An Advanced eLearning Environment Developed for Engineering Learners

Maria Samarakou, Emmanouil Fylladitakis, Wolf-Gerrit Fruh, Antonis Hatziapostolou, John J Gelegenis

Research output: Contribution to journalArticlepeer-review

5 Citations (Scopus)
82 Downloads (Pure)

Abstract

Monitoring and evaluating engineering learners through computer-based laboratory exercises is a difficult task, especially under classroom conditions. A complete diagnosis requires the capability to assess both the competence of the learner to use the scientific software and the understanding of the theoretical principles. This monitoring and evaluation needs to be continuous, unobtrusive and personalized in order to be effective. This study presents the results of the pilot application of an eLearning environment developed specifically with engineering learners in mind. As its name suggests, the Learner Diagnosis, Assistance, and Evaluation System based on Artificial Intelligence (StuDiAsE) is an Open Learning Environment that can perform unattended diagnostic, evaluation and feedback tasks based on both quantitative and qualitative parameters. The base architecture of the system, the user interface and its effect on the performance of postgraduate engineering learners are being presented.
Original languageEnglish
Pages (from-to)22-33
JournalInternational Journal of Emerging Technologies in Learning
Volume10
Issue number3
Publication statusPublished - 2015

Keywords

  • Electronic Learning
  • Engineering Education
  • Semisupervised Learning
  • Unsupervised learning

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