TOWARDS A USER FOCUSED DEVELOPMENT OF A DIGITAL STUDY ASSISTANT THROUGH A MIXED METHODS DESIGN
Autor(en): | Schurz, K. Schrumpf, J. Weber, F. Lübcke, M. Seyfeli, F. Wannemacher, K. |
Stichwörter: | AI in education; Design; Digital study assistant; Digital Study Assistant (DSA); E-learning; High educations; Higher education; Individual learning process; Information management; Innovative learning; Innovative learning management system; Innovative Learning Management Systems (LMS); Learning management system; Learning systems; Mixed method; Mixed method design; Mixed methods design; Recommender systems; Recommender systems, Artificial intelligence in education; User data, Students | Erscheinungsdatum: | 2021 | Herausgeber: | IADIS Press | Journal: | 18th International Conference on Cognition and Exploratory Learning in Digital Age, CELDA 2021 | Startseite: | 45 | Seitenende: | 52 | Zusammenfassung: | Digital Study Assistants (DSA) aim to support individual learning processes by designing them appropriately and efficiently based on recommendations. In this paper we present a prototype of a DSA for students in higher education of three German universities. The digital data driven DSA is integrated into the local learning management system and consists of recommender modules with a certain kind of recommendation for a specific purpose, e.g., recommending Academic Contacts that fit an expressed academic interest. The modules implemented so far use a wide range of methods: Classic rule-based Artificial Intelligence (AI) or Neural Networks, that can detect complex features and patterns in large data sets. To evaluate the current prototype of the DSA we used a mixed methods design approach with concurrently collected user data and qualitative data. A first insight in the user data suggests that recommender modules providing personalized recommendations are more likely to be used by students. A focus group discussion with students confirmed these findings with the suggestion to make the DSA more personal, individual, interactive, supportive, and user-friendly. In conclusion we present ideas for the further development of the prototype based on these findings. © 2021 Virtual Simulation Innovation Workshop, SIW 2021. All rights reserved. |
Beschreibung: | Conference of 18th International Conference on Cognition and Exploratory Learning in Digital Age, CELDA 2021 ; Conference Date: 13 October 2021 Through 15 October 2021; Conference Code:174791 |
ISBN: | 9789898704337 | Externe URL: | https://www.scopus.com/inward/record.uri?eid=2-s2.0-85124092521&partnerID=40&md5=ad10f5a990712eb0d474490c57136d75 |
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geprüft am 17.05.2024