceptualize potential learning situations. Both fields begin with the basic understanding that learners need to be able to respond to novel learning situations and both fields have created terminology to abstractly describe the characteristics of those situations. Metacognitive theorists describe those learning situations as “problem-solving” situations; they say that in order for a student to negotiate the situation well, she needs to understand the relationship between herself, the task, and the strategies available for the task. The three kinds of problem-solving knowledge – self, task, and strategy knowledge – form an interdependent, triangular relationship (Flavell, 1979). All three elements are present in any problem-solving situation and a change to one of the three requires an adjustment of the other two (i.e., if the task is an assignment given to whole class, then the task will remain the same; however, since each student is different, each student will need to figure out which strategies will help him or her best accomplish the task).

Metacognitive Triangle

The field of writing studies describes these novel learning situations as “rhetorical situations.” Similarly, the basic framework for the rhetorical situation is comprised of three elements – the writer, the subject, and the audience – that form an interdependent triangular relationship (Rapp, 2010). Writers then make strategic persuasive choices based upon their understanding of the rhetorical situation.
Rhetorical vs Persuasive

 In order for a writer to negotiate his rhetorical situation, he must understand his own relationship to his subject and to his audience, but he also must understand the audience’s relationship to him and to the subject. Once a student understands these relationships, or understands his rhetorical situation, he can then conscientiously choose his persuasive strategies; in the best-case scenario, a student’s writing choices and persuasive strategies are based on an accurate assessment of the rhetorical situation. In writing classrooms, a student’s understanding of the rhetorical situation of his writing assignment is one pivotal factor that allows him to make appropriate writing choices.

Theorists in metacognition and writing studies both know that students must be able to understand the elements of their particular situation before choosing strategies for negotiating the situation. Writing studies theorists call this understanding the rhetorical situation while metacognitive theorists call it task knowledge, and this is where two fields come together: the rhetorical situation of a writing assignment is a particular kind of problem-solving task.

When the basic concepts of rhetoric and metacognition are brought together it is clear that the rhetorical triangle fits inside the metacognitive triangle and creates the meta-rhetorical triangle.

Meta-Rhetorical Triangle

The meta-rhetorical triangle offers a concrete illustration of the relationship between the basic theoretical frameworks in metacognition and rhetoric. The subject is aligned with the task because the subject of the writing aligns with the guiding task and the writer is aligned with the self because the writerly identity is one facet of a larger sense of self or self-knowledge. However, audience does not align with strategy because audience is the other element a writer must understand before choosing a strategy; therefore, it is in the center of the triangle rather than the right side. In the strategy corner, however, the meta-rhetorical triangle includes the three Aristotelian strategies for persuasion, logos, ethos, and pathos (Rapp, 2010). When the conceptual frameworks for rhetoric and metacognition are viewed as nested triangles this way, it is possible to see that the rhetorical situation offers specifics about how metacognitive knowledge supports a particular kind problem-solving in the writing classroom.

So let’s come back to our student who is looking at her three assignments for 6-8 papers that require research, synthesis of ideas, and analysis. Her confusion comes from the fact that although each requires a different subject, the three tasks are appear to be the same. However, the audience for each is different, and although she, as the writer, is the same person, her relationship to each of the three subjects will be different, and she will bring different interests, abilities, and challenges to each situation. Finally, each assignment will require different strategies for success. For each assignment, she will have to figure out whether or not personal opinion is appropriate, whether or not she needs recent research, and – maybe the most difficult for students – she will have to use three entirely different styles of formatting and citation (MLA, APA, and GSA). Should she add a cover page? Page numbers? An abstract? Is it OK to use footnotes?

These are big hurdles for students to clear when writing in various disciplines. Unfortunately, most faculty are so immersed in our own fields that we come to see these writing choices as obvious and “simple.” Understanding the way metacognitive concepts relate to rhetorical situations can help students generalize their metacognitive knowledge beyond individual, specific writing situations, and potentially reduce confusion and improve their ability to ask pointed questions that will help them choose appropriate writing strategies. As teachers, the meta-rhetorical triangle can help us offer the kinds of assignment details students really need in order to succeed in our classes. It can also help us remember the kinds of challenges students face so that we can respond to their missteps not with irritation, but with compassion and patience.

