2020 |
Drivas, Ioannis C; Georgios, Giannakopoulos; Sakas, Damianos Learning Analytics in Big Data Era. Exploration, Validation and Predictive Models Development Conference Intelligent Tutoring Systems, Springer, 2020. Abstract | Links | BibTeX | Tags: Big data, intelligent tutoring systems, Learning analytics, Learning management systems, online learning platforms @conference{Drivas2020b, The untamed big data era raises opportunities in learning analytics sector for the provision of enhanced educational material to learners. Nevertheless, big data analytics, brings big troubles in exploration, validation and predictive model development. In this paper, the authors present a data-driven methodology for greater utilization of learning analytics datasets, with the purpose to improve the knowledge of instructors about learners performance and provide better personalization with optimized intelligent tutoring systems. The proposed methodology is unfolded in three stages. First, the learning analytics summarization for initial exploratory purposes of learners experience and their behavior in e-learning environments. Subsequently, the exploration of possible interrelationships between metrics and the validation of the proposed learning analytics schemas, takes place. Lastly, the development of predictive models and simulation both on an aggregated and micro-level perspective through agent-based modeling is recommended, with the purpose to reinforce the feedback for instructors and intelligent tutoring systems. The study contributes to the knowledge expansion both for researchers and practitioners with the purpose to optimize the provided online learning experience. |
2019 |
Sant-Geronikolou, Stavroula; Kouis, Dimitris; Koulouris, Alexandros Capitalizing on new forms of academic library's intellectual assets: a new library mobile application proposition Journal Article In: Education and Information Technologies, vol. 24, no. 6, pp. 3707–3730, 2019, ISSN: 15737608. Abstract | Links | BibTeX | Tags: Academic libraries, Institutional shared analytics, Learning analytics, Library and information science, Library mobile application, Prototyping @article{Sant-Geronikolou2019, Library and information science experts around the globe are currently exploring ways of capitalizing student workflow data within library walls. Within this realm, the researchers designed and pilot-tested a user-driven lightweight application that envisions library as a crucial contributor of co-curricular data to learner profiles' contextual integrity. The prototype usability test conducted in December 2018 with the participation of 30 students at the University of West Attica, Greece, aimed not only to record participants' perspectives about the application but also to trace their attitudes towards this new kind of intervention. Post-test questionnaires yield a variety of positive rich-textured comments indicating students' interest in the emerging conversation around library use data capitalization. The participants felt positive about the need to develop a culture that fosters the reconsideration of library value constituents and their new dynamic role in the educational context. The pilot-tested application could serve as a reference for the improvement of academic library use data collection practices. |