Developing a Curriculum Framework of Artificial Intelligence Teaching for Gifted Students

Mehmet Aydın; Halil Yurdugül

Article Details

Developing a Curriculum Framework of Artificial Intelligence Teaching for Gifted Students

Authors:

Mehmet Aydın | Halil Yurdugül

Publisher:

Kastamonu University

Main Topics:

Eğitimde Program Geliştirme

Journal:

Kastamonu Eğitim Dergisi Vol.32 Issue 1, pp.14-37

Document Type:

Article

Publication Date:

1/2024

Document Language:

English

Document ID (Org No.):

2001310609

pISSN:

2147-9844

Keywords:

Abstract:

 Purpose: The aim of this study is to determine the artificial intelligence AI subjects that can be handled at the beginner level for gifted students at the 6th grade -10th level studying in Science and Art Centers BİLSEMs and to prepare a framework curriculum for artificial intelligence to guide teachers. DesignMethodologyApproach: This study was also considered as a design-based research; however, it was limited to needs analysis and design dimensions. In the needs analysis phase of this study, content analysis of existing curricula was used and in the design phase, quantitative analysis based on expert opinions was used. Within the scope of the needs analysis, 54 curricula structured at undergraduate and graduate levels of 41 different universities were examined. An AI subject list was created by examining the subjects included in AI curriculums. In the design phase, the AI subject list was presented to the expert opinion. Content validity criterion was used to determine whether each topic predicted by the experts to be in the AI curriculum was statistically significant. Hierarchical clustering analysis was also applied to the data set including the subject that the experts marked from the subject list. Based on the content validity rates CVR and hierarchical clustering analysis, the framework curriculum was created by determining the prominent topics. Findings: According to the opinions of 20 experts in the research, it was seen that eight AI subjects were at the minimum CVR value and above. In the grouping made with cluster analysis, 13 subjects were obtained. Although there is a great deal of similarity between CVR and cluster analysis results, minor differences emerged between them. Based on both analyses, 6 learning domains and 22 sub-learning domains were determined regarding the subjects to be included in the curriculum. Highlights: When compared to the studies on AI education in the literature, the prepared curriculum mostly overlaps with machine learning techniques and learning from data. There is a need to design, implement and evaluate the results of different activities aimed at the acquisitions of the curriculum put forward as a result of the study.

 Purpose: The aim of this study is to determine the artificial intelligence AI subjects that can be handled at the beginner level for gifted students at the 6th grade -10th level studying in Science and Art Centers BİLSEMs and to prepare a framework curriculum for artificial intelligence to guide teachers. DesignMethodologyApproach: This study was also considered as a design-based research; however, it was limited to needs analysis and design dimensions. In the needs analysis phase of this study, content analysis of existing curricula was used and in the design phase, quantitative analysis based on expert opinions was used. Within the scope of the needs analysis, 54 curricula structured at undergraduate and graduate levels of 41 different universities were examined. An AI subject list was created by examining the subjects included in AI curriculums. In the design phase, the AI subject list was presented to the expert opinion. Content validity criterion was used to determine whether each topic predicted by the experts to be in the AI curriculum was statistically significant. Hierarchical clustering analysis was also applied to the data set including the subject that the experts marked from the subject list. Based on the content validity rates CVR and hierarchical clustering analysis, the framework curriculum was created by determining the prominent topics. Findings: According to the opinions of 20 experts in the research, it was seen that eight AI subjects were at the minimum CVR value and above. In the grouping made with cluster analysis, 13 subjects were obtained. Although there is a great deal of similarity between CVR and cluster analysis results, minor differences emerged between them. Based on both analyses, 6 learning domains and 22 sub-learning domains were determined regarding the subjects to be included in the curriculum. Highlights: When compared to the studies on AI education in the literature, the prepared curriculum mostly overlaps with machine learning techniques and learning from data. There is a need to design, implement and evaluate the results of different activities aimed at the acquisitions of the curriculum put forward as a result of the study.

