Tag: Students

Exploring the Developmental Progression of Metacognition

by Sarah L. Bunnell at Ohio Wesleyan University (slbunnel@owu.edu)

As a developmental psychologist, it is difficult to consider student learning (and my own learning as well) without a strong nod to developmental process. Metacognition, as has been described by many others on this blog and in other venues (e.g., Baxter-Magolda, 1992; Flavell, 1979; Kuhn, 1999; Perry, 1970), requires the cognitive skills of reflection, connection, evaluation, and revision. Metacognitive acts are initially quite cognitively demanding, and like most conscious cognitive processes, require practice to become more automatic or at least less consuming of cognitive resources. In addition to examining how students acquire the tools required for the hard work of metacognition, I have also been interested in whether there are developmental differences in students’ ability to make connections and reflections across the college years.

I recently conducted two examinations of metacognitive development; the first project involved my Introductory Psychology course, which enrolls primarily first year students, and the second project involved my Adolescent Psychology course, which enrolls primarily sophomore-level students. Below, I will provide a brief summary of each study and then discuss what I see as some take-home points and next-steps for inquiry.

In the Introductory Psychology course (n = 45), each student completed a metacognitive portfolio (hosted through the MERLOT website; http://eportfolio.merlot.org/) throughout the semester. In this portfolio, students responded to a series of prompts to reflect on their current thinking about course concepts and the ways in which these concepts play out in their own lives. At the end of the semester, students were asked to review their responses, identify any responses that they would now change, and explain why they would now alter their responses. They were also asked to describe how they thought their thinking had changed over the course of the semester.

Given the large body of work on the learning benefits associated with metacognition, I was not surprised that students who wanted to change a greater number of their responses performed significantly better on the final exam than did students who identified fewer points of change. More surprising, however, was the finding that students who did well on the final exam were significantly more likely to have endorsed changes in their thinking about themselves as opposed to changes in their thinking about others. A year after this class ended, I contacted these same students again, and I asked them to reflect on their thinking at the end of the course relative to their thinking about Psychology and themselves now. Of note, an analysis of these responses indicated that the students who were high performers on the final exam and in the course overall were no longer reporting many self-related metacognitive links. Instead, these students were significantly more likely to say that they now had a greater understanding of others than they did before. Thus, there was a powerful shift over time in the focus of metacognition from self to other.

In my Adolescent Psychology course (n = 35), students conduct a semi-structured interview of an adolescent, transcribe the interview, and then analyze the interview according to developmental theory. This assignment is designed to foster connection and application, and I have compelling evidence indicating that this experience enhances learning. What was less clear to me, however, is whether participating in this course and in the interview paper activity contributes to students’ metacognitive awareness of self? To address this question, I implemented a pre-post test design. On the first day of class, students were asked, “Are you currently an adolescent? Please explain your answer.” To answer this question, one must consider multiple ways in which we may conceptualize adolescence (i.e., age, legal responsibility, physical maturity, financial responsibility); as you can clearly see, the lens we apply to ourselves and others leads to quite varied views of when adolescence ends and adulthood begins! At the end of the term, students were again asked the same question, plus an additional prompt that asked them to reflect on how their thinking about themselves had changed across the semester.

On Day 1, 17 students endorsed currently being an adolescent, 16 students reported no longer being an adolescent, and 2 students said they did not feel that they had enough information to respond. It is important to note that all students in the course were between the ages of 18 and 21 years and as such, all were technically late adolescents. On the last day of class, 21 class members labeled themselves as adolescents, 4 students said that they did not consider themselves to be adolescents, and 5 said that they were an adolescent in some contexts of their life and not others. As an example of a contextual way of thinking, one student said: “I believe that neurologically I am still an adolescent because I am below the age of 25 and therefore do not have a fully developed frontal lobe, which can alter decision making, and from a Piagetian standpoint I believe I am out of adolescence because I have reached the formal operational stage of development and possibly even beyond that. Overall though, I believe that I can’t fully define myself as an adolescent or not because there are so many factors in play.”

I examined these group-level differences in terms of course performance from a number of angles, and two interesting patterns emerged. First, students who adopted a more context-dependent view of self did significantly better on the application-based, cumulative final exam than did students who held an absolute view of self. This first finding is consistent with the work on Marcia Baxter-Magolda (1992), William Perry (1970), and others, which views contextual knowing as a complicated and mature form of meta-knowing. Second, students who changed their view of themselves across the semester conducted significantly more advanced analyses of the interview content relative to those whose view of self did not change. Thus, the students who displayed greater advances in metacognition were better able to apply these reflections and connections to themselves and, in turn, to the lives of others.

Taken together, this work suggests to me that the ability to engage in metacognitive reflection and connection may initially develop in a self-focused way and then, following additional experience and metacognitive skill attainment, extend beyond the self. Please note that I am careful to suggest that the ability of other-related connection emerges following experience and the acquisition of lower-level preparatory skills, rather than merely the passage of time, even though there is clearly a temporal dimension at play. Instead, as Donald Baer warned us, age is at best a proxy for development; at the most extreme, development is “age-irrelevant” (Baer, 1970). Why do students demonstrate improved metacognition across the college years? It is certainly not merely because the days have ticked by. Instead, these advances in thinking, as well as students’ willingness to refine their thinking about the self, are supported and constructed by a range of experiences and challenges that their college experience affords. To understand age- or college-level changes in thinking, therefore, we should focus on the developmental tasks and experiences that support this development. I hope that my lines of inquiry contribute in small part to this process.

References

Baer, D. M. (1970). An age-irrelevant concept of development. Merrill-Palmer Quarterly, 16, 238-245.

Baxter Magolda, M. B. (1992). Students’ epistemologies and academic experiences: implications for pedagogy, Review of Higher Education, 15, 265-87.

Flavell, J. H. (1979). Metacognition and cognitive monitoring: A new area of cognitive-developmental inquiry. American Psychologist, 34, 906 – 911.

Kuhn, D. (1999). A developmental model of critical thinking. Educational Researcher, 28, 16-25.

Perry, William G., Jr. (1970). Forms of intellectual and ethical development in the college years: A scheme. New York: Holt, Rinehart, & Winston.


Linking Mindset to Metacognition

By Charity Peak, Ph.D. (U. S. Air Force Academy)

As part of our institution’s faculty development program, we are currently reading Carol Dweck’s Mindset: The New Psychology of Success. Even though the title and cover allude to a pop-psychology book, Dweck’s done a fabulous job of pulling together decades of her scholarly research on mindsets into a layperson’s text.

After announcing the book as our faculty read for the semester, one instructor lamented that she wished we had selected a book on the topic of metacognition. We have been exploring metacognition as a theme this year through our SoTL Circles and our participation in the multi-institutional Metacognitive Instruction Project. My gut reaction was, “But Mindset is about metacognition!” Knowing your own mindset requires significant metacognition about your own thinking and attitudes about learning. And better yet, understanding and recognizing mindsets in your students helps you to identify and support their development of mindsets that will help them to be successful in school and life.

