Validity and Reliability Study of a Turkish Form of the Machine Learning Attitude Scale

Abstract

This study aims to adapt the learners’ machine learning technologies attitude scale to Turkish. Participants of the study are 309 university students. Confirmatory factor analysis (CFA) was used on data obtained from Turkish students for construct validity of the scale. Following this, 23 items were excluded. A confirmatory factor analysis was performed again, completing adaptation of the scale to Turkish. Three reasons for excluding the items and factor following the confirmatory factor analysis emerged: item structure, domain self-efficacy, and the cultural adaptation process. This study has enabled the scale of attitudes toward artificial intelligence to be adapted to Turkish specifically for machine learning techniques and technologies. The scale can be used as a resource for further studies.

Keywords

• Artificial intelligence
• Machine learning
• Attitude
• Scale adaptation
• Teacher candidates

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