Development of assessment indicators for measuring the student learning effects of artificial intelligence-based robot design

Wen-Jye Shyr, Fu Chun Yang, Po Wen Liu, Ying Ming Hsieh, Ci Syong You, Dyi-Cheng Chen

Research output: Contribution to journalArticle

Abstract

This study identified a number of indicators that are essential for measuring the learning effects on students involved in artificial intelligence (AI)-based robot design. Ten experts were recruited as Delphi group members, including three mechanical engineers in the field of robot design and seven scholars from a university. The data collected from the questionnaires were analyzed using Z values from the Kolmogorov–Smirnov test. The questionnaire was used to identify assessment indicators in six dimensions: (a) Remember, (b) understand, (c) apply, (d) analyze, (e) evaluate, and (f) create. Our findings provide a valuable reference for educators in the field of engineering and technology education involved in the development of programs in AI-based robot design.

Original languageEnglish
Pages (from-to)863-868
Number of pages6
JournalComputer Applications in Engineering Education
Volume27
Issue number4
DOIs
Publication statusPublished - 2019 Jul 1

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learning success
artificial intelligence
robot
Artificial intelligence
Robots
Students
questionnaire
student
group membership
engineer
Education
expert
educator
engineering
Engineers
university
Values
education

All Science Journal Classification (ASJC) codes

  • Computer Science(all)
  • Education
  • Engineering(all)

Cite this

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Development of assessment indicators for measuring the student learning effects of artificial intelligence-based robot design. / Shyr, Wen-Jye; Yang, Fu Chun; Liu, Po Wen; Hsieh, Ying Ming; You, Ci Syong; Chen, Dyi-Cheng.

In: Computer Applications in Engineering Education, Vol. 27, No. 4, 01.07.2019, p. 863-868.

Research output: Contribution to journalArticle

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