Recognition of Learner's Personality Traits through Digital Annotations in Distance Learning
Nizar Omheni, Anis Kalboussi, ReDCAD Research Laboratory, Sfax University, Sfax, Tunisia ; Omar Mazhoud, Department of Computer Science, University of Kairouan, Kairouan, Tunisia ; Ahmed Kacem, ReDCAD Research Laboratory, Sfax University, Sfax, Tunisia
IJDET Volume 15, Number 1, ISSN 1539-3100 Publisher: IGI Global
Researchers in distance education are interested in observing and modelling of learner's personality profile, and adapting their learning experiences accordingly. When learners read and interact with their reading materials, they do unselfconscious activities like annotation which may be key feature of their personalities. Annotation activity requires the reader to be active, to think critically and to analyse what has been written, and to make specific annotations in the margins of the text. These traces are reflected through underlining, highlighting, scribbling comments, summarizing, asking questions, expressing confusion or ambiguity, and evaluating the content of reading. In this paper, the authors present a semi-automatic approach to build learners' personality profiles based on their annotation traces yielded during active reading sessions. The experimental results show the system's efficiency to measure, with reasonable accuracy, the scores of learner's personality traits.
Omheni, N., Kalboussi, A., Mazhoud, O. & Kacem, A. (2017). Recognition of Learner's Personality Traits through Digital Annotations in Distance Learning. International Journal of Distance Education Technologies, 15(1), 28-51. IGI Global.