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Recognition of Learner's Personality Traits through Digital Annotations in Distance Learning
ARTICLE

, , ReDCAD Research Laboratory, Sfax University, Sfax, Tunisia ; , Department of Computer Science, University of Kairouan, Kairouan, Tunisia ; , ReDCAD Research Laboratory, Sfax University, Sfax, Tunisia

IJDET Volume 15, Number 1, ISSN 1539-3100 Publisher: IGI Global

Abstract

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.

Citation

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. Retrieved April 9, 2020 from .

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