Month: February 2015

Who says Metacognition isn’t Sexy?

By Michael J. Serra at Texas Tech University

This past Sunday, you might have watched “The 87th Academy Awards” (i.e., “The Oscars”) on television. Amongst the nominees for the major awards were several films based on true events and real-life people, including two films depicting key events in the lives of scientists Stephen Hawking (The Theory of Everything) and Alan Turing (The Imitation Game).

There are few things in life that I am sure of, but one thing I can personally guarantee is this: No film studio will ever make a motion picture about the life of your favorite metacognition researcher. Believe it or not, the newest issue of Entertainment Weekly does not feature leaked script details about an upcoming film chronicling how J. T. Hart came up with the idea to study people’s feelings of knowing (Hart, 1967), and British actors are not lining up to depict John Flavell laying down the foundational components for future theory and research on metacognition (Flavell, 1979). Much to my personal dismay, David Fincher hasn’t returned my calls regarding the screenplay I wrote about that time Thomas Nelson examined people’s judgments of learning at extreme altitudes on Mt. Everest (Nelson et al., 1990).

Just as film studios seem to lack interest in portraying metacognition research on the big screen, our own students sometimes seem uninterested in anything we might tell them about metacognition. Even the promise of improving their grades sometimes doesn’t seem to interest them! Why not?

One possibility, as I recently found out from a recent blog post by organic-chemistry professor and tutor “O-Chem Prof”, is that the term “metacognition” might simply not be sexy to our students (O-Chem Prof, 2015). He suggests that we instead refer to the concept as “sexing up your noodle”.

Although the idea of changing the name of my graduate course on the topic to “PSY 6969: Graduate Seminar in Sexing-up your Noodle” is highly tempting, I do not think that the problem is completely one of branding or advertising. Rather, regardless of what we call metacognition (or whether or not we even put a specific label on it for our students), there are other factors that we know play a crucial role in whether or not students will actually engage in self-regulated learning behaviors such as the metacognitive monitoring and control of their learning. Specifically, Pintrich and De Groot (1990; see Miltiadou & Savenye, 2003 for a review) identified three major factors that determine students’ motivation to learn that I suggest will also predict their willingness to engage in metacognition: value, expectancy, and affect.

The value component predicts that students will be more interested and motivated to learn about topics that they see value in learning. If they are struggling to learn a valued topic, they should be motivated to engage in metacognition to help improve their learning about it. A wealth of research demonstrates that students’ values and interest predict their motivation, learning, and self-regulation behaviors (e.g., Pintrich & De Groot, 1990; Pintrich et al., 1994; Wolters & Pintrich, 1998; for a review, see Schiefele, 1991). Therefore, when students do not seem to care about engaging in metacognition to improve their learning, it might not be that metacognition is not “sexy” to them; it might be that the topic itself (e.g., organic chemistry) is not sexy to them (sorry, O-Chem Prof!).

The expectancy component predicts that students will be more motivated to engage in self-regulated learning behaviors (e.g., metacognitive control) if they believe that their efforts will have positive outcomes (and won’t be motivated to do so if they believe their efforts will not have an effect). Some students (entity theorists) believe that they cannot change their intelligence through studying or practice, whereas other students (incremental theorists) believe that they can improve their intelligence (Dweck et al., 1995; see also Wolters & Pintrich, 1998). Further, entity theorists tend to rely on extrinsic motivation and to set performance-based goals, whereas incremental theorists tend to rely on intrinsic motivation and to set mastery-based goals. Compared to entity theorists, students who are incremental theorists earn higher grades and are more likely to persevere in the face of failure or underperformance (Duckworth & Eskreis-Winkler, 2013; Dweck & Leggett, 1988; Romero et al., 2014; see also Pintrich, 1999; Sungur, 2007). Fortunately, interventions have been successful at changing students to an incremental mindset, which in turn improves their learning outcomes (Aronson et al., 2002; Blackwell et al., 2007; Good et al., 2003; Hong et al., 1999).