If you haven’t read the book, below are some very basic distinctions between the fixed and growth mindsets that Dweck (2006) discovered in her research and outlines eloquently in her book:

Fixed Mindset Growth Mindset
Intelligence is static. Intelligence can be developed.
Leads to a desire to look smart and therefore a tendency to:

  • avoid challenges
  • give up easily due to obstacles
  • see effort as fruitless
  • ignore useful feedback
  • be threatened by others’ success
 Leads to a desire to learn and therefore a tendency to:

  • embrace challenges
  • persist despite obstacles
  • see effort as a path to mastery
  • learn from criticism
  • be inspired by others’ success

 

What does this mean for metacognition? Dweck points out that people go through life with fixed mindsets without even realizing they are limiting their own potential. For example, students will claim they are “not good at art,” “can’t do math,” “don’t have a science brain.” These mindsets restrict their ability to see themselves as successful in these areas. In fact, even when instructors attempt to refute these statements, the mindsets are so ingrained that they are extremely difficult to overcome.

What’s an instructor to do? Help students have metacognition about their self-limiting beliefs! Dweck offers a very simple online assessment on her website that takes about 5 minutes to complete. Instructors can very easily suggest that students take the assessment, particularly in subjects where these types of fallacious self-limiting attitudes abound, as a pre-emptive way to begin a course. These assessment results would help instructors easily identify who might need the most assistance in overcoming mental barriers throughout the course. Instructors can also make a strong statement to the class early in the semester that students should fight the urge to succumb to these limiting beliefs about a particular subject area (such as art or math).   As Dweck has proven through her research, people can actually become artistic if taught the skills through learnable components (pp. 68-69). Previously conceived notions of talent related to a wide variety of areas have been refuted time and again through research. Instead, talent is likely a cover for hard work, perseverance, and overcoming obstacles. But if we don’t share those insights with students, they will never have the metacognition of their own self-limiting – and frankly mythical – belief systems.

Inspired but wish you knew how to apply it to your own classes? A mere Google search on metacognition and mindset will yield a wealth of resources, but I particularly appreciate Frank Noschese’s blog on creating a metacognition curriculum. He started his physics course by having students take a very simple survey regarding their attitudes toward science. He then shared a short video segment called “Grow Your Brain” from the episode Changing Your Mind (jump to 13:20) in the Scientific American Frontiers series from PBS. Together, he and his students began a journey of moving toward a growth mindset in science. Through an intentional metacognition lesson, he sent a very clear message to his students that “I can’t” would not be tolerated in his course. He set them up for success by demonstrating clearly that everyone can learn physics if they put their minds (or mindsets) to it.

Metacognition about mindsets offers instructors an opportunity to give students the gift of a lifetime – the belief that they can overcome any learning obstacles if they just persevere, that their intelligence is not fixed but actually malleable, that learning is sometimes hard but not impossible! When I reflect on why I am so deeply dedicated to education as a profession, it is my commitment to helping students see themselves using a growth mindset. Helping them to change their mindsets can change their future, and metacognition is the first step on that journey!

 

References:

“Changing the Mind.” (11/21/00). Scientific American Frontiers. Boston: Ched-Angier Production Co. Retrieved from http://chedd-angier.com/frontiers/season11.html

Dweck, C. S. (2006). Mindset: The new psychology of success. New York: Ballantine Books.

Noschese, F. (September 10, 2012). Metacognition curriculum (Lesson 1 of ?). Retrieved from https://fnoschese.wordpress.com/2012/09/10/metacognition-curriculum-lesson-1-of/

 


Fostering Metacognition: Right-Answer Focused versus Epistemologically Transgressive

by Craig E. Nelson at Indiana University (Contact: nelson1@indiana.edu)

I want to enrich some of the ideas posted here by Ed Nuhfer (2014 a, b, c and d) and Lauren Scharff (2014). I will start by emphasizing some key points made by Nuhfer (2014 a):

  • Instead of focusing on more powerful ways of thinking, most college instruction has thus far focused on information, concepts and discipline specific skills. I will add that even when concepts and skills are addressed they, too, are often treated as memorizable information both by students and faculty. Often little emphasis is placed on demonstrating real understanding, let alone on application and other higher-level skills.
  • “Adding metacognitive components to our assignments and lessons can provide the explicit guidance that students need. However, authoring these components will take many of us into new territory…” This is tough because such assignments require much more support for students and many of faculty members have had little or no practice in designing such support.
  • The basic framework for understanding higher-level metacognition was developed by Perry in the late 1960s and his core ideas have since been deeply validated, as well as expanded and enriched, by many other workers (e.g. Journal of Adult Development, 2004; Hoare, 2011.).
  • “Enhanced capacity to think develops over spans of several years. Small but important changes produced at the scale of single quarter or semester-long courses are normally imperceptible to students and instructors alike.”

It is helpful (e.g. Nelson, 2012, among many) to see most of college-level thinking as spanning four major levels, a truncated condensation of Perry’s 9 stages as summarized in Table 1 of Nuhfer (2014 a). Each level encompasses a different set of metacognitive skills and challenges. Individual students’ thinking is often a mix or mosaic where they approach some topics on one level and others at the next.

In this post I am going to treat only the first major level, Just tell me what I need to know (Stages 1 & 2 of Table 1 in Nuhfer, 2012 a). In this first level, students view knowledge fundamentally as Truth. Such knowledge is eternal (not just some current best model), discovered (not constructed) and objective (not temporally or socially situated). In contrast, some (but certainly not all) faculty members view what they are teaching as constructed best current model or models and as temporally and socially situated with the subjectivity that implies.

The major cognitive challenges within this first level are usefully seen as moving toward a more complete mastery of right-answer reasoning processes (Nelson, 2012), sometimes referred to as a move from concrete to formal reasoning (although the extent to which Piaget’s stages actually apply is debated). A substantial majority of entering students at most post-secondary institutions have not yet mastered formal reasoning. However, many (probably most) faculty members tacit assume that all reasonable students will quickly understand anything that is asked in terms of most right-answer reasoning. As a consequence, student achievement is often seriously compromised.

Lawson et al. (2007) showed that a simple test of formal reasoning explained about 32% of the variance in final grades in an introductory biology course and was the strongest such predictor among several options. This is quite remarkable considering that the reasoning test had no biological content and provided no measure of student effort. Although some reasoning tasks could be done by most students, an understanding of experimental designs was demonstrated largely by students who scored as having mastered formal reasoning. Similar differences in achievement have been documented for some other courses (Nelson, 2012).

Nuhfer (2014 b) and Scharff (2014) discuss studies of the associations among various measures of student thinking. From my viewpoint, their lists start too high up the thinking scale. I think that we need to start with the transitions between concrete and formal reasoning. I have provided a partial review of key aspects of this progression and of the teaching moves that have been shown to help students master more formal reasoning, as well as sources for key instruments (Nelson, 2012). I think that such mastery will turn out to be especially helpful, and perhaps essential, to more rapid development of higher level-reasoning skills.

