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

Keiichi Muramatsu, Eiichiro Tanaka, Keiichi Watanuki, Tatsunori Matsui

Research output: Contribution to journalArticle

2 Citations (Scopus)

Abstract

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
Volume11
Issue number1
DOIs
Publication statusPublished - 2016 Dec 1

Fingerprint

Statistical Models
Intelligent systems
Boredom
Ontology
boredom
Emotions
emotion
mentoring
ontology
Eye movements
Scaffolds
Learning
Eye Movements
Specifications
electronic learning
learning environment
Psychology
university
Experiments
experiment

Keywords

  • Academic emotions
  • Boredom
  • Construct
  • Ontology

ASJC Scopus subject areas

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

Cite this

@article{144fd355d9164cbe93e0dd944de53a1f,
title = "Framework to describe constructs of academic emotions using ontological descriptions of statistical models",
abstract = "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.",
keywords = "Academic emotions, Boredom, Construct, Ontology",
author = "Keiichi Muramatsu and Eiichiro Tanaka and Keiichi Watanuki and Tatsunori Matsui",
year = "2016",
month = "12",
day = "1",
doi = "10.1186/s41039-016-0029-1",
language = "English",
volume = "11",
journal = "Research and Practice in Technology Enhanced Learning",
issn = "1793-7078",
publisher = "Springer Open",
number = "1",

}

TY - JOUR

T1 - Framework to describe constructs of academic emotions using ontological descriptions of statistical models

AU - Muramatsu, Keiichi

AU - Tanaka, Eiichiro

AU - Watanuki, Keiichi

AU - Matsui, Tatsunori

PY - 2016/12/1

Y1 - 2016/12/1

N2 - 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.

AB - 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.

KW - Academic emotions

KW - Boredom

KW - Construct

KW - Ontology

UR - http://www.scopus.com/inward/record.url?scp=84986317060&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=84986317060&partnerID=8YFLogxK

U2 - 10.1186/s41039-016-0029-1

DO - 10.1186/s41039-016-0029-1

M3 - Article

VL - 11

JO - Research and Practice in Technology Enhanced Learning

JF - Research and Practice in Technology Enhanced Learning

SN - 1793-7078

IS - 1

M1 - 5

ER -