A quantitative analysis of the AI usage in students' learning performance
DOI:
https://doi.org/10.71085/joclsi.04.01.56Keywords:
Artificial Intelligence, Chat GPT, Student Learning, Quantitative Research, Academic PerformanceAbstract
The research focuses on the impact of Artificial Intelligence in student learning in Government Post Graduate College Mardan. Surveys and inferential statistics analyzed data gained from 320 students selected randomly who took part in this quantitative research. Respondents rated AI usage as M = 3.89 (SD = 0.543) and its effectiveness scored M = 4.187 (SD = 0.121). Student engagement together with learning outcomes demonstrated positive outcomes according to participants with mean ratings of M = 3.656 (SD = 0.333) and M = 3.132 (SD = 0.231) respectively. Moreover, AI usage acts as a predictor of student engagement to the extent of 45.5% based on the regression analysis (R² = 0.455, p = 0.001) while also explaining 46.6% of perceived learning effectiveness (R² = 0.466, p = 0.005). The determination of learning outcomes variance reaches 51.3% (R² = 0.513, p = 0.004) yet other performance variables remain significant. This study concluded that most students are deficient in knowledge processes in applying AI tools efficiently due to not having undergone appropriate training concerning their application. While the supportive aspect of AI is useful to educational systems, but students still need to retain their basic ability in creativity and critical thinking.
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References
Akgun, S., & Greenhow, C. (2022). Artificial intelligence in education: Addressing ethical challenges in K-12 settings. AI and Ethics, 2(3), 431-440.
Al-Awamreh, S. Y. A., Al-Zoubi, A. S., & Al-Amoush, I. B. (2024). The Effectiveness of a Training Program Based on Educational Technology Applications in Developing Learning Management Skills among Female English Language Teachers. Journal of Humanities and Social Sciences Studies, 6(12), 112-128.
Andersen, T. (2013). Andersen, J. C. (2013). Learner satisfaction in online learning: An analysis of the perceived impact of learner-social media and learner-instructor interaction (Doctoral dissertation, East Tennessee State University).
Arnold, K. E., Pistilli, M. D., & Whitmer, J. C. (2012). Analytics in higher education: Establishing a common language. EDUCAUSE Review, 47(2), 14–24.
Aymen, D. I. F., & Zakarya, B. O. U. S. I. O. U. D. (2024). The Influence of Artificial Intelligence on Students' Critical Thinking (Doctoral dissertation, university center of abdalhafid boussouf-MILA).
Baker, S., & Xiang, W. (2023). Artificial intelligence of things for smarter healthcare: a survey of advancements, challenges, and opportunities. IEEE Communications Surveys & Tutorials, 25(2), 1261-1293.
Bolliger, D. U., & Martin, F. (2018). Instructor and student perceptions of online student engagement strategies.Distance Education, 39(4), 568–583. https://doi.org/10.1080/01587919.2018.1520041
Brown, T. B., Mann, B., Ryder, N., Subbiah, M., Kaplan, J., Dhariwal, P., ... & Amodei, D. (2020). Language models are few-shot learners. Advances in Neural Information Processing Systems, 33, 1877–1901.
Chen, L., Chen, P., & Lin, Z. (2020). Artificial intelligence in education: A review. IEEE Access, 8, 75264–75278.
Chiu, T. K. F., Xia, Q., Zhou, X., Chai, C. S., & Cheng, M. (2023). Systematic literature review on opportunities, challenges, and future research recommendations of artificial intelligence in education. Computers & Education, 193, 1–18. https://doi.org/10.1016/j.compedu.2022.104662
Chivose, E. M. (2023). The Adoption and Usage Patterns of ChatGPT Among Students and Faculty Members in Higher Education: A Study of the University of Nairobi, Faculty of Education (Doctoral dissertation, University of Nairobi).
Creswell, J. W., & Creswell, J. D. (2017). Research design: Qualitative, quantitative, and mixed methods approaches (5th ed.). Thousand Oaks, CA: SAGE Publications.
Dabbagh, N., & Kitsantas, A. (2012). Personal learning environments, social media, and self-regulated learning: A natural formula for connecting formal and informal learning. The Internet and Higher Education, 15(1), 3–8. https://doi.org/10.1016/j.iheduc.2011.06.002
Fu, Q., Lin, Y., & Wang, H. (2020). AI-driven language assessment systems: A meta-analysis of engagement outcomes. Language Learning & Technology, 24(3), 1–22.
