Automated Author ProfileKiremit, Birgül Yabana
Kiremit, Birgül Yabana
Current S-Index
Sum of Dataset Indices for all datasets
Average Dataset Index per Dataset
Average Dataset Index per dataset
Total Datasets
Total datasets for this author
Average FAIR Score
Average FAIR Score per dataset
Total Citations
Total citations to the author's datasets
Total Mentions
Total mentions of the author's datasets
S-Index Interpretation
The S-Index (Sharing Index) is a comprehensive metric that represents the cumulative impact of all your datasets. It is calculated as the sum of Dataset Index scores across all your claimed datasets.
What it means:
- A higher S-index indicates greater overall impact of your datasets relative to typical datasets in their fields of research
- The S-Index grows as you add more datasets or as existing datasets gain more citations and mentions
- It provides a single number to track your research data impact over time
Current S-Index: 1.6 (sum of 2 datasets Dataset Index scores)
More information here.
S-Index Over Time
Cumulative Citations Over Time
Cumulative Mentions Over Time
Datasets
Artificial intelligence (AI) literacy is the ability to understand, use, monitor, and critically evaluate AI applications without needing to create AI models. As many professionals outside technical fields frequently engage with AI, this literacy is essential. This study evaluates the validity and reliability of the Turkish adaptation of the Artificial Intelligence Literacy Scale (AILS) to measure AI literacy among healthcare professionals in Türkiye. The study included 210 healthcare professionals—physicians, dentists, nurses, and midwives—aged 18 and older. AILS is a seven-point Likert scale with 12 items divided into four factors: “awareness,” “usage,” “evaluation,” and “ethics.” Cronbach’s alpha indicated good internal consistency for the scale, with a coefficient of 0.85. Confirmatory Factor Analysis (CFA) showed satisfactory fit indices: χ2/df = 1.665, Comparative Fit Index = 0.968, Goodness of Fit Index = 0.944, Tucker-Lewis Index = 0.955, Standardized Root Mean Square Residual = 0.040, and Root Mean Square Error Estimate = 0.056. The 12-item, 4-factor AILS shows a strong fit and robust structure for the sample data. Our study validates the Turkish version of the AILS as a reliable tool for assessing artificial intelligence literacy among Turkish healthcare professionals.
Authors
- Kiremit, Birgül Yabana
Artificial intelligence (AI) literacy is the ability to understand, use, monitor, and critically evaluate AI applications without needing to create AI models. As many professionals outside technical fields frequently engage with AI, this literacy is essential. This study evaluates the validity and reliability of the Turkish adaptation of the Artificial Intelligence Literacy Scale (AILS) to measure AI literacy among healthcare professionals in Türkiye. The study included 210 healthcare professionals—physicians, dentists, nurses, and midwives—aged 18 and older. AILS is a seven-point Likert scale with 12 items divided into four factors: “awareness,” “usage,” “evaluation,” and “ethics.” Cronbach’s alpha indicated good internal consistency for the scale, with a coefficient of 0.85. Confirmatory Factor Analysis (CFA) showed satisfactory fit indices: χ2/df = 1.665, Comparative Fit Index = 0.968, Goodness of Fit Index = 0.944, Tucker-Lewis Index = 0.955, Standardized Root Mean Square Residual = 0.040, and Root Mean Square Error Estimate = 0.056. The 12-item, 4-factor AILS shows a strong fit and robust structure for the sample data. Our study validates the Turkish version of the AILS as a reliable tool for assessing artificial intelligence literacy among Turkish healthcare professionals.
Authors
- Kiremit, Birgül Yabana