Tag: Regulation of Cognition

Metacognition and the Fish in the Water

by Steven J. Pearlman, Ph.D. The Critical Thinking Initiative

As the saying goes, you cannot ask a fish about water. Having had no other environmental experience as a counter reference, the fish cannot understand what water is because the fish has never experienced what water isn’t.

Cognition—broadly meaning that the mind is working—is to homo sapiens as water is to fish. So steeped are we in the water of our own cognitive processing that we cannot recognize it. Even though we all possess an extensive list of examples of other people failing to think well, we nevertheless lack an internal reference point for being devoid of thought; every consideration we might make of what it would be like to not-think can only happen through the process of thinking about it.

cartoon drawing of a goldfish on a blue background

This is the difference between metacognition, which is being intentionally self-aware of what we are doing when we are thinking, and critical thinking, which, loosely speaking, is the capacity to reason through problems and generate ideas. In one sense, we seem to do just fine thinking critically without that metacognitive awareness. We solve problems. We invent the future. We cure diseases. We build communities. But in another all-too-real sense, we struggle, for if we lack the metacognitive acumen to understand what critical thinking is, then we equally lack the capacity to improve our capability to do it and to monitor and evaluate our progress.

The Problem and the Need

Case in point, even though research shows that critical thinking is typically listed among necessary outcomes at educational institutions, “it is not supported and taught systematically in daily instructions” because “teachers are not educated in critical thinking” (Astleitner, 2002). Worse than that, one study of some 30 educators found that not a single one could provide “a clear idea of critical thinking” (Choy & Cheah, 2009). Thus, even though “one would be hard pressed to construct a serious counterargument to the claim that we would like to see students become careful, rigorous thinkers as an outcome of the education we provide them. … By most accounts, we remain far from achieving it” (Kuhn, 1999).

But we do need to achieve that rigorous thinking, because nothing is arguably more important than improving our overall capacity to think. To do so, we must seek to understand the relationship between critical thinking and metacognition, for though interrelated, they’re not the same. In fact, we can think critically without being metacognitive, but we cannot be metacognitive without thinking critically. And that might make metacognition the seminal force of true critical thinking development.

Some Classroom Examples

Consider, for example, asking a student, “What is your thinking about the assigned readings about the Black Lives Matter movement”? Were the student to respond with anything substantive, then we could loosely say the student exercised at least some critical thinking, such as some analysis of the sources and some evaluation of their usefulness. For example, were the student to state that “by referencing statistics on black arrests, source A made a more compelling argument than source B,” then we could rightly say that the student generated some critical thinking. But we cannot say that the student engaged in any metacognitive effort.

But what if the student responded, “Because of its use of statistics on black arrests, Source A changed my thinking about the Black Lives Matter because I was previously unaware of the disparities between white arrest rates and black arrest rates”? Is that metacognitive? Not truly. Even though the student was aware of a change in their own thoughts, they expressed no self-awareness of the internal thinking process that catalyzed that change. There is not necessarily a meaningful distinction between what that student did and someone who says that they had not liked mashed potatoes until they tried these mashed potatoes. They recognized a shift in thought, but not necessarily the underlying mechanism of that shift.

However, if the student responded as follows, we would begin to see metacognition on top of critical thinking: “I realized upon reading Source A that I held a tacit bias about the issue, one that was framed from my own experience being white. I had been working under the assumption that race didn’t matter, and it wasn’t until the article presented the statistics that my thinking was impacted enough for me to become aware of my biases and change my position.” In that sentence, we see the student metacognitively recognizing an aspect of their own thinking process, namely their personal biases and the relationship between those biases and new information. As Mahdvi (2014) said, “Metacognitive thoughts do not spring from a person’s immediate external reality; rather, their source is tied to the person’s own internal mental representations of that reality, which can include what one knows about that internal representation, how it works, and how one feels about it.” And that’s what this example demonstrates: the student’s self-awareness of “internal mental representations of … reality.”

The Value of Metacognition to Critical Thinking

When metacognition is present, all thinking acts are critical because they are by nature under reflection, and scrutiny. While one could interpret a love poem without being metacognitive, one could not be metacognitive about why they interpret a poem a certain way—such as in considering one’s biases about “love” from their personal history—without thinking critically. Since metacognition can only happen when we are monitoring our thinking about something, the metacognition inherently makes the thinking act critical.

Yet, even though metacognition infuses some measure of criticality to thinking, metacognition nevertheless isn’t synonymous with critical thinking. Metacognition alone does not successfully critique existing ideas, analyze the world, develop meaningful questions, produce new solutions, etc. So, we can think without being metacognitive, but if we want to improve our thinking—if we want to understand and enhance the machinations of our mind—then we must seek and attain the metacognitive skills that reveal what our mind is doing and why it is doing it.

Accomplishing that goal requires an introspective humility. It means embracing the premise that our own thinking process is at best always warped, if not often mortally wounded, by our biases, predisposition, and measures of ignorance. It means that we often cannot efficiently solve problems unless we first solve for ourselves, and that’s not easy to do for a bunch of fish who are steeped in the waters cognitive.

References

Astleitner, H. (2002). Teaching Critical Thinking Online. Journal of Instructional Psychology, 29(2), 53-76.

Choy, S.C. & Cheah, P.K. (2009). Teacher perceptions of critical thinking among students and its influence on higher education. International Journal of Teaching and Learning in Higher Education, 20(2), 198-206.

Kuhn, D. (1999). A developmental model of critical thinking. Educational Researcher, 28(2), 16-25.

Madhavi, M. (2014). An Overview: Metacognition in Education. International Journal of Multidisciplinary and Current Research, 2.


What Pandemics Can Teach Us about Critical Thinking and Metacognition

by Stephen L. Chew, Ph.D. Samford University (slchew@samford.edu)

Critical thinking leads to fewer errors and better outcomes, fueling personal and societal success (Halpern, 1998; Willingham, 2019). The current view is that critical thinking is discipline specific and arises out of subject expertise. For example, a chess expert can think critically about chess, but that analytical skill does not transfer to non-chess situations. The evidence for general critical thinking skills, and our ability to teach them to students, is weak (Willingham, 2019). But these are strange times that challenge that consensus.

The world is currently dealing with COVID-19, a pandemic unprecedented in our lifetime in scope, virulence, and level of contagion. No comprehensive expertise exists about the most effective policies to combat the pandemic. Virologists understand the virus, but not the epidemiology. Epidemiologists understand models of infection, but not public policy. Politicians understand public policy, but not viruses. We are still discovering the properties of COVID-19, fine tuning pandemic models, and trying out new policies.  As a result, different countries have responded to the pandemic in different ways. Unfounded beliefs and misinformation have proliferated to fill the void of knowledge, which range from useless to counterproductive and even harmful.

graph with virus molecule and question marks

The Relationship between Metacognition and Critical Thinking

If critical thinking can only occur with sufficient expertise, then virtually no one should be able to think critically about the pandemic, yet I believe that critical thinking can play a vital role. In this essay, I argue that metacognition is a crucial element of critical thinking and, because of this, critical thinking is both a general skill and teachable. While critical thinking is most often seen (and studied) in situations where  prior knowledge matters, it is in unprecedented situations like this pandemic where more general critical thinking skills emerge and can make a crucial difference in terms of decision making and problems solving.  

