Month: December 2014

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.


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

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

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

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

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

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

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

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

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

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

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

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

and thereafter to monitor their mastery as the course unfolds.

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


Mind the Feedback Gap

by Roman Taraban (Texas Tech University)

mindthegap

The saying “Mind the Gap” originated in 1969 to warn riders on London subways of the gap between the platform and subway car. Since then, it has been broadly applied to situations in which there may be something missing or lacking between where you are and where you want to be. The cautionary message sounded loudly this semester when I realized that my undergraduate students were not particularly interested in the constructive feedback they were receiving on their bi-weekly formative evaluations over the course content, consisting of short-answer and brief essay responses. This was troubling since I was trying to promote metacognition through my feedback. But I am getting a bit ahead of myself.

Feedback in the Classroom

Technology now affords instructors easy-to-use means of providing timely and detailed feedback on work that is submitted digitally. As one example, assignments can be sent to a website and the instructor can use tools like “Track Changes” and “New Comment” in Microsoft WordTM to insert edits and comments in a clear and readable fashion. Beyond these basic digital tools, the coming of age of automated instructional tutors has brought with it a science of just-in-time feedback, synced with the computer’s best guess as to what a student knows at any given moment, and providing little to extensive feedback and guidance, depending on a student’s ability and prior experience (Graesser et al. 2005; Koedinger et al., 1997). In terms of technology, there are broad options available to instructors, from easy markup tools to software that will automatically grade papers. Indeed, there has not been a better time for developing and delivering effective feedback to students.

Students’ Perceptions of Feedback

The utility of feedback has been examined empirically, and has produced several practical suggestions (Koedinger et al., 1997; Shute, 2008). Students’ perceptions of feedback, though, have not been extensively researched; however, a few things are known. Weaver (2006) reported that students found several aspects of feedback to be unhelpful: when the comments provided were general or vague, when the comments did not provide guidance for rethinking or revising, when they focused on the negative, and when they were unrelated to the task. On a more positive note, Higgins and Harley (2002) conducted a survey of college students and reported the criteria that over 75% of students considered important:

  • Comments that tell you what you could do to improve – 92%
  • Comments that explain your mistakes – 91%
  • Comments that focus on the level of critical analysis – 90%
  • Comments that focus on your argument – 89%
  • Comments that focus on the tutor’s overall impressions – 87%
  • Comments that tell you what you have done badly – 86%
  • Comments that focus on the subject matter – 82%
  • Comments that correct your mistakes – 80%
  • Feedback that tells you the grade – 79%
  • Comments that focus on your use of supporting evidence – 79% (p. 60)

Students’ Reactions to Feedback

For several semesters I have been following Weaver’s and Higgins and Harley’s dictums, using formative evaluations in an undergraduate class that prompt critical, reflective, and evaluative thinking, for many of the questions. This semester, I dutifully edited and commented on students’ responses and electronically delivered these back to students. After the second formative evaluation, I announced to students that grades had been posted and that if they wanted more detailed comments to let me know and I would email them as I had done for the first exam. Here is the irony: only 2 out of 30 students wanted the feedback.   Assuring students that sending commented responses would not create extra work for me did not change the outcome on subsequent evaluations. Students simply did not care to hear my thoughts on their work. As it turns out, Higgins and Hartley (2002) had already anticipated my situation when they suggested that students may be extrinsically motivated to achieve a specific grade and to acquire related credentials, and may not be intrinsically motivated to reflect on their understanding of the material through the critical lens afforded by instructors’ comments.

Perceptions of Feedback – A Touchstone

Feedback may be a touchstone of metacognition. Often, to boost metacognition in the classroom, we implement tasks intended to evoke critical thinking. But what better way to increase metacognition than through developing a keener sense in students for feedback. In a way, deeply considering the teacher’s feedback requires “thinking about someone else’s thinking” in order to improve one’s own “thinking about thinking.” It appears that for too long, I have been over-estimating students’ interest in thinking critically about their own work. And as is true with the development of other cognitive abilities, several things will need to happen for change to occur. From my side, more “demandingness” may be required: to be explicit about what I want, to sensitize students to my feedback through questioning and prompting, and to scaffold the process of reflecting on feedback through directed exercises. Most importantly, the feedback needs to have carry-over value to future student work.

It is generally accepted that feedback is an essential component of learning, providing a vehicle for thinking about one’s own thinking. Logically, alerting students to their strengths and weaknesses can provide the means by which they can reflect on how they thought through a task and how to constructively modify their approach in future work. None of this will happen, though, if students fail to consider the feedback. Wojtas (1998) warned of this possibility some years ago, when he reported on the research findings in one university, suggesting that some students were concerned only with their grade and not with substantive feedback. It may be helpful to pose the same stark question to our students in order to begin to close the feedback gap: Are you only interested in your grade?

My own experience has led me to other researchers confronting similar disconcerting situations. Jollards et al. (2009) write “teachers often feel their time is wasted when it is invested in marking work and making comments on assignments, only to see work not collected in class and then left at their doorstep at the end of semester. Even if it is collected the students might not read the feedback, and even if it is read, they might not act on it. As Shute (2008) points out, “Feedback can promote learning, if it is received mindfully” (p. 172). In sum, feedback is necessary because it can give students something to think about and can prompt deeper levels of reflection. Feedback needs to be good if the gap is going to be closed. But it is also the case that good feedback alone is not enough. Metacognition is necessary if feedback is going to lead to meaningful improvement. Students must process the feedback via metacognition if they are to close the gap. (Thanks to John Draeger for these summary points!)