References

Flavell, J.H. (1979). Metacognition and cognitive monitoring: A new era cognitive development inquiry. American Psychologist, 34, 906-911.

Rapp, C. (2010). Aristotle’s Rhetoric. In E. Zalta (Ed.), The stanford encyclopedia of

philosophy. Retrieved from http://plato.stanford.edu/archives/spr2010/entries/aristotle-rhetoric/


Distance Graduate Programs and Metacognition

by Tara Beziat at Auburn University at Montgomery 

As enrollment in online programs and online courses continues to increase (Merriman & Bierema, 2014), institutions have recognized the importance of building quality learning experiences for their students. To accomplish this goal, colleges and universities provide professional development, access to instructional designers and videos to help faculty build these courses. The focus is on how to put the content in an online setting. What I think is lacking in this process is the “in the moment” discussions about managing learning. Students often do not get to “hear” how other students are tackling the material for the course and how they are preparing for the assignments. Activities that foster metacognition are not built into the instructional design process.

In the research on learning and metacognition, there is a focus on undergraduates (possibly because they are an easily accessible population for college researchers) and p-12 students. The literature does not discuss helping graduate students hone their metacognitive strategies. Knowing the importance of metacognition and its relationship to learning, I have incorporated activities that focus on metacognition into my online graduate courses.

Though graduate students are less likely to procrastinate than undergraduate students (Cao, 2012), learning online requires the use of self-regulation strategies (Dunn & Rakes, 2015). One argument many students have for liking distance courses is that they can do the work at their own pace and at a time that works with their schedule. What they often to do not take into account is that they need to build time into their schedule for their course work. Dunn and Rakes (2015) found that online graduate students are not always prepared to be “effective learners” but can improve their self-regulation skills in an online course. Graduate students in an online course need to use effective metacognitive strategies, like planning, self- monitoring and self-evaluation.

In addition to managing their time, which may now include family and work responsibilities, their course work may present its own set of new challenges. Graduate work asks students to engage in complex cognitive processes often in an online setting.

To help graduate students with their learning process I have built in metacognitive questions in to our discussion posts. For each module of learning, students are asked to answer a metacognitive question related to the planning, monitoring or evaluation of their learning. They are also asked to answer a content question. I have found their answers to the metacognitive questions surprising, enlightening and helpful. Additionally, these discussions have provided insights into how to preparing for the class, various resources for this course on their own classrooms and managing time, juggling “life.”

Early in the semester I ask, “How are you going to actively monitor your learning in this course?” Often students respond that they will check their grades on Blackboard (our course management system), specifically they will check to see how they did on assignments. I raise a concern with these ways of monitoring. Students need to be doing some form of self-evaluation before turning in their work. If they are waiting until they get the “grade” to know how well they are doing it may be too late. Other students have a better sense of how to monitor their knowledge during a course. Below are some examples:

  • “setting my goals with each unit and reflecting back after each reading to be sure my goals and understanding are met.”
  • “I intend on reading the required text and being able to ask myself the following questions ‘how well did I understand this’ or ‘can I explain this information to a classmate if asked to do so.’”
  • “comparing my knowledge with the course objectives”
  • “checking my work to make sure the guideline set by the rubric are being followed.”

These are posted in the discussions and their fellow classmates can see the strategies that they are using to manage and monitor their learning. In their responses they will note they had not thought about doing x but they plan to try it. By embedding a metacognitive prompt in each of the 8 modules and giving students a chance share how they monitor their learning I hope to build a better understanding of the importance of metacognition in the learning process and give them ways to foster metacognition in their own classrooms.

Later on in the class I ask the students about how things are going with their studying. Yes, this is a graduate level class. But this may be the students’ first graduate level course or this may be their first online course. Or this could be their last class in a fully online program but we can always improving our learning. Below are some example of students responses to: What confusions have you gotten clarified? What changes have you made to your study habits or learning strategies?

  • “The only changes to the study habits or strategies that I have used is to try the some of the little tips or strategies that come up in the modules or discussions.”
  • “I allow myself more time to study.”
  • “I have reduced the amount of notes I take.  Now, my focus is more on summarizing text and/or writing a “gist” for each heading.”
  • “I continue to use graphic organizers to assist me with learning and understanding new information.  This is a tactic that is working well for me.”

