Students’ Perceptions on The Artificial Intelligence (AI) Tools As Academic Support

  • Zulaikha Khairuddin Academy of Language Studies, Universiti Teknologi MARA, 40450 Shah Alam, Selangor, Malaysia
  • Nor Syahiza Shahabani Academy of Language Studies, Universiti Teknologi MARA, 40450 Shah Alam, Selangor, Malaysia
  • Siti Nurshafezan Ahmad Academy of Language Studies, Universiti Teknologi MARA, 40450 Shah Alam, Selangor, Malaysia
  • Azrin Raimi Ahmad Academy of Language Studies, Universiti Teknologi MARA, 40450 Shah Alam, Selangor, Malaysia
  • Nur Adibah Zamri Academy of Language Studies, Universiti Teknologi MARA, 40450 Shah Alam, Selangor, Malaysia
Keywords: Perception, Artificial Intelligence, AI, Academic Support, Tools

Abstract

In today’s world, technology is considered a necessity as many can benefit from using it. Education sector also cannot run from integrating and incorporating technology in the teaching and learning process. Therefore, this study would like to investigate students’ perceptions on the use of artificial intelligence (AI) as a tool in the classroom. This study employed a quantitative approach in obtaining the data. There were 284 respondents who participated in this study. The instrument used to obtain the data was a set of questionnaires where there were 20 items in it. Other than that, there were 6 sections in the questionnaire representing the constructs of the perceptions. The results showed that students perceived AI as a tool that could help them in their learning process. This implies that educators need to be more ready in using technology in the classroom and they should equip themselves with 21st century skills that are relevant in today’s education system. Therefore, integrating technology in teaching and learning processes may assist the educators and students to be more engaged in the classroom and two-way communication may occur.

Downloads

Download data is not yet available.

References

Ahada, R., Solong, N. P., & Nelza, N. (2024). The era of connectivity: the role of education in shaping adaptive digital intelligence. International Journal Of Social And Education, 1(1), 243-252. https://btqur.or.id/index.php/injosedu/article/view/140

Ahmed, V., & Opoku, A. (2022). Technology supported learning and pedagogy in times of crisis: the case of COVID-19 pandemic. Education and information technologies, 27(1), 365-405. https://doi.org/10.1007/s10639-021-10706-w

Almufarreh, A. (2024). Determinants of students’ satisfaction with ai tools in education: A pls-sem-ann approach. Sustainability, 16(13), 5354. https://doi.org/10.3390/su16135354

Almulla, M. A. (2024). Investigating Influencing Factors of Learning Satisfaction in AI ChatGPT for Research: University Students Perspective. Heliyon, 10(11), e32220. https://doi.org/10.1016/j.heliyon.2024.e32220

Al-Zahrani, A. M. (2024). Balancing act: Exploring the interplay between human judgment and artificialintelligence in problem-solving, creativity, and decision-making. Igmin Research, 2(3), 145-158. https://doi.org/10.61927/igmin158

Ayala-Pazmiño, M. (2023). Artificial intelligence in education: exploring the potential benefits and risks. Digital Publisher CEIT, 8(3), 892-899. http://dx.doi.org/10.33386/593dp.2023.3.1827

Baidoo-anu, D., & Owusu Ansah, L. (2023). Education in the era of generative artificial intelligence (AI): Understanding the potential benefits of chatgpt in promoting teaching and learning. Journal of AI, 7(1), 52-62. https://doi.org/10.61969/jai.1337500

Brill, T. M., Munoz, L., & Miller, R. J. (2022). Siri, Alexa, and other digital assistants: a study of customer satisfaction with artificial intelligence applications. Journal of Marketing Management, 35(15-16), 1401-1436. https://doi.org/10.1080/0267257X.2019.1687571

Chaudhary, A. A.,Arslan Asad Chaudhary, Sehar Arif, Calimlim, R. J. F.,Rodolfo Jr F. Calimlim, Khan, S. Z., & Dr. Shahan Zeb Khan, & Asma Sadia. (2024). The impact of ai-powered educational tools on student engagement and learning outcomes at higher education level. International Journal of Contemporary Issues in Social Sciences, 3(2), 2842–2852. Retrieved from https://ijciss.org/index.php/ijciss/article/view/1027

