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Towards adapting to learners at scale: integrating MOOC and intelligent tutoring frameworks

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Ryan BakerAuthors Info & Claims

L@S '18: Proceedings of the Fifth Annual ACM Conference on Learning at Scale

Article No.: 14, Pages 1 - 4

https://doi.org/10.1145/3231644.3231671

Published: 26 June 2018 Publication History

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Abstract

Instruction that adapts to individual learner characteristics is often more effective than instruction that treats all learners as the same. A practical approach to making MOOCs adapt to learners may be by integrating frameworks for intelligent tutoring systems (ITSs). Using the Learning Tools Interoperability standard (LTI), we integrated two intelligent tutoring frameworks (GIFT and CTAT) into edX. We describe our initial explorations of four adaptive instructional patterns in the PennX MOOC "Big Data and Education." The work illustrates one route to adaptivity at scale.

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Huang XXu WLiu R(2025)Effects of Intelligent Tutoring Systems on Educational OutcomesInternational Journal of Distance Education Technologies10.4018/IJDET.36842023:1(1-25)Online publication date: 6-Feb-2025
https://doi.org/10.4018/IJDET.368420
Ghosh UJermsittiparsert K(2024)Personalised Learning Systems and the Human Touch in Society 5.0Sustainable Development, Humanities, and Social Sciences for Society 5.010.4018/979-8-3693-7989-9.ch012(211-232)Online publication date: 18-Oct-2024
https://doi.org/10.4018/979-8-3693-7989-9.ch012
Proske AKörndle HDrexler KKirsten JSchröder KKucharski SKubica TBraun I(2023)Towards Designing and Evaluating an Adaptable Assistance System for Technology-Enhanced Vocational EducationResponsive and Sustainable Educational Futures10.1007/978-3-031-42682-7_51(618-623)Online publication date: 28-Aug-2023
https://doi.org/10.1007/978-3-031-42682-7_51
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Published In

L@S '18: Proceedings of the Fifth Annual ACM Conference on Learning at Scale

June 2018

391 pages

ISBN:9781450358866

DOI:10.1145/3231644

Conference Chair:
Rose Luckin
UCL Institute of Education, UK
,
Program Chairs:
Scott Klemmer
University of California at San Diego
,
Kenneth Koedinger
Carnegie Mellon University

Publication rights licensed to ACM. ACM acknowledges that this contribution was authored or co-authored by an employee, contractor or affiliate of the United States government. As such, the Government retains a nonexclusive, royalty-free right to publish or reproduce this article, or to allow others to do so, for Government purposes only.

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Association for Computing Machinery

New York, NY, United States

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Published: 26 June 2018

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L@S '18

L@S '18: Fifth (2018) ACM Conference on Learning @ Scale

June 26 - 28, 2018

London, United Kingdom

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L@S '18 Paper Acceptance Rate 24 of 58 submissions, 41%;

Overall Acceptance Rate 117 of 440 submissions, 27%

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Huang XXu WLiu R(2025)Effects of Intelligent Tutoring Systems on Educational OutcomesInternational Journal of Distance Education Technologies10.4018/IJDET.36842023:1(1-25)Online publication date: 6-Feb-2025
https://doi.org/10.4018/IJDET.368420
Ghosh UJermsittiparsert K(2024)Personalised Learning Systems and the Human Touch in Society 5.0Sustainable Development, Humanities, and Social Sciences for Society 5.010.4018/979-8-3693-7989-9.ch012(211-232)Online publication date: 18-Oct-2024
https://doi.org/10.4018/979-8-3693-7989-9.ch012
Proske AKörndle HDrexler KKirsten JSchröder KKucharski SKubica TBraun I(2023)Towards Designing and Evaluating an Adaptable Assistance System for Technology-Enhanced Vocational EducationResponsive and Sustainable Educational Futures10.1007/978-3-031-42682-7_51(618-623)Online publication date: 28-Aug-2023
https://doi.org/10.1007/978-3-031-42682-7_51
Smaili EAzzouzi SEl Hassan Charaf M(2022)An Optimized Adaptive Learning Approach Based on Cuckoo Search Algorithm2022 8th International Conference on Optimization and Applications (ICOA)10.1109/ICOA55659.2022.9934280(1-4)Online publication date: 6-Oct-2022
https://doi.org/10.1109/ICOA55659.2022.9934280
Ma SSpector JLiu DBhagat KTiruneh DMancini JLin LNielsen RKinshuk (2022)Smart Learning in Support of Critical Thinking: Lessons Learned and a Theoretically and Research-Based FrameworkBridging Human Intelligence and Artificial Intelligence10.1007/978-3-030-84729-6_22(309-326)Online publication date: 24-Feb-2022
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Kusumastuti DMeyliana Hidayanto APrabowo H(2021)Models of Adaptive Learning System in MOOC: A Systematic Literature Review2021 9th International Conference on Information and Education Technology (ICIET)10.1109/ICIET51873.2021.9419580(242-246)Online publication date: 27-Mar-2021
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Garg MGoel A(2021)A Data-Driven Approach for Peer Recommendation to Reduce Dropouts in MOOCAdvances in Computing and Network Communications10.1007/978-981-33-6977-1_18(217-229)Online publication date: 21-Apr-2021
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Díaz Redondo RCaeiro Rodríguez MLópez Escobar JFernández Vilas A(2020)Integrating micro-learning content in traditional e-learning platformsMultimedia Tools and Applications10.1007/s11042-020-09523-zOnline publication date: 19-Sep-2020
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Folsom-Kovarik JMostafavi BSottilare RDavidson IPerez RWalker L(2019)Approaches to Enhancing Transfer of Training using Adaptive Instructional Systems2019 International Conference on Software, Telecommunications and Computer Networks (SoftCOM)10.23919/SOFTCOM.2019.8903774(1-6)Online publication date: Sep-2019
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Personalized E-learning system with self-regulated learning assisted mechanisms for promoting learning performance

Exploring Factors Affecting Learners' Acceptance of MOOCs Based on Kirkpatrick's Model

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