References

Graesser, A. C., McNamara, D., & VanLehn, K. (2005). Scaffolding deep comprehension strategies through AutoTutor and iSTART. Educational Psychologist, 40, 225–234.

Higgins, R., & Hartley, P. (2002). The Conscientious Consumer: Reconsidering the role of assessment feedback in student learning. Studies in Higher Education, 27(1), 53-64. DOI:10.1080/0307507012009936 8

Jollands, M., McCallum, N., & Bondy, J. (2009). If students want feedback why don’t they collect their assignments? 20th Australasian Association for Engineering Education Conference, University of Adelaide, Australia.

Koedinger, K., Anderson, J. R., Hadley, W. H., Mark, M. (1997). Intelligent tutoring goes to school in the big city. International Journal of Artificial Intelligence in Education, 8, 30-43.

Shute, V. (2008). Focus on formative feedback. Review of Educational Research, 78(1), 153–189. DOI:10.3102/0034654307313795

Weaver, M. R. (2006). Do students value feedback? Student perceptions of tutors’ written responses. Assessment & Evaluation in Higher Education, 31(3), 379-394. DOI:10.1080/02602930500353061

Wojtas, O. (1998). Feedback? No, just give us the answers. Times Higher Education Supplement, September 25 1998.

 


Thinking about How Faculty Learn about Learning

By Cynthia Desrochers, California State University Northridge

Lately, two contradictory adages have kept me up nights:  “K.I.S.S. – Keep It Simple, Stupid” (U.S. Navy) and “For every complex problem there is an answer that is clear, simple, and wrong” (H.L. Mencken).  Which is it?  Experts have a wealth of well-organized, conditionalized, and easily retrievable knowledge in their fields (Bradford, et al., 2000).  This may result in experts skipping over steps when they teach a skill that has become automatic to them.  But where does this practice leave our novice learners who need to be taught each small step—almost in slow motion—to begin to grasp a new skill?

I have just completed co-facilitating five of ten scheduled faculty learning community (FLC) seminars in a yearlong Five GEARS for Activating Learning FLC.  As a result of this experience, my takeaway note to self now reads in BOLD caps:  (1) keep it simple in the early stages of learning and (2) model the entire process and share my thinking out loud—no secrets hidden behind the curtains!

The Backstory

The Five Gears for Activating Learning project at California State University, Northridge, began in fall 2012. It was my idea, and I asked seven university-wide faculty leaders to join me in a grassroots effort. Our goals were to improve student learning from inside the classroom (vs. policy modifications), promote faculty use of the current research on learning, provide a lens for judging the efficacy of various teaching strategies (e.g., the flipped classroom), and develop a common vocabulary for use campuswide (e.g., personnel communications).  Support for this project came from the University Provost and the dean of the Michael D. Eisner College of Education in the form of reassigned time for me and 3-unit buyouts for each of the eight FLC members, spread over the entire academic year, 2014-15.

We read as a focus book How Learning Works: 7 Research-Based Principles for Smart Teaching (Ambrose, et al., 2010). We condensed Ambrose’s seven principles to five GEARS, one of which is Developing Mastery, which we defined as deep learning, reflection, and self-direction—critical elements of metacognition and the focus of this blog site.

On Keeping It Simple

I have been in education for forty-five years, yet I’m having many light-bulb moments with this FLC group – I’m learning something new, or reorganizing prior knowledge, or having increased clarity.  Hence, I’ve given a lot of thought to the conflict between keeping it simple and omitting some important elements versus sharing more complex definitions and relationships and overwhelming our FLC members. My rationale for choosing simple: If I am still learning about how learning works, how can I expect new faculty—who teach Political Science, Business Law, Research Applications, and African Americans in Film, all without benefit of a teaching credential—to process some eighty years of research on learning in two semesters?

In opting for the K.I.S.S. approach, we have developed a number of activities and tools that scaffold learning to use the five GEARS in our teaching; moreover, each activity or tool models explicitly with faculty some practices we are encouraging them to use with their students.  This includes (1) reflective writing in the form of learning logs and diaries, (2) an appraisal instrument to self-assess their revised (using the GEARS) spring 2015 course design, and (3) a class-session plan to scaffold their use of the GEARS.  [See the detailed descriptions given in the handout resource posted on this site.] I hope to have some results data regarding their use in my spring blog.

Looking to next semester, our spring FLC projects will likely center around not only teaching the redesigned five GEARS course but also disseminating the five GEARS campuswide.  As a direct result of the Daily Diary that FLC members kept for three weeks on others’ use and misuse of the five GEARS, they want to share our work.  [See handout for further description of the Daily Diaries.] Dissemination possibilities include campus student tour guides, colleagues who teach a common course, Freshman Seminar instructors, librarians, and the Career Center personnel.  If another adage is true, “Tell me and I forget, teach me and I may remember, involve me and I learn” (Benjamin Franklin), our FLC faculty will likely move of their own accord along the continuum from a simple to complex understanding of the five GEARS in their efforts to teach the five GEARS to others on campus.

A Word about GEARS

Why is this blog not focusing solely on the metacognition gear, which we call Developing Mastery? The simple answer is that learning is so intertwined that all the GEARS likely support metacognition in some way.  However, any one of the activities or tools we have employed can be modified to limit the scope to your definition of metacognition.  Our postcard below shows all five GEARS:

5_GEARS_postcard