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 language | English |
|---|---|
| Pages (from-to) | 863-868 |
| Number of pages | 6 |
| Journal | Computer Applications in Engineering Education |
| Volume | 27 |
| Issue number | 4 |
| DOIs | |
| Publication status | Published - 2019 Jul 1 |
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All Science Journal Classification (ASJC) codes
- Computer Science(all)
- Education
- Engineering(all)
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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 journal › Article
TY - JOUR
T1 - Development of assessment indicators for measuring the student learning effects of artificial intelligence-based robot design
AU - Shyr, Wen-Jye
AU - Yang, Fu Chun
AU - Liu, Po Wen
AU - Hsieh, Ying Ming
AU - You, Ci Syong
AU - Chen, Dyi-Cheng
PY - 2019/7/1
Y1 - 2019/7/1
N2 - 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.
AB - 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.
UR - http://www.scopus.com/inward/record.url?scp=85068962849&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85068962849&partnerID=8YFLogxK
U2 - 10.1002/cae.22118
DO - 10.1002/cae.22118
M3 - Article
AN - SCOPUS:85068962849
VL - 27
SP - 863
EP - 868
JO - Computer Applications in Engineering Education
JF - Computer Applications in Engineering Education
SN - 1061-3773
IS - 4
ER -