References
Ahmad, R. (2019). The degree of using modern technology in teaching biology from the perspectives of secondary school teachers in zarqa schools (Unpublished master’s thesis [Middle East University]). Ali, N., & Ullah, S. (2020). Review to analyze and compare virtual chemistry laboratories for their use in education. Journal of Chemical Education, 97(10), 3563-3574. https://doi.org/10.1021/acs.jchemed. 0c00185 AL Khateeb, K. (2021). Perceptions of UAE science teachers on effectiveness of online science learning in COVID-19 pandemic [master dissertation. The British University (in Dubai]). Asiri, M., & El Aasar, S. (2022). Employing technology acceptance model to assess the reality of using augmented reality applications in teaching from teachers’point of view in najran. Journal of Positive School Psychology, 6(2), 5241–5255. Babateen H.M. (2011). The Role of Virtual Laboratories in Science Education. 5 th International Conference on Distance Learning and Education IPCSIT 12:100-104. Bakar H.N.B. & Zaman, H.,H.,B.(2007). Development of VLab-Chem for Chemistry Subject Based on Constructivism-Cognitivism-Contextual Approach, Proceedings of the International Conference on Electrical Engineering and Inf. Institut Teknologi Bandung, Indonesia, 567-570. Barney D., Andrea B. and Danny B., (2003) “The potential of virtual laboratories for distance science education teaching: reflections from the initial development and evaluation of a irtual chemistry laboratory”, Proceedings of the Improving Learning Outcomes Through Flexible Science Teaching, Symposium, The University of Sydney, pp. 90-95. Bennie, S.J.; Ranaghan, K.E.; Deeks, H.; Goldsmith, H.E.; O’Connor, M.B.; Mulholland, A.J.; Glowacki, D.R. Teaching Enzyme Catalysis Using Interactive Molecular Dynamics in Virtual Reality. J. Chem. Educ. 2019, 96, 2488–2496. Beri, N., & Sharma, L. (2019). Teachers’ attitude towards integrating ICT in teacher education. International Journal of Innovative Technology and Exploring Engineering, 8(8), 285– 295. Bibic, L.; Druskis, J.;Walpole, S.; Angulo, J.; Stokes, L. Bug O_ Pain: An Educational Virtual Reality Game on Spider Venoms and Chronic Pain for Public Engagement. J. Chem. Educ. 2019, 96, 1486–1490 Bilek, M. & Skalická , P., (2010). Combination of Real and Virtual Environment In Early Chemistry Experimental Activities, XIV IOSTE Symposium, June 13-18, Bled, Slovenia. Boettcher, J. V., & Conrad, R. M. (2016). The online teaching survival guide: Simple and practical pedagogical tips (2nd ed.). UK: Wiley. Borji, A. A Categorical Archive of ChatGPT Failures. arXiv 2023, 1–41. Bryant, J. (2022a) Digital technologies and inclusion in humanitarian response. HPG report. London: ODI Buenano-Fernandez, D., Gil, D., & Lujan-Mora, S. (2019). Application of machine learning in predicting performance for computer engineering students: A case study. Sustainability, 11(10), 1–18. https:// doi. org/ 10. 3390/ su111 02833 Capuano, N., & Caballe, S. (2020). Adaptive Learning Technologies. Ai Magazine, 41(2), 96–98. https:// doi. org/ 10. 1609/ aimag. v41i2. 5317 Chocarro, R., Cortinas, M., & Matas, G. (2021). Teachers’ attitudes towards chatbots in education: A technology acceptance model approach considering the effect of social language, bot proactiveness, and users’ characteristics. Educational Studies. https:// doi. org/ 10. 1080/ 03055 698. 2020. 18504 26 Cukurova, M., Khan-Galaria, M., Mill´an, E., & Luckin, R. (2021). A learning analytics approach to monitoring the quality of online one-to-one tutoring. Journal of Learning Analytics, 9(2), 105–120. https://doi.org/10.35542/osf.io/qfh7z Deo, R. C., Yaseen, Z. M., Al-Ansari, N., Nguyen-Huy, T., Langlands, T. A. M., & Galligan, L. (2020). Modern artificial intelligence model development for undergraduate student performance prediction: An investigation on engineering mathematics courses. IEEE Access, 8, 136697–136724. https:// doi. org/ 10. 1109/ ACCESS. 