Month: March 2016

Teach Students How to Learn: A review of Saundra McGuire’s strategy-packed book

by Jessica Santangelo, Ph.D. Hofstra University

For those interested in helping students develop strong metacognitive skills, Dr. Saundra McGuire’s book, Teach Students How to Learn: Strategies You Can Incorporate Into Any Course to Improve Student Metacognition, Study Skills, and Motivation, is concise, practical, and much less overwhelming than trying to figure out what to do on your own. It is both a consolidation of the research surrounding metacognition, mindset, and motivation and a how-to guide for putting that research into practice.

I have been interested in metacognition for several years. Having waded through the literature on teaching metacognition (e.g., using tutors, student self-check, writing assignments, reflective writing, learning records, “wrappers”, or any number of other strategies) I found Dr. McGuire’s book to be an excellent resource. It places many of the strategies I already use in my courses in a larger context which helps me better articulate to my students and colleagues why I am teaching those strategies. I also picked up a few strategies I had not used previously.

While metacognition is the focus of the book, Dr. McGuire includes strategies for promoting a growth mindset (Chapter 4) and for boosting student motivation (Chapters 7, 8 and 9). I hadn’t expected such an explicit focus on these two topics, but the book makes clear why they are important: they increase the probability of success. If students (and faculty) have a growth mindset, believing that success is due to behaviors and actions rather than innate talent or being “smart”, they are more likely to embrace the metacognitive strategies outlined in the book. The same principle applies to a person’s emotional state. Both emotions and learning arise in the brain and affect each other. If students and faculty are motivated to learn, they are more likely to embrace the metacognitive strategies.

The part of the book that is perhaps most practically useful is Chapter 11: Teaching Learning Strategies to Groups. Dr. McGuire details an approach she has honed over many years to teach metacognitive skills to groups of students in one, 50-minute presentation (a detailed discussion of the metacognitive skills and evidence for them are provided in Chapters 3-5). Slides that can be tailored for any course are available at the book’s accompanying website, along with a video of Dr. McGuire giving the presentation throughout which she sprinkles in data and anecdotes that foster a growth mindset and increase student motivation.

Before reading Dr. McGuire’s book, I had had success using several strategies to promote student metacognition. I had a student go from failing exams to making high C’s, and other students move from C’s to B’s and A’s. However, I felt like my approach was haphazard since I had pulled ideas from different places in the literature without a cohesive framework for implementation. The book provided the framework I was missing.

This semester, I decided to use Dr. McGuire’s cohesive 50-minute session to see its impact on my students. I adapted it to be an online workshop because 1) I have limited class time this semester, and 2) an online intervention may benefit my colleagues who are interested in this approach but who aren’t able to use a class period for this purpose. In addition to the online workshop, I re-emphasize key points from the book when students come to office hours. I use phrasing and examples presented in the book to reinforce a growth mindset and boost motivation. I intentionally discuss “metacognitive learning strategies” rather than “study skills” because, as Dr. McGuire points out, many students think they have all the “study skills” they need but are often intrigued by how “metacognitive learning strategies” (which most have not heard of before) could help them.

You can jump in with both feet, as I did, or start with one or two strategies and build from there. Either way, this book allows you to take advantage of Dr. McGuire’s extensive experience as Director Emerita of the Center for Academic Success at LSU. I anticipate my copy will become dogeared with use as I continue to be metacognitive about my teaching and the strategies that work best for me, my students, and my colleagues. Stay tuned for an update on my online adaptation of Dr. McGuire’s session once the semester wraps up!


When is Metacognitive Self-Assessment Skill “Good Enough”?

Ed Nuhfer Retired Professor of Geology and Director of Faculty Development and Director of Educational Assessment, enuhfer@earthlink.net, 208-241-5029 (with Steve Fleisher CSU-Channel Islands; Christopher Cogan, Independent Consultant; Karl Wirth, Macalester College and Eric Gaze, Bowdoin College)

We noted the statement by Zell and Krizan (2014, p. 111) that: “…it remains unclear whether people generally perceive their skills accurately or inaccurately” in Nuhfer, Cogan, Fleisher, Gaze and Wirth (2016) In our paper, we showed why innumeracy is a major barrier to the understanding of metacognitive self-assessment.

Another barrier to progress exists because scholars who attempt separately to do quantitative measures of self-assessment have no common ground from which to communicate and compare results. This occurs because there is no consensus on what constitutes “good enough” versus “woefully inadequate” metacognitive self-assessment skills. Does overestimating self-assessment skill by 5% allow labeling a person as “overconfident?” We do not believe so. We think that a reasonable range must be exceeded before those labels should be considered to apply.

The five of us are working now on a sequel to our above Numeracy paper. In the sequel, we interpret the data taken from 1154 paired measures from a behavioral science perspective. This extends our first paper’s describing of the data through graphs and numerical analyses. Because we had a database of over a thousand participants, we decided to use it to propose the first classification scheme for metacognitive self-assessment. It defines categories based on the magnitudes of self-assessment inaccuracy (Figure 1).

metacogmarchfig1
Figure 1. Draft of a proposed classification scheme for metacognitive self-assessment based upon magnitudes of inaccuracy of self-assessed competence as determined by percentage points (ppts) differences between ratings of self-assessed competence and scores from testing of actual competence, both expressed in percentages.

If you wonder where the “good” definition comes from in Figure 1, we disclosed on page 19 of our Numeracy paper: “We designated self-assessment accuracies within ±10% of zero as good self-assessments. We derived this designation from 69 professors self-assessing their competence, and 74% of them achieving accuracy within ±10%.”

The other breaks that designate “Adequate,” “Marginal,” “Inadequate,” and “Egregious” admittedly derive from natural breaks based upon measures expressed in percentages. By distribution through the above categories, we found that over 2/3 of our 1154 participants had adequate self-assessment skills, a bit over 21% exhibited inadequate skills, and the remainder lay within the category of “marginal.” We found that less than 3% qualified by our definition as “unskilled and unaware of it.”

These results indicate that the popular perspectives found in web searches that portray people in general as having grossly overinflated views of their own competence may be incomplete and perhaps even erroneous. Other researchers are now discovering that the correlations between paired measures of self-assessed competence and actual competence are positive and significant. However, to establish the relationship between self-assessed competency and actual competency appears to require more care in taking the paired measures than many of us researchers earlier suspected.

Do the categories as defined in Figure 1 appear reasonable to other bloggers, or do these conflict with your observations? For instance, where would you place the boundary between “Adequate” and “Inadequate” self-assessment? How would you quantitatively define a person who is “unskilled and unaware of it?” How much should a person overestimate/underestimate before receiving the label of “overconfident” or “underconfident?”

If you have measurements and data, please compare your results with ours before you answer. Data or not, be sure to become familiar with the mathematical artifacts summarized in our January Numeracy paper (linked above) that were mistakenly taken for self-assessment measures in earlier peer-reviewed self-assessment literature.

Our fellow bloggers constitute some of the nation’s foremost thinkers on metacognition, and we value their feedback on how Figure 1 accords with their experiences as we work toward finalizing our sequel paper.