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Blending Peer Instruction with Just-In-Time Teaching: Jointly Optimal Task Scheduling with Feedback for Classroom Flipping

Published: 08 June 2021 Publication History

Abstract

Blended learning often requires alternating between asynchronous pre-class and synchronous in-class activities using online technologies to enhance the overall learning experience. Subject to constraints on desired learning outcome specifications and individual student preference, can we jointly optimize pre-class and in-class tasks to improve the two-way interaction between students and the instructor? We leverage ideas of self-assessment in Just-In-Time Teaching and Peer Instruction to propose an optimization-theoretic framework to analyze the optimal trade-off between the time invested in two different learning tasks for each individual student. We show that the problem can be formulated as a linear program, which can be efficiently solved to determine the optimal amount of time for pre-class and in-class learning. We develop a mobile chatbot software integrated with feedback data analytics to blend asynchronous pre-class quiz assessment together with the synchronous in-class poll-quiz routine of Peer Instruction to achieve classroom flipping that can be used for remote and hybrid teaching and learning.

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Blending Peer Instruction with Just-In-Time Teaching: Jointly Optimal Task Scheduling with Feedback for Classroom Flipping

References

[1]
Joseph Beck, Beverly Park Woolf, and Carole R Beal. 2000. ADVISOR: A machine learning architecture for intelligent tutor construction. AAAI/IAAI 2000, 552--557 (2000), 1--2.
[2]
Luciana Benotti, Mara Cecilia Martnez, and Fernando Schapachnik. 2017. A tool for introducing computer science with automatic formative assessment. IEEE Transactions on Learning Technologies 11, 2 (2017), 179--192.
[3]
Maxwell Bigman and John C Mitchell. 2020. Teaching Online in 2020: Experiments, Empathy, Discovery. In 2020 IEEE Learning With MOOCS (LWMOOCS). IEEE, 156--161.
[4]
Stephen Boyd and Lieven Vandenberghe. 2004. Convex Optimization. Cambridge University Press.
[5]
Christopher G Brinton, Ruediger Rill, Sangtae Ha, Mung Chiang, Robert Smith, and William Ju. 2014. Individualization for education at scale: MIIC design and preliminary evaluation. IEEE Transactions on Learning Technologies 8, 1 (2014), 136--148.
[6]
Catherine H Crouch and Eric Mazur. 2001. Peer instruction: Ten years of experience and results. American journal of physics 69, 9 (2001), 970--977.
[7]
George B Dantzig. 1971. A control problem of Bellman. Management Science 17, 9 (1971), 542--546.
[8]
Louis Deslauriers, Ellen Schelew, and Carl Wieman. 2011. Improved learning in a large-enrollment physics class. Science 332, 6031 (2011), 862--864.
[9]
Virginia Gewin. 2020. Five tips for moving teaching online as COVID-19 takes hold. Nature 580, 7802 (2020), 295--297.
[10]
Sten Govaerts, Adrian Holzer, Bruno Kocher, Andrii Vozniuk, Benot Garbinato, and Denis Gillet. 2018. Blending Digital and Face-to-face Interaction using a Co-located Social Media App in Class. IEEE Transactions on Learning Technologies 11, 4 (2018), 478--492.
[11]
David Gross, Evava S Pietri, Gordon Anderson, Karin Moyano-Camihort, and Mark J Graham. 2015. Increased preclass preparation underlies student outcome improvement in the flipped classroom. CBE-Life Sciences Education 14, 4 (2015), 1--8.
[12]
Joshua Grossman, Zhiyuan Lin, Hao Sheng, Johnny T-Z Wei, Joseph J Williams, and Sharad Goel. 2019. MathBot: Transforming online resources for learning math into conversational interactions. AAAI 2019 Story-Enabled Intelligence (2019).
[13]
Maureen J. Lage, Glenn J. Platt, and Michael Treglia. 2000. Inverting the Classroom: A Gateway to Creating an Inclusive Learning Environment. The Journal of Economic Education 31, 1 (2000), 30--43.
[14]
Chiu-Lin Lai and Gwo-Jen Hwang. 2016. A self-regulated flipped classroom approach to improving students' learning performance in a mathematics course. Computers and Education 100 (2016), 126--140.
[15]
Nathaniel Lasry, Eric Mazur, and Jessica Watkins. 2008. Peer instruction: From Harvard to the two-year college. American Journal of Physics 76, 11 (2008), 1066--1069.
[16]
Lin Ling and Chee Wei Tan. 2018. Pilot study on optimal task scheduling in learning. In Proceedings of the Fifth Annual ACM Conference on Learning at Scale. ACM, 1--4.
[17]
Chung Laung Liu. 1960. A study in machine-aided learning. Ph.D. Dissertation. Massachusetts Institute of Technology.
[18]
Steven Low. 2015. Another Puzzle: Produce or Learn? https://rigorandrelevance.wordpress.com/2015/01/10/another-puzzle-produce-or-learn/. (2015). Accessed: 2021-04-07.
[19]
Margie Martyn. 2007. Clickers in the classroom: An active learning approach. Educause quarterly 30, 2 (2007), 71--74.
[20]
Eric Mazur. 1997. Peer Instruction: A User's Manual. Pearson, ISBN 978-0135654415.
[21]
Gregor M. Novak, Evelyn Patterson, Andrew Gavrin, and Wolfgang Christian. 1999. Just-in-Time Teaching: Blending Active Learning with Web Technology. Prentice Hall, Saddle River, NJ, ISBN 0--13-085034--9.
[22]
Scott Simkins and Mark Maier. 2010. Just-in-time teaching: Across the disciplines, across the academy. Stylus Publishing, LLC.
[23]
Richard D. Smallwood. 1962. A decision structure for teaching machines. Massachusetts Institute of Technology Press (1962).
[24]
Richard D Smallwood. 1971. The analysis of economic teaching strategies for a simple learning model. Journal of Mathematical Psychology 8, 2 (1971), 285--301.
[25]
Pavel Smutny and Petra Schreiberova. 2020. Chatbots for learning: A review of educational chatbots for the Facebook Messenger. Computers & Education 151 (2020), 103862.
[26]
Jeffrey D Ullman. 2005. Gradiance on-line accelerated learning. In Proceedings of the Twenty-eighth Australasian conference on Computer Science-Volume 38. Australian Computer Society, Inc., 3--6.
[27]
Carl Wieman. 2017. Improving How Universities Teach Science. Harvard University Press.
[28]
Shanshan Yang and Chris Evans. 2019. Opportunities and challenges in using AI chatbots in higher education. In Proceedings of the 2019 3rd International Conference on Education and E-Learning. 79--83.