I’m building on the work of Halpern (1998) who argued that critical thinking is a teachable, general, metacognitive skill. She states, “When people think critically, they are evaluating the outcomes of their thought processes – how good a decision is or how well a problem is solved” (Halpern, 1998, p. 451). Reflection on one’s own thought processes is the very definition of metacognition. Based on Halpern’s work, we can break critical thinking down into five core components:

  1. Predisposition toward Engaging in Thoughtful Analysis
  2. Awareness of One’s Own Knowledge, Thought Processes and Biases
  3. Evaluation of the Quality and Completeness of Evidence
  4. Evaluation of the Quality of the Reasoning, Decision Making, or Problem Solving 
  5. An Ability to Inhibit Poor and Premature Decision Making

Predisposition toward Engaging in Thoughtful Analysis

Critical thinking involves a personal disposition toward engaging in thoughtful analysis. Strong critical thinkers display this tendency in situations where many people do not see the need, and they engage in more detailed, thorough analysis than many people feel necessary (Willingham, 2019). The variation in the predisposition to think analytically has been on display during the pandemic. Some people simply accept what they hear or read without verifying its validity. In social media, they might pass along information they find interesting or remarkable without distinguishing between valid information, conspiracy, opinion, and propaganda.

The penchant for complex thinking as a habit can be developed and trained. Our educational system should reinforce the value of detailed analysis in preventing costly errors and should give students extensive practice in carrying it out within whatever field the student is studying.

Awareness of One’s Own Knowledge, Thought Processes and Biases

Critical thinking requires insight into the accuracy of what one knows and the extent and importance of what one doesn’t know. It also involves insight into how one’s biases might influence judgment and decision making (West et al., 2008). Metacognition plays a major role in accurate self-awareness.

Self-awareness is prone to serious error and bias (Bjork et al., 2013; Metcalfe, 1998). Greater confidence is not the same as greater knowledge. Metacognitive awareness can be poor and misleading (McIntosh et al., 2019). The good news, though, is that poor self-awareness can be overcome through proper experience and feedback (Metcalfe, 1998).

In this pandemic, key critical thinking involves understanding the implications of what we know and continue to discover about COVID-19. One example is the exponential growth rate of COVID-19  infection. Effective responding to the exponential growth involves taking aggressive preventative measures before there is any symptomatic evidence of spread, which, intuitively, seems like an overreaction. Confirmation bias made it easy to accept what people wanted to be true as fact and reject what they did not want to be true as unlikely. Thus, people often ignored warnings about distancing and avoiding large gatherings until the pandemic was well underway.

Recognizing one’s own biases and how to avoid them is a general skill that can be developed through education. Students can be taught to recognize the many biases that can undermine rational, effective thinking (Kahneman, 2011). For example, students can learn to seek out disconfirming evidence to counter confirmation bias (Anglin, 2019). To guard against overconfidence, students can learn to assess their understanding against an objective standard (Chew, 2016).

Evaluation of the Quality and Completeness of Evidence

Critical thinkers understand the importance of evaluating the quality and completeness of their evidence, which involves a metacognitive appraisal. Do I have data of sufficient quality from sufficiently representative samples in order to make valid decisions? What data am I missing that I need? The quality of evidence continues to be of immense concern in the U.S. because of the lack of rapid testing for COVID-19. Critical thinkers understand that data vary in reliability, validity and measurement error. Early in the pandemic, some people believed that COVID-19 was milder than the flu. These people accepted early estimates at face value, without understanding the limitations of the data. What counts for valid data is one aspect of critical thinking that is more discipline specific. Critical thinkers may not be able to evaluate the quality of evidence outside their area of expertise, but they can at least understand that data can vary in quality and it matters greatly for making decisions.

Non-critical thinkers consider data in a biased manner. They may search only for information that supports their beliefs and ignore or discount contradictory data (Schulz-Hardt et al., 2000). Critical thinkers consider all the available data and are aware if there are data they need but do not have. During the pandemic, there were leaders who dismissed the severity of COVID-19 and waited too long to order a quarantine, and there were leaders who wanted to remove the quarantine restrictions despite the data.  

Evaluation of the Quality of the Reasoning, Decision Making, or Problem Solving

Critical thinking includes evaluating how well the evidence is used to create a solution or make a decision (e.g. Schwartz et al. 2005). There are general metacognitive questions that people can use to evaluate the quality of any argument. Have all perspectives been considered?  Have all alternative explanations been explored? How might a course of action go wrong? Like judgments of evidence, judgments of the strength of an argument is fraught with biases (e.g. Gilovich, 2008; Kraft et al., 2015; Lewandowsky et al., 2012). People more readily accept arguments that agree with their views and are more skeptical of arguments they disagree with, instead of considering the strength of the argument. The pandemic has already spawned dubious studies with selection bias, lack of a control group, or lack careful control, but the “findings” of these studies are embraced by people who want them to be true. Furthermore, people persist in beliefs in the face of clear contradictory evidence (Guenther & Alicke, 2008).

Students should learn about the pitfalls of bias and motivated cognition regardless of their major. Critical thinking involves intellectual humility, an openness to alternative views and a willingness to change beliefs in light of sufficient evidence (Porter, & Schumann, 2018).

An Ability to Inhibit Poor and Premature Decision Making

The last component of a critical thinker is resistance to drawing premature conclusions. Critical thinkers know the limitations of their evidence and keep their reasoning and decision making within its bounds (Noone et al., 2016). They resist tempting but premature conclusions. The inhibitory aspect of critical thinking is probably the least well understood of all the components and deserves more research attention.

Metacognition Supports Critical Thinking

Metacognition, the ability to reflect on one’s own knowledge, plays a crucial role in critical thinking. We see it in the awareness of one’s own knowledge (Component 2), awareness of the quality of evidence and possible biases (Component 3) and the evaluation of the strength of an argument (Component 4). If we wish to teach critical thinking, we need to emphasize these metacognitive skills, both as part of a student’s training in a major and as part of general education. The other two components of critical thinking, the predisposition to engage in critical thinking and the inhibition of premature conclusions, are habits that can be trained.

Critical thinking is hard to do. It takes conscious mental effort and requires overcoming powerful human biases. No one is immune to bad decisions. I assert that critical thinking is a general, teachable skill, especially in situations where decisions have to be made in unprecedented conditions. The pandemic shows that critical decisions often have to be made before sufficient evidence is available. Critical thinking leads to better outcomes by making the best use of available evidence and minimizing error and vulnerability to bias. In these situations, critical thinking is a vital skill, and metacognition plays a major role.

References

Anglin, S. M. (2019). Do beliefs yield to evidence? Examining belief perseverance vs Change in response to congruent empirical findings. Journal of Experimental Social Psychology, 82, 176–199. https://doi-org.ezproxy.samford.edu/10.1016/j.jesp.2019.02.004

Bjork, R.A., Dunlosky, J., & Kornell, N. (2013) Self-regulated learning: Beliefs, techniques, and illusions. Annual Review of Psychology, 64, 417-444.  https://pdfs.semanticscholar.org/4efb/146e5970ac3a23b7c45ffe6c448e74111589.pdf

Chew, S. L. (2016, February). The Importance of Teaching Effective Self-Assessment. Improve with Metacognition Blog. Retrieved from https://www.improvewithmetacognition.com/the-importance-of-teaching-effective-self-assessment/

Gilovich T. (2008). How We Know What Isn’t So: Fallibility of Human Reason in Everyday Life (Reprint edition). Free Press.