This insight also may helps to resolve a contrast, between the experience of Scharff and her colleagues (Scharff, 2014) and Nuhfer’s perspective (2014 b). Scharff reports: “At my institution we have some evidence that such an approach does make a very measurable difference in aspects of critical thinking as measured by the CAT (Critical Thinking Assessment, a nationally normed, standardized test …).” In his responses, Nuhfer (2014 b) emphasizes that, given how we teach, there is, not surprisingly, very little change over the course an undergraduate degree in higher-order thinking. (“… the typical high school graduate is at about [Perry] level 3 2/3 and the typical college graduate is a level 4. That is only one-third of a Perry stage gain made across 4-5 years of college.”)

It is my impression that the “Critical Thinking Assessment” discussed by Scharff deals primarily with right-answer reasoning. The mastery of the skills underlying right-answer reasoning questions is largely a matter of mastering formal reasoning processes. Indeed, tests of concrete versus formal reasoning usually consist exclusively of questions that have very clear right answers. I think that several of the other thinking assessments that Nuhfer and Scharff discuss also have exclusively or primarily clear right-answers. This approach contrasts markedly with the various instruments for assessing intellectual development in the sense of Perry and related authors, none of which focuses on right-answer questions. An easily accessible instrument is given the appendices of King and Kitchener (1994).

This leads to three potentially helpful suggestions for fostering metacognition.

  • Use one of the instruments for assessing concrete versus formal reasoning as a background test for all of your metacognitive interventions. This will allow you to ask whether students who perform differently on such an assessment also perform differently on your pre- or post-assessment, or even in the course as a whole (as in Lawson et al. 2007).
  • Include interventions in your courses that are designed to help students succeed with formal, right-answer reasoning tasks. In STEM courses, teaching with a “learning cycle” approach that starts with the examination or even the generation of data is one important, generally applicable such approach.
  • Carefully distinguish between the ways that you are helping students master right-answer reasoning and the ways you are trying to foster more complex forms of reasoning. Fostering right-answer reasoning will include problem-focused reasoning, self-monitoring and generalizing right-answer reasoning processes (e.g. “Would using a matrix help me solve this problem?”).

Helping students move to deeper sophistication requires epistemologically transgressive challenges. Those who wish to pursue such approaches seriously should examine first, perhaps, Nuhfer’s (2014d) “Module 12 – Events a Learner Can Expect to Experience” and ask how one could foster each successive step.

Unfortunately, the first key step to helping students move beyond right-answer thinking requires helping them understand the ways in which back-and-white reasoning fails in one’s discipline. For this first epistemologically transgressive challenge, understanding that knowledge is irredeemably uncertain, one might want to provide enough scaffolding to allow students to make sense of readings such as: Mathematics: The Loss of Certainty (Kline, 1980); Be Forewarned: Your Knowledge is Decaying (Arbesman, 2012); Why Most Published Research Findings Are False (Ioannidis, 2005); and Lies, Damned Lies, and Medical Science (Freedman, 2010).

As an overview for students of the journey in which everything becomes a matter of better and worse ideas and divergent standards for judging better, I have had some success using a heavily scaffolded approach (detailed study guides, including exam ready essay questions, and much group work) to helping students understand Reality Isn’t What It Used to Be: Theatrical Politics, Ready-to-Wear Religion, Global Myths, Primitive Chic, and Other Wonders of the Postmodern World (Anderson,1990).

We have used various heavily scaffolded, epistemologically transgressive challenges to produce an average gain of one-third Perry stage over the course of a single semester (Ingram and Nelson, 2009). As Nuhfer (2014b) noted, this is about the gain usually produced by an entire undergraduate degree of normal instruction.

And for the bravest, most heavily motivated faculty, I would suggest In Over Our Heads: The Mental Demands of Modern Life (Kegan, 1994). Kegan attempts to make clear that each of us has our ability to think in more complex ways limited by epistemological assumptions of which we are unaware. This is definitely not a book for undergraduates nor is it one that easily embraced by most faculty members.

REFERENCES CITED

  • Hoare, Carol. Editor (2011). The Oxford Handbook of Reciprocal Adult Development and Learning. 2nd Edition. Oxford University Press.
  • Ingram, Ella L. and Craig E. Nelson (2009). Applications of Intellectual Development Theory to Science and Engineering Education. P 1-30 in Gerald F. Ollington (Ed.), Teachers and Teaching: Strategies, Innovations and Problem Solving. Nova Science Publishers.
  • Ioannidis, John (2005). “Why Most Published Research Findings Are False.” PLoS Medicine August; 2(8): e124. http://www.ncbi.nlm.nih.gov/pmc/articles/PMC1182327/ [The most downloaded article in the history of PLoS Medicine. Too technical for many first-year students even with heavy scaffolding?]
  • Journal of Adult Development (2004). [Special volume of nine papers on the Perry legacy of cognitive development.] Journal of Adult Development 11(2):59-161.
  • King, Patricia M. and Karen Strohm Kitchner (1994). Developing Reflexive Judgment: Understanding and Promoting Intellectual Growth and Critical Thinking in Adolescents and Adults. Jossey-Bass.
  • Kline, Morris (1980). Mathematics: The Loss of Certainty. Oxford University Press. [I used the summary (the Preface) in a variety of courses.]
  • Nelson, Craig E. (2012). “Why Don’t Undergraduates Really ‘Get’ Evolution? What Can Faculty Do?” Chapter 14 (p 311-347) in Karl S. Rosengren, E. Margaret Evans, Sarah K. Brem, and Gale M. Sinatra (Editors.) Evolution Challenges: Integrating Research and Practice in Teaching and Learning about Evolution. Oxford University Press. [Literature review applies broadly, not just to evolution]

Unskilled and Unaware of It: How Difficulties in Recognizing One’s Own Incompetence Lead to Inflated Self-Assessments

This sometimes humorous article by Justin Kruger and David Dunning describes a series of four experiments that “that incompetent individuals have more difficulty recognizing their true level of ability than do more competent individuals and that a lack of metacognitive skills may underlie this deficiency.”  It also includes a nice review of the literature and several examples to support their study.

Unskilled and Unaware of It: How Difficulties in Recognizing One’s Own Incompetence Lead to Inflated Self-Assessments, Journal of Personality and Social Psychology 1999, Vol. 77, No. 6. 121-1134


Self-Assessment, It’s A Good Thing To Do

by Stephen Fleisher, CSU Channel Islands

McMillan and Hearn (2008) stated persuasively that:

In the current era of standards-based education, student self-assessment stands alone in its promise of improved student motivation and engagement, and learning. Correctly implemented, student self-assessment can promote intrinsic motivation, internally controlled effort, a mastery goal orientation, and more meaningful learning (p. 40).

In her study of three meta-analyses of medical students’ self-assessment, Blanch-Hartigan (2011) reported that self-assessments did prove to be fairly accurate, as well as improving in later years of study. She noted that if we want to increase our understanding of self-assessment and facilitate its improvement, we need to attend to a few matters. To understand the causes of over- and underestimation, we need to address direction in our analyses (using paired comparisons) along with our correlational studies. We need also to examine key moderators affecting self-assessment accuracy, for instance “how students are being inaccurate and who is inaccurate” (p. 8). Further, the wording and alignment of our self-assessment questions in relation to the criteria and nature of our performance questions are essential to the accuracy of understanding these relationships.