The affective component predicts that students will be hampered by negative thoughts about learning or anxiety about exams (e.g., stereotype threat; test anxiety). Unfortunately, past research indicates that students who experience test anxiety will struggle to regulate their learning and ultimately end up performing poorly despite their efforts to study or to improve their learning (e.g., Bandura, 1986; Pintrich & De Groot, 1990; Pintrich & Schunk, 1996; Wolters & Pintrich, 1998). These students in particular might benefit from instruction on self-regulation or metacognition, as they seem to be motivated and interested to learn the topic at hand, but are too focused on their eventual test performance to study efficiently. At least some of this issue might be improved if students adopt a mastery mindset over a performance mindset, as increased learning (rather than high grades) becomes the ultimate goal. Further, adopting an incremental mindset over an entity mindset should reduce the influence of beliefs about lack of raw ability to learn a given topic.

In summary, although I acknowledge that metacognition might not be particularly “sexy” to our students, I do not think that is the reason our students often seem uninterested in engaging in metacognition to help them understand the topics in our courses or to perform better on our exams. If we want our students to care about their learning in our courses, we need to make sure that they feel the topic is important (i.e., that the topic itself is sexy), we need to provide them with effective self-regulation strategies or opportunities (e.g., elaborative interrogation, self-explanation, or interleaved practice questions; see Dunlosky et al., 2013) and help them feel confident enough to employ them, we need to work to reduce test anxiety at the individual and group/situation level, and we need to convince our students to adopt a mastery (incremental) mindset about learning. Then, perhaps, our students will find metacognition to be just as sexy as we think it is.

ryan gosling metacog (2)

References

Aronson, J., Fried, C. B., & Good, C. (2002). Reducing the effects of stereotype threat on African American college students by shaping theories of intelligence. Journal of Experimental Social Psychology, 38, 113-125. doi:10.1006/jesp.2001.1491

Bandura, A. (1986). Social foundations of thought and action: A social cognitive theory. Englewood Cliffs, NJ: Prentice-Hall.

Blackwell, L. S., Trzesniewski, K. H., & Dweck, C. S. (2007). Implicit theories of intelligence predict achievement across an adolescent transition: A longitudinal study and an intervention. Child Development, 78, 246-263. doi: 10.1111/j.1467-8624.2007.00995.x

Duckworth, A., & Eskreis-Winkler, L. (2013). True Grit. Observer, 26. http://www.psychologicalscience.org/index.php/publications/observer/2013/april-13/true-grit.html

Dunlosky, J., Rawson, K. A., Marsh, E. J., Nathan, M. J., & Willingham, D. T. (2013). Improving students’ learning with effective learning techniques promising directions from cognitive and educational psychology. Psychological Science in the Public Interest, 14, 4-58. doi: 10.1177/1529100612453266

Dweck, C. S., Chiu, C. Y., & Hong, Y. Y. (1995). Implicit theories and their role in judgments and reactions: A world from two perspectives. Psychological Inquiry, 6, 267-285. doi: 10.1207/s15327965pli0604_1

Dweck, C. S., & Leggett, E. L. (1988). A social-cognitive approach to motivation and personality. Psychological Review, 95, 256-273. doi: 10.1037/0033-295X.95.2.256

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

Good, C., Aronson, J., & Inzlicht, M. (2003). Improving adolescents’ standardized test performance: An intervention to reduce the effect of stereotype threat. Applied Developmental Psychology, 24, 645-662. doi: 10.1016/j.appdev.2003.09.002

Hart, J. T. (1967). Memory and the memory-monitoring process. Journal of Verbal Learning and Verbal Behavior, 6, 685-691. doi: 10.1016/S0022-5371(67)80072-0

Hong, Y., Chiu, C., Dweck, C. S., Lin, D., & Wan, W. (1999). Implicit theories, attributions, and coping: A meaning system approach. Journal of Personality and Social Psychology, 77, 588-599. doi: 10.1037/0022-3514.77.3.588

Miltiadou, M., & Savenye, W. C. (2003). Applying social cognitive constructs of motivation to enhance student success in online distance education. AACE Journal, 11, 78-95. http://www.editlib.org/p/17795/

Nelson, T. O., Dunlosky, J., White, D. M., Steinberg, J., Townes, B. D., & Anderson, D. (1990). Cognition and metacognition at extreme altitudes on Mount Everest. Journal of Experimental Psychology: General, 119, 367-374.