Guenther, C. L., & Alicke, M. D. (2008). Self-enhancement and belief perseverance. Journal of Experimental Social Psychology, 44(3), 706-712. doi:10.1016/j.jesp.2007.04.010

Halpern, D. F. (1998). Teaching critical thinking for transfer across domains: Disposition, skills, structure training, and metacognitive monitoring. American Psychologist, 53(4), 449-455.

Kahneman, D. (2011). Thinking, fast and slow. New York: Farrar, Straus and Giroux.

Kraft, P. W., Lodge, M., & Taber, C. S. (2015). Why people ‘don’t trust the evidence’: Motivated reasoning and scientific beliefs. Annals of the American Academy of Political and Social Science, 658(1), 121–133. https://doi-org/10.1177/0002716214554758

Lewandowsky, S., Ecker, U. K. H., Seifert, C. M., Schwarz, N., & Cook, J. (2012). Misinformation and Its Correction: Continued Influence and Successful Debiasing. Psychological Science in the Public Interest, 13(3), 106–131. https://doi-org.ezproxy.samford.edu/10.1177/1529100612451018

Metcalfe, J. (1998). Cognitive optimism: Self-deception or memory-based processing heuristics? Personality and Social Psychology Review, 2(2), 100–110. https://doi-org.ezproxy.samford.edu/10.1207/s15327957pspr0202_3

McIntosh, R. D., Fowler, E. A., Lyu, T., & Della Sala, S. (2019). Wise up: Clarifying the role of metacognition in the Dunning-Kruger effect. Journal of Experimental Psychology: General, 148(11), 1882–1897. https://doi.org/10.1037/xge0000579

Noone, C., Bunting, B., & Hogan, M. J. (2016). Does mindfulness enhance critical thinking? Evidence for the mediating effects of executive functioning in the relationship between mindfulness and critical thinking. Frontiers in Psychology, 6. https://doi.org/10.3389/fpsyg.2015.02043

Porter, T., & Schumann K., (2018) Intellectual humility and openness to the opposing view, Self and Identity, 17(2), 139-162, DOI: 10.1080/15298868.2017.1361861

Schulz-Hardt, S., Frey, D., Lüthgens, C., & Moscovici, S. (2000). Biased information search in group decision making. Journal of Personality and Social Psychology, 78(4), 655–669. https://doi-org /10.1037/0022-3514.78.4.655

Schwartz, D., Bransford, J., & Sears, D. (2005). Efficiency and innovation in transfer. In J. Mestre (Ed.), Transfer of learning from a modern multidisciplinary perspective (pp. 1-51). Greenwich, CT: Information Age Publishing.

West, R. F., Toplak, M. E., & Stanovich, K. E. (2008). Heuristics and biases as measures of critical thinking: Associations with cognitive ability and thinking dispositions. Journal of Educational Psychology, 100(4), 930–941. https://doi-org/10.1037/a0012842

Willingham, D. T. (2019).  How to Teach Critical Thinking. Education Future Frontiers, New South Wales Department of Education.


Metacognition, the Representativeness Heuristic, and the Elusive Transfer of Learning

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

When we instructors think about student learning, we often default to immediate learning in our courses. However, when we take a moment to reflect on our big picture learning goals, we typically realize that we want much more than that. We want our students to engage in transfer of learning, and our hopes can be grand indeed…

  • We want our students to show long-term retention of our material so that they can use it in later courses, sometimes even beyond those in our disciplines.
  • We want our students to use what they’ve learned in our course as they go through life, helping them both in their profession and in their personal lives.

These grander learning goals often involve learning of ways of thinking that we endeavor to develop, such as critical thinking and information literacy. And, for those of us who believe in the broad value of metacognition, we want our students to develop metacognition skills. But, as some of us have argued elsewhere (Scharff, Draeger, Verpoorten, Devlin, Dvorak, Lodge & Smith 2017), metacognition might be key for the transfer of learning and not just a skill we want our students to learn and then use in our course.

Metacognition involves engaging in intentional awareness of a process and using that awareness to guide subsequent behavioral choices (self-regulation). In our 2017 paper, we argued that students don’t engage in transfer of learning because they aren’t aware of the similarities of context or process that would indicate that some sort of learning transfer would be useful or appropriate. What we didn’t explore in that paper is why that first step might be so difficult.

If we look to research in cognitive psychology, we can find a possible answer to that question – the representativeness heuristic. Heuristics are mental short-cuts based on assumptions built from prior experience. There are several different heuristics (e.g. representativeness heuristic, availability heuristic, anchoring heuristic). They allow us to more quickly and efficiently respond to the world around us. Most of the time they serve us well, but sometimes they don’t.

The representativeness heuristic occurs when we attend to obvious characteristics of some type of group (objects, people, contexts) and then use those characteristics to categorize new instances as part of that group. If obvious characteristics aren’t shared, then the new instances are categorized separately.

  • photo of cows in a field
  • photo of horses in a field

For example, if a child is out in the countryside for the first time, she might see a four-legged animal in the field. She might be familiar with dogs from her home. When she sees the four-legged creature in the field, so might immediately characterize the new creature as a dog based on that characteristic. Her parents will correct her, and say, “No. Those are cows. They say moo moo. They live in fields.” The young girl next sees a horse in a field. She might proudly say, “Look another cow!” Her patient parents will now have to add characteristics that will help her differentiate between cows and horses, and so on. At some level, however, the young girl must also learn meta-characteristics that make all these animals connected as mammals: warm-blooded, furred, live-born, etc. Some of these characteristics may be less obvious from a glance across a field.

Now – how might this natural, human way-of-thinking impact transfer of learning in academics?

  • To start, what are the characteristics of academic situations that support the use of the representative heuristic in ways that decrease the likelihood of transfer of learning?
  • In response, how might metacognition help us encourage transfer of learning?

There are many aspects of the academic environment that might answer the first question – anything that leads us to perceive differences rather than connections. For example, math is seen as a completely different domain than literature, chemistry, or political science. The content and the terminology used by each discipline are different. The classrooms are typically in different buildings and may look very different (chemistry labs versus lecture halls or small group active learning classrooms), none of which look or feel like the physical environments in “real life” beyond academics. Thus, it’s not surprising that students do not transfer learning across classes, much less beyond classes.

In response to the second question, I believe that metacognition can help increase the transfer of learning because both mental processes rely on awareness/attention as a first step. Representativeness categorization depends on the characteristics that are attended. Without conscious effort, the attended characteristics are likely to be those most superficially obvious, which in academics tend to highlight differences rather than connections.

But, with some guidance and encouragement, other less obvious characteristics can become more salient. If these additional characteristics cross course/disciplinary/academic boundaries, then opportunities for transfer will enter awareness. The use of this awareness to guide behavior, transfer of learning in this case, is the second step in metacognition.