As educators, we need to make sure we are addressing metacognition with our graduate students and that we are providing opportunities for them to practice metacognition in an online setting. Additionally, I would be interested in conducting future research that examines online graduate students awareness of metacognitive strategies, their use of these strategies in an online learning environment and ways to improve their metacognitive strategies. If you would be interested in collaborating on a project about online graduate students metacognitive skills send me an email.

 References

Cao, L. (2012). Differences in procrastination and motivation between undergraduate and graduate students. Journal of the Scholarship of Teaching and Learning, 12(2), 39-64.

Dunn, K.E. & Rakes, G.C. (2015). Exploring online graduate students’ responses to online self-regulation training. Journal of Interactive Online Learning, 13(4), 1-21.

Merriam, S.B., & Bierema, L.L. (2014). Adult learning: Linking theory and practice. San Francisco, CA: Jossey-Bass.

 


Does Processing Fluency Really Matter for Metacognition in Actual Learning Situations? (Part Two)

By Michael J. Serra, Texas Tech University

Part II: Fluency in the Classroom

In the first part of this post, I discussed laboratory-based research demonstrating that learners judge their knowledge (e.g., memory or comprehension) to be better when information seems easy to process and worse when information seems difficult to process, even when eventual test performance is not predicted by such experiences. In this part, I question whether these outcomes are worth worrying about in everyday, real-life learning situations.

Are Fluency Manipulations Realistic?

Researchers who obtain effects of perceptual fluency on learners’ metacognitive self-evaluations in the laboratory suggest that similar effects might also obtain for students in real-life learning and study situations. In such cases, students might study inappropriately or inefficiently (e.g., under-studying when they experience a sense of fluency or over-studying when they experience a sense of disfluency). But to what extent should we be worried that any naturally-occurring differences in processing fluency might affect our students in actual learning situations?

Look at the accompanying figure. This figure presents examples of several ways in which researchers have manipulated visual processing fluency to demonstrate effects on participants’ judgments of their learning. When was the last time you saw a textbook printed in a blurry font, or featuring an upside down passage, or involving a section where pink text was printed on a yellow background? fluencyWhen you present in-person lectures, do your PowerPoints feature any words typed in aLtErNaTiNg CaSe? (Or, in terms of auditory processing fluency, do you deliver half of the lesson in a low, garbled voice and half in a loud, booming voice?). You would probably – and purposefully – avoid such variations in processing fluency when presenting to or creating learning materials for your students. Yet, even in the laboratory with these exaggerated fluency manipulations, the effects of perceptual fluency on both learning and metacognitive monitoring are often small (i.e., small differences between conditions). Put differently, it takes a lot of effort and requires very specific, controlled conditions to obtain effects of fluency on learning or metacognitive monitoring in the laboratory.

Will Fluency Effects Occur in the Classroom?

Careful examination of methods and findings from laboratory-based research suggests that such effects are unlikely to occur in the real-life situations because of how fragile these effects are in the laboratory. For example, processing fluency only seems to affect learners’ metacognitive self-evaluations of their learning when they experience both fluent and disfluent information; experiencing only one level of fluency usually won’t produce such effects. For example, participants only judge information presented in a large, easy-to-read font as better learned than information presented in a small, difficult-to-read font when they experience some of the information in one format and some in the other; when they only experience one format, the formatting does not affect their learning judgments (e.g., Magreehan et al., 2015; Yue et al., 2013). The levels of fluency – and, perhaps more importantly, disfluency – must also be fairly distinguishable from each other to have an effect on learners’ judgments. For example, consider the example formatting in the accompanying figure: learners must notice a clear difference in formatting and in their experience of fluency across the formats for the formatting to affect their judgments. Learners likely must also have limited time to process the disfluent information; if they have enough time to process the disfluent information, the effects on both learning and on metacognitive judgments disappear (cf. Yue et al., 2013; but see Magreehan et al., 2015). Perhaps most important, the effects of fluency on learning judgments are easiest to obtain in the laboratory when the learning materials are low in authenticity or do not have much natural variation in intrinsic difficulty. For example, participants will base their learning judgments on perceptual fluency when all of the items they are asked to learn are of equal difficulty, such as pairs of unrelated words (e.g., “CAT – FORK”, “KETTLE – MOUNTAIN”), but they ignore perceptual fluency once there is a clear difference in difficulty, such as when related word pairs (e.g., “FLAME – FIRE”, “UMBRELLA – RAIN”) are also part of the learning materials (cf. Magreehan et al., 2015).

