What Type of Debrief is Best for Learning during Think-Pair-Shares?

Authors

  • Martin Barrett Carnegie Mellon University
  • Chad Hershock Carnegie Mellon University
  • Michael McCarthy Carnegie Mellon University
  • Michael Melville Carnegie Mellon University
  • Joe Mertz Carnegie Mellon University

DOI:

https://doi.org/10.20343/teachlearninqu.9.1.5

Keywords:

active learning, Think-pair-share, large courses, explanation feedback

Abstract

Copious research demonstrates the benefits of adding active learning to traditional lectures to enhance learning and reduce failure/withdrawal rates. However, many questions remain about how best to implement active learning to maximize student outcomes. This paper investigates several “second generation” questions regarding infusing active learning, via Think-Pair-Share (TPS), into a large lecture course in Computer Science. During the “Share” phase of TPS, what is the best way to debrief the associated course concepts with the entire class? Specifically, does student learning differ when instructors debrief the rationale for every answer choice (full debrief) versus only the correct answer (partial debrief)? And does the added value for student outcomes vary between tasks requiring recall versus deeper comprehension and/or application of concepts? Regardless of discipline, these questions are relevant to instructors implementing TPS with multiple-choice questions, especially in large lectures. Similar to prior research, when lectures included TPS, students performed significantly better (~13%) on corresponding exam items. However, students’ exam performance depended on both the type of debrief and exam questions. Students performed significantly better (~5%) in the full debrief condition than the partial debrief condition. Additionally, benefits of the full debrief condition were significantly stronger (~5%) for exam questions requiring deeper comprehension and/or application of underlying Computer Science processes, compared to simple recall. We discuss these results and lessons learned, providing recommendations for how best to implement TPS in large lecture courses in STEM and other disciplines.

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Author Biographies

Martin Barrett, Carnegie Mellon University

Martin Barrett is an Associate Teaching Professor in the Institute of Software Research and Heinz College of Public Policy and Information Management at Carnegie Mellon University (USA). His teaching focuses Information Systems and Computer Science.

Chad Hershock, Carnegie Mellon University

Chad Hershock is the Director of Faculty & Graduate Student Programs at the Eberly Center for Teaching Excellence & Educational Innovation at Carnegie Mellon University (USA). His work supports the adoption of evidenced-based pedagogy and SoTL.

Michael McCarthy, Carnegie Mellon University

Michael McCarthy is an Associate Teaching Professor in the Heinz College of Public Policy and Information Management at Carnegie Mellon University (USA). His teaching focuses Information Systems.

Michael Melville, Carnegie Mellon University

Michael Melville is a Data Science Research Associate at the Eberly Center for Teaching Excellence & Educational Innovation at Carnegie Mellon University (USA). His work supports the Scholarship of Teaching & Learning conducted by instructors.

Joe Mertz, Carnegie Mellon University

Joe Mertz is a Teaching Professor in the Dietrich College of Humanities and Social Sciences and Heinz College of Public Policy and Information Management at Carnegie Mellon University (USA).

References

Ambrose, Susan A., Marsha C. Lovett, Michael W. Bridges, Michele DiPietro, and Marie K. Norman. 2010. How Learning Works: Seven Research-Based Principles for Smart Teaching. San Francisco, CA: Jossey-Bass.

Bertsch, Sharon, Bryan J. Pesta, Richard Wiscott, and Michael A. McDaniel. 2007. “The Generation Effect: A Meta-Analytic View.” Memory & Cognition 35, no. 2: 201–10. https://doi.org/10.3758/BF03193441. Bruff, Derek. 2009. Teaching with Classroom Response Systems. San Francisco, CA: Jossey-Bass.

Butler, Andrew. C. 2010. “Repeated Testing Produces Superior Transfer of Learning Relative to Repeated Studying.”Journal of Experimental Psychology 36, no. 5: 1118–33. https://doi.org/10.1037/a0019902.

Butler, Andrew C., Namrata Godbole, and Elizabeth J. Marsh. 2013. “Explanation Feedback is Better than Correct Answer Feedback for Promoting Transfer of Learning.” Journal of Educational Psychology 105, no. 2: 290–98. https://doi.org/10.1037/a0031026290.

Cepeda, Nicholas J., Edward Vul, Doug Rohrer, John T. Wixted, and Harold Paschler. 2008. “Spacing Effects in Learning: A Temporal Ridgeline of Optimal Retention.” Psychological Science 19, no. 11: 1095-102. https://doi.org/10.1111/j.1467-9280.2008.02209.x.