Therefore, there are multiple opportunities for instructors to promote learning transfer, but we might have to become more metacognitive about the process in order to do so. First we must develop awareness of connections that will promote transfer, rather than remaining within the comfort zone of their disciplinary expertise. Then we must use that awareness and self-regulate our interactions with students to make those connections salient to students. We can further increase the likelihood of transfer behaviors by communicating their value.

We typically can’t do much about the different physical classroom environments that reinforce the distinctions between our courses and nonacademic environments. Thus, we need to look for and explicitly communicate other types of connections. We can share examples to bridge terminology differences and draw parallels across disciplinary processes.

For example, we can point out that creating hypotheses in the sciences is much like creating arguments in the humanities. These disciplinary terms sound like very different words, but both involve a similar process of thinking. Or we can point out that MLA and APA writing formats are different in the details, but both incorporate respect for citing others’ work and give guidance for content organization that makes sense for the different disciplines. These meta-characteristics unite the two formatting approaches (as well as others that students might later encounter) with a common set of higher-level goals. Without such framing, students are less likely to appreciate the need for formatting and may interpret the different styles as arbitrary busywork that doesn’t deserve much thought.

We can also explicitly share what we know about learning in general, which also crosses disciplinary boundaries. A human brain is involved regardless of whether it’s learning in the social sciences, the humanities, the STEM areas, or the non-academic professional world. In fact, Scharff et al (2017) found significant positive correlations between thinking about learning transfer and thinking about learning processes and the likelihood to use awareness of metacognition to guide practice.

Cognitive psychologists know that we can reduce errors that occur from relying on heuristics if we turn conscious attention to the processes involved and disengage from the automatic behaviors in which we tend to engage. Similarly, as part of a metacognitive endeavor, we can help our students become aware of connections rather than differences across learning domains, and encourage behaviors that promote transfer of learning.

Scharff, L., Draeger, J., Verpoorten , D., Devlin, M., Dvorakova, L., Lodge, J. & Smith, S. (2017). Exploring Metacognition as Support for Learning Transfer. Teaching and Learning Inquiry, Vol 5, No. 1. DOI: http://dx.doi.org/10.20343/5.1.6 A Summary of this work can also be found at https://www.improvewithmetacognition.com/researching-metacognition/

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


Scratch and Win or Scratch and Lose? Immediate Feedback Assessment Technique

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

When prepping my courses for this spring semester, I was thinking about how I often struggle with providing quick and easy feedback on quiz and exam performance to my students. I expressed this to my colleague, Dr. Anna Ropp (@AnnaRopp), and she quickly suggested that I check out Immediate Feedback Assessment Technique (IF-AT) by Epstein Educational Enterprises. When she showed me the IF-ATs, I was intrigued and thought I might as well give it a try—so I ordered some. IF-AT is used to instantaneously provide performance feedback to learners by allowing students to scratch off what they believe to be the correct answer on a multiple-choice exam, quiz or test. See Figure 1a and 1b for student examples of a completed IF-AT.  Students can find out what the incorrect or correct answer is by just scratching the chosen answer (see question 1 in Figure 1a). Students can scratch more than one answer to find the correct answer (see question 2 in Figure 1a). You may also use it as a way of providing partial credit for sequenced attempts (e.g., scratch 1 choice for full credit if correct, then scratch a second choice, and maybe a third, to get decreasing amounts of partial credit). See question 6 in Figure 1b for an example of this.  Epstein and colleagues suggest that IF-AT not only assesses student learning, but it can also teach at the same time. However, it occurred to me that this is not only an assessment and teaching tool, rather it is a great opportunity to increase metacognition.

                                                        (a)                                                (b)

Figure 1. Completed and Unscored 10-Question IF AT Completed 10-Question IF AT Student and Teacher Scored

How to Use IF-AT
Epstein and colleagues suggest that IF-AT is fair, fast, active, fun, and respectful and builds knowledge. The IF-AT scratch assessments come in 10, 25, or 50-item test options with 5 different orders of correct answers. The Epsteins suggest that IF-AT can be used in many ways. For example, they can be used for chapter tests; individual study (at home or in class); quizzes; pyramidal-sequential-process quizzing; exams; team-based and cooperative-learning; study-buddy learning; and most importantly as a feedback mechanism (see http://www.epsteineducation.com/home/about/uses.aspx website for further explanation). There are several metacognitive functions (although the Epstein’s do not couch their claims using this term) of the IF-AT. First, the Epstein’s argue that you can arrange your IF-AT so that the first question (and the immediate feedback of the correct answer) can be used in a pyramidal sequential process. That is, the correct answer to the first question is needed to answer subsequent questions as it is foundational knowledge for the remaining question. This sequential process allows the instructor and student to pin-point where the student’s knowledge of the integrated content broke down. This is implicit metacognitive modeling of a student’s metacognitive knowledge that should be made explicit. Meaning, by explaining to your students how the exam is set up, students can use cues and knowledge from previous questions and answers on the test to assist in their understanding of subsequent questions and answers. This is a key step to the learning process. Second, the IF-AT may also be used in a Team-Based way (i.e., distributed cognition) by forming groups, problem solving, and the team discovering what the correct answer is. IF-AT may also be used in dyads to allow students to discuss correct and incorrect answers. Students read a question, discuss the correct and incorrect answer, then cooperatively make a decision and receive immediate feedback. Third, IF-AT may be used to increase cognitive and metacognitive strategies. That is, by providing feedback immediately, students (if you explicitly instruct them to do so) may adjust their cognitive and metacognitive strategies for future study. For example, if a student used flashcards to study, and did poorly, they may want to adjust how they construct and use flashcards (e.g., distributed practice). Finally, and most importantly, IF-AT may improve student’s metacognitive regulation via calibration (i.e., the accuracy of knowing when you do and don’t know the answer to a question). That is, by providing immediate feedback, students may become more accurate in their judgments of knowing or even their feelings of knowing based on the feedback.

Is it Scratch to Win or is Scratch to Lose?
As described, by using the IF-AT, students get immediate feedback on whether they got the question correct, incorrect, and what is the appropriate answer. From a metacognitive perspective, this is outstanding. Students can calibrate (i.e., adjust their estimations and confidence in knowing an answer) in real-time, engage in distributed cognition, provide feedback on choice of cognitive and metacognitive strategies, can increase cognitive monitoring, and regulation control. These are all WIN, WIN, WIN, byproducts. HOWEVER, is there a down-side to instantaneously knowing you are wrong? That is, is there an emotional regulation and reactivity to IF-AT? As I have been implementing the use of the IF-AT, I have noticed (anecdotally) that about 1 in 10 students react negatively and it seems to increase their test anxiety. Presumably, the other 90% of the students love it and appreciate the feedback. Yet, what about the 10%? Does IF-AT stunt or hinder their performance? Again, my esteemed colleague Dr. Anna Ropp and I engaged in some scholarly discourse to answer this question, and Anna suggested that I make the first 3-5 questions on each IF-AT “soft-ball” questions. That is, questions that 75% of students will get correctly so that students’ fears and anxiety is remediated to some degree. Another alternative is to provide students with a copy of the test or exam and let them rank order or weight their answers (see Chris Was’ IwM Blog, 2014; on how to do this). Despite these two sound suggestions, there still may be an affective reaction that could be detrimental to student learning. To date, there has been no research to investigate this issue and there are only a hand full of well-designed studies to investigate IF-AT (e.g., Brosvic et al., 2006; Dihov et al., 2005; Epstein et al., 2002, 2003; Slepkov & Sheill, 2014). As such, more well-constructed and executed empirical research is needed to investigate this issue (Hint: all you scholars looking for a SoTL project…here’s your sign).

