본문 바로가기
  • Home

Design of Teaching-Learning Plan Based on Instructional Strategy Ontology of Direct Instruction Model

  • Journal of Knowledge Information Technology and Systems
  • Abbr : JKITS
  • 2017, 12(1), pp.59-67
  • DOI : 10.34163/jkits.2017.12.1.006
  • Publisher : Korea Knowledge Information Technology Society
  • Research Area : Interdisciplinary Studies > Interdisciplinary Research
  • Published : February 28, 2017

Lee, Jae Mu 1

1부산교육대학교

Accredited

ABSTRACT

This study is to build an instructional strategy ontology to aid the effective design of a Teaching-Learning plan for novice designers who lack instructional design knowledge. Most of designer tend to represent ambiguously the instructional strategy. Therefore they need to provide fluently learning procedures and activities to achieve the learning goals. The Instructional model was selected as a direct instructional model that is appropriate for learning computer skills and is used widely in computer education field. This study constructed instructional strategy ontology for direct instruction model using ontology authoring tools. The study proposes a method for designing a Teaching-Learning plan in addition to analysis effects through the questionnaire. This method uses instructional strategy ontology of direct instruction model that was built by the author. The instructional ontology can be shared and reused among the designers. The proposed method made a Teaching-Learning plan that could describe teacher’ and learner’s activities concretely by decomposed instructional strategy. Finally, it made a Teaching-Learning plan with fluent content using instructional strategy ontology for novice designers. Moreover, it supports a balanced design considering the overall structure through the visual interface. However, we have limitations as this study proposes the only design method for Teaching-Learning plan using instructional strategy ontology. In the future, we will need further researches to support the automatic design of Teaching-Learning plan with intelligent facilities.

Citation status

* References for papers published after 2023 are currently being built.