Best Paper Award der 18. Internationalen Tagung Wirtschaftsinformatik
Auf der 18. Internationalen Tagung Wirtschaftsinformatik (WI) wurde der Artikel ?Addressing Learners' Heterogeneity in Higher Education: An Explainable AI-based Feedback Artifact for Digital Learning Environments“, der aus einer Zusammenarbeit des LifBi (Philipp Handschuh, Maria Klose) und der Universit?t Bamberg (Felix Haag, Sebastian Günther, Konstantin Hopf, Thorsten Staake) hervorgegangen ist, mit dem Best Paper Award ausgezeichnet. Die WI Konferenz gilt als die bedeutendste wissenschaftliche Konferenz für Wirtschaftsinformatik im deutschsprachigen Raum und fand in diesem Jahr in Paderborn unter dem Leitmotto ?Digital Responsibility: Social, Ethical, Ecological Implications of IS“ statt. Mit der Auszeichnung würdigt die Konferenz die Exzellenz der Beitr?ge des pr?mierten Artikels.
Abstract: Due to the advent of digital learning environments and the freedom they offer for learners, new challenges arise for students' self-regulated learning. To overcome these challenges, the provision of feedback has led to excellent results, such as less procrastination and improved academic performance. Yet, current feedback artifacts neglect learners’ heterogeneity when it comes to prescriptive feedback that should meet personal characteristics and self-regulated learning skills. In this paper, we derive requirements from self-regulated learning theory for a feedback artifact that takes learners’ heterogeneity into account. Based on these requirements, we design, instantiate, and evaluate an Explainable AI-based approach. The results demonstrate that our artifact is able to detect promising patterns in data on learners' behaviors and characteristics. Moreover, our evaluation suggests that learners perceive our feedback as valuable. Ultimately, our study informs Information Systems research in the design of future Explainable AI-based feedback artifacts that seek to address learners' heterogeneity.