Concluding Thoughts and Questions for You
After investigating, reflecting on, and using IF-AT in my classroom, I think that it is a valuable assessment tool in your quiver of assessments to increase metacognition—but of course not an educational panacea. Furthermore, in my investigation of this assessment technique, (as usual), more questions popped up on the use of IF-AT. So, I will leave you with a charge and call to help me answer the questions below:

  1. Are there similar assessments that provide immediate feedback that you use? If so, are they less expensive or free?
  2. If you are using IF-AT, what is your favorite way to use it?
  3. Do you think IF-AT could cause substantial test anxiety? If so, to whom and to what level within your classes?
  4. How could you use IF-AT be used as a tool for calibration more efficiently? Or, what other ways do you think IF-AT can be used to increase metacognition?
  5. I think there are enormous opportunities for SoTL on IF-AT (e.g., the effects on calibration, distributed cognition, cognitive monitoring, conditional knowledge of strategy use, etc.), which means we all have some more work to do. J

References
Brosvic, G. M., Epstein, M. L., Dihoff, R. E., & Cook, M. J. (2006). Acquisition and retention of Esperanto: The case for error correction and immediate feedback. The Psychological Record, 56(2), 205.

Dihoff, R. E., Brosvic, G. M., Epstein, M. L., & Cook, M. J. (2005). Adjunctive role for immediate feedback in the acquisition and retention of mathematical fact series by elementary school students classified with mild mental retardation. The Psychological Record, 55(1), 39.

Epstein, M. L., Brosvic, G. M., Costner, K. L., Dihoff, R. E., & Lazarus, A. D. (2003). Effectiveness of feedback during the testing of preschool children, elementary school children, and adolescents with developmental delays. The Psychological Record, 53(2), 177.

Epstein, M. L., Lazarus, A. D., Calvano, T. B., & Matthews, K. A. (2002). Immediate feedback assessment technique promotes learning and corrects inaccurate first responses. The Psychological Record, 52(2), 187.

Slepkov, A. D., & Shiell, R. C. (2014). Comparison of integrated testlet and constructed-response question formats. Physical Review Special Topics-Physics Education Research, 10(2), 020120.

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


Using Metacognition to Make International Connections

by Lauren Scharff, PhD, U. S. Air Force Academy and John Draeger, PhD, SUNY Buffalo State

If you’re one of our longer-term followers, you’ll notice that this post is a bit different from others on our site. We just wrapped up a fantastic week in Melbourne, Australia working with six colleagues from around the globe, and we want to share some of our metacognition endeavors and reflections with you. This experience was part of the second International Collaborative Writing Groups  (ICWG) that is an affiliate effort for the International Society for the Scholarship of Teaching and Learning (ISSoTL).

Eight groups were part of the ICWG. The groups formed in May and met virtually over the summer to focus their topics and develop an outline prior to the face-to-face meeting this past week. Our group’s topic was The Student Learning Process, and we focused our efforts on how metacognition would support the transfer of learning from one situation or context to another. We believe the transfer of learning is one of the ultimate goals of education because it supports lifelong learning and employability.

The group’s work on how metacognition supports the transfer of learning will be revealed when it’s published, but meanwhile, we will share some ways that metacognition was part of our experience of facilitating the group. We’ll start with some pictures to set the tone. The first shows our group working: from left to right, Lauren, Susan Smith (Leeds Beckett University, UK), Lucie S Dvorakova (Honors Student, University of Queensland, Australia), Marion Tower (University of Queensland), Dominic Verpoorten (IFRES-University of Liège, Belgium), Marie Devlin (Newcastle University, UK), and Jason M. Lodge (University of Melbourne, Australia), [John Draeger taking the pic]. The second gives you a sense of the overall setting, showing multiple groups all kept to task by savvy ICWG coordinators, Mick Healy (University of Gloucestershire, retired) and Kelly Matthews (University of Queensland). Fortunately, Mick and Kelly also built in some social time for community building. The third picture shows our group at the Victoria State Library, left to right: Dominique, Sam, Marion, Sue, Marion, John, Lauren and Jason.

ICWG_SLP_Working

ICWG_mult_groups

ICWG_SLP_Social

How Metacognition Found Its Way into Our Facilitating Experiences

If you read the home page of this site, you’ll notice that we loosely define metacognition as the intertwined awareness and self-regulation of a process/skill, specifically with the goal of developing that process or skill. Although the site is focused on metacognition as it relates to teaching and learning, it can refer to any skill or process. Facilitating a group can be much like teaching, but it involves some additional processes that might more traditionally be linked to leadership and communication.

We noticed ourselves using metacognition in the following aspects of our work:

Use of Language: Given the international character of the group, self-monitoring and self-regulation allowed us to navigate differences in language and underlying assumptions. For example, through our discussions we learned that academic faculty might be referred to as ‘staff,’ ‘tutor,’ ‘instructor’ or ‘professor.’ Individual courses might be referred to as ‘classes,’ ‘modules’ or ‘units’ of study.

Assumptions about education: Our discussion revealed differences in the structures of the university systems in different countries. When discussing how students might use their learning in one course to inform their learning in another, the two North Americans on the team (John and Lauren) tended to think about transfer learning between a diverse set of courses across a broad liberal arts core curriculum in addition to transfer across more closely related courses within a major. Because undergraduate education in Australia and the United Kingdom tend not to be structured around a broad core curriculum, members of the team from these countries tended to focus on transfer learning within a particular field of study.

As we drafted our text and created a survey that was to be used in four different countries, we each engaged in self-monitoring of the terms as the conversation was in progress and would regulate behavior accordingly. For example, someone would start by saying “I think that staff might…” but then quickly add “or perhaps you might say ‘professors.’” Similarly, we would use our newly developed awareness of the different educational structures to guide our discussion about how transfer of learning might be supported across all of our learning environments.

Management of Project Scope: Both transfer of learning and metacognition are vast areas of study. Given the wide variety of experiences and individual interests in our group, we explored a wide array of possible directions for our paper, some of which we decided we would table for follow-on papers (e.g. how student level of intellectual development might impact transfer of learning and the creation of a “toolkit” for instructors that would help them support transfer of learning). Moving the conversation in fruitful directions required that all of us remain mindful of the task at hand (i.e. working towards a 6000-word article). Self-monitoring allowed us to detect when an interesting discussion had gone beyond the scope of our current article and self-regulation more quickly brought us back to the task at hand.

In summary, the international character of the writing group added a depth and richness to the conversation, but it also increased the likelihood of misunderstanding and the challenge of group management. Self-monitoring and self-regulation allowed us to overcome those challenges.