Crouch, Catherine H., and Eric Mazur. 2001. “Peer Instruction: Ten Years of Experience and Results.” American Journal of Physics 69, no. 9: 970-77, Retrieved from https://doi.org/10.1119/1.1374249.

Eddy, Sarah L., and Kelly A. Hogan. 2014. “Getting under the Hood: How and for Whom Does Increasing Course Structure Work?” CBE-Life Sciences Education 13, no. 3: 453-68. https://doi.org/10.1187/cbe.14-03-0050.

Freeman, Scott, Sarah L. Eddy, Miles McDonough, Michelle K. Smith, Nnadozie Okoroafor, Hannah Jordt, and Mary Pat Wenderoth. 2014. “Active Learning Increases Student Performance in Science, Engineering, and Mathematics. Proceedings of the National Academy of Sciences 111, no. 23: 8410-15. https://doi.org/10.1073/pnas.1319030111.

Gavassa, Sat, Rocio Benabentos, Marcy Kravec, Timothy Collins, and Sarah Eddy. 2019. “Closing the Achievement Gap in a Large Introductory Course by Balancing Reduced In-Person Contact with Increased Course Structure.” CB—Life Sciences Education 18, no. 1. https://doi.org/10.1187/cbe.18-08-0153

Goeden, Terrah J., Martha J. Kurtz, Ian J. Quitadamo, and Carin Thomas. 2015. “Community-Based Inquiry in Allied Health Biochemistry Promotes Equity by Improving Critical Thinking for Women and Showing Promise for Increasing Content Gains for Ethnic Minority Students.” Journal of Chemistry Education 92, no. 5: 788-96. http://dx.doi.org/10.1021/ed400893f.

Haak, David C., Janneke HilleRisLambers, Emile Pitre, and Scott Freeman. 2011. “Increased Structure and Active Learning Reduce the Achievement Gap in Introductory Biology.” Science 332, no. 3: 1213-16. https://doi.org/10.1126/science.1204820.

Hattie, John, and Helen Timperley. 2007. “The Power of Feedback.” Review of Educational Research, 77, no. 1: 81-112. https://doi.org/10.3102/003465430298487.

Kapler, Irina V., Tina Weston, and Melody Wiseheart. 2015. “Spacing in a Simulated Undergraduate Classroom: Long-Term Benefits for Factual and Higher-Level Learning.” Learning and Instruction, 36: 38-45. https://doi.org/10.1016/j.learninstruc.2014.11.001.

Kothiyal, Aditi, Rwitajit Majumdar, Sahana Murthy, and Sridhar Iyer. 2013. “Effect of Think-Pair-Share in a Large CS1 Class: 83% Sustained Engagement.” Proceedings from ICER ’13: The Ninth Annual International ACM Conference on International Computing Education Research, San Diego, CA, 12-13 August 2013, ACM Press, New York, NY, 226-36. https://doi.org/10.1145/2493394.2493408.

Linton, Debra L., Jan Keith Farmer, and Ernie Peterson. 2014. “Is Peer Interaction Necessary for Optimal Active Learning?” CBE—Life Sciences Education 13, no. 2: 243-52. https://doi.org/10.1187/cbe.13-10-0201.

Lovett, Marsha, Oded Meyer, and Candace Thille. 2008. “The Open Learning Initiative: Measuring the Effectiveness of the OLI Statistics Course in Accelerating Student Learning.” Journal of Interactive Media in Education 2008, no. 1. https://doi.org/10.5334/2008-14.

Lyman, Frank. 1987. “Think-Pair-Share: An Expanding Teaching Technique.” MAA-CIE Cooperative News 1: 1-2. Michael, Joel. 2007. “Faculty Perceptions about Barriers to Active Learning.” College Teaching 55, no. 2: 42-47. https://doi.org/10.3200/CTCH.55.2.42-47.

Miller, Cynthia J., and Michael J. Metz. 2014. “A Comparison of Professional-Level Faculty and Student Perceptions of Active Learning: Its Current Use, Effectiveness, and Barriers.” Advances in Physiological Education 38: 246–52. https://doi.org/10.1152/advan.00014.2014.

Pashler, Harold, Nicholas J. Cepeda, John T. Wixted, and Doug Rohrer. 2005. “When Does Feedback Facilitate Learning of Words?” Journal of Experimental Psychology: Learning, Memory, and Cognition 31, 3-8. https://doi.org/10.1037/0278-7393.31.1.3.

