research-article

Multimodal learning analytics

Author:

Paulo BliksteinAuthors Info & Claims

LAK '13: Proceedings of the Third International Conference on Learning Analytics and Knowledge

Pages 102 - 106

https://doi.org/10.1145/2460296.2460316

Published: 08 April 2013 Publication History

Abstract

New high-frequency data collection technologies and machine learning analysis techniques could offer new insights into learning, especially in tasks in which students have ample space to generate unique, personalized artifacts, such as a computer program, a robot, or a solution to an engineering challenge. To date most of the work on learning analytics and educational data mining has focused on online courses or cognitive tutors, in which the tasks are more structured and the entirety of interaction happens in front of a computer. In this paper, I argue that multimodal learning analytics could offer new insights into students' learning trajectories, and present several examples of this work and its educational application.

References

[1]

Amershi, S., & Conati, C. 2009. Combining Unsupervised and Supervised Classification to Build User Models for Exploratory Learning Environments. Journal of Educational Data Mining, 1(1), 18--71.

[2]

Baker, R. & Yacef, K. 2009. The State of Educational Data Mining in 2009: A Review and Future Visions. Journal of Educational Data Mining, 1(1).

[3]

Baker, R. S., Corbett, A. T., Koedinger, K. R., & Wagner, A. Z. 2004. Off-task behavior in the cognitive tutor classroom: when students "game the system". Proceedings of the SIGCHI conference on Human factors in computing systems.

Digital Library

[4]

Blikstein, P. 2011. Using learning analytics to assess students' behavior in open-ended programming tasks, in Proceedings of the 1st International Conference on Learning Analytics and Knowledge. ACM: Banff, Canada. 110--116.

Digital Library

[5]

Barron, B., & Darling-Hammond, L. 2010. Prospects and challenges for inquiry-based approaches to learning: OECD.

[6]

Beck, J. E., & Sison, J. 2006. Using Knowledge Tracing in a Noisy Environment to Measure Student Reading Proficiencies. International Journal of Artificial Intelligence in Education, 16(2), 129--143.

Digital Library

[7]

Chris Manning and Hinrich Schütze, Foundations of Statistical Natural Language Processing, MIT Press.

Digital Library

[8]

D'Mello, S., Craig, S., Witherspoon, A., McDaniel, B., & Graesser, A. 2008. Automatic detection of learner's affect from conversational cues. User Modeling and User-Adapted Interaction, 18(1), 45--80.

Digital Library

[9]

Dewey, J. 1902. The school and society. U of Chicago Press.

[10]

Dutson, A. J., Todd, R. H., Magleby, S. P., & Sorensen, C. D. 1997. A Review of Literature on Teaching Engineering Design through Project-Oriented Capstone Courses. J of Engineering Education, 86(1), 17--28.

[11]

Dym, C. L. 1999. Learning Engineering: Design, Languages, and Experiences. J of Engineering Education, 145--148.

[12]

Freire, P. 1970. Pedagogia do Oprimido. Paz e Terra, Rio de Janeiro.

[13]

Kirschner, P. A., Sweller, J., & Clark, R. E. 2006. Why minimal guidance during instruction does not work: An analysis of the failure of constructivist, discovery, problem-based, experiential, and inquiry-based teaching. Educational Psychologist, 41(2), 75--86.

[14]

Klahr, D., & Nigam, M. 2004. The equivalence of learning paths in early science instruction. Psychological Science, 15(10), 661.

[15]

Levy, F., & Murnane, R. J. 2004. The new division of labor: How computers are creating the next job market: Princeton University Press.

Digital Library

[16]

Montessori, M. 1965. Spontaneous activity in education. Schocken Books, New York.

[17]

Pang, Bo and Lillian Lee. 2008. Opinion mining and sentiment analysis. Foundations and Trends in Information Retrieval 2(1): 1--135.

Digital Library

[18]

Papert, S. 1980. Mindstorms: children, computers, and powerful ideas. Basic Books, New York.

Digital Library

[19]

Piech, C., et al. Modeling how students learn to program. 2012. In Proceedings of the 43rd ACM Symposium on Computer Science Education (SIGCSE '12). ACM.

Digital Library

[20]

Rus, V., Lintean, M. and Azevedo, R. 2009. Automatic Detection of Student Mental Models During Prior Knowledge Activation in MetaTutor. In Proc. of the 2nd Int. Conference on Educational Data Mining. 161--170.

