Teacher, Student and Domain Based Educational Recommender System for Assessing Student's Preferences on Multiple Recommendation Sources

EasyChair Preprint 1264

Abstract

In our modern world, preferences that learners have regarding the source of information they are receiving can be overwhelming, since the access to information and learning materials is almost unlimited due to the wide spread of online learning resources. In the educational environment, this implies the need to offer guidance to the student in terms of suggesting suitable materials to be studied along their learning path, and also the need to personalize these suggestions to correspond to each individual student’s preferences and learning requirements. Such recommendations, in in formal education, have multiple sources, such as the teacher, other students, and the domain of knowledge itself. In this research, the balance between these different recommendation sources, as well as the change of student dependency upon each one of them is investigated. An experimental procedure is designed and proposed in order to answer the question: How can different recommendation approaches and perspectives be fused and balanced in order to provide students with suitable and personalized recommendations on which topics to learn in a specific domain of learning. Since this experimental environment depends considerably on the feedback gained from students, the research is also intended to evaluate the role of conversational procedures as a mean of interacting with the user. Thus, a conversational voice-based engine is designed to provide a human-like interaction, which can help in validating the amount of feedback provided, in contrast to traditional click-based rating interfaces.

Keyphrases: Domain Networks, Domain Preferences, Educational Recommender System, Recommendation source, Recommender System, Teacher Preferences, student preferences, voice based conversational engine

@booklet{EasyChair:1264,
  author    = {Hasan Abu Rasheed and Christian Weber and Scott Harrison and Johannes Zenkert and Madjid Fathi},
  title     = {Teacher, Student and Domain Based Educational Recommender System for Assessing Student's Preferences on Multiple Recommendation Sources},
  howpublished = {EasyChair Preprint 1264},
  year      = {EasyChair, 2019}}