Porter, Leo, Cynthia Bailey Lee, Beth Simon, and Daniel Zingaro. 2011. “Peer Instruction: Do Students Really Learn from Peer Discussion in Computing?” Proceedings from ICER ’11: The ACM SIGCSE 2011 International Computing Education Research Workshop, Providence, RI, 8-9 August 2011, ACM Press, New York, NY, 45-52. https://doi.org/10.1145/2016911.2016923.

Prince, Michael. 2004. “Does Active Learning Work? A Review of the Research.” Journal of Engineering Education 93, no. 3: 223-31. https://doi.org/10.1002/j.2168-9830.2004.tb00809.x.

Radermacher, Alex D., and Gursimran S. Walia. 2011. “Investigating the Effective Implementation of Pair Programming: An Empirical Investigation.” Proceedings from SIGCSE '11: The 42nd ACM Technical Symposium on Computer Science Education, Dallas, TX, 9-11 March 2011, ACM Press, New York, NY, 655-60. https://doi.org/10.1145/1953163.1953346.

Roediger, Henry L., and Jeffrey Karpicke. 2006. “Test-Enhanced Learning: Taking Memory Tests Improves Long-Term Retention.” Psychological Science 17, no. 3: 249-55. https://doi.org/10.1111/j.1467- 9280.2006.01693.x.

Rohrer, Doug, and Kelli Taylor. 2006. “The Effects of Overlearning and Distributed Practise on the Retention of Mathematics Knowledge.” Applied Cognitive Psychology 20, no. 9: 1209-24. https://doi.org/10.1002/acp.1266.

Schweitzer, Dino, Jeff Boleng, and Lauren Scharff. 2011. “Interactive Tools in the Graphics Classroom.” Proceedings from ITiCSE '11: The 16th Annual Joint Conference on Innovation and Technology in Computer Science Education, Darmstadt, Germany, 27-29 June, 2011, ACM Press, New York, NY, 113-17. https://doi.org/10.1145/1999747.1999781.

Smith, Michelle K., William B. Wood, Wendy K. Adams, C. E. Wieman, Jennifer K. Knight, Nancy Guild, and Tin Tin Su. 2009. “Why Peer Discussion Improves Student Performance on In-Class Concept Questions.” Science 323, no. 5910: 122-24. https://doi.org/10.1126/science.1165919.

Tinkle, Theresa, Daphna Atias, Ruth M. McAdams, and Cordelia Zukerman. 2013. “Teaching Close Reading Skills in a Large Lecture Course.” Pedagogy: Critical Approaches to Teaching Literature, Language, Composition, and Culture 13, no. 3 505-35. https://doi.org/10.1215/15314200-2266432.

Trumbo, Michael C., Kari A. Leiting, Mark A. McDaniel, and Gordon K. Hodge. 2016. “Effects of Reinforcement on Test-Enhanced Learning in a Large, Diverse Introductory College Psychology Course.” Journal of Experimental Psychology: Applied 22, no. 2: 148-60. https://doi.org/10.1037/xap0000082.

Webb, David J. 2017. “Concepts First: A Course with Improved Educational Outcomes and Parity for Underrepresented Students.” American Journal of Physics 85, no. 8: 628-32. https://doi.org/10.1119/1.4991371.

Winkelmes, Mary-Ann, Matthew Bernacki, Jeffrey Butler, Michelle Zochowski, Jennifer Golanics, and Kathryn Harriss Weavil. 2016. “A Teaching Intervention that Increases Underserved College Students’ Success.” Peer Review 18, no. 1: 31-36.

Wormeli, Rick. 2004. Summarization in Any Subject: 50 Techniques to Improve Student Learning. Alexandria, VA: Association for Supervision and Curriculum Development.

Zheng, Jun, Sohee Kang, and Brian Harrington. 2019. “Immediate Feedback Collaborative Code Tracing." Proceedings from WCCCE ‘19: The Western Canadian Conference on Computing Education, Calgary, Canada, 3-4 May 2019, ACM Press, New York, NY, 12:1-12:2. https://doi.org/10.1145/3314994.3325087.

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Published

2021-03-07

How to Cite

Barrett, Martin, Chad Hershock, Michael McCarthy, Michael Melville, and Joe Mertz. 2021. “What Type of Debrief Is Best for Learning During Think-Pair-Shares?”. Teaching and Learning Inquiry 9 (1):45-60. https://doi.org/10.20343/teachlearninqu.9.1.5.