research-article

Design and Application of Intervention Model based on Learning Analytics under Blended Learning Environment

Authors:

Lilin Gong,

Yang LiuAuthors Info & Claims

ICIET 2019: Proceedings of the 2019 7th International Conference on Information and Education Technology

Pages 225 - 229

https://doi.org/10.1145/3323771.3323825

Published: 29 March 2019 Publication History

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Abstract

The arrival of big data and AI era promote educational reforms, which make personalized learning become normalization. Teaching intervention is an indispensable bridge between big data and students' personalized learning. This study proposes an intervention model based on learning analytics from four iteration modules: data collection, data processing, intervention implementation and effect evaluation, and applies it to blended learning environment. Through one-group pretest-posttest experiment design, the effect of the intervention model were measured by learning engagement and learning achievement. The results show that the intervention model can effectively improve students' behavioral engagement and cognitive engagement as well as learning achievement, especially for risky students.

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Cited By

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Bittencourt IChalco GSantos JFernandes SSilva JBatista NHutz CIsotani S(2023)Positive Artificial Intelligence in Education (P-AIED): A RoadmapInternational Journal of Artificial Intelligence in Education10.1007/s40593-023-00357-y34:3(732-792)Online publication date: 3-Aug-2023
https://doi.org/10.1007/s40593-023-00357-y
Yang LLuo XGao A(2022)Study on Document Measurement and Visual Analysis of Big Data Education EvaluationProceedings of the 2022 2nd International Conference on Education, Information Management and Service Science (EIMSS 2022)10.2991/978-94-6463-024-4_53(504-513)Online publication date: 29-Dec-2022
https://doi.org/10.2991/978-94-6463-024-4_53
Yürüm OYıldırım STaşkaya-Temizel T(2022)An intervention framework for developing interactive video lectures based on video clickstream behavior: a quasi-experimental evaluationInteractive Learning Environments10.1080/10494820.2022.204231231:10(6611-6626)Online publication date: 28-Feb-2022
https://doi.org/10.1080/10494820.2022.2042312
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Index Terms

Design and Application of Intervention Model based on Learning Analytics under Blended Learning Environment
1. Applied computing
  1. Education
    1. Learning management systems

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Published In

ICIET 2019: Proceedings of the 2019 7th International Conference on Information and Education Technology

March 2019

338 pages

ISBN:9781450366397

DOI:10.1145/3323771

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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Osaka University: Osaka Universtiy
University of Aizu: University of Aizu

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 29 March 2019

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ICIET 2019

ICIET 2019: 2019 7th International Conference on Information and Education Technology

March 29 - 31, 2019

Aizu-Wakamatsu, Japan

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Cited By

View all

Bittencourt IChalco GSantos JFernandes SSilva JBatista NHutz CIsotani S(2023)Positive Artificial Intelligence in Education (P-AIED): A RoadmapInternational Journal of Artificial Intelligence in Education10.1007/s40593-023-00357-y34:3(732-792)Online publication date: 3-Aug-2023
https://doi.org/10.1007/s40593-023-00357-y
Yang LLuo XGao A(2022)Study on Document Measurement and Visual Analysis of Big Data Education EvaluationProceedings of the 2022 2nd International Conference on Education, Information Management and Service Science (EIMSS 2022)10.2991/978-94-6463-024-4_53(504-513)Online publication date: 29-Dec-2022
https://doi.org/10.2991/978-94-6463-024-4_53
Yürüm OYıldırım STaşkaya-Temizel T(2022)An intervention framework for developing interactive video lectures based on video clickstream behavior: a quasi-experimental evaluationInteractive Learning Environments10.1080/10494820.2022.204231231:10(6611-6626)Online publication date: 28-Feb-2022
https://doi.org/10.1080/10494820.2022.2042312
Oliva-Córdova LGarcia-Cabot AAmado-Salvatierra H(2021)Application of Learning Analytics in Virtual Tutoring: Moving toward a Model Based on Interventions and Learning Performance AnalysisApplied Sciences10.3390/app1104180511:4(1805)Online publication date: 18-Feb-2021
https://doi.org/10.3390/app11041805
Moon JDo JLee DChoi G(2020)A conceptual framework for teaching computational thinking in personalized OERsSmart Learning Environments10.1186/s40561-019-0108-z7:1Online publication date: 13-Feb-2020
https://doi.org/10.1186/s40561-019-0108-z
Knobbout JVan Der Stappen E(2020)Where is the Learning in Learning Analytics? A Systematic Literature Review on the Operationalization of Learning-Related Constructs in the Evaluation of Learning Analytics InterventionsIEEE Transactions on Learning Technologies10.1109/TLT.2020.299997013:3(631-645)Online publication date: 1-Jul-2020
https://doi.org/10.1109/TLT.2020.2999970
Zotou MTambouris ETarabanis K(2020)Data-driven problem based learning: enhancing problem based learning with learning analyticsEducational Technology Research and Development10.1007/s11423-020-09828-8Online publication date: 21-Sep-2020
https://doi.org/10.1007/s11423-020-09828-8

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