Manuscript received September 25, 2022; revised October 23, 2022; accepted November 23, 2022.
Abstract—Current lifelong learning platforms offer users a
query option to select a wide variety of courses. However,
finding a suitable course among the seemingly endless catalogs
of options presented by the platforms is not
straightforward. We argue that digital counseling can enhance
this process. In this paper, we present a set of three formative
studies where we explored the main aspects that can provide the
counseling needed. The methods comprise an analysis of user
profile characteristics and learning analytics indicators (e.g.,
learning progress/self-regulation) by means of an expert
workshop, evaluating the feasibility of current technologies (e.g.,
natural language processing) for automatically assessing users'
competencies, and a survey on the use of Chatbots as the
interaction interface between the users and the lifelong learning
portals. The analysis resulted in the extraction of basic
requirements for digital counseling. We conclude the paper by
presenting a system design derived from these studies.
Index Terms—Learning analytics, indicators, dashboard,
Chatbot, lifelong learning, natural language processing
The authors are with the DIPF | Leibniz Institute for Research and
Information in Education, Frankfurt, Germany.
*Correspondence: a.ahmad@dipf.de (A.A.)
Cite: Atezaz Ahmad*, Natalie Kiesler, Daniel Schiffner, Jan Schneider, and Sebastian Wollny, "Caught in the Lifelong Learning Maze: Helping People with Learning Analytics and Chatbots to Find Personal Career Paths," International Journal of Information and Education Technology vol. 13, no. 3, pp. 423-429, 2023.
Copyright © 2023 by the authors. This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).