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European First Year Experience Conference 2017, Date: 2017/06/28 - 2017/06/30, Location: Birmingham

Publication date: 2017-06-01

Author:

De Laet, Tinne
Charleer, Sven ; Verbert, Katrien ; Langie, Greet ; Van Soom, Carolien

Abstract:

Each year around 2500 new students enroll in the bachelor programs of the Faculties of Science, Engineering Science, Engineering Technology, and Bio-engineering at the KU Leuven. The Flemish (Belgium) higher education system presents the universities with a particular challenge as they have to accept all students with a secondary education diploma (no selection is allowed, except for the Bachelors of Medicine and Dentistry). As a result, not all students have the right qualifications for the programs and the overall drop-out rate is around 40%. Both KU Leuven researchers, student support services, tutorial services, teachers, etc. heavily invest in advising students before and throughout their first-year (Vanderoost et al. 2014; Vanderoost et al. 2015; Callens et al. 2016). Due to the particular Flemish context, the focus is not only on retention but also on in-time reorientation to a bachelor’s program that better fits the student’s interests, skills, and qualifications. The ABLE Erasmus+ project (“ABLE Project” 2017), Achieving Benefits from LEarning analytics, explores how learning analytics can be used to support both staff and students in higher education. The partners, Nottingham Trent University (UK), KU Leuven (Belgium) and Universiteit Leiden (Netherlands) focus on the first-year experience. Learning analytics (LA) is 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 (Ferguson 2012). The objectives of learning analytics are manifold, from identification of at-risk students over predictive analytics to the personalization of learning content and contexts, to support teachers, students, study advisors, etc. (Verbert et al. 2012) . Our work focuses on how to use learning analytics to support the live interaction between study advisors and first-year students. To this end, a dashboard was designed and developed that provides an at-a-glance overview of the “facts”: • the obtained grades for the different test moments, • the positioning of the individual grades with respect to the peers (histogram), • the overall position with respect to the peers, and • a “predictive” part that shows the number of years students with similar results needed to obtain the bachelor degree. The picture below provides a view of the dashboard. During the academic year 2016-2017 the Faculty of Science, Engineering Science, Engineering Technology, and Bio-engineering deployed this dashboard during the conversations with students after receiving their results for the first examination period (January 2017). The study advisor and the student in need for support are challenged to supplement these facts with personal information and individual circumstances, as to obtain a complete picture of the student’s study experience. In the session we will present the feedback of student advisors obtained during the dashboard development, and the evaluation results of both students and study advisors after the dashboard deployment. We will carefully formulate the pros and cons of the current approach and provide hints for further development. “ABLE Project.” 2017. Accessed January 2. http://www.ableproject.eu/. Callens, Riet (KU Leuven), Tinne (KU Leuven) De Laet, Koen (KU Leuven) Paes, Jef (KU Leuven) Vanderoost, An (KU Leuven) Vanfroyenhoven, and Jasper (KU Leuven) Witters. 2016. “Feedback Path for First Year Students Engineering Science: A Data-Based Approach.” In EUROPEAN FIRST YEAR EXPERIENCE CONFERENCE 2016, 1–4. Ferguson, R. 2012. “Learning Analytics: Drivers, Developments and Challenges.” International Journal of Technology Enhanced Learning 4 (5/6): 304–317. doi:10.1504/IJTEL.2012.051816. Vanderoost, Jef (KU Leuven), Riet (KU Leuven) Callens, Joos (KU Leuven) Vandewalle, and Tinne (KU Leuven) De Laet. 2014. “Engineering Positioning Test in Flanders : A Powerful Predictor for Study Success ? Conference Topic : The Attractiveness of Engineering ; Education Al Research Methods INTRODUCTION.” In Proceedings of the 42nd Annual SEFI Conference. Vanderoost, Jef (KU Leuven), Carolien (KU Leuven) Vansoom, Greet (KU Leuven) Langie, Johan (KU Leuven) Van den Bossche, Riet (KU Leuven) Callens, Joos (KU Leuven) Vandewalle, and Tinne (KU Leuven) De Laet. 2015. “Engineering and Science Positioning Tests in Flanders : Powerful Predictors for Study Success ?” In Proceedings of the 43nd Annual SEFI Conference. Verbert, Katrien, Nikos Manouselis, Hendrik Drachsler, and Erik Duval. 2012. “Dataset-Driven Research to Support Learning and Knowledge Analytics.” Educational Technology & Society 15: 133–48.