Many thanks to our group members for a fantastic face-to-face experience, and we look forward to our continued exchanges as we finalize the paper and carry on with the follow-on papers.


Metacognition in Psychomotor Development and Positive Error Cultures

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

All of us experience the “tip of the tongue” phenomenon. This state occurs when we truly do know something, such as the name of a person, but we cannot remember the person’s name at a given moment. The feeling that we do know is a form of metacognitive awareness that confirms the existence of a real neural network appropriate to the challenge. It is also an accurate knowing that carries confidence that we can indeed retrieve the name given the right memory trigger.

In “thinking about thinking” some awareness of the connection between our psychomotor domain and our efforts to learn can be useful. The next time you encounter a tip-of-the-tongue moment, try clenching your left hand. Ruth Propper and colleagues confirmed that left hand clenching activates the right hemisphere of the brain and can enhance recall. When learning names, clenching of the right hand activates the left hemisphere and can enhance encoding (http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0062474). Not all connections between the psychomotor domain and intellectual development are this direct, but it is very useful to connect efforts to develop intellectually with established ways that promote psychomotor development.

Young people are active, so many things that excite them to initiate their learning have a heavy emphasis on psychomotor development. Examples are surfing, snowboarding, dance, tennis, martial arts, yoga, or a team sport. We can also include the hand-eye coordination and learning patterns involved in many addictive video games as heavy on kinesthetic learning, even though these do not offer health benefits of endurance, strength, flexibility, balance, etc. It is rare that anyone who commits to learning any of these fails to achieve measurably increased proficiency.

K-12 teacher Larry Ferlazzo uses the act of missing a wastebasket with a paper wad to help students understand how to value error and use it to inform strategies for intellectual development (http://larryferlazzo.edublogs.org/2011/10/31/an-effective-five-minute-lesson-on-metacognition). His students begin to recognize how the transfer of practices that they already accept as valid from their experiences may likely improve their mastery in less familiar challenges during intellectual development.

College teachers also know that the most powerful paths to high-level thinking engage the psychomotor domain. Visualization that involves explaining to self by diagram and developing images of the knowledge engages psychomotor skills. Likewise, writing engages the psychomotor in developing text, tracking and explaining reasoning and in revising the work (Nuhfer, 2009, 2010 a, b).

Students already “get” that many trips down the ski trail are needed to master snowboarding; they may not “get” that writing many evaluative argument papers is necessary to master critical thinking. In the former, they learn from their most serious error and focus on correcting it first. They correctly surmise that the focused effort to correct one troublesome issue will be beneficial. In efforts to develop intellectually, students deprived of metacognitive training may not be able to recognize or prioritize their most serious errors. This state deprives them of awareness needed to do better on subsequent challenges.

It is important for educators to recognize how particular cultures engage with error. Author and neuroscientist Gerd Gigerenzer, Director of the Max Planck Institute for Human Development and  the Harding Center for Risk Literacy (2014) contrasts positive and negative error cultures. A positive error culture promotes recognition and understanding of error. They discuss error openly, and sharing of experienced error is valued as a way to learn. This culture nurtures a growth mindset in which participants speak metacognitively to self in terms of: “Not yet… change this …better next time.” Gigerenzer cites aviation as a positive error culture of learning that has managed to reduce plane crashes to one in ten million flights. Interestingly, the cultures of surfing, snowboarding, dance, tennis, martial arts and yoga all promote development through positive error cultures. Positive error cultures make development through practice productive and emotionally safe.

Gigerenzer cites the American system of medical practice as one example of a negative error culture, wherein systems of reporting, discussing and learning from serious errors are nearly nonexistent. Contrast aviation safety with the World Heath Organization report that technologically advanced hospitals harm about 10% of their patients. James (2013) deduced that hospital error likely causes over 400,000 deaths annually (http://journals.lww.com/journalpatientsafety/Fulltext/2013/09000/A_New,_Evidence_based_Estimate_of_Patient_Harms.2.aspx). Negative error cultures make it unsafe to discuss or to admit to error and therefore, they are ineffective learning organizations. In negative error cultures, error discovery results in punishment. Negative error cultures nurture fear and humiliation and thereby make learning unsafe. Error there delivers the metacognitive declaration, “I failed.”

We should think in what ways our actions in higher education support positive or negative error cultures and what kinds of metacognitive conversations we nurture in participants (colleagues, students) of the culture. We can often improve intellectual development through understanding how the positive error cultures promote psychomotor development.

 

References

Gigerenzer, G. (2014) Risk Savvy: How to Make Good Decisions. New York New York: Penguin.

Nuhfer, E.B. (2009) “A Fractal Thinker Designs Deep Learning Exercises: Learning through Languaging. Educating in Fractal Patterns XXVIII, Part 2.” The National Teaching & Learning Forum, Vol. 19, No. 1, pp. 8-11.

Nuhfer, E.B. (2010a) “A Fractal Thinker Designs Deep Learning Exercises: Acts of Writing as “Gully Washers”- Educating in Fractal Patterns XXVIII, Part 3.” The National Teaching & Learning Forum, Vol. 19, No. 3, pp. 8-11.

Nuhfer, E.B. (2010b) “A Fractal Thinker Designs Deep Learning Exercises: Metacognitive Reflection with a Rubric Wrap Up – Educating in Fractal Patterns XXVIII, Part 4.” The National Teaching & Learning Forum, Vol. 19, No. 4, pp. 8-11.


To Test or Not to Test: That is the Metacognitive Question

by John Schumacher & Roman Taraban at Texas Tech University

In prepping for upcoming classes, we are typically interested in how to best structure the class to promote the most effective learning. Applying best-practices recommendations in the literature, we try to implement active learning strategies that go beyond simple lecturing. One such strategy that has been found to be effective from research is the use of testing. The inference to draw from the research literature is quite simple: test students frequently, informally, and creatively, over and above standard course tests, like a mid-term and final. Testing is a useful assessment tool, but research has shown that it is also a learning tool that has been found to promote learning above and beyond simply rereading material (Roediger & Karpicke, 2006a). This is called the testing effect. In controlled studies, researchers have shown testing effects with a variety of materials, including expository texts and multimedia presentations (e.g., Carrier & Pashler, 1992; Huff, Davis, & Meade, 2013; Johnson & Mayer, 2009; Roediger & Karpicke, 2006b). Testing has been found to increase learning when implemented in a classroom setting (McDaniel, Anderson, Derbish, & Morrisette, 2007) and is a useful learning tool for people of all ages (Meyer & Logan, 2013). The theoretical explanation for the benefits of testing is that testing strengthens retrieval paths to the stored information in memory more so than simply rereading the material. Therefore, later on a person can more effectively recover the information from memory.

Although implementing testing and other active learning strategies in the classroom is useful in guiding and scaffolding student learning, it is important that we develop an understanding of when and for whom these strategies are most helpful. Specifically, regarding testing, research from our lab and in others is starting to show that testing may not always be as beneficial as past research suggests. Characteristics of the students themselves may nullify or even reverse the benefits of testing. Thus, the first question we address is whether frequent classroom testing will benefit all students. Yet a more pertinent question, which is our second question, is whether frequent testing develops metacognitive practices in students. We will discuss these in turn.