Gibson, D., Broadley, T., & Downie, J. (2018). Personalized learning in the digital age: AI-driven approaches. British Journal of Educational Technology, 49(5), 879–891. https://doi.org/10.1111/bjet.12672
Holstein, K., McLaren, B. M., & Aleven, V. (2019). Intelligent tutoring systems: A historical review and modern applications. International Journal of Artificial Intelligence in Education, 29(1), 160–178. https://doi.org/10.1007/s40593-018-0169-0
Hwang, G. J., Xie, H., & Wah, B. W. (2020). Vision, challenges, and future directions of AI in education. Computers & Education, 157, 1–15. https://doi.org/10.1016/j.compedu.2020.104043
Ilić, M. P., Kuleto, V., & Stanescu, M. (2021). The role of AI robots in STEM education: A systematic review. Educational Technology Research and Development, 69(5), 2301–2325. https://doi.org/10.1007/s11423-021-09985-4
Ingersoll, R. M., & Strong, M. (2011). The impact of induction and mentoring programs for beginning teachers: A critical review of the research. Review of Educational Research, 81(2), 201–233. https://doi.org/10.3102/0034654311403323
Kang, M., & Im, T. (2013). Factors of learner-instructor interaction in online learning environments. Journal of Educational Technology & Society, 16(4), 310–322.
Kessler, M., Bikowski, D., & Boggs, J. (2020). Collaborative writing in L2 classrooms: A research agenda. Language Teaching Research, 24(2), 238–257. https://doi.org/10.1177/1362168819867027
Krishnamurthy, R., & Davis, R. (2022). AI-driven writing assistants: Enhancing student outcomes. Journal of Educational Computing Research, 60(1), 123–145. https://doi.org/10.1177/07356331211032589
Kuh, G. D. (2009). What student affairs professionals need to know about student engagement. Journal of College Student Development, 50(6), 683–706. https://doi.org/10.1353/csd.0.0099
Kuleto, V., Ilić, M. P., Stanescu, M., Ranković, M., & Šević, N. P. (2021). The role of AI robots in STEM education: A systematic review. Educational Technology Research and Development, 69(5), 2301–2325. https://doi.org/10.1007/s11423-021-09985-4
Lai, J. W., & Bower, M. (2020). How is the use of technology in education evaluated? A systematic review. Computers & Education, 151, 1–18. https://doi.org/10.1016/j.compedu.2020.103839
LeCun, Y., Bengio, Y., & Hinton, G. (2015). Deep learning. Nature, 521(7553), 436–444. https://doi.org/10.1038/nature14539
Lee, E., & Hannafin, M. J. (2016). A design framework for enhancing engagement in student-centered learning. Educational Technology Research and Development, 64(4), 707–734. https://doi.org/10.1007/s11423-015-9422-5
Li, X., & Zhao, Y. (2019). AI in education: Opportunities and challenges. Journal of Educational Technology Development and Exchange, 12(1), 1–12.
Linnell, A. E. (2024). Assessing Malevolent Creativity in the Workplace (Master's thesis, University of Nebraska at Omaha).
Liu, M., & Lin, C. (2018). AI-powered language practice: Effects on speaking fluency. ReCALL, 30(2), 232–249. https://doi.org/10.1017/S0958344017000353
Lockyer, L., Heathcote, E., & Dawson, S. (2019). Ethics and privacy in AI-driven education. Australasian Journal of Educational Technology, 35(6), 1–14. https://doi.org/10.14742/ajet.5502
Martínez-Comesanã, L., Troncoso-Pastoriza, J. R., & Pérez-Rodríguez, R. (2023). Intelligent buildings and learning spaces: The role of artificial intelligence. Journal of Educational Technology, 15(2), 123-135.
McNamara, D. S., Crossley, S. A., & Roscoe, R. D. (2013). Natural language processing in writing education. Educational Psychologist, 48(4), 256–268. https://doi.org/10.1080/00461520.2013.844785
Mitrovic, A., Martin, B., & Suraweera, P. (2014). Intelligent tutors for all: The constraint-based approach. IEEE Transactions on Learning Technologies, 7(4), 346–359. https://doi.org/10.1109/TLT.2014.2330687
Mitrovic, A., Ohlsson, S., & Barrow, D. K. (2023). AI-driven educational tools: A global perspective. Educational Technology & Society, 26(1), 1–15.
