Caught in the Lifelong Learning Maze: Helping People with Learning Analytics and Chatbots to Find Personal Career Paths

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.