Building anEducational Social Media Application forHigher Education

Autor(en): Weber, F.
Dettmer, N.
Schurz, K.
Thelen, T. 
Herausgeber: Meiselwitz, G.
Stichwörter: Artificial intelligence; Digital Study Assistants (DSA); E-learning; Education technology; Educational Social Media Applications (edSMA); Educational social medium application; High educations; Higher education; Information management; Innovative education; Innovative education technologies; Innovative education technology; Learning management system; Learning Management Systems (LMS); Learning systems; Life cycle; Media application; Social media, Students; Social networking (online); Software design; Software prototyping; Software testing, Digital study assistant
Erscheinungsdatum: 2022
Herausgeber: Springer Science and Business Media Deutschland GmbH
Journal: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volumen: 13316 LNCS
Startseite: 210
Seitenende: 220
In this paper, we present an overview of an ongoing field study by the Siddata (Studienindividualisierung durch Digitale Datengestuetzte Assistenten [Joint project for Individualization of Studies through Digital, Data-Driven Assistants]) joint research project at the Universities of Bremen, Hannover, and Osnabrück in Northern Germany, with a digital data-driven study assistant (DSA), integrated into the local learning management system (LMS). Some of the included functions, especially those combining data from LMS, OER repositories, and user data with recommendation algorithms, are similar to functions of social media applications. Based on these similarities, we introduce the idea of educational social media applications (edSMA), which implement social media functions for educational purposes. Since 2018, four prototypes (P0, P1, P2, P3) have been developed, deployed, and tested in annual software development cycles. We overview the general user interaction schema, prototype, lifetimes, usage statistics, and features. A remarkable finding is a high demand for digital assistance in the early stages of the student life cycle. For any student differing from the default student, implicitly assumed by education systems, recommender systems can make less frequent educational opportunities accessible and consequently individualize educational pathways and increase equality. We conclude with an outlook on planned developments in the future, such as making the Siddata study assistant available for a broader range of students. © 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.
Conference of 14th International Conference on Social Computing and Social Media, SCSM 2022 Held as Part of the 24th HCI International Conference, HCII 2022 ; Conference Date: 26 June 2022 Through 1 July 2022; Conference Code:279329
ISBN: 9783031050633
ISSN: 0302-9743
DOI: 10.1007/978-3-031-05064-0_16
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