 Purpose: The aim of this study is to determine the artificial intelligence AI subjects that can be handled at the beginner level for gifted students at the 6th grade -10th level studying in Science and Art Centers BİLSEMs and to prepare a framework curriculum for artificial intelligence to guide teachers. DesignMethodologyApproach: This study was also considered as a design-based research; however, it was limited to needs analysis and design dimensions. In the needs analysis phase of this study, content analysis of existing curricula was used and in the design phase, quantitative analysis based on expert opinions was used. Within the scope of the needs analysis, 54 curricula structured at undergraduate and graduate levels of 41 different universities were examined. An AI subject list was created by examining the subjects included in AI curriculums. In the design phase, the AI subject list was presented to the expert opinion. Content validity criterion was used to determine whether each topic predicted by the experts to be in the AI curriculum was statistically significant. Hierarchical clustering analysis was also applied to the data set including the subject that the experts marked from the subject list. Based on the content validity rates CVR and hierarchical clustering analysis, the framework curriculum was created by determining the prominent topics. Findings: According to the opinions of 20 experts in the research, it was seen that eight AI subjects were at the minimum CVR value and above. In the grouping made with cluster analysis, 13 subjects were obtained. Although there is a great deal of similarity between CVR and cluster analysis results, minor differences emerged between them. Based on both analyses, 6 learning domains and 22 sub-learning domains were determined regarding the subjects to be included in the curriculum. Highlights: When compared to the studies on AI education in the literature, the prepared curriculum mostly overlaps with machine learning techniques and learning from data. There is a need to design, implement and evaluate the results of different activities aimed at the acquisitions of the curriculum put forward as a result of the study.

 Purpose: The aim of this study is to determine the artificial intelligence AI subjects that can be handled at the beginner level for gifted students at the 6th grade -10th level studying in Science and Art Centers BİLSEMs and to prepare a framework curriculum for artificial intelligence to guide teachers. DesignMethodologyApproach: This study was also considered as a design-based research; however, it was limited to needs analysis and design dimensions. In the needs analysis phase of this study, content analysis of existing curricula was used and in the design phase, quantitative analysis based on expert opinions was used. Within the scope of the needs analysis, 54 curricula structured at undergraduate and graduate levels of 41 different universities were examined. An AI subject list was created by examining the subjects included in AI curriculums. In the design phase, the AI subject list was presented to the expert opinion. Content validity criterion was used to determine whether each topic predicted by the experts to be in the AI curriculum was statistically significant. Hierarchical clustering analysis was also applied to the data set including the subject that the experts marked from the subject list. Based on the content validity rates CVR and hierarchical clustering analysis, the framework curriculum was created by determining the prominent topics. Findings: According to the opinions of 20 experts in the research, it was seen that eight AI subjects were at the minimum CVR value and above. In the grouping made with cluster analysis, 13 subjects were obtained. Although there is a great deal of similarity between CVR and cluster analysis results, minor differences emerged between them. Based on both analyses, 6 learning domains and 22 sub-learning domains were determined regarding the subjects to be included in the curriculum. Highlights: When compared to the studies on AI education in the literature, the prepared curriculum mostly overlaps with machine learning techniques and learning from data. There is a need to design, implement and evaluate the results of different activities aimed at the acquisitions of the curriculum put forward as a result of the study.

Article Details

Developing a Curriculum Framework of Artificial Intelligence Teaching for Gifted Students

Authors:

Mehmet Aydın | Halil Yurdugül

Publisher:

Kastamonu University

Main Topics:

Eğitimde Program Geliştirme

Journal:

Kastamonu Eğitim Dergisi Vol.32 Issue 1, pp.14-37

Document Type:

Article

Publication Date:

1/2024

Document Language:

English

Document ID (Org No.):

2001310609

pISSN:

2147-9844

Artificial Intelligence

BİLSEM

Gifted Students

Curriculum

Special Ability

Issues

Article Details

Developing a Curriculum Framework of Artificial Intelligence Teaching for Gifted Students

Authors: Mehmet Aydın | Halil Yurdugül

Publisher: Kastamonu University

Main Topics: Eğitimde Program Geliştirme

Journal: Kastamonu Eğitim Dergisi Vol.32 Issue 1, pp.14-37

Document Type: Article

Publication Date: 1/2024

Document Language: English

Document ID (Org No.): 2001310609

pISSN: 2147-9844

Artificial Intelligence

BİLSEM

Gifted Students

Curriculum

Special Ability

Issues

Authors:

Mehmet Aydın | Halil Yurdugül

Publisher:

Kastamonu University

Main Topics:

Eğitimde Program Geliştirme

Journal:

Kastamonu Eğitim Dergisi Vol.32 Issue 1, pp.14-37

Document Type:

Article

Publication Date:

1/2024

Document Language:

English

Document ID (Org No.):

2001310609

pISSN:

2147-9844