Chatbots as a Tool to Scale Mentoring Processes: Individually Supporting Self-Study in Higher Education

• Main Authors: Alexander Tobias Neumann, Tamar Arndt, Laura Köbis, Roy Meissner, Anne Martin, Peter de Lange, Norbert Pengel, Ralf Klamma, Heinz-Werner Wollersheim
• Format: Article
• Language: English
• Published: Frontiers Media S.A. 2021-05-01
• Series: Frontiers in Artificial Intelligence
• Subjects: automated feedback; chatbot; mentoring; self-study activities; technology-enhanced learning
• Online Access: https://www.frontiersin.org/articles/10.3389/frai.2021.668220/full

Like most curricula in the humanities and social sciences, the curriculum of pre-service teacher training in educational sciences often includes time-consuming reading and writing tasks, which require high quality support and feedback in a timely manner. A well-known way to provide this support to students is one-to-one mentoring. However, limited time and resources in the German university context require to effectively scale the benefits of individual feedback. The use of scalable technologies to support learning processes seems to be promising, but its development usually requires a deep technical understanding. With an interdisciplinary approach, this contribution investigates how personal mentoring can be made available to as many students as possible, taking into account the didactic, organizational and technical frameworks at universities. We describe the development and implementation process of two chatbots that both aim to support students of educational sciences in their self-study of the seminar topics and literature. The chatbots were used by over 700 students during the course of 1 year and our evaluations show promising results that bear the potential to improve the availability of digital mentoring support for all students.