Mohanty, S. (2023). Enhancing customer experience with AI-driven chatbots. International Journal of Service Industry Management, 34(1), 45-60.
Moraes, E. B., Silva, J. M., & Barbosa, J. L. (2023). Industry 4.0 technologies in education: A systematic review of engagement and cost-benefit outcomes. Computers in Human Behavior, 139, 1–12. https://doi.org/10.1016/j.chb.2022.107512
Paramesha, M., Rane, N. L., & Rane, J. (2024). Artificial intelligence, machine learning, deep learning, and blockchain in financial and banking services: A comprehensive review. Partners Universal Multidisciplinary Research Journal, 1(2), 51-67.
Punch, K. F. (2016). Introduction to social research: Quantitative and qualitative approaches (3rd ed.). Thousand Oaks, CA: SAGE Publications.
Ribeiro, S., Silva, A., & Moreira, A. (2019). Automating administrative tasks in education: An AI approach. Educational Technology Research and Development, 67(4), 923–941. https://doi.org/10.1007/s11423-019-09670-7
Russell, S., & Norvig, P. (2021). Artificial intelligence: A modern approach (4th ed.). Pearson.
Sekaran, U., & Bougie, R. (2016). Research methods for business: A skill-building approach (7th ed.). Hoboken, NJ: Wiley.
Seo, K., Dodson, S., & Bensen, A. (2021). Artificial intelligence in education: The potential for personalized learning. Educational Technology Research and Development, 69(3), 897-912.
Shackelford, J. L., & Maxwell, M. (2012). Sense of community in graduate online education: Contribution of learner-learner interaction. International Review of Research in Open and Distributed Learning, 13(4), 228–249.
Siemens, G. (2013). Learning analytics: The emergence of a discipline. American Behavioral Scientist, 57(10), 1380–1400. https://doi.org/10.1177/0002764213498851
Smith, J., Jones, R., & Brown, T. (2018). AI in higher education: Opportunities and ethical implications. Journal of Learning Analytics, 5(2), 45–60.
Sparrow, B., Liu, J., & Wegner, D. M. (2011). Google effects on memory: Cognitive consequences of having information at our fingertips. Science, 333(6043), 776–778. https://doi.org/10.1126/science.1207745
Topol, E. J. (2019). High-performance medicine: The convergence of human and artificial intelligence. Nature Medicine, 25(1), 44-56. https://doi.org/10.1038/s41591-018-0300-7
VanLehn, K. (2011). The relative effectiveness of human tutoring, intelligent tutoring systems, and other tutoring systems. Educational Psychologist, 46(4), 197–221. https://doi.org/10.1080/00461520.2011.611369
Walker, R. (2016). Student engagement in online learning: A review of literature. Journal of Educational Technology Systems, 44(3), 291–307. https://doi.org/10.1177/0047239515618516
Wilcox, T. (2023). The impact of ChatGPT on modern education. Journal of Educational Innovation, 45(3), 112–125.
Wong, L., & Howitt, P. (2020). Social isolation in digital classrooms: The unintended consequences of AI-driven education. Journal of Educational Psychology, 112(4), 789–801. https://doi.org/10.1037/edu0000438
Xia, Q., Chiu, T. K. F., & Zhou, X. (2022). AI robots in K-12 education: A meta-analysis of engagement effects. Educational Technology & Society, 25(1), 1–15.
Yang, Y., Oh, S., & Wang, R. (2020). AI-enabled robots in higher education: A case study of engagement outcomes. Journal of Educational Computing Research, 58(7), 1359–1382. https://doi.org/10.1177/0735633120921581
Yeşilyurt, Y. E. (2023). The role of artificial intelligence (AI) in transforming foreign language education: trends, applications, and ethical considerations. Current studies in foreign language education, 365.
Zhang, Z., Gao, X., & Liu, T. (2018). Online discussion forums and learning communities: A review of engagement strategies. Computers & Education, 123, 1–14. https://doi.org/10.1016/j.compedu.2018.04.007
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