In a formal study of the testing effect, or in an informal test in any classroom, one needs two conditions, a control condition in which participants study the material on their own for a fixed amount of time, and an experimental condition in which participants study and are tested over the material, for instance, in a Study-Test-Study-Test format. Both groups spend an equal amount of time either simply studying or studying and testing. All participants take a final recall test over the material. Through a series of testing-effect studies incorporating expository texts as the learning material, we have produced a consistent grade-point average (GPA) by testing-effect interaction. This means that the benefits of testing (i.e., better later retrieval of information) depend on students’ GPAs! A closer look at this interaction showed us that students with low GPAs benefited most from the implementation of testing whereas mid to high GPA students benefited just as much by simply studying the material.

While at this preliminary stage it is difficult to ascertain why exactly low GPA students benefit from testing in our experiments while others do not, a few observations can be put forth. First, at the end of the experiments, we asked participants to report any strategies they used on their own to help them learn the materials. Metacognitive reading strategies that the participants reported included focusing on specific aspects of the material, segmenting the material into chunks, elaborating on the material, and testing themselves. Second, looking further into the students’ self-reports of metacognitive strategy use, we found that participants in the medium to high GPA range used these strategies often, while low GPA students used them less often. Simply, the self-regulated use of metacognitive strategies was associated with higher GPAs and better recall of the information in the texts that the participants studied. Lower GPA students benefited when the instructor deliberately imposed self-testing.

These results are interesting because they indicate that the classroom implementation of testing may only be beneficial to low achieving students because they either do not have metacognitive strategies at their disposal or are not applying these strategies. High-achieving students may have metacognitive strategies at their disposal and may not need that extra guidance set in place by the instructor.

Another explanation for the GPA and testing-effect interaction may simply be motivation. Researchers have found that GPA correlates with motivation (Mitchell, 1992). It is possible that implementing a learning strategy may be beneficial to low GPA students because it forces them to work with the material. Motivation may also explain why GPA correlated with metacognitive strategy use. Specifically if lower GPA students are less motivated to work with the material it stands to reason that they would be less likely to employ learning strategies that take time and effort.

This leads to our second question: Does frequent testing develop metacognitive skills in students, particularly self-regulated self-testing? This is a puzzle that we cannot answer from the current studies. Higher-GPA students appear to understand the benefits of applying metacognitive strategies and do not appear to need additional coaxing from the experimenter/teacher to apply them. Will imposing self-testing, or any other strategy on lower-GPA students lead them to eventually adopt the use of these strategies on their own? This is an important question and one that deserves future attention.

While testing may be useful for bolstering learning, we suggest that it should not be blindly utilized in the classroom as a learning tool. A consideration of what is being taught and to whom will dictate the effectiveness of testing as a learning tool. As we have suggested, more research also needs to be done to figure out how to bring metacognitive strategies into students’ study behaviors, particularly low-GPA students.

References

Carrier, M., & Pashler, H. (1992). The influence of retrieval on retention. Memory & Cognition,   20(6), 633-642.

Huff, M. J., Davis, S. D., & Meade, M. L. (2013). The effects of initial testing on false recall and             false recognition in the social contagion of memory paradigm. Memory & Cognition, 41(6), 820-831.

Johnson, C. I., & Mayer, R. E. (2009). A testing effect with multimedia learning. Journal of          Educational Psychology, 101(3), 621-629.

McDaniel, M. A., Anderson, J. L., Derbish, M. H., & Morrisette, N. (2007). Testing the testing effect in the classroom. European Journal of Cognitive Psychology, 19(4-5), 494-513.

Meyer, A. D., & Logan, J. M. (2013). Taking the testing effect beyond the college freshman:        Benefits for lifelong learning. Psychology and Aging, 28(1), 142-147.

Mitchell Jr, J. V. (1992). Interrelationships and predictive efficacy for indices of intrinsic,                         extrinsic, and self-assessed motivation for learning. Journal of Research and       Development in Education, 25(3), 149-155.

Roediger, H., & Karpicke, J. D. (2006a). The power of testing memory: Basic research and           implications for educational practice. Perspectives on Psychological Science, 1(3), 181-       210.

Roediger, H., & Karpicke, J. D. (2006b). Test-enhanced learning: Taking memory tests     improves long-term retention. Psychological Science, 17(3), 249-255.


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.


Metacognition, Self-Regulation, and Trust

by  Dr. Steven Fleisher, CSU Channel Islands, Department of Psychology

Early Foundations

I’ve been thinking lately about my journey through doctoral work, which began with studies in Educational Psychology. I was fortunate to be selected by my Dean, Robert Calfee, Graduate School of Education at University of California Riverside, to administer his national and state grants in standards, assessment, and science and technology education. It was there that I began researching self-regulated learning.

Self-Regulated Learning

Just before starting that work, I had completed a Masters Degree in Marriage and Family Counseling, so I was thrilled to discover the relevance of the self-regulation literature. For example, I found it interesting that self-regulation studies began back in the 1960s examining the development of self-control in children. Back then the framework that evolved for self-regulation involved the interaction of personal, behavioral, and environmental factors. Later research in self-regulation focused on motivation, health, mental health, physical skills, career development, decision-making, and, most notable for our purposes, academic performance and success (Zimmerman, 1990), and became known as self-regulated learning.

Since the mid-1980s, self-regulated learning researchers have studied the question: How do students progress toward mastery of their own learning? Pintrich (2000) noted that self-regulated learning involved “an active, constructive process whereby learners set goals for their learning and then attempt to monitor, regulate, and control their cognition, motivation, and behavior, guided and constrained by their goals and the contextual features in the environment” (p. 453). Zimmerman (2001) then established that, “Students are self-regulated to the degree that they are metacognitively, motivationally, and behaviorally active participants in their own learning process” (p. 5). Thus, self-regulated learning theorists believe that learning requires students to become proactive and self-engaged in their learning, and that learning does not happen to them, but by them (see also Leamnson, 1999).

Next Steps

And then everything changed for me. My Dean invited Dr. Bruce Alberts, then President of the National Academy of Sciences, to come to our campus and lecture on science and technology education. Naturally, as Calfee’s Graduate Student Researcher, I asked “Bruce” what he recommended for bringing my research in self-regulated learning to the forefront. His recommendation was to study the, then understudied, role and importance of the teacher-student relationship. Though it required changing doctoral programs to accommodate this recommendation, I did it, adding a Doctorate in Clinical Psychology to several years of coursework in Educational Psychology.

Teacher-Student Relationships 

Well, enough about me. It turns out that effective teacher-student relationships provide the foundation from which trust and autonomy develop (I am skipping a lengthy discussion of the psychological principles involved). Suffice it to say, where clear structures are in place (i.e., standards) as well as support, social connections, and the space for trust to develop, students have increased opportunities for exploring how their studies are personally meaningful and supportive of their autonomy, thereby taking charge of their learning.

Additionally, when we examine a continuum of extrinsic to intrinsic motivation, we find the same principles involved as with a scale showing minimum to maximum autonomy, bringing us back to self-regulated learning. Pintrich (2000) included the role of motivation in his foundations for self-regulated learning. Specifically, he reported that a goal orientation toward performance arises when students are motivated extrinsically (i.e., focused on ability as compared to others); however, a goal orientation toward mastery occurs when students are motivated more intrinsically (i.e., focused on effort and learning that is meaningful to them).