Consider a real-life example: perhaps you photocopied a magazine article for your students to read, and the image quality of that photocopy was not great (i.e., disfluent processing fluency). We might be concerned that the poor image quality would lead students to incorrectly judge that they have not understood the article, when in fact they had been able to comprehend it quite well (despite the image quality). Given the evidence above, however, this instance of processing fluency might not actually affect your students’ metacognitive judgments of their comprehension. Students in this situation are only being exposed to one level of fluency (i.e., just disfluent formatting), and the level of disfluency might not be that discordant from the norm (i.e., a blurry or dark photocopy might not be that abnormal). Further, students likely have ample time to overcome the disfluency while reading (i.e., assuming the assignment was to read the article as homework at their own pace), and the article likely contains a variety of information besides fluency that students can use for their learning judgments (e.g., students might use their level of background knowledge or familiarity with key terms in the article as more-predictive bases for judging their comprehension). So, despite the fact that the photocopied article might be visually disfluent – or at least might produce some experience of disfluency – it would not seem likely to affect your students’ judgments of their own comprehension.

In summary, at present it seems unlikely that the experience of perceptual processing fluency or disfluency is likely to affect students’ metacognitive self-evaluations of their learning in actual learning or study situations. Teachers and designers of educational materials might of course strive by default to present all information to students clearly and in ways that are perceptually fluent, but it seems premature – and perhaps even unnecessary – for them to worry about rare instances where information is not perceptually fluent, especially if there are counteracting factors such as students having ample time to process the material, there only being one level of fluency, or students having other information upon which to base their judgments of learning.

Going Forward

The question of whether or not laboratory findings related to perceptual fluency will transfer to authentic learning situations certainly requires further empirical scrutiny. At present, however, the claim that highly-contrived effects of perceptual fluency on learners’ metacognitive judgments will also impair the efficacy of study behaviors in more naturalistic situations seems unfounded and unlikely.

Researchers might be wise to abandon the examination of highly-contrived fluency effects in the laboratory and instead examine more realistic variations in fluency in more natural learning situations to see if such conditions actually matter for students. For example, Carpenter and colleagues (Carpenter, et al., in press; Carpenter, et al., 2013) have been examining the effects of a factor they call instructor fluency – the ease or clarity with which information is presented – on learning and judgments of learning. Importantly, this factor is not perceptual fluency, as it does not involve purported variations in perceptual processing. Rather, instructor fluency invokes the sense of clarity that learners experience while processing a lesson. In experiments on this topic, students watched a short video-recorded lesson taught by either a confident and well-organized (“fluent”) instructor or a nervous and seemingly disorganized (“disfluent”) instructor, judged their learning from the video, and then completed a test over the information. Much as in research on perceptual fluency, participants judged that they learned more from the fluent instructor than from the disfluent one, even though test performance did not differ by condition.

These findings related to instructor fluency do not validate those on perceptual fluency. Rather, I would argue that they actually add further nails to the coffin of perceptual fluency. There are bigger problems out there besides perceptual fluency we can be worrying about in order to help our students learn and help them to accurately make metacognitive judgments. Perhaps instructor fluency is one of those problems, and perhaps it isn’t. But it seems that perceptual fluency is not a problem we should be greatly concerned about in realistic learning situations.

References

Carpenter, S. K., Mickes, L., Rahman, S., & Fernandez, C. (in press). The effect of instructor fluency on students’ perceptions of instructors, confidence in learning, and actual learning. Journal of Experimental Psychology: Applied.

Carpenter, S. K., Wilford, M. M., Kornell, N., & Mullaney, K. M. (2013). Appearances can be deceiving: instructor fluency increases perceptions of learning without increasing actual learning. Psychonomic Bulletin & Review, 20, 1350-1356.

Magreehan, D. A., Serra, M. J., Schwartz, N. H., & Narciss, S. (2015, advanced online publication). Further boundary conditions for the effects of perceptual disfluency on judgments of learning. Metacognition and Learning.

Yue, C. L., Castel, A. D., & Bjork, R. A. (2013). When disfluency is—and is not—a desirable difficulty: The influence of typeface clarity on metacognitive judgments and memory. Memory & Cognition, 41, 229-241.