Chen, L., Chen, P., & Lin, Z. (2020). Artificial intelligence in education: A review. IEEE Access, 8, 75264-75278. https://doi.org/10.1109/ACCESS.2020.2988510

Cronqvist, M. (2021). Joy in learning: when children feel good and realize they learn. Educare, (3), 54–77. https://doi.org/10.24834/educare.2021.3.3

Darwin, Rusdin, D., Mukminatien, N., Suryati, N., Laksmi, E. D., & Marzuki. (2024). Critical thinking in the AI era: An exploration of EFL students’ perceptions, benefits, and limitations. Cogent Education, 11(1), 2290342. https://doi.org/10.1080/2331186X.2023.2290342

Dahri, N. A., Yahaya, N., Al-Rahmi, W. M. et al. (2024). Investigating AI-based academic support acceptance and its impact on students’ performance in Malaysian and Pakistani higher education institutions. Educ Inf Technol, 29, 18695–18744. https://doi.org/10.1007/s10639-024-12599-x

Deng, X., & Yu, Z. (2022). A systematic review of machine-translation-assisted language learning for sustainable education. Sustainability, 14(13), 7598. https://doi.org/10.3390/su14137598

Ezeoguine, E. P., & Eteng-Uket, S. (2024). Artificial intelligence tools and higher education student’s engagement. Edukasiana: Jurnal Inovasi Pendidikan, 3(3), 300-312. https://doi.org/10.56916/ejip.v3i3.733

González-González, C. S., Muñoz-Cruz, V., Toledo-Delgado, P. A., & Nacimiento-García, E. (2023). Personalized gamification for learning: A reactive chatbot architecture proposal. Sensors, 23(1), 545. https://doi.org/10.3390/s23010545

Habib, S., Vogel, T., Anli, X., & Thorne, E. (2024). How does generative artificial intelligence impact student creativity?. Journal of Creativity, 34(1), 100072. https://doi.org/10.1016/j.yjoc.2023.100072

Hemachandran, K., Verma, P., Pareek, P., Arora, N., Rajesh Kumar, K. V., Ahanger, T. A., ... & Ratna, R. (2022). Artificial intelligence: A universal virtual tool to augment tutoring in higher education. Computational Intelligence and Neuroscience, 2022(1), 1410448. https://doi.org/10.1155/2022/1410448

Janschitz, G., & Penker, M. (2022). How digital are ‘digital natives’ actually? Developing an instrument to measure the degree of digitalisation of university students–the DDS-Index. Bulletin of Sociological Methodology/Bulletin de Méthodologie Sociologique, 153(1), 127-159. https://doi.org/10.1177/07591063211061760

Krejcie, R. V., & Morgan, D. W. (1970). Determining sample size for research activities. Educational and psychological measurement, 30(3), 607-610. https://doi.org/10.1177/001316447003000308

Maini, R., Sehgal, S., & Agrawal, G. (2021). Todays' digital natives: an exploratory study on students' engagement and satisfaction towards virtual classes amid COVID-19 pandemic. The International Journal of Information and Learning Technology, 38(5), 454-472. https://doi.org/10.1108/IJILT-03-2021-0055

Mallillin, L. L. D. (2024). Artificial Intelligence (AI) Towards Students’ Academic Performance. Innovare Journal of Education, 12(4), 16–21. https://doi.org/10.22159/ijoe.2024v12i4.51665

Marques, L. S., Gresse von Wangenheim, C., & Hauck, J. C. (2020). Teaching machine learning in school: A systematic mapping of the state of the art. Informatics in Education, 19(2), 283-321. https://doi.org/10.15388/infedu.2020.14

Marrone, R., Taddeo, V., & Hill, G. (2022). Creativity and artificial intelligence—A student perspective. Creativity, Intelligence, and Collaboration in 21st Century Education, 10, 259. https://doi.org/10.3390/ jintelligence10030065

Marrone, R., Zamecnik, A., Joksimovic, S., Johnson, J., & De Laat, M. (2024). Understanding student perceptions of artificial intelligence as a teammate. Technology, Knowledge and Learning, 1-23. https://doi.org/10.1007/s10758-024-09780-z