Cited By

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  • (2024) Empowering student self‐regulated learning and science education through ChatGPT : A pioneering pilot study British Journal of Educational Technology10.1111/bjet.1345455:4(1328-1353)Online publication date: 22-Mar-2024
  • (2024)Unleashing ChatGPT's Power: A Case Study on Optimizing Information Retrieval in Flipped Classrooms via Prompt EngineeringIEEE Transactions on Learning Technologies10.1109/TLT.2023.332471417(629-641)Online publication date: 1-Jan-2024
  • (2024)Disrupting Higher Education: A Comparative Study of Synchronous Lecturing and Self-Paced Learning in Higher Education2024 2nd International Conference on Software Engineering and Information Technology (ICoSEIT)10.1109/ICoSEIT60086.2024.10497469(19-24)Online publication date: 28-Feb-2024
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      cover image ACM Other conferences
      L@S '21: Proceedings of the Eighth ACM Conference on Learning @ Scale
      June 2021
      380 pages
      ISBN:9781450382151
      DOI:10.1145/3430895
      Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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      New York, NY, United States

      Publication History

      Published: 08 June 2021

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      Author Tags

      1. blended learning
      2. classroom flipping
      3. just-in-time teaching
      4. learning task scheduling
      5. mobile chatbot software
      6. optimization theory
      7. peer instruction

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      L@S '21
      L@S '21: Eighth (2021) ACM Conference on Learning @ Scale
      June 22 - 25, 2021
      Virtual Event, Germany

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      Overall Acceptance Rate 117 of 440 submissions, 27%

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      Cited By

      View all
      • (2024) Empowering student self‐regulated learning and science education through ChatGPT : A pioneering pilot study British Journal of Educational Technology10.1111/bjet.1345455:4(1328-1353)Online publication date: 22-Mar-2024
      • (2024)Unleashing ChatGPT's Power: A Case Study on Optimizing Information Retrieval in Flipped Classrooms via Prompt EngineeringIEEE Transactions on Learning Technologies10.1109/TLT.2023.332471417(629-641)Online publication date: 1-Jan-2024
      • (2024)Disrupting Higher Education: A Comparative Study of Synchronous Lecturing and Self-Paced Learning in Higher Education2024 2nd International Conference on Software Engineering and Information Technology (ICoSEIT)10.1109/ICoSEIT60086.2024.10497469(19-24)Online publication date: 28-Feb-2024
      • (2024)A Comparative Analysis of Cognitive Feedback Between GPT-4.0 and Teacher in Flipped Classrooms2024 13th International Conference on Educational and Information Technology (ICEIT)10.1109/ICEIT61397.2024.10540884(149-154)Online publication date: 22-Mar-2024
      • (2024)MCQGen: A Large Language Model-Driven MCQ Generator for Personalized LearningIEEE Access10.1109/ACCESS.2024.342070912(102261-102273)Online publication date: 2024
      • (2023)A review of integrating AI-based chatbots into flipped learning: new possibilities and challengesFrontiers in Education10.3389/feduc.2023.11757158Online publication date: 22-May-2023
      • (2022)Online reach and engagement of a child nutrition peer-education program (PICNIC): insights from social media and web analyticsBMC Public Health10.1186/s12889-022-13252-322:1Online publication date: 26-Apr-2022
      • (2022)The Value of CooperationACM SIGMETRICS Performance Evaluation Review10.1145/3543146.354314949:4(8-13)Online publication date: 6-Jun-2022
      • (2022)Automatic Feedback in the Teaching of Programming in Undergraduate Courses: a Literature Mapping2022 IEEE Frontiers in Education Conference (FIE)10.1109/FIE56618.2022.9962723(1-9)Online publication date: 8-Oct-2022

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