[21]

Worsley, M. and Blikstein P. 2011. What's an Expert? Using learning analytics to identify emergent markers of expertise through automated speech, sentiment and sketch analysis. In Proceedings for the 4th Annual Conference on Educational Data Mining, Eindhoven, The Netherlands.

[22]

Worsley, M. and Blikstein P. 2012. A Framework for Characterizing Student Changes in Student Identity During Constructionist Learning Activities. Proceedings of Constructionism 2012, Athens, Greece.

[23]

Worsley, M. and Blikstein, P. 2013. Toward the Development of Multimodal Action Based Assessment. In Proceedings for the 2013 Learning Analytics and Knowledge (LAK 2013) Conference, Leuven, Belgium.

Digital Library

Cited By

Joseph JThomas BJose JPathak N(2024)Decoding the growth of multimodal learning: A bibliometric exploration of its impact and influenceIntelligent Decision Technologies10.3233/IDT-23072718:1(151-167)Online publication date: 20-Feb-2024
https://doi.org/10.3233/IDT-230727
Gubenko A(2024)Creativity, embodiment, and COVID-19: Discovering new research horizons under methodological and environmental constraintsPossibility Studies & Society10.1177/27538699241273734Online publication date: 19-Sep-2024
https://doi.org/10.1177/27538699241273734
Echeverria VYan LZhao LAbel SAlfredo RDix SJaggard HWotherspoon ROsborne ABuckingham Shum SGasevic DMartinez-Maldonado R(2024)TeamSlides: a Multimodal Teamwork Analytics Dashboard for Teacher-guided Reflection in a Physical Learning SpaceProceedings of the 14th Learning Analytics and Knowledge Conference10.1145/3636555.3636857(112-122)Online publication date: 18-Mar-2024
https://dl.acm.org/doi/10.1145/3636555.3636857
Show More Cited By

Index Terms

Multimodal learning analytics
1. Software and its engineering
  1. Software notations and tools
    1. General programming languages
      1. Language features

Recommendations

Social learning analytics: five approaches
LAK '12: Proceedings of the 2nd International Conference on Learning Analytics and Knowledge

This paper proposes that Social Learning Analytics (SLA) can be usefully thought of as a subset of learning analytics approaches. SLA focuses on how learners build knowledge together in their cultural and social settings. In the context of online social ...
Multimodal learning analytics: enabling the future of learning through multimodal data analysis and interfaces
ICMI '12: Proceedings of the 14th ACM international conference on Multimodal interaction

Project-based learning has found its way into a range of formal and informal learning environments. However, systematically assessing these environments remains a significant challenge. Traditional assessments, which focus on learning outcomes, seem ...
Learning analytics: Expanding the frontier
TEEM 2017: Proceedings of the 5th International Conference on Technological Ecosystems for Enhancing Multiculturality

1Learning analytics is one of the most active research topics in the field of education and educational technologies. Yet, research on learning analytics still has to address many topics related to the application of learning analytics techniques, such ...

Comments

Please enable JavaScript to view thecomments powered by Disqus.

Information & Contributors

Information

Published In

cover image ACM Conferences

LAK '13: Proceedings of the Third International Conference on Learning Analytics and Knowledge

April 2013

300 pages

ISBN:9781450317856

DOI:10.1145/2460296

Editors:
Dan Suthers
University of Hawaii, USA
,
Katrien Verbert
Eindhoven University of Technology, The Netherlands
,
Erik Duval
University of Leuven, Belgium
,
Xavier Ochoa
Escuela Superior Politécnica del Litoral, Ecuador

Copyright © 2013 ACM.

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]

Sponsors

SIGWEB: ACM Special Interest Group on Hypertext, Hypermedia, and Web
K.U. Leuven: K.U. Leuven
SIGCHI: ACM Special Interest Group on Computer-Human Interaction

Publisher

Association for Computing Machinery

New York, NY, United States

Publication History

Published: 08 April 2013

Permissions

Request permissions for this article.

