Framework to describe constructs of academic emotions using ontological descriptions of statistical models

Keiichi Muramatsu*, Eiichirou Tanaka, Keiichi Watanuki, Tatsunori Matsui

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

5 Citations (Scopus)


Many studies have been conducted during the last two decades examining learner reactions within e-learning environments. In an effort to assist learners in their scholastic activities, these studies have attempted to understand a learner’s mental states by analyzing participants’ facial images, eye movements, and other physiological indices and data. To add to this growing body of research, we have been developing the intelligent mentoring system (IMS), which performs automatic mentoring by using an intelligent tutoring system (ITS) to scaffold learning activities and an ontology to provide a specification of learner’s models. To identify learner’s mental states, the ontology operates on the basis of the theoretical and data-driven knowledge of emotions. In this study, we use statistical models to examine constructs of emotions evaluated in previous psychological studies and then produce a construct of academic boredom. In concrete terms, we develop ontological descriptions of academic boredom that are represented with statistical models. To evaluate the validity and utility of the descriptions, we conduct an experiment to obtain subjective responses regarding learners’ academic emotions in their university course and describe them as instances on the basis of the ontological descriptions.

Original languageEnglish
Article number5
JournalResearch and Practice in Technology Enhanced Learning
Issue number1
Publication statusPublished - 2016 Dec 1


  • Academic emotions
  • Boredom
  • Construct
  • Ontology

ASJC Scopus subject areas

  • Social Psychology
  • Education
  • Media Technology
  • Management of Technology and Innovation


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