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Can learning analytics improve engineering education in both MOOC and traditional learning contexts?

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Slides of the SEFI 2017 workshop delivered by the STELA and ABLE Erasmus+ project in Tampere, Finland.

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Can learning analytics improve engineering education in both MOOC and traditional learning contexts?

  1. 1. CAN LEARNING ANALYTICS IMPROVE ENGINEERING EDUCATION IN BOTH MOOC AND TRADITIONAL LEARNING CONTEXTS? Tinne De Laet Jan-Paul van Staalduinen
  2. 2. Presentation Overview • Introduction to STELA and ABLE projects • Considerations for using learning analytics • Demonstration of learning analytics dashboards • Reflections on using learning analytics in different contexts
  3. 3. Introduction to the STELA and ABLE Projects
  4. 4. STELA Project • Successful Transition from secondary to higher Education using Learning Analytics • Project partners: • The main goal of the STELA project is to enhance a successful transition from secondary to higher education by means of learning analytics. • The STELA project…  Involves designing and building student and staff-facing analytics dashboards  Aims to develop dashboards that go beyond identifying as-risk students; allowing actionable feedback for all students on a large scale STELA Project: 562167-EPP-1-2015-1-BE-EPPKA3-PI-FORWARD www.stela-project.eu @STELA_Project
  5. 5. ABLE Project • Project partners: • The main goal of the ABLE Project team is to research strategies and practices for using learning analytics to support students during their first year at university. • The ABLE project…  Involves developing the technological aspects of learning analytics  Focuses on how learning analytics can be used to support students ABLE Project: 2015-1-BE-EPPKA3-PI-FORWARD www.ABLEproject.eu @ABLEproject_eu
  6. 6. Considerations for using learning analytics
  7. 7. What is Learning Analytics? • no universally agreed definition “the measurement, collection, analysis and reporting of data about learners and their contexts, for purposes of understanding and optimizing learning and the environments in which it occurs” [1] [1] Learning and Academic Analytics, Siemens, G., 5 August 2011, http://www.learninganalytics.net/?p=131 [2] What is Analytics? Definition and Essential Characteristics, Vol. 1, No. 5. CETIS Analytics Series, Cooper, A., http://publications.cetis.ac.uk/2012/521 “the process of developing actionable insights through problem definition and the application of statistical models and analysis against existing and/or simulated future data” [2]
  8. 8. What is Learning Analytics? 8 [3] Learning Analytics and Educational Data Mining, Erik Duval’s Weblog, 30 January 2012, https://erikduval.wordpress.com/2012/01/30/learning-analytics-and-educational-data-mining/ “learning analytics is about collecting traces that learners leave behind and using those traces to improve learning” [Erik Duval, 3] † 12 March 2016 • no universally agreed definition
  9. 9. Is it about institutional data? • high-level figures: provide an overview for internal and external reports; used for organisational planning purposes. • academic analytics: figures on retention and success, used by the institution to assess performance. • educational data mining: searching for patterns in the data. • learning analytics: use of data, which may include ‘big data’, to provide actionable intelligence for learners and teachers. [4] Learning analytics FAQs, Rebecca Ferguson, Slideshare, http://www.slideshare.net/R3beccaF/learning-analytics-fa-qs
  10. 10. Discussion • Please spend 5 minutes talking to others on the table about the following: 1. What are your core questions about learning analytics? 2. What are your initial thoughts on causes of concern and/or perception of benefits for first year students?
  11. 11. Demonstration of learning analytics dashboards
  12. 12. study advisor STUDENT interaction self-reflection
  13. 13. interaction self-reflection1 2 3 scores scores learning skills study advisor STUDENT 1 Erasmus+ project ABLE 2 Erasmus+ project STELA3
  14. 14. interaction self-reflection1 2 3 scores scores learning skills study advisor STUDENT 1 Erasmus+ project ABLE 2 Erasmus+ project STELA3
  15. 15. interaction self-reflection1 2 3 scores scores learning skills study advisor STUDENT 1 Erasmus+ project ABLE 2 Erasmus+ project STELA3
  16. 16. interaction self-reflection1 2 3 scores scores learning skills study advisor STUDENT 1 Erasmus+ project ABLE 2 Erasmus+ project STELA3
  17. 17. Learning analytics for learners Do learners change their behaviour when confronted with their learning performance relative to that of successful learners? Tracker deployed in the Drinking Water MOOC Dan Davis, Guanliang Chen, Ioana Jivet, Claudia Hauff, and Geert-Jan Houben. Encouraging Metacognition & Self-Regulation in MOOCs through Increased Learner Feedback. LAL Workshop 2016. 5,462 learners were exposed to the intervention TU Delft MOOC learning tracker
  18. 18. Do learners change their behaviour when confronted with their learning performance relative to that of successful learners? Dan Davis, Ioana Jivet, Rene Kizilcec, Guanliang Chen, Claudia Hauff, and Geert-Jan Houben. Follow the Successful Crowd: Raising MOOC Completion Rates through Social Comparison at Scale, LAK, pp. 454-463, 2017. Social comparison raises MOOC completion rates Learning Tracker deployed in 4 MOOCs 33,726 learners were exposed to the intervention
  19. 19. Reflections on using learning analytics in different contexts
  20. 20. Workshop Activity • On your tables please pick one of the Dashboards to discuss and consider: 1. How might your institute use the Dashboard to support student transition? 2. How might the Dashboard work with other initiatives at your institution to support student transition? 3. If you were designing your own learning analytics tool which elements would you keep or enhance and remove or edit? Assign one person for a “one minute” plenary statement at the end
  21. 21. Thank you for listening. Any questions? www.ABLEproject.eu @ABLEproject_eu www.stela-project.eu @STELA_Project

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