Analysis of Artificial Intelligence Literacy in the Blended Learning Model in Higher Education - Fathahillah Fathahillah; M. Miftach Fakhri; Ansari Saleh Ahmar (EduLine: Journal of Education and Learning Innovation, 2023)
The purpose of the study was to determine the literacy of artificial intelligence in the blended learning model by looking at the influence of: (1) introduction to artificial intelligence (IAI) on data security and privacy (DSP), (2) Advantages and Disadvantages of Artificial Intelligence (ADAI) on DSP, (3) Implications of Artificial Intelligence (IAII) on DSP, (4) IAI on DSP moderated by Ethics and Laws of Artificial Intelligence (ELAI), (5) ADAI on DSP moderated by ELAI, (6) IAII on DSP moderated by ELAI, and (7) ELAI on DSP. The research design is expost de facto. The research sample is 4th semester 2021 students who have studied web programming courses in the department of informatics and computer engineering with a total of 156 students. Data analysis with partial least square (PLS) using the SmartPLS application. The results showed that: (1) IAI has a positive but insignificant effect on DSP, (2) ADAI has a positive and significant effect on DSP, (3) IAII has a positive and significant effect on DSP, (4) IAI has no positive and insignificant effect on DSP moderated by ELAI, (5) ADAI has a positive and significant effect on DSP moderated by ELAI, (6) IAII has no positive and insignificant effect on DSP moderated by ELAI, and (7) ELAI has a positive and significant effect on DSP. In addition, the analysis results show an acceptable level of variance of the lecturer trust model (68.8%). This means that there is 31.2% variance in the dependent variable explained by other factors.