Request Permissions

Check for updates

Author Tags

Qualifiers

Research-article

Conference

LAK '13

Sponsor:

SIGWEB
K.U. Leuven
SIGCHI

LAK '13: Third Conference on Learning Analytics and Knowledge

April 8 - 13, 2013

Leuven, Belgium

Acceptance Rates

LAK '13 Paper Acceptance Rate 16 of 58 submissions, 28%;

Overall Acceptance Rate 236 of 782 submissions, 30%

Contributors

Other Metrics

View Article Metrics

Bibliometrics & Citations

Bibliometrics

Article Metrics

171
Total Citations
View Citations
3,526
Total Downloads

Downloads (Last 12 months)501
Downloads (Last 6 weeks)52

Reflects downloads up to 19 Nov 2024

Other Metrics

View Author Metrics

Citations

Cited By

Joseph JThomas BJose JPathak N(2024)Decoding the growth of multimodal learning: A bibliometric exploration of its impact and influenceIntelligent Decision Technologies10.3233/IDT-23072718:1(151-167)Online publication date: 20-Feb-2024
https://doi.org/10.3233/IDT-230727
Gubenko A(2024)Creativity, embodiment, and COVID-19: Discovering new research horizons under methodological and environmental constraintsPossibility Studies & Society10.1177/27538699241273734Online publication date: 19-Sep-2024
https://doi.org/10.1177/27538699241273734
Echeverria VYan LZhao LAbel SAlfredo RDix SJaggard HWotherspoon ROsborne ABuckingham Shum SGasevic DMartinez-Maldonado R(2024)TeamSlides: a Multimodal Teamwork Analytics Dashboard for Teacher-guided Reflection in a Physical Learning SpaceProceedings of the 14th Learning Analytics and Knowledge Conference10.1145/3636555.3636857(112-122)Online publication date: 18-Mar-2024
https://dl.acm.org/doi/10.1145/3636555.3636857
Zhang FPossaghi ISharma KPapavlasopoulou S(2024)High-performing Groups during Children's Collaborative Coding Activities: What Can Multimodal Data Tell Us?Proceedings of the 23rd Annual ACM Interaction Design and Children Conference10.1145/3628516.3655805(533-559)Online publication date: 17-Jun-2024
https://dl.acm.org/doi/10.1145/3628516.3655805
Heilala VLehesvuori SHämäläinen RKärkkäinen THong JPark J(2024)Toward Scalable and Transparent Multimodal Analytics to Study Standard Medical Procedures: Linking Hand Movement, Proximity, and Gaze DataProceedings of the 39th ACM/SIGAPP Symposium on Applied Computing10.1145/3605098.3635929(3-10)Online publication date: 8-Apr-2024
https://dl.acm.org/doi/10.1145/3605098.3635929
Moon JYeo SBanihashem SNoroozi O(2024)Using multimodal learning analytics as a formative assessment tool: Exploring collaborative dynamics in mathematics teacher educationJournal of Computer Assisted Learning10.1111/jcal.1302840:6(2753-2771)Online publication date: 5-Jun-2024
https://doi.org/10.1111/jcal.13028
Yan LEcheverria VJin YFernandez‐Nieto GZhao LLi XAlfredo RSwiecki ZGašević DMartinez‐Maldonado R(2024)Evidence‐based multimodal learning analytics for feedback and reflection in collaborative learningBritish Journal of Educational Technology10.1111/bjet.1349855:5(1900-1925)Online publication date: 22-Jun-2024
https://doi.org/10.1111/bjet.13498
Silva MRoberto RRadu ICavalcante PSchneider BTeichrieb V(2024)Development of Design Principles for AR Authoring Tools for Education Based on Teacher's PerspectivesIEEE Transactions on Learning Technologies10.1109/TLT.2023.332759217(677-690)Online publication date: 2024
https://doi.org/10.1109/TLT.2023.3327592
Lee-Cultura SSharma KGiannakos M(2024)Multimodal Teacher Dashboards: Challenges and Opportunities of Enhancing Teacher Insights Through a Case StudyIEEE Transactions on Learning Technologies10.1109/TLT.2023.327684817(181-201)Online publication date: 2024
https://doi.org/10.1109/TLT.2023.3276848
Sepp STindall-Ford SAgostinho SPaas F(2024)Capturing Movement: A Tablet App, Geometry Touch, for Recording Onscreen Finger-Based Gesture DataIEEE Transactions on Learning Technologies10.1109/TLT.2023.324650717(73-83)Online publication date: 1-Jan-2024
https://dl.acm.org/doi/10.1109/TLT.2023.3246507
Show More Cited By

View Options

Login options

Check if you have access through your login credentials or your institution to get full access on this article.

Full Access

Get this Publication

View options

PDF

View or Download as a PDF file.

eReader

View online with eReader.

Media

Figures

Other

Tables

View Table of Contents