THE ALGORITHMIC CLASSROOM: INTEGRATING ONLINE APPS AND AI TOOLS FOR ENHANCED LANGUAGE LEARNING AND TEACHING.
Abstract
This theme establishes the central theme: the transformative impact of modern technology on English language education. It highlights the shift from traditional methods to technology-driven learning. The inclusion of AI tools and online programs emphasizes the evolving landscape. Furthermore, it sets the scope of the article by stating that it will examine the impact of user choice when using the tools and that it will offer examples of advantages, disadvantages, and effective usage. This provides the reader with a clear understanding of the article's focus and intended content.
References
1. Anderson, T., & Shattuck, J. (2012). Design-based research. Educational Researcher, 41(1), 16–25.
2. Angeli, C., & Valanides, N. (2020). Developing pre-service teachers’ technological pedagogical knowledge: Designing and evaluating an instructional package. Journal of Educational Computing Research, 58(2), 373–401.
3. Arkorful, V., & Abaidoo, N. (2015). The role of e-learning, advantages and disadvantages of its adoption in higher education. International Journal of Instructional Technology and Distance Learning, 12(1), 29–42.
4. Ashktorab, H., & Bernstein, M. S. (2015). Value-sensitive argumentation support. Proceedings of the 18th ACM Conference on Computer Supported Cooperative Work & Social Computing, 1694–1704.
5. Baepler, P., Walker, J. D., & Driessen, M. (2014). It’s not about seat time: Blending, flipping, and efficiency in active learning classrooms. Computers & Education, 78, 227–236.
6. Bearne, E., Clark, C., & Whitehead, M. (2012). Concluding uncomfortably: Researching literacy as social practice. Oxford Review of Education, 38(5), 619–634.
7. Bostrom, N. (2014). Superintelligence: Paths, dangers, strategies. Oxford University Press.
8. Bozkurt, A. (2020). Koronavirüs (Covid-19) pandemi süreci ve Türkiye’de uzaktan eğitimin sorunları [Coronavirus (Covid-19) pandemic process and problems of distance education in Turkey]. Açıköğretim Uygulamaları ve Araştırmaları Dergisi, 6(3), 112–130.
9. Braun, V., & Clarke, V. (2006). Using thematic analysis in psychology. Qualitative Research in Psychology, 3(2), 77–101.
10. Bryman, A. (2016). Social research methods. Oxford University Press.
11. Bull, S., & Kay, J. (2010). An architecture for peer review in distributed e-learning environments. Journal of Computer Assisted Learning, 26(3), 203–220.
12. Chen, L., Chen, P., & Lin, Z. (2020). Artificial intelligence in education: A review. IEEE Access, 8, 75254–75278. https://doi.org/10.1109/ACCESS.2020.2988549
13. Chen, Y. C., & Huang, T. C. (2014). Applying synchronous discussion to Web 2.0-based collaborative learning environments: Effects on students’ learning performance. Computers & Education, 77, 1–13.
14. Chiu, T. K. F., & Hew, T. K. (2018). Factors influencing peer assessment in online learning. Journal of Educational Technology & Society, 21(4), 5–18.
15. Choi, H., Kim, M., & Kang, S. (2020). Effects of artificial intelligence functions on learning achievement and self-efficacy in elementary school students. Computers and Education, 157, 103952.
16. Crompton, H., & Burke, D. (2018). The use of social media in higher education: A systematic review. Computers & Education, 155, 103926.
17. Davenport, T., & Mittal, N. (2020). Working in the age of AI. MIT Sloan Management Review, 61(4), 49–58.
18. De Weger, H., & Agyei, D. D. (2023). Artificial intelligence in higher education: A mixed methods study of lecturers’ experiences and attitudes. Computers and Education Open, 4, 100122.
19. De Wit, H., Gacel-Ávila, J., & Knight, J. (2015). Internationalization of higher education: Today’s global and local challenges. Industry and Higher Education, 29(3), 147–154.
20. De Vries, J., Van de Weijer, J., & Pluim, J. P. W. (2020). Evaluating deep learning for nuclear segmentation. In 2020 IEEE 17th International Symposium on Biomedical Imaging (ISBI) (pp. 1198–1201). IEEE.
21. Dhawan, S. (2020). Online learning: A panacea in the time of COVID-19 crisis. Journal of Educational Technology Systems, 49(1), 5–22.
22. Duhaydeb, L., & Nappa, R. (2020). The promise of artificial intelligence in education. Educational Leadership, 78(1), 56–61.
