Adaptation of Artificial Intelligence Literacy Scale: Latent Profile Analysis
Artificial intelligence literacy is vital for individuals' adaptation to the future workforce and societal changes by enabling them to understand and effectively use AI technologies and critically evaluate their impact on society. In this study, the validity and reliability of the artificial in...
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| Language: | English |
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Sakarya University
2024-12-01
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| Series: | Sakarya University Journal of Education |
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| Online Access: | https://dergipark.org.tr/en/download/article-file/3909323 |
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| author | Mübin Kıyıcı Mehmet Yıldız Ali Kırksekiz Metin Yıldız |
| author_facet | Mübin Kıyıcı Mehmet Yıldız Ali Kırksekiz Metin Yıldız |
| author_sort | Mübin Kıyıcı |
| collection | DOAJ |
| description | Artificial intelligence literacy is vital for individuals' adaptation to the future workforce and societal changes by enabling them to understand and effectively use AI technologies and critically evaluate their impact on society. In this study, the validity and reliability of the artificial intelligence literacy scale in Turkish language were tested and the latent profiles of the students were determined. This methodological study was carried out with a total of 729 students between December 2023 and February 2024. Validity and reliability analyses were conducted with SPSS 27 and AMOS 24, and latent profile analysis was handled with R programming language. According to the results of the CFA analysis of the Artificial Intelligence Literacy Scale, the fit indices were found to be significant (X²/sd= 3.832, RMSEA=.062, CFI=.949, AGFI=.933, GFI=.960, NFI=.949, TLI=.928, IFI=.916). Considering the Cronbach Alpha value of the scale consisting of 4 sub-dimensions and 12 items, the internal consistency coefficientwas found to be 0.814. Since the lowest BIC value in the latent profile analysis was found in the VVV model, the VVV model was considered as the appropriate one in the study, and the class analyses were carried out through this model. With the LPA analysis, it was designated that the scale was divided into 3 classes. It was determined that the Artificial intelligence literacy scale is a valid and reliable measurement tool. After latent profile analysis, it was found out that the scale was divided into 3 classes. |
| format | Article |
| id | doaj-art-f195e674b7db4582b9336fc05bb6cd39 |
| institution | Kabale University |
| issn | 2146-7455 |
| language | English |
| publishDate | 2024-12-01 |
| publisher | Sakarya University |
| record_format | Article |
| series | Sakarya University Journal of Education |
| spelling | doaj-art-f195e674b7db4582b9336fc05bb6cd392025-01-07T08:59:44ZengSakarya UniversitySakarya University Journal of Education2146-74552024-12-0114358159610.19126/suje.147929428Adaptation of Artificial Intelligence Literacy Scale: Latent Profile AnalysisMübin Kıyıcı0https://orcid.org/0000-0001-9458-7831Mehmet Yıldız1https://orcid.org/0000-0002-9523-3805Ali Kırksekiz2https://orcid.org/0000-0002-7873-3402Metin Yıldız3https://orcid.org/0000-0003-0122-5677SAKARYA UNIVERSITYSAKARYA UYGULAMALI BİLİMLER ÜNİVERSİTESİSAKARYA UYGULAMALI BİLİMLER ÜNİVERSİTESİSAKARYA UNIVERSITYArtificial intelligence literacy is vital for individuals' adaptation to the future workforce and societal changes by enabling them to understand and effectively use AI technologies and critically evaluate their impact on society. In this study, the validity and reliability of the artificial intelligence literacy scale in Turkish language were tested and the latent profiles of the students were determined. This methodological study was carried out with a total of 729 students between December 2023 and February 2024. Validity and reliability analyses were conducted with SPSS 27 and AMOS 24, and latent profile analysis was handled with R programming language. According to the results of the CFA analysis of the Artificial Intelligence Literacy Scale, the fit indices were found to be significant (X²/sd= 3.832, RMSEA=.062, CFI=.949, AGFI=.933, GFI=.960, NFI=.949, TLI=.928, IFI=.916). Considering the Cronbach Alpha value of the scale consisting of 4 sub-dimensions and 12 items, the internal consistency coefficientwas found to be 0.814. Since the lowest BIC value in the latent profile analysis was found in the VVV model, the VVV model was considered as the appropriate one in the study, and the class analyses were carried out through this model. With the LPA analysis, it was designated that the scale was divided into 3 classes. It was determined that the Artificial intelligence literacy scale is a valid and reliable measurement tool. After latent profile analysis, it was found out that the scale was divided into 3 classes.https://dergipark.org.tr/en/download/article-file/3909323artificial intelligenceliteracyscale adaptationlatent profile analysis |
| spellingShingle | Mübin Kıyıcı Mehmet Yıldız Ali Kırksekiz Metin Yıldız Adaptation of Artificial Intelligence Literacy Scale: Latent Profile Analysis Sakarya University Journal of Education artificial intelligence literacy scale adaptation latent profile analysis |
| title | Adaptation of Artificial Intelligence Literacy Scale: Latent Profile Analysis |
| title_full | Adaptation of Artificial Intelligence Literacy Scale: Latent Profile Analysis |
| title_fullStr | Adaptation of Artificial Intelligence Literacy Scale: Latent Profile Analysis |
| title_full_unstemmed | Adaptation of Artificial Intelligence Literacy Scale: Latent Profile Analysis |
| title_short | Adaptation of Artificial Intelligence Literacy Scale: Latent Profile Analysis |
| title_sort | adaptation of artificial intelligence literacy scale latent profile analysis |
| topic | artificial intelligence literacy scale adaptation latent profile analysis |
| url | https://dergipark.org.tr/en/download/article-file/3909323 |
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