2020. 30109 38 Dewi, C. A., Pahriah, P., & Purmadi, A. (2021). The Urgency of Digital Literacy for Generation Z Students in Chemistry Learning. International Journal of Emerging Technologies in Learning, 16(11), 88–103. https://doi.org/10.3991/ijet.v16i11.19871 Do?an, B. (2006). Zeki ö?retim sistemlerinde veri madencili?i kullan?lmas? (The use of data mining in intelligent tutoring systems) (Doctorial dissertation, Institute of Science and Technology, Marmara University). Dougherty, K. (2015). Factors that influence college faculty to adopt digital technologies in their practice. In Proceedings of the Higher Education in Transformation Conference (pp. 307– 318). https:// arrow. tudub lin. ie/ cgi/ viewc ontent. cgi? artic le= 1005& conte xt= st3 Eccles, J. S. (2015). Gendered socialization of STEM interests in the family. International Journal of Gender, Science and Technology, 7(2), 116-132. Ezekiel .O. B., and Akinyemi;.A. L., (2022) utilisation of artificial intelligence in Education: the perception of university of Ibadan lecturers JOGRESS, 16(5): 32-40. Gambari, A. I., Kawu, H., & Falode, O. C. (2018). Impact of virtual laboratory on the achievement of secondary school chemistry students in homogeneous and heterogeneous collaborative environments. Contemporary Educational Technology, 9(3), 246-263. https://doi.org/10.30935/cet.444108 Georgiou, J.; Dimitropoulos, K.; Manitsaris, A. A Virtual Reality Laboratory for Distance Education. Int. J. Human. Soc. Sci. Res. 2007, 1. Available online: https://www.researchgate.net/publication/301346180_A_ Virtual_Reality_Laboratory_for_Distance_Education_in_Chemistry (accessed on 10 January 2019). Goda, Y. (2014). The role of AMPA receptors in postsynaptic mechanisms of synaptic plasticity. Front Cell Neurosci. doi: 10.3389/fncel.2014.00401. Harry E. P., (2020). How Should Chemistry Educators Respond to the Next Generation of Technology Change? Educ. Sci. 2020, 10, 34; doi:10.3390/educsci10020034 Hébert, C., Jenson, J., and Terzopoulos, T. (2021). “Access to technology is the major challenge”: teacher perspectives on barriers to DGBL in K-12 classrooms. E-Learn. Digital Media 18, 307–324. doi: 10.1177/2042753021995315 Hellings, J., & Haelermans, C. (2020). The effect of providing learning analytics on student behaviour and performance in programming: A randomized controlled experiment. Higher Education, 83(1), 1–18. https:// doi. org/ 10. 1007/ s10734-020-00560-z Herold, B. The Case(s) Against Personalized Learning. In Education Week; Editorial Projects in Education, Inc.: Bethesda, MD, USA, 2017; Available online: https://www.edweek.org/ew/articles/2017/11/08/the-casesagainst- personalizedlearning.html (accessed on 18 January 2019) Highet, C., Skelly, H. and Alexandra T. (2017). Gender and Information Communication Technology (ICT) Survey Toolkit. Washington DC: USAID, https://2012- 2017.usaid.gov/documents/15396/gender-and-ict-toolkit Hwang, G. J., & Tu, Y. F. (2021). Roles and research trends of artificial intelligence in mathematics education: A bibliometric mapping analysis and systematic review. Mathematics, 9(6). https://doi.org/10.3390/math9060584 Kafyulilo, A., Fisser, P., & Voogt, J. (2015). Factors affecting teachers’ continuation of technology use in teaching. Educationand Information Technologies, 21(6), 1535–1554. https:// doi. org/ 10. 1007/ s10639- 015-9398-0 Kim, S.-G. Using ChatGPT for Language Editing in Scientific Articles. Maxillofac. Plast. Reconstr. Surg. 2023, 45 (1), 13. https://doi.org/10.1186/s40902-023-00381-x.. Kok, J. N., Boers, E. J., Kosters, W. A., van der Putten, P., & Poel, M. (2009). Artificial intelligence: Definition, trends, techniques, and cases. Knowledge for sustainable development: An insight into the encyclopedia of life support systems. Eolss Publishers Lawrence, J. E., & Tar, U. A. (2018). Factors that influence teachers’ adoption and integration of ICT in teaching/learning process. Educati