23. Dwivedi, Y. K., Kshetri, N., Bagga, C., Jha, N., & Filippaios, F. (2023). "So what if ChatGPT wrote it?": Multidisciplinary perspectives on opportunities, challenges, and implications of generative conversational AI for research, practice, and policy. International Journal of Information Management, 102693.
24. Eaton, S. E. (2020). Academic integrity during COVID-19: How contract cheating providers try to help. International Studies in Educational Administration, 48(1), 80–87.
25. Ekwunife, O. I., & Tijani, A. A. (2021). Artificial intelligence in education. In Artificial Intelligence in Education (pp. 1–15). Springer.
26. El Saddik, A. (2018). Digital twins: The convergence of multimedia technologies. IEEE MultiMedia, 25(2), 87–92.
27. Fawns, R., Jones, D., & Aitken, G. (2021). Online learning as emergency responses during the COVID-19 pandemic: A rapid systematic review. The Internet and Higher Education, 46, 100770.
28. Feldan, K., & Valverde, J. (2021). Artificial intelligence in education: Current status and prospects. International Journal of Educational Technology, 13(1), 1–18.
29. Fouh, E., Akbar, M. A., & Shaffer, C. A. (2013). A large-scale study of peer assessment in computer science education. ACM Transactions on Computing Education (TOCE), 13(4), 1–25.
30. Fryer, L. J., Ainley, J., Thompson, J., Dumbreck, A., & Mercer, J. (2017). Investigating the impact of using lecture capture on student attendance, participation, and learning outcomes. Computers & Education, 114, 17–28.
31. Gartner. (2021). Gartner's top strategic technology trends for 2021.
32. Gartner. (2023). What is generative AI?
33. Gautam, P., & Gautam, V. (2020). Online education during COVID-19 pandemic: Perception and attitude of teachers towards online teaching. Jashore University of Science and Technology Studies, 1(1), 109–122.
34. Gill, T. G., Ashton, T., & Roberts, N. (2016). Developing graduate attributes for 2020 and beyond. Higher Education Research & Development, 35(1), 177–191.
35. Gledhill, A., & Hoyle, K. (2015). The impact of technology on assessment practice. Assessment & Development Matters, 7(1), 10–13.
36. Gong, Z. Y., & Chiou, C. C. (2017). An artificial intelligence approach to English writing instruction. Computers & Education, 115, 114–131.
37. Goodfellow, I. J., Pouget-Abadie, J., Mirza, M., Xu, B., Warde-Farley, D., Ozair, S., Courville, A., & Bengio, Y. (2014). Generative adversarial nets. Advances in neural information processing systems, 27.
38. Goshtasby, A. A. (2012). Image registration: Principles, tools, and applications. Springer Science & Business Media.
39. Graesser, A. C., Wiemer-Hastings, P., Kreuz, R. J., Wiemer-Hastings, K., & Marquis, K. (1994). Question asking and answering in second language learning. Journal of Educational Psychology, 86(3), 373.
40. Greenhow, C., & Lewin, C. (2016). Social media and education: Reconceptualizing the digital divide. Teachers College Record, 118(1), 1–32.
41. Holmes, W., Bialik, M., & Fadel, C. (2021). Artificial intelligence in education. UNESCO Publishing.
42. Hussain, M., & Thaheem, M. J. (2023). ChatGPT applications in academia: A SWOT analysis, opportunities and challenges. SSRN.
43. Hwang, G. J., & Wu, P. H. (2014). Applications of mobile teaching strategies in K-12 education: A review of empirical research. International Journal of Mobile Learning and Organisation, 8(2), 163–179.
44. IBM. (2023). What is generative AI?
45. Johnson, L., Adams Becker, S., Cummins, M., Estrada, V., Gentil, S., & Weber, N. (2016). NMC horizon report: 2016 higher education edition. The New Media Consortium.
46. Johnson, N., & Sherlock, D. (2016). How does the use of social networking sites affect the academic performance of students in higher education? A systematic review and meta-analysis. Computers & Education, 96, 61–68.
47. Jordan, K., & Weller, M. (2018). Higher education in the digital age: Openness, scale, and interaction. Routledge.
48. Kahn, P., & Walsham, G. (2008). Interpretation in IS research: Description or deconstruction. European Journal of Information Systems, 17(5), 508–520.
49. Kazakoff, E. R. (2019). Coding in kindergarten: The impact of coding activities on kindergartners’ language skills. Journal of Educational Psychology, 111(1), 164.
50. Kearns, G. S. (2012). The student guide to success in higher education. Macmillan International Higher Education.
51. Khalil, M., & Ebner, M. (2017). Deconstructing learning analytics: Exploring the role of artificial intelligence and data mining in modern learning. Online Learning, 21(4), 59–80.
