IV LAIKA workshop
Last Thursday 29th November, IV LAIKA workshop was celebrated at the Open University of Catalonia in Barcelona.
20 People from several institutions (Universidad de León, Universidad Carlos III, Universidad Nacional de Educación a Distancia, Universitat Pompeu Fabra, Universitat Autònoma de Barcelona, Institut Obert de Catalunya, Universitat Oberta de Catalunya) participated in the event.
The main objective of this workshop was sharing experiences regarding Evidence Based Decision-Making using Learning Analytics institutional policies.
“Toma de decisiones basada en analíticas de aprendizaje”, by Miguel Ángel Conde (Universidad de León)
He posed the main aspects about a student centered learning where the track of the student over the Internet (beyond Virtual Campuses) allows us to understand his or her learning process and improve it through interventions in real time. He emphasized the relevance of 5 key elements in a learning analytics process:
- a clear strategic question and a a well-defined context
- data collection
- definition of variables, analysis and prediction
- make a decision (context, agents, type of decisions, consequences)
First, Antonio Robles and Rafael Pastor (UNED) presented an example of using learning analytics in an engineering degree, where students use remote laboratories. Combining data from the LoT@UNED platform (used to provide access to the remote laboratory) and student surveys, they evaluate the way students use the LoT platform and their perception of usefulness or easiness, following an extended version of the Technology Acceptance Model (TAM).
Other references related to TAM:
Then, Pedro Manuel Moreno (U. Carlos III de Madrid) presented two EU projects related to learning analytics. The first project, named SHEILA, aims to assist European universities to become more mature users and custodians of digital data about their students as they learn online, by building a policy development framework that promotes formative assessment and personalized learning, taking advantage of direct engagement of stakeholders in the development process. The second project, named LALA, aims to build the local capacity to design, implement and use Learning Analytics tools in Latin America Higher Education Institutions(HEI), with the aid of European Universities, to provide a powerful tool to solve any problem where academic data analysis is necessary.
Results about other LA projects were also presented; among them, the analysis of social interaction in communication spaces, using LA for predicting MOOC success using different timespan windows and how to use LA for promoting and predicting self-regulated learning.
Final Research Report: http://sheilaproject.eu/wp-content/uploads/2018/11/SHEILA-research-report.pdf
– Yi-Shan Tsai, Pedro Manuel Moreno-Marcos, Ioana Jivet, Maren Scheffel, Kairit Tammets, Kaire Kollom, and Dragan Gasevic. 2018. The SHEILA framework: informing institutional strategies and policy processes of learning analytics. Journal of Learning Analytics [aceptado]. Accepted in: http://sheilaproject.eu/wp-content/uploads/2018/09/JLA_accepted-manuscript.pdf
– Yi-Shan Tsai, Pedro Manuel Moreno-Marcos, Kairit Tammets, Kaire Kollom, and Dragan Gasevic. 2018. SHEILA policy framework: informing institutional strategies and policy processes of learning analytics. In Proceedings of the International Conference on Learning Analytics and Knowledge, Sydney, Australia, March 2018 (LAK’18), 10 pages, pp. 320-329. DOI: 10.1145/3170358.3170367.
Social interactions analysis
– Pedro Manuel Moreno-Marcos, Carlos Alario-Hoyos, Pedro J. Muñoz-Merino, Iria Estévez-Ayres and Carlos Delgado Kloos. 2018. A learning analytics methodology for understanding social interactions in MOOCs. IEEE Transactions on Learning Technologies. DOI: 10.1109/TLT.2018.2883419
Predicción en MOOCs:
– Pedro Manuel Moreno-Marcos, Carlos Alario-Hoyos, Pedro J. Muñoz-Merino, and Carlos Delgado Kloos. 2018. Prediction in MOOCs: A review and future research directions. IEEE Transactions on Learning Technologies. DOI: 10.1109/TLT.2018.2856808
– Pedro Manuel Moreno-Marcos, Pedro J. Muñoz-Merino, Carlos Alario-Hoyos, Iria Estévez-Ayres and Carlos Delgado Kloos. 2018. Analysing the predictive power for anticipating assignment grades in a Massive Open Online Course. Behaviour & Information Technology, 37(10-11):1021-1036. DOI: 10.1080/0144929X.2018.1458904
Prediction and self-regulated learning
– Jorge Maldonado-Mahauad, Mar Perez-Sanagustin, Pedro Manuel Moreno-Marcos, Carlos Alario-Hoyos, Pedro J. Muñoz-Merino and Carlos Delgado Kloos. 2018. Predicting Learners’ Success in a Self-Paced MOOC Based on Sequence Patterns of Self-Regulated Learning. In Proceedings of the 13th European Conference on Technology Enhanced Learning, Leeds, UK, September 2018 (EC-TEL’18), 14 pages, pp. 355-369. DOI: 10.1007/978-3-319-98572-5_27
– Pedro Manuel Moreno-Marcos, Carlos Alario-Hoyos, Pedro J. Muñoz-Merino, Iria Estévez-Ayres, and Carlos Delgado Kloos. 2018. Sentiment Analysis in MOOCs: A case study. In Proceedings of the IEEE Global Engineering Education, Santa Cruz de Tenerife, Spain, April 2018 (EDUCON’18), 8 pages, pp. 1489-1496. DOI: 10.1109/EDUCON.2018.8363409.
Finally, David Pinyol (IOC) presented how they apply Big Data at small scale, focusing on teacher needs.
Conclusions from the LAIKA workshop were presented by Julià Minguillón (UOC). The importance of having plenty of quality data was also discussed, using the UOC eLearn Center datamart as an example of evidence-based LRS. As an example of institutional learning analytics policies, the ESPRIA project aimed to provide personalized support to new students was also briefly presented.
-Minguillón, J., Conesa, J., Rodríguez, M. E., & Santanach, F. (2018). Learning Analytics in Practice: Providing E-Learning Researchers and Practitioners with Activity Data. In Frontiers of Cyberlearning (pp. 145-167). Springer, Singapore. https://doi.org/10.1007/978-981-13-0650-1_8
-González, L., Minguillón, J., Martínez-Aceituno, J., & Meneses, J. (2018). Institutional support to provide freshmen with flexible learning paths at course and semester level in open higher education.” In 10th EDEN Research Workshop, 344-350. Barcelona: European Distance and E-Learning Network, 2018. http://hdl.handle.net/10609/86165