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Annotated Bibliography

Julie Stanton


1) Ambrose, S. A., Bridges, M. W., DiPietro, M., Lovett, M.C., & Norman. M. K.  (2010).  How Learning Works Chapter Seven: How Do Students Become Self-Directed Learners?  San Francisco, CA: Jossey-Bass.


The authors explore five metacognitive skills used by self-directed learners.  These include the ability to: 1) understand what a task involves, 2) identify personal strengths and weaknesses related to the task, 3) create a plan for completing the task, 4) execute the plan and monitor how well it is working, and 5) change the plan as needed upon reflection.  The authors also explain how students’ beliefs about their abilities and the learning process affect metacognition.  The authors believe it is important for instructors to help students learn metacognitive skills and give them opportunities to practice using them.  Several suggestions for encouraging students to improve on each of the five skills are provided.  Overall this is an excellent applied summary of key facets of metacognition.  This source is valuable because it explains the role of these metacognitive processes and what can happen when students have not developed each one. 


            Reference relates to: rationale or motivation for study, design of study.


2) Haak, D. C., HilleRisLambers, J., Pitre, E., & Freeman, S.  (2011).  Increased Structure and Active Learning Reduce the Achievement Gap in Introductory Biology.  Science, 332, 1213-1216.


The authors hypothesized that increasing the structure of an introductory biology course would result in higher grades for undergraduate students from disadvantaged backgrounds.  Their primary goal was to lower the “achievement gap” between disadvantaged and non-disadvantaged students.  As the amount of formal active learning exercises increased, student performance as measured by course grades rose.  The effect was disproportionate, resulting in a decrease in the achievement gap.  The authors concluded that the extensive opportunities for practice allowed the disadvantaged students to succeed.  Since my research is aimed at decreasing the failure rate in an introductory biology course, this source is valuable as it describes positive results for students who are at risk of failing.  I plan to utilize the methods outlined for calculating predicted grades and the achievement gap.


            Reference relates to: methods for data collection and analysis, interpretation of results.


3) Miller, T. M. & Geraci, L.  (2011).  Training metacognition in the classroom: the influence of incentives and feedback on exam predictions.  Metacognition Learning.  6, 303-314.


The authors asked whether providing feedback and incentive in the form of extra credit could increase metacognition monitoring as measured by students’ ability to accurately predict their overall exam grades (calibration).  Following an initial baseline experiment, the authors gave student some group feedback in class and access to their predicted and actual grade.  They found that students categorized as “low performers” often overestimated their grades, but they could be trained to increase their calibration.  This was achieved by lowering their predictions rather than by raising their performance.  The authors suggest that students may need more individual feedback to increase metacognitive monitoring.  The paper provided a good introduction to this area of research, but the text should have been proofread more carefully before publication.  The value of this source is that it describes an effort to train students in a particular metacognitive skill and provides evidence of improvement following that training.


Reference relates to: design of study, interpretation of results.



4) Tanner, K. D. (2012).  Promoting Student Metacognition.  CBE – Life Science Education, 11, 113-120.


The author aims to promote student metacognition by summarizing its importance and providing strategies for developing the metacognitive areas of planning, monitoring and evaluating in biology courses.  She recommends that biology instructors be direct about encouraging students to develop these skills by including formal questions that address these areas and by imbedding metacognitive prompts throughout a course.  She also suggests that biology instructors take a metacognitive approach to teaching.  The author believes that the current focus on active learning in undergraduate education will not be successful without a substantial metacognitive component.  This is a valuable source for my research because it provides several ways of readily incorporating metacognition into a biology course, although data to supporting these approaches is not provided because this is a feature article.  I plan to use the author’s suggested questions and prompts to help my students develop metacognitive skills.


Reference relates to: design of study.


5) Young, A. & Fry, J. D.  (2008).  Metacognitive awareness and academic achievement in college students.  Journal of Scholarship of Teaching and Learning, 8, 1-10.


The authors hypothesized that metacognition correlates with academic achievement.  They used the Metacognitive Awareness Inventory (MAI) (Schraw & Dennison 1994) to measure metacognition in undergraduate and graduate students, and found a correlation with course grades and cumulative GPA, but not with exam grades.  They also discovered that undergraduate and graduate students have similar metacognitive knowledge scores, but graduate students have higher metacognitive regulation scores.  The authors recommend that the MAI is given as a diagnostic test at the start of a term to help faculty identify students who need additional training in metacognition.  While the results are reported to be statistically significant, I am not familiar enough with the Spearman’s Rho nonparametric correlation analysis to know whether the data are truly convincing.  The study would have been enhanced by the inclusion of interventions to help students develop metacognitive skills.  Nonetheless, this source is valuable to my research because it demonstrates the use of the MAI.


            Reference relates to: methods for data collection and analysis, interpretation of results.




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