O-Chem Prof. (2015, Jan 7). Our Problem with Metacognition is Not Enough Sex. [Web log]. Retrieved from http://phd-organic-chemistry-tutor.com/our-problem-with-metacognition-not-enough-sex/

Pintrich, P. R. (1999). The role of motivation in promoting and sustaining self-regulated learning. International Journal of Educational Research, 31, 459-470. doi: 10.1016/S0883-0355(99)00015-4

Pintrich, P. R., & De Groot, E. V. (1990). Motivational and self-regulated learning components of classroom academic performance. Journal of Educational Psychology, 82, 33-40. doi: 10.1037/0022-0663.82.1.33

Pintrich, P. R., Roeser, R., & De Groot, E. V. (1994). Classroom and individual differences in early adolescents’ motivation and self-regulated learning. Journal of Early Adolescence, 14, 139-161. doi: 10.1177/027243169401400204

Pintrich, P. R., & Schunk D. H. (1996). Motivation in education: Theory, research, and applications. Englewood Cliffs, NJ: Merrill/Prentice Hall.

Romero, C., Master, A., Paunesku, D., Dweck, C. S., & Gross, J. J. (2014). Academic and emotional functioning in middle school: The role of implicit theories. Emotion, 14, 227-234. doi: 10.1037/a0035490

Schiefele, U. (1991). Interest, learning, and motivation. Educational Psychologist, 26, 299-323. doi: 10.1080/00461520.1991.9653136

Sungur, S. (2007). Modeling the relationships among students’ motivational beliefs, metacognitive strategy use, and effort regulation. Scandinavian Journal of Educational Research, 51, 315-326. doi: 10.1080/00313830701356166

Wolters, C. A., & Pintrich, P. R. (1998). Contextual differences in student motivation and self-regulated learning in mathematics, English, and social studies classrooms. Instructional Science, 26, 27-47. doi: 10.1023/A:1003035929216


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


Goal Monitoring in the Classroom

by Tara Beziat at Auburn University at Montgomery 

What are your goals for this semester? Have you written down your goals? Do you think your students have thought about their goals and written them down? Though these seem like simple tasks, we often do not ask our students to think about their goals for our class or for the semester. Yet, we know that a key to learning is planning, monitoring and evaluating one’s learning (Efklides, 2011; Nelson, 1996; Schraw and Dennison, 1994; Nelson & Narens, 1994). By helping our students engage in these metacognitive tasks, we are teaching them how to learn.

Over the past couple of semesters, I have asked my undergraduate educational psychology students to complete a goal-monitoring sheet so they can practice, planning, monitoring and evaluating their learning. Before we go over the goal-monitoring sheet, I explain the learning process and how a goal-monitoring sheet helps facilitate learning. We discuss how successful students set goals for their learning, monitor these goals and make necessary adjustments through the course of the semester (Schunk, 1990). Many first-generation students and first-time freshman come to college lacking self-efficacy in academics and one set back can make them feel like college is not for them (Hellman, 1996). As educators we need to help them understand we all make mistakes and sometimes fail, but we need to make adjustments based on those failures not quit.

Second, I talk with my class about working memory, long-term memory, and how people access information in one of two ways: verbally or visually (Baddeley, 2000, 2007). Seeing and/or hearing the information does not make learning happen. As a student, they must take an active role and practice retrieving the information (Karpicke & Roediger, 2008; Roediger & Butler, 2011). Learning takes work. It is not a passive process. Finally, we discuss the need to gauge their progress and reflect on what is working and what is not working. On the sheet I reiterate what we have discussed with the following graphic:

LearningGoalsCycleTaraBeziat

After this brief introduction about learning, we talk about the goal-monitoring sheet, which is divided into four sections: Planning for Success, Monitoring your Progress, Continued Monitoring and Early Evaluation and Evaluating your Learning. Two resources that I used to make adjustments to the initial sheet were the questions in Tanner’s (2012) article on metacognition in the classroom and the work of Gabrielle Oettingen (2014). Oettigen points out that students need to consider possible obstacles to their learning and evaluate how they would handle them. Students can use the free WOOP (Wish, Outcome, Obstacle, Plan) app to “get through college.”