Milicevic, N., Kalas, B., Djokic, N., Malcic, B., & Djokic, I. (2024). Students’ intention toward artificial intelligence in the context of digital transformation. Sustainability, 16(9), 3554. https://doi.org/10.3390/su16093554

Nguyen, A., Kremantzis, M., Essien, A., Petrounias, I., & Hosseini, S. (2024). Enhancing student engagement through artificial intelligence (AI): Understanding the basics, opportunities, and challenges. Journal of University Teaching and Learning Practice, 21(06). https://doi.org/10.53761/caraaq92

Noor, S., Tajik, O., & Golzar, J. (2022). Simple random sampling. International Journal of Education & Language Studies, 1(2), 78-82. https://doi.org/10.22034/ijels.2022.162982

Nurhaliza, N. (2024). An analysis of applications employed by students to cheat on exams. EDUJ: English Education Journal, 2(1), 64-68. https://doi.org/10.59966/eduj.v2i1.1084

Ouyang, F., Wu, M., Zheng, L., Zhang, L., & Jiao, P. (2023). Integration of artificial intelligence performance prediction and learning analytics to improve student learning in online engineering course. International Journal of Educational Technology in Higher Education, 20(1), 4. https://doi.org/10.1186/s41239-022-00372-4

Patil, N. H., Patel, S. H., & Lawand, S. D. (2023). Research paper on artificial intelligence and it's applications. Journal of Advanced Zoology, 44. https://doi.org/10.53555/jaz.v44iS8.3544

Porter, B., & Grippa, F. (2020). A platform for AI-enabled real-time feedback to promote digital collaboration. Sustainability, 12(24), 10243. https://doi.org/10.3390/su122410243

Prestoza, M. J. R., & Banatao, J. C. M. (2024). Exploring the efficacy of AI passion-driven pedagogy in enhancing student engagement and learning outcomes: A case study in philippines. Asian Journal of Assessment in Teaching and Learning, 14(1), 45-54. https://doi.org/10.37134/ajatel.vol14.1.5.2024

Queirós, A., Faria, D., & Almeida, F. (2017). Strengths and limitations of qualitative and quantitative research methods. European Journal of Education Studies, 3(9), 369-387. https://zenodo.org/records/887089

Rakhmawati, D. E. N., & Kusuma, A. W. (2015). Digital native: A study on the first-year student. LiNGUA, 10(2), 82-89. http://doi.org/10.18860/ling.v10i2.3261

Shahabani, N. S., Jais, I. R. M., Khairuddin, Z., & Ismail, O. (2022). Integrating ARCS motivational model with computer-based syntax learning. International Journal of Asian Social Science, 12(9), 360-378. https://doi.org/10.55493/5007.v12i9.4605

Sharma, R., & Singh, A. (2024). Use of Digital Technology in Improving Quality Education: A Global Perspectives and Trends. Implementing Sustainable Development Goals in the Service Sector, 14-26. https://doi.org/10.4018/979-8-3693-2065-5.ch002

Wang, F., King, R. B., Chai, C. S., & Zhou, Y. (2023). University students’ intentions to learn artificial intelligence: the roles of supportive environments and expectancy–value beliefs. International Journal of Educational Technology in Higher Education, 20(1), 51. https://doi.org/10.1186/s41239-023-00417-2

Wei, L. (2023). Artificial intelligence in language instruction: impact on English learning achievement, L2 motivation, and self-regulated learning. Frontiers in psychology, 14, 1261955. https://doi.org/10.3389/fpsyg.2023.1261955

Zhang, Z., & Wasie, S. (2023, September). Educational Technology in the Post-Pandemic Era: Current Progress, Potential, and Challenges. In Proceedings of the 15th International Conference on Education Technology and Computers (pp. 40-46). https://doi.org/10.1145/3629296.3629303

Published
2024-11-28
How to Cite
Khairuddin, Z., Shahabani, N. S., Ahmad, S. N., Ahmad, A. R. and Zamri, N. A. (2024) “Students’ Perceptions on The Artificial Intelligence (AI) Tools As Academic Support”, Malaysian Journal of Social Sciences and Humanities (MJSSH), 9(11), p. e003087. doi: 10.47405/mjssh.v9i11.3087.
Section
Articles

Most read articles by the same author(s)