EduLine: Journal of Education and Learning Innovation
Vol. 3 No. 4 (2023), Pages 566-575 · 2023-12-30
OriginalPaper | Open access | Published: December 30, 2023
Analysis of Artificial Intelligence Literacy in the Blended Learning Model in Higher Education
- Publication History
- Published online: December 30, 2023
- DOI
- https://doi.org/10.35877/454RI.eduline2049
- Copyright
- Copyright (c) 2023 Fathahillah, M. Miftach Fakhri, Ansari Saleh Ahmar
Abstract
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.
Keywords
References (32)
- Badri, M., Rashedi, A. Al, Yang, G., Mohaidat, J., & Hammadi, A. Al. (2016). Students’ Intention to Take Online Courses in High School: A Structural Equation Model of Causality and Determinants. Education and Information Technologies, 21(2), 471–497.
- Barclay, D., Higgins, C., & Thompson, R. (1995). The Partial Least Square (PLS). Approach to Causal Modeling: Personal Computer Adoption and Use as an Illustration. Technol. Stud, 2(2).
- Calatayud, V., Espinosa, M., & Roig-Vila, R. (2021). Artificial intelligence for student assessment: a systematic review". Applied Sciences, 11(12), 5467. https://doi.org/10.3390/app11125467
- Chan, E. (2019). Blended learning dilemma: teacher education in the confucian heritage culture". Australian Journal of Teacher Education, 36–51. https://doi.org/10.14221/ajte.2018v44n1.3
- Conijn, R., Martinez-Maldonado, R., Knight, S., Shum, S., Waes, L., & Zaanen, M. (2020). How to provide automated feedback on the writing process? a participatory approach to design writing analytics tools". Computer Assisted Language Learning, 35(8), 1838–1868. https://doi.org/10.1080/09588221.2020.1839503
- Della Fadhilatunisa, Rosidah, & M. Miftach Fakhri. (2020). THE EFFECTIVENESS OF THE BLENDED LEARNING MODEL ON THE STUDENTS’ CRITICAL THINKING SKILLS AND LEARNING MOTIVATION IN ACCOUNTING DEPARTMENT. LENTERA PENDIDIKAN : JURNAL ILMU TARBIYAH DAN KEGURUAN, 194–208.
- Fadhilatunisa, D., Fakhri, M. M., & Rosidah, R. (2020). PENGARUH BLENDED LEARNING TERHADAP AKTIVITAS BELAJAR DAN HASIL BELAJAR MAHASISWA AKUNTANSI. Jurnal Pendidikan Akuntansi Indonesia, 18(2), 93–106. https://doi.org/10.21831/jpai.v18i2.35345
- Fahimirad, M., & Kotamjani, S. (2018). A review on application of artificial intelligence in teaching and learning in educational contexts". International Journal of Learning and Development, 8(4), 106. https://doi.org/10.5296/ijld.v8i4.14057
- Fakhri, M. M., Wahid, A., Fadhilatunisa, D., Surianto, D. F., Fajar B, M., & Hidayat, A. (2022). PENGARUH MODEL BLENDED PROBLEM BASED LEARNING BERBASIS LMS MOODLE TERHADAP MOTIVASI BELAJAR DAN HASIL BELAJAR MAHASISWA JURUSAN AKUNTANSI. KLASIKAL : JOURNAL OF EDUCATION, LANGUAGE TEACHING AND SCIENCE, 4(3), 670–684. https://doi.org/10.52208/klasikal.v4i3.501
- Fornell, C., & Larcker, D. F. (1981). Evaluating Structural Equation Models with Unobservable Variables and Measurement Error. Journal of Marketing Research, 18(1), 39–50.
- Ghozali, I., & Fuad. (2012). Teori, Konsep Dan Aplikasi Dengan Program LISREL. Badan Penerbit Universitas Diponegoro.
- Guan, X., Feng, X., & Islam, A. (2023). The dilemma and countermeasures of educational data ethics in the age of intelligence". Humanities and Social Sciences Communications, 10(1). https://doi.org/10.1057/s41599-023-01633-x
- Hair, J. F. (2017). A Primer on Partial Least Squares Structural Equation Modeling (PLS-SEM (J. F. Hair, Ed.; Second). Sage.
