Evaluation of an intelligent open learning system for engineering education

Maria Samarakou, Emmanouil Fylladitakis, Wolf-Gerrit Fruh, Dimitrios Karolidis, Antonis Hatziapostolou, Spyros Athinaios, Maria Grigoriadou

Research output: Contribution to journalArticlepeer-review

13 Citations (Scopus)
364 Downloads (Pure)


In computer-assisted education, the continuous monitoring and assessment of the learner is crucial for the delivery of personalized education to be effective. In this paper, we present a pilot application of the Student Diagnosis, Assistance, Evaluation System based on Artificial Intelligence (StuDiAsE), an open learning system for unattended student diagnosis, assistance and evaluation based on artificial intelligence. The system demonstrated in this paper has been designed with engineering students in mind and is capable of monitoring their comprehension, assessing their prior knowledge, building individual learner profiles, providing personalized assistance and, finally, evaluating a learner's performance both quantitatively and qualitatively by means of artificial intelligence techniques. The architecture and user interface of the system are being exhibited, the results and feedback received from a pilot application of the system within a theoretical engineering course are being demonstrated and the outcomes are being discussed.
Original languageEnglish
Pages (from-to)496–513
Number of pages18
JournalKnowledge Management and E-Learning: an International Journal
Issue number3
Publication statusPublished - Sept 2016


  • Interactive learning environment
  • student profiling
  • computer-assisted education
  • eLearning
  • online learning


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