When we establish strong and clear relationships between our self-assessment and performance questions for our students, we facilitate their use of metacognitive monitoring (self-assessment, and attunement to progress and achievement), metacognitive knowledge (understanding how their learning works and how to improve it), and metacognitive control (changing efforts, strategies or actions when required). As instructors, we can then also provide guidance when performance problems occur, reflecting on students’ applications and abilities with their metacognitive monitoring, knowledge, and control.

Self-Assessment and Self-Regulated Learning

For Pintrich (2000), self-regulating learners set goals, and activate prior cognitive and metacognitive knowledge. These goals then serve to establish criteria against which students can self-assess, self-monitor, and self-adjust their learning and learning efforts. In monitoring their learning process, skillful learners make judgments about how well they are learning the material, and eventually they become better able to predict future performance. These students can attune to discrepancies between their goals and their progress, and can make adjustments in learning strategies for memory, problem solving, and reasoning. Additionally, skillful learners tend to attribute low performance to low effort or ineffective use of learning strategies, whereas less skillful learners tend to attribute low performance to an over-generalized lack of ability or to extrinsic things like teacher ability or unfair exams. The importance of the more adaptive attributions of the aforementioned skillful learners is that these points of view are associated with deeper learning rather than surface learning, positive affective experiences, improved self-efficacy, and greater persistence.

Regarding motivational and affective experiences, self-regulating learners adjust their motivational beliefs in relation to their values and interests. Engagement improves when students are interested in and value the course material. Importantly, student motivational beliefs are set in motion early in the learning process, and it is here that instructional skills are most valuable. Regarding self-regulation of behavior, skillful learners see themselves as in charge of their time, tasks, and attention. They know their choices, they self-initiate their actions and efforts, and they know how and when to delay gratification. As well, these learners are inclined to choose challenging tasks rather than avoid them, and they know how to persist (Pintrich, 2000).

McMillan and Hearn (2008) summarize the role and importance of self-assessment:

When students set goals that aid their improved understanding, and then identify criteria, self-evaluate their progress toward learning, reflect on their learning, and generate strategies for more learning, they will show improved performance with meaningful motivation. Surely, those steps will accomplish two important goals—improved student self-efficacy and confidence to learn—as well as high scores on accountability tests (p. 48). 

As a teacher, I see one of my objectives being to discover ways to encourage the development of these intellectual tools and methods of thinking in my own students. For example, in one of my most successful courses, a colleague and I worked at great length to create a full set of specific course learning outcomes (several per chapter, plus competencies we cared about personally, for instance, life-long learning). These course outcomes were all established and set into alignment with the published student learning outcomes for the course. Lastly, homework, lectures, class activities, individual and group assignments, plus formative and summative assessments were created and aligned. By the end of this course, students not only have gained knowledge about psychology, but tend to be pleasantly surprised to have learned about their own learning.

 

References

Blanch-Hartigan, D. (2011). Medical students’ self-assessment of performance: Results from three meta-analyses. Patient Education and Counseling, 84, 3-9.

McMillan, J. H., & Hearn, J. (2008). Student self-assessment: The key to stronger student motivation and higher achievement. Educational Horizons, 87(1), 40-49. http://files.eric.ed.gov/fulltext/EJ815370.pdf

Pintrich, P. R. (2000). The role of goal orientation in self-regulated learning. In M. Boekaerts, P. R. Pintrich, & M. Zeidner (Eds.) Handbook of self-regulation. San Diego, CA: Academic.


Evidence for metacognition as executive functioning

by Kristen Chorba, PhD and Christopher Was, PhD, Kent State University

Several authors have noted that metacognition and executive functioning are descriptive of a similar phenomenon (see Fernandez-Duque, et al., 2000; Flavell, 1987; Livingston, 2003; Shimamura, 2000; Souchay & Insingrini, 2004). Many similarities can be seen between these two constructs: both regulate and evaluate cognitions, both are employed in problem solving, both are required for voluntary actions (as opposed to automatic responses), and more. Fernandez-Duque, et al. (2000) suggest that, despite their similarities, these two areas have not been explored together because of a divide between metacognitive researchers and cognitive neuroscientists; the metacognitive researchers have looked exclusively at metacognition, focusing on issues related to its development in children and its implications for education. They have preferred to conduct experiments in naturalistic settings, as a way to maximize the possibility that any information gained could have practical applications. Cognitive neuroscientists, on the other hand, have explored executive functioning using neuroimaging techniques, with the goal of linking them to brain structures. In the metacognitive literature, it has been noted metacognition occurs in the frontal cortex; this hypothesis has been evaluated in patients with memory disorders, and studies have noted that patients with frontal lobe damage, including some patients with amnesia, had difficulties performing metacognitive functions, including FOK judgments (Fernandez-Duque, et al., 2000; Janowsky, Shimamura, & Squire, 1989; Shimamura & Squire, 1986; as cited in Shimamura, 2000). Additionally, source monitoring and information retrieval has also been linked with the frontal cortex; source monitoring is an important metacognitive judgment (Shimamura, 2000). As previously stated, executive functions seem to be located generally in the frontal lobes, as well as specifically in other areas of the brain, contributing to the growing body of literature indicating that executive functions are both correlated and function independently. To explore the link between executive functioning and metacognition, Souchay and Isingrini (2004) carried out an experiment in which subjects were first asked to make evaluations on their own metacognition; they were then given a series of neurological tests to assess their executive functioning. They not only found a “significant partial correlation between metamemory control and executive functioning” (p. 89) but, after performing a hierarchical regression analysis, found that “age-related decline in metamemory control may be largely the result of executive limitations associated with aging” (p. 89).

As it relates to executive functioning, Fernandez-Duque, et al. (2008) noted that “the executive system modulates lower level schemas according to the subject’s intentions . . . [and that] without executive control, information processing loses flexibility and becomes increasingly bound to the external stimulus” (p. 289). These authors use the terms executive function and metacognition as essentially interchangeable, and note that these functions enable humans to “guide actions” where preestablished schema are not present and allow the individual to make decisions, select appropriate strategies, and successfully complete a task. Additionally, the primary task of both metacognition and executive functions are top-down strategies, which inform the lower level (i.e.: in metacognition, the object level; in executive functioning, as the construct which controls the “selection, activation, and manipulation of information in working memory” [Shimamura, 2000, p. 315]). Reviewing the similarities between metacognition and executive function, it seems that they are highly correlated constructs and perhaps share certain functions.

Executive functions and metacognition, while exhibiting similar functions and characteristics have, largely, been investigated along separate lines of research. Metacognitive research has focused on application and informing the teaching and learning processes. Executive functions, on the other hand, have primarily been researched as they relate to structures and locations within the brain. Recent literature and research indicates that executive functions and metacognition may be largely the same process.

References

Baddeley, A. (2005). Human Memory: Theory and Practice, Revised Edition. United Kingdom; Bath Press.

Blavier, A., Rouy, E., Nyssen, A., & DeKeyster, V. (2005). Prospective issues for error   detection. Ergonomics, 7(10), 758-781.