- Hair, J. F., Black, W. C., Babin, B. J., Anderson, R. E., & Tatham, R. L. (2006). Multivariate data analysis (6th ed.). Pearson Prentice Hall.
- Hair, J. F., Joe, F., Lucy, M. M., Ryan, L. M., & Sarstedt, M. (2017). PLS-SEM or CB-SEM: Updated Guidelines on Which Method to Use. International Journal of Multivariate Data Analysis, 1(2). https://doi.org/10.1504/ijmda.2017.10008574.
- Isaac, S., & Michael, W. B. (1981). Handbook in research and evaluation. Knapp.
- Jiang, J., Kantarci, B., Oktug, S., & Soyata, T. (2020). Federated learning in smart city sensing: challenges and opportunities". Sensors, 20(21), 6230. https://doi.org/10.3390/s20216230
- Kerlinger, F. N. (1986). Foundation of behavioral research (3rd ed.). Holt, Rinehart, and Winston.
- Lainjo, B., & Tsmouche, H. (2023). Impact of artificial intelligence on higher learning institutions". International Journal of Education Teaching and Social Sciences, 3(2), 96–113. https://doi.org/10.47747/ijets.v3i2.1028
- Loftus, T., Ruppert, M., Shickel, B., Ozrazgat-Baslanti, T., Balch, J., & al, P. E. (2022). Federated learning for preserving data privacy in collaborative healthcare research". Digital Health, 8, 205520762211344. https://doi.org/10.1177/20552076221134455
- Mehmetoglu, M. (2021). Structural Equation Modelling with Partial Least Squares Using Stata and R. CRC Press.
- Ng, D., Leung, J., Chu, K., & Qiao, M. (2021). ai literacy: definition, teaching, evaluation and ethical issues". Proceedings of the Association for Information Science and Technology, 58(1), 504–509. https://doi.org/10.1002/pra2.487
- Nunnally, B., & Bernstein, I. R. (1994). Psychometric Theory. Oxford University Press.
- Popenici, S., & Kerr, S. (2017). Exploring the impact of artificial intelligence on teaching and learning in higher education". Research and Practice in Technology Enhanced Learning, 12(1), 2017. https://doi.org/10.1186/s41039-017-0062-8
- Qiu, X., Du, Z., & Sun, X. (2019). Artificial intelligence-based security authentication: applications in wireless multimedia networks". Ieee Access, 7, 172004–172011. https://doi.org/10.1109/access.2019.2956480
- Santosa, P. I. (2018). Metode Penelitian Kuantitatif-Pengembangan Hipotesis Dan Pengujiannya Menggunakan SmartPLS (1st ed.). ANDI.
- Shapiro, R., Fiebrink, R., & Norvig, P. (2018). How machine learning impacts the undergraduate computing curriculum". Communications of the ACM, 61(11), 27–29. https://doi.org/10.1145/3277567
- Tapalova, O., & Zhiyenbayeva, N. (2022). Artificial intelligence in education: aied for personalised learning pathways". The Electronic Journal of E-Learning, 20(5), 639–653. https://doi.org/10.34190/ejel.20.5.2597
- Xu, Z., Xiang, D., & He, J. (2022). Data privacy protection in news crowdfunding in the era of artificial intelligence". Journal of Global Information Management, 30(7), 1–17. https://doi.org/10.4018/jgim.286760
- Yi, P., & Li, Z. (2022). Construction and management of intelligent campus based on student privacy protection under the background of artificial intelligence and internet of things". Mobile Information Systems, 2022, 1–6. https://doi.org/10.1155/2022/2154577
- Zawacki-Richter, O., Marín, V., Bond, M., & Gouverneur, F. (2019). Systematic review of research on artificial intelligence applications in higher education – where are the educators?". International Journal of Educational Technology in Higher Education, 16(1). https://doi.org/10.1186/s41239-019-0171-0
- Zhao, L., Wu, X., & Luo, H. (2022). Developing ai literacy for primary and middle school teachers in china: based on a structural equation modeling analysis". Sustainability, 14(21), 14549. https://doi.org/10.3390/su142114549
How to Cite
Fathahillah, F., Fakhri, M. M., & Ahmar, A. S. (2023). Analysis of Artificial Intelligence Literacy in the Blended Learning Model in Higher Education. EduLine: Journal of Education and Learning Innovation, 3(4), 566–575. https://doi.org/10.35877/454RI.eduline2049