The above concepts can help us define our roles as teachers. For instance, we are doing our jobs well when we choose and enact instructional strategies that not only communicate clearly our structures and standards but also provide needed instructional support. I know that when I use knowledge surveys, for example, in building a course and for disclosing to my students the direction and depth of our academic journey together, and support them in taking meaningful ownership of the material, I’m helping their development of metacognitive skill and autonomous self-regulated learning. We teachers can help improve our students’ experience of learning. For them, learning in order to get the grades pales in comparison to learning a subject that engages their curiosity, along with investigative and social skills that will last a lifetime.

References

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

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.

Zimmerman, B. J. (1990). Self-regulating academic learning and achievement: The emergence of a social cognitive perspective. Educational Psychology Review, 2(2), 173-201.

Zimmerman, B. J. (2001). Theories of self-regulated learning and academic achievement: An overview and analysis. In B. J. Zimmerman & D. H. Schunk (Eds.) Self-regulated learning and academic achievement: Theoretical perspectives (2e). New York: Lawrence Erlbaum.


A Mindfulness Perspective on Metacognition

by Chris Was, Kent State University

If you have any interest in metacognition, you have likely come across the description of metacognition as thinking about one’s thinking. A number of posts to this blog (including my own) provide evidence to support the conclusion that metacognition can be “learned” and improved. Further, improved metacognition leads to improve self-regulation and positive academic outcomes. There is also a good deal of evidence that training in mindfulness improves cognitive function and attention (e.g., Chambers, Lo, & Allen, 2008). Flook, et al (2010) found that mindfulness-training program improved executive functions in young elementary school students. Zeidan, et al (2010) found that mindfulness training improved executive function and metacognitive insight. This post will focus on the relationship between metacognition and mindfulness.

Let me preface by stating that mindfulness need not refer to esoteric religious beliefs, but it is often defined as a mental state achieved by focusing one’s awareness on the present moment and acknowledging one’s feelings, thoughts and bodily sensations. Kabat-Zinn (1990) describes mindfulness as bringing attention to moment-to-moment experience. In my own work on metacognitive knowledge monitoring, I have required students to make moment-to-moment (more accurately, item-by-item) judgments of their knowledge.. Hypotheses, such as cue-familiarity, provide reasonable explanations for how students and research participants rate feelings of knowing (FOK), judgments of learning (JOLs), judgments of knowing (JOK), etc. However, the simple fact is one must attend to these feelings and thoughts to provide a judgment. In psychological and educational literature, we refer to one using metacognition to make these judgments. Clinical psychology programs such as mindfulness based stress reduction (MBSR) and cognitive behavior therapy (CBT) refer to the patient/participant as being mindful about their emotions, thoughts, and actions. Although the majority of research and application of mindfulness has occurred in clinical settings, there is a great deal of potential in examining the relationship between mindfulness and metacognition.

It isn’t clear how metacognition and mindfulness are related. Some argue that metacognition is not mindful because a true expert in mindfulness does not need to reflect upon his or her thinking, but only to attend to what they are presently doing. I am not convinced. Much of the work on metacognitive improvement has focused on semester long training to improve students knowledge monitoring. The mindfulness research has focused on training students to focus on their moment-to-moment experiences and thoughts. Clearly, there is a relationship between metacognition and executive function, but I have yet to see evidence that training in one improves the other.

One argument made to dissociate mindfulness from metacognition is that metacognitive processes are by necessity reflective or retrospective and that truly being mindful does not require reflection. For example, for a student to practice metacognition during study, she must ask herself, “Do I understand this concept?” Then, depending on the answer the student may or may not adjust the cognitive actions in which she is engaged to learn. This cycle is simply explained by the Nelson and Narens (1990). Now let’s think about a practitioner of mindfulness meditation. While meditating he may chose to focus his attention on the breath. Noticing when he is breathing in and noticing when he is breathing out. During this practice his mind may wander (this is true of even the most practiced at meditation). When this happens, he will gently bring his attention back to the breath. This process, just like that of the studying student, requires one to observe the cognitive processes and exert control over those processes when necessary. This to fits nicely into the metacognitive model offered by Nelson and Narens.

Imagine you are reading a novel on summer vacation. The book is enjoyable, but not a challenging read. Your are enjoying the sun and the sounds on the beach as you read, but suddenly notice you have not really attended to the last couple of pages and are not sure what has transpired in the plot. You choose to reread the last couple of pages and pay more attention. Imagine now you are a student. You are reading a very dull textbook chapter with the TV on and your smart phone near by. A student with little metacognitive resources (whether it be due working memory capacity, attentional control, executive function, etc.) is likely to mind wander (Hollis & Was, 2014). Students in my classes have often told me the hardest part of studying is staying focused, even when the topic is of interest. Ben Hollis and I found that students watching a video as part of an online course were often distracted by thoughts of checking the social media outlets. Not distracted by checking, but just thought of checking them. What if students were practiced at focusing attention, noticing when their minds wander and bringing the attention back to the task at hand?

It seems to me that if metacognition is knowledge and control of one’s cognitive processes and training in mindfulness increases one’s ability to focus and control awareness in a moment-by-moment manner, then perhaps we should reconsider, and investigate the relationship between mindfulness and metacognition in education and learning.

 

References

Bishop, S. R., Lau, M., Shapiro, S., Carlson, L., Anderson, N. D., Carmody, J., Segal, Z. V.,    Abbey, S., Speca, M., Velting, D. and Devins, G. (2004), Mindfulness: A Proposed Operational Definition. Clinical Psychology: Science and Practice,     11: 230–241. doi: 10.1093/clipsy.bph077

Chambers, R., Lo, B. C. Y., & Allen, N. B. (2008). The impact of intensive mindfulness training on attentional control, cognitive style, and affect. Cognitive Therapy and Research, 32(3), 303-322.

Flavell, J. H. (1979). Metacognition and cognitive monitoring: A new area of cognitive–developmental inquiry. American psychologist, 34(10), 906.

Flook, L., Smalley, S. L., Kitil, M. J., Galla, B. M., Kaiser-Greenland, S., Locke, J., … &  Kasari, C. (2010). Effects of mindful awareness practices on executive functions in elementary school children. Journal of Applied School         Psychology,26(1), 70-95.

Kabat-Zinn, J. (1990). Full catastrophe living: Using the wisdom of your mind to face    stress, pain and illness. New York : Dell.

Zeidan, F., Johnson, S. K., Diamond, B. J., David, Z., & Goolkasian, P. (2010).  Mindfulness meditation improves cognition: evidence of brief mental training.Consciousness and cognition, 19(2), 597-605.


Promoting general metacognitive awareness

This informative article by Gregory Schraw begins with a distinction between knowledge of cognition and regulation of cognition (lots of great references included), continues with a a discussion of generalization and a summary of some additional research that examines the relationship between metacognition and expertise (cognitive abilities), and finishes with several strategies that instructors can use to develop both metacognitive awareness and regulation.

http://wiki.biologyscholars.org/@api/deki/files/87/=schraw1998-meta.pdf