Dinsmore, D., Alexander, P., & Loughlin, S. (2008). Focusing the conceptual lens on metacognition, self-regulation, and self-regulated learning. Educational psychology review, 20(4), 391-409.

Dunlosky, J., Metcalfe, J. (2008). Metacognition. Los Angeles: Sage.

Fernandez-Duque, D., Baird, J., Posner, M. (2000). Executive attention and metacognitive regulation. Consciousness and Cognition, 9, 288-307.

Flavell, J. (1987). Speculations about the nature and development of metacognition. In F. Weinert and R. H. Kluwe, (Eds.) Metacognition, Motivation, and Understanding. Hillsdale, NJ: Lawrence Erlbaum.

Friedman, N. P., Haberstick, B. C., Willcutt, E. G., Miyake, A., Young, S. E., Corley, R.   P., & Hweitt, J. K. (2007). Greater attention problems during childhood predict        poorer executive functioning in late adolescence. Psychological Science, 18(10), 893-900.

Friedman, N. P., Miyake, A., Young, S. E., DeFries, J. C., Corley, R. P., Hewitt, J. K. (2008).  Individual differences in executive functions are almost entirely genetic in origin.  Journal of Experimental Psychology, General, 137(2), 201-225.

Friedman, N. P., Miyake, Corley, R. P., Young, S. E., DeFries, J. C., & Hewitt, J. K. (2006). Not all executive functions are related to intelligence. Psychological Science, 17(2), 172-179.

Georghiades, P. (2004). From the general to the situated: Three decades of metacognition.  research report. International Journal of Science Education, 26(3), 365-383.

Higham, P. A. & Gerrard, C. (2005). Not all errors are created equal: Metacognition and   changing answers on multiple-choice tests. Canadian Journal of Experimental   Psychology, 59(1), 28-34.

Keith, N. & Frese, M. (2005) Self-regulation in error management training: Emotion control and    metacognition as mediators of performance effects. Journal of Applied Psychology,  90(4), 677-691.

Keith, N. & Frese, M. (2008). Effects of error management training: A meta-analysis. Journal of Applied Psychology, 93(1), 59-69.

Lajoie, S. (2008). Metacognition, self regulation, and self-regulated learning: A rose by any other name? Educational Psychology Review, 20(4), 469-475.

Livingston, J. A. (2003). Metacognition: An overview. Online ERIC Submission.

Miyake, A., Friedman, N. P., Emerson, M. J., Witzki, A. H., & Howenter, A. (2000). The unity and diversity of executive functions and their contributions to complex         “frontal lobe” tasks: A latent variable analysis. Cognitive Psychology, 41, 49-100.

Nelson, T. O., & Narens, L. (1990). Metamemory: A theoretical framework and new

findings. In G. H. Bower (Ed.), The Psychology of Learning and Knowing. Cambridge, MIT Press, p. 1-26.

PP, N. (2008). Cognitions about cognitions: The theory of metacognition. Online ERIC Submission.

Shimamura, A. (2000). Toward a cognitive neuroscience of metacognition. Consciousness and Cognition, 9, 313-323.

Souchay, C., & Isingrini, M. (2004). Age related differences in metacognitive control: Role of executive functioning. Science Direct. 56(1), 89-99.

Thiede, K. W., & Dunlosky, J. (1994). Delaying students’ metacognitive monitoring improves their accuracy in predicting their recognition performance. Journal of educational psychology, 86(2), 290-302.

Winne, P. H., & Hadwin, A. F. (1998). Studying as self-regulated learning. In D. J. Hacker, J., Dunlosky, & A. Graessser (Eds.), Metacognition in educational theory       and practice, (p. 277-304). Hillsdale, NJ: Lawrence Erlbaum.


Self-assessment and the Affective Quality of Metacognition: Part 1 of 2

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

In The Feeling of What Happens: Body and Emotion in the Making of Consciousness(1999, New York, Harcourt), Antonio Damasio distinguished two manifestations of the affective domain: emotions (the external experience of others’ affect) and feelings(the internal private experience of one’s own affect). Enacting self-assessment constitutes an internal, private, and introspective metacognitive practice.

Benjamin Bloom recognized the importance of the affective domain’s involvement in successful cognitive learning, but for a time psychologists dismissed the importance of both affect and metacognition on learning (See Damasio, 1999; Dunlosky and Metcalfe, 2009, Metacognition, Los Angeles, Sage). To avoid repeating these mistakes, we should recognize that attempts to develop students’ metacognitive proficiency without recognizing metacognition’s affective qualities are likely to be minimally effective.

In academic self-assessment, an individual must look at a cognitive challenge and accurately decide her/his capability to meet that challenge with present knowledge and resources. Such decisions do not spring only from thinking cognitively about one’s own mental processes. Affirming that “I can” or “I cannot” meet “X” (the cognitive challenge) with current knowledge and resources draws from affective feelings contributed by conscious and unconscious awareness of what is likely to be an accurate decision.

“Blind insight” (http://pss.sagepub.com/content/early/2014/11/11/0956797614553944) is a new term in the literature of metacognition. It confirms an unconscious awareness that manifests as a feeling that supports sensing the correctness of a decision. “Blind insight” and “metacognitive self-assessment” seem to overlap with one another and with Damasio’s “feelings.”

Research in medical schools confirmed that students’ self-assessment skills remained consistent throughout medical education (http://files.eric.ed.gov/fulltext/ED410296.pdf.)  Two hypotheses compete to explain this confirmation.  One is that self-assessment skills establish early in life and cannot be improved in college. The other is that self-assessment skill remains fixed in post-secondary education only because it is so rarely taught or developed. The first hypothesis seems contradicted by the evidence supporting brain plasticity, constructivist theories of learning and motivation, metacognition theory, self-efficacy theory (http://files.eric.ed.gov/fulltext/EJ815370.pdf), and by experiments that confirm self-assessment as a learnable skill that improves with training (http://psych.colorado.edu/~vanboven/teaching/p7536_heurbias/p7536_readings/kruger_dunning.pdf).

Nursing is perhaps the discipline that has most recognized the value of developing intuitive feelings informed by knowledge and experience as part of educating for professional practice.

“At the expert level, the performer no longer relies on an analytical principle (rule, guideline, maxim) to connect her/his understanding of the situation to an appropriate action. The expert nurse, with her/his enormous background of experience, has an intuitive grasp of the situation and zeros in on the accurate region of the problem without wasteful consideration of a large range of unfruitful possible problem situations. It is very frustrating to try to capture verbal descriptions of expert performance because the expert operates from a deep understanding of the situation, much like the chess master who, when asked why he made a particularly masterful move, will just say, “Because it felt right. It looked good.” (Patricia Benner, 1982, “From novice to expert.” American Journal of Nursing, v82 n3 pp 402-407)

Teaching metacognitive self-assessment should include an aim toward improving students’ ability to clearly recognize the quality of “feels right” regarding whether one’s own ability to meet a challenge with present abilities and resources exists. Developing such capacity requires practice in committing errors and learning from them through metacognitive reflection. In such practice, the value of Knowledge Surveys (see http://profcamp.tripod.com/KS.pdf and http://profcamp.tripod.com/Knipp_Knowledge_Survey.pdf) becomes apparent.

