HAPA: Harvester and Pedagogical Agents in E-learning Environments

  • Mirjana Ivanović Department of Mathematics and Informatics Faculty of Sciences, University of Novi Sad, Serbia
  • Dejan Mitrović Department of Mathematics and Informatics Faculty of Sciences, University of Novi Sad, Serbia
  • Zoran Budimac Department of Mathematics and Informatics Faculty of Sciences, University of Novi Sad, Serbia
  • Ljubomir Jerinić Department of Mathematics and Informatics Faculty of Sciences, University of Novi Sad, Serbia
  • Costin Bădică Computer and Information Technology Department Faculty of Automatics, Computers and Electronics, University of Craiova, Romania

Abstract

In the field of e-learning and tutoring systems two categories of software agents are of the special interest: harvester and pedagogical agents. This paper proposes a novel e-learning system that successfully combines both of these agent categories and introduces two distinct sub-types of pedagogical agents helpful and misleading. Whereas helpful agents provide the correct guidance for the given problem, misleading agents try to guide the learning process in the wrong direction by offering false hints and inadequate solutions. The rationale behind this approach is to motivate students not to trust the agent’s instructions blindly, but to employ critical thinking. Consequently, students will be put in a "softly stressed" environment in order to prepare them for real working environments in their future work in companies. Nevertheless students themselves will decide on the correct solution to the problem in question.

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Published
2015-04-01
How to Cite
IVANOVIĆ, Mirjana et al. HAPA: Harvester and Pedagogical Agents in E-learning Environments. INTERNATIONAL JOURNAL OF COMPUTERS COMMUNICATIONS & CONTROL, [S.l.], v. 10, n. 2, p. 200-210, apr. 2015. ISSN 1841-9844. Available at: <http://univagora.ro/jour/index.php/ijccc/article/view/1753>. Date accessed: 05 july 2020. doi: https://doi.org/10.15837/ijccc.2015.2.1753.

Keywords

E-learning, adaptability, personalization, intelligent agent, harvester agents, pedagogical agents