History, Architecture, and Future of a Digital Data-Driven Study Assistant

Autor(en): Weber, Felix
Schrumpf, Johannes
Dettmer, Niklas
Thelen, Tobias 
Stichwörter: Application programs; Artificial intelligence; Data driven; Digital datas; Digital student assistant; E - learning; E-learning; Innovative learning; Innovative learning technologies; Innovative learning technology; Learning systems; Learning technology; Self-regulated learning; Software design; Software development cycles; Students; Universal platform
Erscheinungsdatum: 2022
Herausgeber: International Association of Online Engineering
Journal: International Journal of Emerging Technologies in Learning
Volumen: 17
Ausgabe: 22
Startseite: 246 – 254
The SIDDATA data-driven digital study assistant offers students various services that help them identify and achieve their personal study goals. The software's features and infrastructure have evolved to become a universal platform for interactive self-regulated learning and digital study planning throughout three annual software development cycle iterations. The software is fully integrated into an existing learning management system (Stud.IP) and has been tested by more than 3000 students from three German universities during the last three years. This paper presents the SIDDATA software architecture, design philosophy, and modular, feature-centered application logic. Developed during a third-party-funded research project with limited temporal scope, the web-based software is publicly available under an MIT license. We conclude with application opportunities for researchers, developers, educators, and higher education institutions. © 2022, International Journal of Emerging Technologies in Learning. All Rights Reserved.
Cited by: 0; All Open Access, Gold Open Access, Green Open Access
ISSN: 1868-8799
DOI: 10.3991/ijet.v17i22.31887
Externe URL: https://www.scopus.com/inward/record.uri?eid=2-s2.0-85143803621&doi=10.3991%2fijet.v17i22.31887&partnerID=40&md5=e047f329aa6a2a7c84e7f61f97e3ad22

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