Knowledge Surveys (Access tutorials for constructing knowledge surveys and obtaining downloadable examples at http://elixr.merlot.org/assessment-evaluation/knowledge-surveys/knowledge-surveys2.) consist of about a hundred to two hundred questions/items relevant to course learning objectives. These query individuals to self-assess by rating their present ability to meet a challenge on a three-point multiple-choice scale:

A. I can fully address this item now for graded test purposes.
B. I have partial knowledge that permits me to address at least 50% of this item.
C. I am not yet able to address this item adequately for graded test purposes.

and thereafter to monitor their mastery as the course unfolds.

In Part 2, we will examine why knowledge surveys are such powerful instruments for supporting students’ learning and metacognitive development, ways to properly employ knowledge surveys to induce measurable gains, and we will provide some surprising results obtained from pairing knowledge surveys in conjunction with a standardized assessment measure.


The Teaching Learning Group at CSUN

Two years ago, eight faculty at California State University, Northridge, began studying how people learn as a grassroots effort to increase student success by focusing on what instructors do in the classroom. Our website shares our efforts, Five Gears for Activating Learning, as well as supporting resources and projects developed to date (e.g., documents, videos, and a yearlong Faculty Learning Community in progress). Although all five gears interact when people learn and develop expertise, our fifth gear, the Developing Mastery gear, focuses on assisting students in developing their metacognitive skills.

http://www.csun.edu/cielo/teaching-learning-group.html


The Six Hour D… And How to Avoid It

This great essay by Russ Dewey (1997) evolved from a handout he used to give his students. He shares some common examples of poor study strategies and explains why they are unlikely to lead to deep learning (even if they are used for 6 hours…). He then shares a simple metacognitive self-testing strategy that could be tailored for courses across the disciplines.

http://www.psywww.com/discuss/chap00/6hourd.htm


Using metacognitive awareness to facilitate healthy engagement with moral issues

By John Draeger, SUNY Buffalo State

As the new semester begins, I am again looking out on a classroom full of students eager to discuss “hot button” moral issues (e.g., abortion, euthanasia, hate-speech, same-sex marriage, drug legalization). In an earlier post entitled, “Using metacognition to uncover the substructure of moral issues,” I argued that metacognitive awareness can help students move beyond media pundit drivel and towards a more careful consideration of moral issues. In “Cultivating the habit of constructive discomfort”, I argued that learning requires cultivating a certain healthy discomfort (much like the discomfort often associated with vigorous exercise) and it is metacognitive awareness that keeps us within our own “zone of proximal development” (Vygotsky 1978). This post considers some of the sources of discomfort that threaten to undermine the discussion of moral issues.

Confronting “hot button” moral issues can be difficult because each of us brings our own complicated history to the conversation (replete with hang ups and blind spots). Based on my many years of teaching moral philosophy, I offer the following list of items that I found seem to derail discussion. The list is by no means exhaustive and whether these are the elements most likely to impede engagement is ultimately an empirical question that the needs to be answered. However, I argue that all of us (instructors, students, those outside the classroom) need to be aware of our own sources of discomfort with moral matters if we hope to move beyond them and towards a healthy engagement with these important issues.

Sources of discomfort: 

(1) Entrenched beliefs— some moral issues are difficult to consider because they force us to confront our foundational values.  For example, those from a wide variety of religious traditions can find it difficult to be completely open-minded to the possibility that abortion and same-sex marriage could be permissible. While they can summarize a particular position on the issue (e.g., for a particular course assignment), many find it difficult to move beyond a “bookish” articulation of the problem towards a genuine consideration of the issues because it threatens to undermine other firmly held beliefs (e.g., religious teachings).

(2) Peer pressure — many students find it difficult to swim against the current of peer opinion. When discussing sex, for example, students want to avoid being seen as either too prudish or too perverted. Sometimes students have views that fall outside the range of perceived acceptability but they refuse to voice them for fear of social disapproval. Other times, it doesn’t even occur them to consider anything outside the norm. In both cases, peer pressure can undermine full consideration of the issues.

(3) Self-interest — shifts in moral position require changes in our behavior. For example, “buying into” arguments for animal rights might demand that we change our eating habits. Often, it is easy to discount these arguments, not because they lack merit, but because we do not want to make the lifestyle changes that might be required if we became convinced by the argument.

(4) “Afraid of looking in the mirror” — discussions of moral issues can reveal uncomfortable truths about ourselves. Discussions of racial and gender discrimination, for example, can make us uncomfortable when we realize that we (or those we love) have attitudes and behaviors are insensitive and even hurtful.

(5) Ripple effects — because moral issues are interrelated, modifying our view on one issue can send ripple effects through our entire conceptual system.  For example, a discussion of euthanasia might lead us to the conclusion the quality life is important and even that some lives are no longer worth living (e.g., extreme pain without the prospect of relief). If true, then we might come to believe that it be better if some people were never born (e.g., extreme pain without the prospect of relief). Thus, thinking carefully about euthanasia might change our view of abortion. Likewise, becoming convinced by arguments for individual freedom in one area (e.g., free speech) can lead us to rethink our views in other areas (e.g., drug legalization, abortion, hate speech). However, if a student senses that a ripple might turn into a tidal wave, they often disengage.

In each case, becoming aware of the sources for our discomfort can help us move beyond a superficial consideration of the issues. In particular, asking a series of metacognitive questions can help uncover whether the discomfort is healthy (e.g., struggle with unfamiliar or difficult material) or unhealthy (e.g., blocked by entrenched beliefs, peer pressure, self-interest, or an inability to look in the mirror).

Questions we might ask our students (or even ourselves):

  • To what extent is my thinking on particular issue being influenced by my firmly held beliefs, the views of my peers, self-interest, a reluctance to take an honest look in the mirror, or concerns about the need revise my entire ethical system?
  • Am I taking the moral issue under consideration seriously? Why or why not?
  • Would I be willing to change my stance if the argument was compelling? Why or why not?
  • Is there something about the view that I cannot bring myself to consider? If so, what?

While awareness of our various blind spots and areas of discomfort will not automatically improve the quality of discussion, it can pave the way for a more meaningful consideration of the issues. As such, metacognitive awareness can facilitate healthy engagement with moral issues.

Reference:

Vygotsky, L. S. (1978). Mind and society: The development of higher mental processes. Cambridge, MA: Harvard University Press.


Metacognition and Reflective Thinking

By Steven C. Fleisher, California State University Channel Islands

Imagine that we are reading an assignment. As we read, do we think: “How long will this take?” “Will this be on the test?” If so, try this instead. Presume that we are reading the article as preparation for meeting later with an important person such as our supervisor to discuss the article. How would this situation change the questions we ask ourselves? Such thinking can make us aware of what constitutes satisfactory mastery of knowing and how to achieve it.

