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Learning Analytics Support for Just-in-time Teaching
The document discusses using learning analytics to support just-in-time teaching. It identifies problems that emerge in highly interactive lab sessions through literature reviews and experiments. Requirements for an in-class live analytics system were determined based on input from teachers, students, and experts. The system was developed and tested over multiple experiments and provided real-time analytics and awareness tools to help teachers manage sessions and provide personalized feedback to students. Evaluation found it helped address initial problems and contributed to the field of learning analytics and orchestration in technology-enhanced learning environments.
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Learning Analytics Support for Just-in-time Teaching
- 1. Learning Analytics support for Just-in-timeTeaching Israel Gutiérrez Jornadas GAST - 8 de julio de 2013
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- 5. Lab sessions photo: berkeleylabat flickr
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- 7. Research Questions “What are theproblems that emerge in highly interactive face-to-face sessions?”
- 8. Research Questions “Could a just-in-timeteaching system be used to overcome the previous problems, facilitating the teacher management of the session driving it to the intended learning objectives and improving the efficiency of the students allowing them to focus on the assignment?” “What are the problems that emerge in highly interactive face-to-face sessions?”
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- 10. Methodology Design-based research • Basedon theory but pragmatic
- 11. Methodology Design-based research • Basedon theory but pragmatic • Real-world setting
- 12. Methodology Design-based research • Basedon theory but pragmatic • Real-world setting • Iterative process
- 13. Methodology Design-based research • Basedon theory but pragmatic • Real-world setting • Iterative process • Mixed methods
- 14. Methodology Design-based research • Basedon theory but pragmatic • Real-world setting • Iterative process • Mixed methods • Research agenda updated with findings
- 15. Problems in lab session LiteratureExperiments Experts
- 16. Literature Lantern (Alavi &Dillenbourg, 2009) PLITAZ (Dong & Hwang, 2012) Problem Source Stakeholder Demand an answer Alavi09 Students Wait longer Alavi09 Students Fails to notice requests Alavi09 Teachers Heavy workload Dong12 Teachers Isolation Dong12 Students Limited awareness Dong12 Teachers Simultaneous requests Dong12 Teachers
- 17. AMM11 (Gutiérrez Rojas,Crespo García, & Delgado Kloos, 11) AS11 (Gutiérrez Rojas & Crespo García, 12) AMM12 (Gutiérrez Rojas, Crespo García, & Delgado Kloos, 12) Problem Source Stakeholder Methodology increases workload AMM11 Teachers Huge number of requests AS11 Teachers Attention to personalized feedback AS11 Students Ask without thinking AS11 Students Shorten explanation if overwhelmed AS11 Teachers Perceive not enough teachers AS11 Students Attention order unfairness AS11 Teachers Devote time monitoring the teacher AS11 Students Not aware of time AS11 Teachers Not like writing questions AMM12 Students Not relevant not current info AMM12 Teachers Interface not straight-forward AMM12 Teachers Experiments
- 18. OUNL UC3M Experts KU Leuven RWTH Aachen ProblemSource Stakeholder Not support for project-based learning EXP Teachers Not support for exchange questions EXP Students Not support for exchange progress EXP Students Not collecting evidences for summative EXP Teachers
- 19. Requirements Requirement Stakeholder Provide timemanagement mechanisms Teachers Provide info about students progression Teachers Provide info about students requests Teachers Straightforward UI Teachers Responsive UI Teachers Store and process students records Teachers Support different teaching methods Teachers Provide info to students for self-awareness Students As much personalized feedback as possible Students Enable students to focus on the assignment Students Share and rate questions and answers Students Share progression Students
- 20. in-Class Live Analytics forAssessment and Orchestration http://www.class-on.org
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- 28. Authentic experiments AMM12 AS12 AMM13 Date March-May 2012 November 2012 February-May 2013 Duration18 sessions 6 sessions 10 sessions* Teachers 4 3 1 Students 70 121 30 Group settings Dyads Dyads Dyads
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- 41. Related Publications Gutiérrez Rojas, I.,Crespo García, R. M., & Delgado Kloos, C. (2012). Enhancing orchestration of lab sessions by means of awareness mechanisms. EC-TEL 2012: 21st century learning for 21st century skills: 7th European Conference of Technology Enhanced Learning, 18-21 September 2012, Saarbrücken (Germany) (Vol. 7563, pp. 113–125). Gutiérrez Rojas, I., & Crespo García, R. M. (2012). Towards efficient provision of feedback in lab sessions. International Conference on Advanced Learning Technologies (ICALT) (Vol. 1). Rome. Gutiérrez Rojas, I., Crespo García, R. M., & Delgado Kloos, C. (2011). Orchestration and feedback in lab sessions: improvements in quick feedback provision. Towards Ubiquitous Learning. 6th European Conference ofTechnology Enhanced Learning, EC-TEL 2011 Palermo, Italy, September 20-23, 2011 Proceedings. LNCS, 6964. doi:10.1007/978-3-642-23985-4
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