Using these resources and the feedback from previous students, I created a new goal-monitoring sheet. Below are the initial questions I ask students (for the full Goal Monitoring Sheet see the link at the bottom):

  • What are your goals for this class?
  • How will you monitor your progress?
  • What strategies will you use to study and prepare for this class?
  • When can you study/prepare for this class?
  • Possible obstacles or areas of concern are:
  • What resources can you use to achieve your goals?
  • What do you want to be able to do by the end of this course?

Interestingly, many students do not list me, the professor as a resource. I make sure to let the students know that I am available and should be considered a resource for the course. As students, move through the semester they submit their goal-monitoring sheets. This continuing process helps me provide extra help but also guide them toward necessary resources. It is impressive to see the students’ growth as they reflect on their goals. Below are some examples of student responses.

  • “I could use the book’s website more.”
  • “One obstacle for me is always time management. I am constantly trying to improve it.”
  • “I will monitor my progress by seeing if I do better on the post test on blackboard than the pre test. This will mean that I have learned the material that I need to know.”
  • “Well, I have created a calendar since the beginning of class and it has really helped me with keeping up with my assignments.”
  • “I feel that I am accomplishing my goals because I am understanding the materials and I feel that I could successfully apply the material in my own classroom.”
  • “I know these [Types of assessment, motivation, and the differences between valid and reliable, and behaviorism] because I recalled them multiple times from my memory.

Pressley and his colleagues (Pressely, 1983; Pressely & Harris, 2006; Pressely & Hilden, 2006) emphasize the need for instructors, at all levels, to help students build their repertoire of strategies for learning. By the end of the course, many students feel they now have strategies for learning in any setting. Below are a few excerpts from students’ final submission on their goal monitoring sheets:

  • “The most unusual thing about this class has been learning about learning. I am constantly thinking of how I am in these situations that we are studying.”
  • “…we were taught new ways to take in work, and new strategies for studying and learning. I feel like these new tips were very useful as I achieved new things this semester.
Goal Monitoring in the Classroom: Have your students have thought about their goals for your course and written them down? Share on X

References

Efklides, A. (2011). Interactions of metacognition with motivation and affect in self-regulated learning: The MASRL model. Educational Psychologist, 46(1), 6-25.

Hellman, C. (1996). Academic self-efficacy: Highlighting the first generation student. Journal of Applied Research in the Community College, 3, 69–75.

Karpicke, J. D., & Roediger, H. L. (2008). The critical importance of retrieval for learning. science, 319(5865), 966-968.

Nelson, T. O. (1996). Consciousness and metacognition. American Psychologist, 51(2), 102-116. doi:10.1037/0003-066X.51.2.102

Nelson, T. O., & Narens, L. ( 1994). Why investigate metacognition?. In J.Metcalfe & A.Shimamura ( Eds.), Metacognition: Knowing about knowing (pp. 1– 25). Cambridge, MA: Bradford Books.

Oettingen, G. (2014). Rethinking Positive Thinking: Inside the New Science of Motivation. New York, NY: Penguin Group.

Pressely, M. (1983). Making meaningful materials easier to learn. In M. Pressely & J.R. Levin (Eds.), Cognitive strategy research: Educational applications. NewYork: Springer-Verlag.

Pressley, M., & Harris, K.R. (2006). Cognitive strategies instruction; From basic research to classroom instruction. In P.A. Alexander & P.H. Winne (Eds.), Handbook of educational psychology (2nd ed). Mahwah, NJ: Erlbaum.

Pressley, M., & Hilden, K. (2006). Cognitive strategies. In W. Damon & R. Lerner (Eds.), Handbook of child psychology (6th ed.). New York: Wiley.

Roediger III, H. L., & Butler, A. C. (2011). The critical role of retrieval practice in long-term retention. Trends in cognitive sciences, 15(1), 20-27.

Schunk, D. H. (1990). Goal setting and self-efficacy during self-regulated learning. Educational psychologist, 25(1), 71-86.

Tanner, K.D. (2012). Promoting Student Metacognition. CBE-Life Sciences Education, 11(2), 113-120. doi:10.1187/cbe.12