52. Klašnja-Milićević, A., Vesin, B., Ivanović, M., & Budimac, Z. (2011). E-learning 2.0: Main components and future directions. Telecommunications Policy, 35(12), 1027–1045.
53. Klopfer, E., Osterweil, S., Groff, J., & Haas, J. (2009). The instructional power of digital games: Social impact, civic engagement, and mathematical learning. ETC Press.
54. Kopp, H. G., & Bilancia, P. (2019). The use of digital technology in higher education: A systematic review of the literature. Journal of Educational Technology & Society, 22(4), 1–14.
55. Kuhail, M. A., Alnajjar, F. S., & Braimi, M. (2023). Exploring the awareness and attitudes of university students towards using ChatGPT in academic research: A case study. Education and Information Technologies, 1–22.
56. Lai, J. W. M., & Bower, M. (2020). How do teachers use technology to support learning? Policy and Practice, 25(7), 889–904.
57. Lallé, S., Conati, C., & Maclaren, H. (2018). Evaluating a model-building tool for teaching and learning about student modelling. International Journal of Artificial Intelligence in Education, 28(2), 241–279.
58. Lau, W. W., & Lee, P. Y. (2016). Vicarious learning with social media: A social network analysis approach. Computers & Education, 95, 1–13.
59. Lau, W. W., Ryu, H., & Lee, P. Y. (2019). The moderating role of social media in the relationship between self-directed learning and academic performance. Computers & Education, 130, 26–35.
60. Lau, W. W., Wong, K. W., & Hui, A. L. (2018). Effects of social media usage and multitasking on students’ academic performance. Computers in Human Behavior, 89, 110–118.
61. Lau, W. W., Yuen, A. H., & Lee, P. Y. (2020). The effects of social media multitasking on learning performance. Computers & Education, 144, 103708.
62. Laurillard, D. (2012). Teaching as a design science: Building pedagogical patterns for learning and technology. Routledge.
63. Lee, K., & Lin, C. J. (2018). The effects of artificial intelligence on students’ learning achievement and learning motivation. Computers & Education, 126, 1–10. https://doi.org/10.1016/j.compedu.2018.06.017
64. Li, Y., & Wong, B. T. M. (2021). ChatGPT in education: Opportunities, challenges, and implications for teaching and learning. SSRN.
65. Liu, C. H., & Tsai, C. C. (2013). Exploring the relationship between students’ science learning self-efficacy and their perceptions of the science classroom learning environment. International Journal of Science Education, 35(10), 1673–1694.
66. Luckin, R., Holmes, W., Griffiths, M., & Forcier, L. B. (2016). Intelligence unleashed: An argument for AI in education. Pearson.
67. Macfadyen, L. P., & Dawson, S. (2012). Numbers are not enough. Why e-learning analytics failed to inform policy and practice. Journal of Educational Technology & Society, 15(3), 149–163.
68. McCutcheon, P., Jang, H., & Towndrow, P. A. (2016). Investigating secondary school students’ use of social media and its impact on their lives. Computers & Education, 92–93, 44–59.
69. Meyer, K. A. (2014). Evaluating online learning: Practical rubrics for success. John Wiley & Sons.
70. Miao, F., Holmes, W., Huang, R., & Zhang, H. C. (2021). AI and education: Guidance for policy-makers. UNESCO Publishing.
71. Mishra, P., & Koehler, M. J. (2006). Technological pedagogical content knowledge: A framework for teacher knowledge. Teachers College Record, 108(6), 1017–1054.
72. Mokmin, N. A. M., & Zakaria, M. A. Z. M. (2020). The impact of artificial intelligence (AI) in education: A review. International Journal of Academic Research in Business and Social Sciences, 10(12), 170–177.
73. Moorhouse, B. L. (2020). Adaptations to a face-to-face initial teacher education course during the COVID-19 pandemic. Journal of Technology and Teacher Education, 28(2), 203–213.
74. Murphy, R. (2023). Is ChatGPT a turning point for AI? Nature, 614(7945), 409–410.
75. O’Donoghue, J., Singh, G., & Elbagir, S. (2014). A social constructivist perspective on e-learning: The information communication technology age. Procedia-Social and Behavioral Sciences, 159, 634–643.
76. Ouyang, F., Jiao, P., Hew, K. F., & Wong, L. H. (2022). Artificial intelligence in education: The state of the art and future directions. Computers & Education, 187, 104559.
77. Padilla