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Patsy Moskal: Panel Presentation - Learning Analytics - Examining the Hype and Reality of Learning Analytics
The document discusses learning analytics in higher education, focusing on the collection and analysis of student data to enhance learning and identify at-risk students. It highlights the ethical considerations and guiding practices necessary for implementing predictive analytics effectively. The text also emphasizes the importance of adaptive learning approaches and the need for a supportive infrastructure to improve student outcomes.
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Patsy Moskal: Panel Presentation - Learning Analytics - Examining the Hype and Reality of Learning Analytics
- 1. Examining the Hypeand Reality of Learning Analytics" Patsy Moskal University of Central Florida
- 2. “the use ofdata, statistical analysis, and explanatory and predictive models to gain insight and act on complex issues.” Analytics! ! The Analy8cs Landscape in Higher Educa8on, 2015 (ECAR). Retrieved from hHps:// library.educause.edu/~/media/files/library/2015/5/ers1504cl.pdf
- 6. Learning Analytics “The measurement,collection, analysis and report of data about learners and their contexts, for purposes of understanding and optimizing learning and the environments in which it occurs.” hHps://solaresearch.org/
- 7. “Learning analytics collectsand analyzes the ‘digital breadcrumbs’ that students leave as they interact with various computer systems to look for correlations between those activities and learning outcomes.” Learning Analytics! ! 7 Things you should know about first-‐genera8on learning analy8cs. EDUCAUSE Learning Ini3a3ve (ELI). 2011. Retrieved from hHps://net.educause.edu/ir/library/ pdf/ELI7079.pdf
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- 11. Major Priority Not a Priority
- 12. Students’ interest inanalytics applications
- 13. Student perspectives onusing analytics Helpful “big mother” Creepy “big brother” Progress toward degree or cer8ficate Performance in current courses Performance in past courses Performance in courses compared to other students Ac8vity in university applica8on or service Ac8vity on a college or university website Campus ac8vi8es logged through student ID/smart card Campus ac8vi8es logged through smartphone Proximity to a college building, office, or resource Loca8on on campus Social media ac8vi8es
- 14. Predictive Analytics inHigher Education:! Five Guiding Practices for Ethical Use! • Have a vision and plan • Build a supportive infrastructure • Work to ensure proper use of data • Design predictive models and algorithms that avoid bias • Meet institutional goals and improve student outcomes by intervening with care. Reported in Inside Higher Ed 3/6/17 – ‘Conversa8on Starter’ on Ethical Data Use For more informa8on, visit newamerica.org/dataethics.
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- 16. Available Data! !SIS • Demographics • Socio-‐economic status • High school informa8on • Placement tests (SAT/ACT) LMS • Students’ behavior/interac8on with system • Access (views, 8me) • Gradebook data Other data (varies widely!) • Use of advising & tutoring • Interac8on with various campus services (library, wri8ng center, dining hall, etc) • AHendance at large lecture classes • Financial behavior • Orienta8on par8cipa8on
- 17. The big issueis…!
- 18. Who is at risk??? hHp://www.youthareawesome.com/wp-‐content/uploads/2010/10/wheres-‐waldo1.jpg
- 19. A more difficulttask is…!
- 20. hHp://matrix.wikia.com/wiki/File:Matrix-‐neo-‐stops-‐bullets-‐wallpaper.jpg How do we stop them from failing? How do we stop them from failing?
- 21. High Level to! Home Grown ! Learning Analytics Approaches!
- 22. § SIS, LMSand other data § Model trends across time to identify and ultimately predict which students are at risk Trawl net approach!
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- 24. UMBC Check My Activity (John Fritz)! Fritz& Whitmer (2017) Learning Analytics Research for LMS Course Design: Two Studies. http://er.educause.edu/articles/2017/2/learning-analytics-research-for-lms-course- design-two-studies
- 25. Some Prototype ! AdaptiveLearners!
- 27. Students’ adaptive learningbehaviors!
- 28. How Students Behavein Personalized Adaptive Courses! • Colm Howlin, Principal Researcher • March 16, 2017 • Realizeit Webinar http://realizeitlearning.com/ community/
- 29. Questions still beingasked…! " " " " " "…your mileage may vary! Issues/strategies with implementaCon Sources of data to use Cost issues InsCtuConal approaches Improving student outcomes Governance strategy and milestones Details, benefits, challenges Security and ethics concerns
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- 31. Special Learning Analyticsissue of Online Learning http://onlinelearningconsortium.org/read/online-learning-journal/ Editors: Karen Vignare, Patsy Moskal, Matthew Pistilli and Alyssa Wise
- 32. Learning Analytics Bibligraphy"! • Online Learning list of articles • Must read articles • General bibliography • Early alert system articles • Articles focused on ethics
- 33. Patsy Moskal! FPatsy.Moskal@ucf.edu! For more informa8on, contact: Director,! Research Initiative for Teaching Effectiveness! Center for Distributed Learning! University of Central Florida!