Think back for a moment to learning a psychomotor skill, such as learning to ride a bicycle. It is normal to master that skill with normal innate balance and strength. We might think: “That’s all there is to it.” However, watching cyclists in a serious bicycle race or triathlon, reveals that reliance only on innate ability cannot produce that kind of performance. That level of expertise requires learning to pedal with cadence, to deliver equal power from both legs, use the gearing appropriately, exploit position within a group of racers and pace oneself relative to challenges. Untrained innate ability can rarely get us far in comparison to the results of informed training.

The same is true in learning. Metacognitive skills (learnable skills) enhance academic performance. People with metacognitive skill will usually outperform others who lack such skill, even others with greater innate intelligence (natural ability). Metacognitive training requires developing three strengths: 1) metacognitive knowledge, 2) metacognitive monitoring, and 3) metacognitive control.

Metacognitive knowledge refers to our understanding about how learning operates and how to improve our learning. We should have enough of this knowledge to articulate how we learn best. For example, we can know when it is best for us to write a reflection about a reading in order to enhance our learning. We should be alert to our misconceptions about how our learning works. When we learn that cramming is not always the best way to study (Believe it!), we must give that up and operate with a better proven practice.

Metacognitive monitoring refers to developed ability to monitor our progress and achievement accurately. For example, self-assessment is a kind of metacognitive monitoring. We should know when we truly understand what we are reading and assess if we are making progress toward solving a problem. When we become accurate and proficient in self-assessment, we are much better informed. We can see when we have mastered certain material well enough, and when we have not.

Metacognitive control. This competency involves having the discipline and control needed to make the best decisions in our own interests. This aspect of metacognition includes acting on changing our efforts or learning strategies, or taking action to recruit help when indicated.

Putting it together. When we engage in metacognitive reflection, we can ask ourselves, for example, “What did we just learn?” “What was problematic, and why?” “What was easy, and why?” “How can we apply what we just learned?” Further, when we gain metacognitive skill, we begin to internalize habits of learning that better establish and stabilize beneficial neural connections.

Reflective Exercises for Students:

  1. Metacognitive knowledge. Consider three learning challenges: acquiring knowledge, acquiring a skill, or making an evidence-based decision. How might the approaches needed to succeed in each of these three separate challenges differ?
  2. Metacognitive monitoring. After you complete your next assignment or project, rate your resultant state of mastery on the following scale of three points: 0 = I have no confidence that I made any meaningful progress toward mastery; 1 = I clearly perceived some gain of mastery, but I need to get farther; 2 = I am currently highly confident that I understand and can meet this challenge.
  3. Next, see if your self-rating causes you to take action such as to re-study the material or to seek help from a peer or an instructor in order to achieve more competence and higher confidence. A critical test will be whether your awareness from monitoring was able to trigger your taking action. Another will come in time. It will be whether your self-assessment proved accurate.
  4. Metacognitive control. To develop better understanding of this, recall an example from life when you made a poor decision that proved to produce a result that you did not desire or that was not in your interests. How did living this experience equip you to better deal with a similar or related life challenge?

References

Chew, S. L. (2010). Improving classroom performance by challenging student misconceptions about learning. Association for Psychological Science: Observer, Vol. 23, No. 4. http://psychologicalscience.org/observer/getArticle.cfm?id=2666

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

Leamnson, R. N. (1999). Thinking about teaching and learning: Developing habits of learning with first year college and university students. Sterling, VA: Stylus.

Pintrich, P. R. (2002). The role of metacognitive knowledge in learning, teaching, and assessing. Theory Into Practice, 41(4), 219-225.

Wirth, K. (2010). The role of metacognition in teaching Geoscience. Science Education Resource Center, Macalester College. http://serc.carleton.edu/NAGTWorkshops/metacognition/activities/27560.html


Using metacognition to uncover the substructure of moral issues

By John Draeger, SUNY Buffalo State

As a moral philosopher, my introductory courses revolve around various controversial issues (e.g., abortion, euthanasia, hate speech, same sex marriage, invasions of privacy in the name of national security or commerce). It is not hard to generate discussion about these topics, but important philosophical issues often to get lost in the mayhem. My students try to keep things straight by focusing on particular bits of content. They hope that a laundry list of terms and distinctions will help them make sense of particular ethical issues. For my part, however, most of the interesting stuff occurs behind the scenes. I don’t much care about which topics we discuss because at some level I don’t think that we are talking about the particular topical issues anyway. Details matter, of course, but I am most interested in helping students uncover the underlying value conflicts common to many ethical debates. This, I argue, requires developing metacognitive awareness.

Consider three possible positions on hate speech: (1) ban hate speech on college campuses because it harms individual students, (2) allow hate speech because banning it would violate the rights of individual students, (3) allow hate speech because banning it would do more harm than good in the long-run. Now consider three possible views on governmental surveillance in the name of national security: (1) allow governmental surveillance because it promotes an important good (e.g., national security), (2) ban governmental surveillance because it violates the rights of citizens (e.g., privacy), (3) ban governmental surveillance because it does more harm than good in the long-run. Note the similar underlying value structures of these positions. One favors well-being (e.g., protect individual students or a nation) over other considerations. Another favors rights (e.g., free-speech or privacy) over harms to well-being caused by the exercise of those rights. The last considers two forms of well-being (e.g., short-term and long-term).

As an instructor, I know that teaching students a process by which they can uncover underlying value structures requires scaffolding and plenty of opportunities to practice (Duron, Limback, & Waugh, 2006). Among my many activities and assignments, I ask students to answer the following questions about each of the readings: (1) what is the author’s core insight/thesis? (2) what are the core values at issue? (3) what are the central philosophical problems at issue? (4) what are the central topics at issue? It is not long before students understand that the last two questions are not actually redundant (e.g., well-being versus rights is not the same as hate speech versus governmental surveillance).

This exercise helps students focus on what I take to be most important, namely the underlying value structure. It also sets up the next exercise in which I ask students to use the resources found in one reading (e.g., hate speech) to answer the topical question raised in another (e.g., government surveillance).  This can be difficult until students recognize there are values common across different topical debates and they recognize the similarities in the philosophical substructure (e.g., well-being over rights, rights over well-being, long-term well-being over short-term well-being). Because it isn’t always easy to fit one view into the structure of another, this exercise leads to many questions about each of the readings. As the semester moves along, we discuss each reading in relation to those that came before.  By the end of the semester, we pick author names “at random” and discuss the connections between them.

With an understanding the underlying value structure of a particular moral issue, students can begin to “think like a philosopher.” It puts them in a position to move beyond mere coffee shop conversation and the rehash of media pundit drivel towards a more careful consideration of the issues. Through the process outlined above, they begin to notice when their discussions lapse into media drivel and thus when they need steer the conversation back towards the underlying value structure. Insofar as this exercise moves students towards the ability to consciously and explicitly understand the substructure of values underlying a wide variety of ethical issues, it moves them towards a more sophisticated understanding of those issues and towards a metacognitive awareness of their own learning.

References

Duron, R., Limbach, B., & Waugh, W. (2006). “Critical Thinking Framework for Any Discipline.” International Journal of Teaching and Learning in Higher Education, 17 (2), 160-166.

 


The effects of distraction on metacognition and metacognition on distraction

Beaman CP, Hanczakowski M and Jones DM (2014) The effects of distraction on metacognition and metacognition on distraction: evidence from recognition memory. Front. Psychol. 5:439. doi: 10.3389/fpsyg.2014.00439

http://journal.frontiersin.org/Journal/10.3389/fpsyg.2014.00439/abstract (open source full text)

According to the authors (p. 11), “The results documented in our study with free-report tests also reveal that effects of distraction do not end with impairing memory processes. Auditory distraction has important consequences for how accurate people are in monitoring their memory processes, as revealed by impaired resolution of confidence judgments under distraction. Even more importantly, auditory distraction modifies metacognitive control and thus shapes performance when the “don’t know”option is available in a memory test. Participants seem to be aware that auditory distraction is harmful for memory as they become much less confident in their correct responses when distraction is present (see also Ellermeier and Zimmer, 1997; Beaman, 2005b).

 


Metacognition distinguishes Good from Great Learners

In the thought-provoking blog post, Why Good Students Do “Bad” in College: Impactful Insights by Leonard Geddes, he discusses why a large percent of good students in college do not live up to their potential. In this post, he makes the statement that “metacognition is where good students and great learners differ most. In fact, research shows that students who are not metacognitively aware will struggle in college (Caverly D.C., 2009).” He goes on to share a couple great resources to help students develop their metacognitive abilities.


What do we mean when we say “Improve with metacognition”? (Part Two)

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

The nature and many benefits of metacognition might seem obvious to those of us working in the field. But because our casual conversations had revealed some “fuzziness” in how the term was interpreted, we asked a convenience sample at our institutions (30 faculty and 11 students) what they believe the term ‘metacognition’ means and why it might be important. As summarized in Part I of this two-part exploration, most respondents offered “thinking about thinking” as a rough shorthand for the meaning of metacognitive processes. Beyond that general response, many faculty offered refinements that we grouped into the categories of awareness, intentionality and understanding. While that conversation is ongoing, this week’s post will focus on responses to the second question in our “survey”, “why might it be important for students and instructors to know about metacognition and perhaps incorporate it in their classes?”

When considering the benefits, the majority of our respondents affirmed importance of metacognition in academic settings. In particular, metacognition was reported to be beneficial because it “improves student learning” and “improves teaching.” As in our last post, where we argued that, while defining ‘metacognition’ as “thinking about thinking” can be a helpful way to get the conversation started but is too simplistic, the goal in this post also is to move toward more useful refinements.

Refinements to “improved student learning” can be grouped into two categories:

(1)  Metacognition improves student learning by increasing efficiency and prompting students to  take ownership of their own learning

  • “As a student, if you can understand how you think and learn, then you can more easily choose the method that will work for you.”
  •  Metacognition can “help [students] create strategies to enhance their study of new concepts to increase their retention of the concepts.”
  •  “I can study faster and more efficiently …”
  •  “Metacognition forces students to take positive control of their own development. Much like the first step to getting your finances in order is to see where your money is going, metacognitive questions help a learner assess whether s/he has actually increased his/her level of understanding or knowledge.”
  • “…they [learners] become more independent in their learning…”

(2)  Metacognition increases the depth of learning engagement with material and supports critical thinking

  • “By reflecting on our understanding we’re more likely to improve that understanding and make connections between bodies of knowledge.”
  • “…figuring out why the wrong answers (and the reasoning behind them) are wrong.  This is often more important than getting the right answer.  It is by repairing errors in our thinking that we learn surprising things we didn’t know we were ignorant about…”
  • “[Metacognition is] an important step in the critical thinking process. If I am not aware of how I am thinking about something, the context, the role and the perspective, then it is difficult to think critically”
  • “The issue is being able to use critical-thinking skills to sift through the mass of information to develop appropriate conclusions, theses, etc.  Metacognition enables us to analyze how we’re doing this and thus, do it better.”
  • “If we can get students to think about thinking, their own and others, it will help them to be better thinkers.  It might also encourage them to be more slow, careful and deliberate in their thinking / writing / speaking.”

 

Refinements to “improves teaching” can be grouped into two categories:

(1)  The more instructors understand about their students’ learning processes and are aware of their state of learning, the more then they can adapt to the needs of their students.

  • “I also have to be able to teach in different ways for people who learn differently than me, and have an idea how they learn”
  • “…helps us [instructors] structure our teaching to best support student learning”
  • “It’s important as instructors because if we understand how our cadets [students] think, we can tweak our teaching methods appropriately. “
  • “Because the more aware that students and teachers are about how each other thinks and learns, the more effective classroom learning techniques can be.”

(2)  The more instructors communicate about metacognition, the better they can help students become better learners.

  • “…if professors and students communicate about metacognition it can allow the instructors to use every resource available to them to better convey information to the students.”
  • “…It’s one thing to be aware of how you learn something or think through complex issues.  However, even better is to have the ability to identify which processes are most effective for you.  Metacognition becomes important when it informs us about how to improve, how to be more efficient, and how to “sift the wheat from the chaff,” so to speak… This self-awareness is not always obvious to a student and thus is most likely enhanced when facilitated by faculty members…”

In conclusion, both teaching and learning are dynamic processes that interact with each other.  Thus, we must continue to adapt to the ever-changing circumstances of our current students’ state of learning and help them do so also. Because instructors are not ever-present in students’ lives, our ultimate goal as instructors should be to help develop independent learners.

Metacognition can play a crucial role in both teaching and learning because it prompts us to be “tuned into” these dynamic processes and because it reminds us to be on the lookout for ways to improve and promote deep, life-long learning. These goals are especially important given recently reported shortcomings in higher-education  (e.g. Arum & Roksa, 2011).  Students need to know how to think critically and communicate well. The term ‘metacognition’ can be understood in a variety of ways and there are many benefits to metacognition. However, they boil down to supporting deep learning goals (beyond mere memorization) and critical thinking at a time when students in higher-education need it most.

References:

Arum, R., & Roksa, J. (2011). Academically adrift: Limited learning on college campuses. Chicago, IL: University of Chicago Press.

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


A Brief History of Learning Inventories

Noel Entwistle and Velda McCune (2004) catalog the evolution of learning inventories over the last fifty years. The article is particularly useful in highlighting the ways similar ideas are discussed using differing terminology. Because of the article’s scope, readers can become quickly familiar with broad trends.

Entwistle, N., & McCune, V. (2004). The conceptual bases of study strategy inventories. Educational Psychology Review, 16(4), 325-345.


Self-regulation and metacognitive judgments among psychology students

Randy Isaacson and Frank Fujita (2006) consider the effects of metacognitive judgments on anticipated performance, self-efficacy, and learning satisfaction in introductory psychology students. Of note, the study allowed students to choose test questions based on their self-assessment of the comprehension of the material.

Isaacson, R. M., & Fujita, F. (2006). Metacognitive Knowledge Monitoring and Self-Regulated Learning: Academic Success and Reflections on Learning. Journal of Scholarship of Teaching and Learning, 6(1), 39-55.