Economic Education Students' Perspectives on AI Utilization in Learning: A Descriptive Study
Abstract
This study explores students' perspectives on the use of Artificial Intelligence (AI) in education. Using a descriptive quantitative approach, data were collected through questionnaires from 45 Economics Education students at Universitas Negeri Gorontalo. The analysis results show that 60% of respondents believe AI enhances learning efficiency, while 55.6% support its development in economic education due to its benefits for job readiness. However, concerns exist that reliance on AI may reduce critical thinking skills (62.2%) and only minimally support student collaboration (62.2%). These findings provide insights for the development of AI-based educational tools, though they are limited to a specific student group. Further research is recommended to include a larger and more diverse sample to gain a broader understanding of students' perceptions of AI in education.
References
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Alalwan, N., Cheng, L., Al-Samarraie, H., Yousef, R., Ibrahim Alzahrani, A., & Sarsam, S. M. (2020). Challenges and Prospects of Virtual Reality and Augmented Reality Utilization among Primary School Teachers: A Developing Country Perspective. Studies in Educational Evaluation, 66, 100876. https://doi.org/10.1016/J.STUEDUC.2020.100876
Bajaj, R., & Sharma, V. (2018). Smart Education with artificial intelligence based determination of learning styles. Procedia Computer Science, 132, 834–842. https://doi.org/10.1016/J.PROCS.2018.05.095
Banabilah, S., Aloqaily, M., Alsayed, E., Malik, N., & Jararweh, Y. (2022). Federated learning review: Fundamentals, enabling technologies, and future applications. Information Processing & Management, 59(6), 103061. https://doi.org/10.1016/J.IPM.2022.103061
Bhutoria, A. (2022). Personalized education and Artificial Intelligence in the United States, China, and India: A systematic review using a Human-In-The-Loop model. Computers and Education: Artificial Intelligence, 3, 100068. https://doi.org/10.1016/J.CAEAI.2022.100068
Chang, D. H., Lin, M. P.-C., Hajian, S., & Wang, Q. Q. (2023). Educational Design Principles of Using AI Chatbot That Supports Self-Regulated Learning in Education: Goal Setting, Feedback, and Personalization. Sustainability, 15(17), 12921. https://doi.org/10.3390/su151712921
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
Cheng, E. C. K., & Wang, T. (2023). Leading digital transformation and eliminating barriers for teachers to incorporate artificial intelligence in basic education in Hong Kong. Computers and Education: Artificial Intelligence, 5, 100171. https://doi.org/10.1016/J.CAEAI.2023.100171
Daniere, A. (1965). GARY S. BECKER. Human Capital: A Theoretical and Empirical Analysis, with Special Reference to Education. Pp. xvi, 187. New York: National Bureau of Economic Research, 1964. $5.00. The ANNALS of the American Academy of Political and Social Science, 360(1), 208–209. https://doi.org/10.1177/000271626536000153
Dwivedi, Y. K., Hughes, L., Ismagilova, E., Aarts, G., Coombs, C., Crick, T., Duan, Y., Dwivedi, R., Edwards, J., Eirug, A., Galanos, V., Ilavarasan, P. V., Janssen, M., Jones, P., Kar, A. K., Kizgin, H., Kronemann, B., Lal, B., Lucini, B., … Williams, M. D. (2021). Artificial Intelligence (AI): Multidisciplinary perspectives on emerging challenges, opportunities, and agenda for research, practice and policy. International Journal of Information Management, 57, 101994. https://doi.org/10.1016/J.IJINFOMGT.2019.08.002
Goldenthal, E., Park, J., Liu, S. X., Mieczkowski, H., & Hancock, J. T. (2021). Not All AI are Equal: Exploring the Accessibility of AI-Mediated Communication Technology. Computers in Human Behavior, 125, 106975. https://doi.org/10.1016/J.CHB.2021.106975
Gomez, C., Unberath, M., & Huang, C. M. (2023). Mitigating knowledge imbalance in AI-advised decision-making through collaborative user involvement. International Journal of Human-Computer Studies, 172, 102977. https://doi.org/10.1016/J.IJHCS.2022.102977
Grassini, S. (2023). Shaping the Future of Education: Exploring the Potential and Consequences of AI and ChatGPT in Educational Settings. Education Sciences, 13(7), 692. https://doi.org/10.3390/educsci13070692
Hamid, H., Zulkifli, K., Naimat, F., Che Yaacob, N. L., & Ng, K. W. (2023). Exploratory study on student perception on the use of chat AI in process-driven problem-based learning. Currents in Pharmacy Teaching and Learning, 15(12), 1017–1025. https://doi.org/10.1016/J.CPTL.2023.10.001
Hornberger, M., Bewersdorff, A., & Nerdel, C. (2023). What do university students know about Artificial Intelligence? Development and validation of an AI literacy test. Computers and Education: Artificial Intelligence, 5, 100165. https://doi.org/10.1016/J.CAEAI.2023.100165
Huang, A. Y. Q., Lu, O. H. T., & Yang, S. J. H. (2023). Effects of artificial Intelligence–Enabled personalized recommendations on learners’ learning engagement, motivation, and outcomes in a flipped classroom. Computers & Education, 194, 104684. https://doi.org/10.1016/J.COMPEDU.2022.104684
Jarrahi, M. H. (2018). Artificial intelligence and the future of work: Human-AI symbiosis in organizational decision making. Business Horizons, 61(4), 577–586. https://doi.org/10.1016/J.BUSHOR.2018.03.007
Labrague, L. J., Aguilar-Rosales, R., Yboa, B. C., & Sabio, J. B. (2023). Factors influencing student nurses’ readiness to adopt artificial intelligence (AI) in their studies and their perceived barriers to accessing AI technology: A cross-sectional study. Nurse Education Today, 130, 105945. https://doi.org/10.1016/J.NEDT.2023.105945
Liu, H., Peng, H., Song, X., Xu, C., & Zhang, M. (2022). Using AI chatbots to provide self-help depression interventions for university students: A randomized trial of effectiveness. Internet Interventions, 27, 100495. https://doi.org/10.1016/J.INVENT.2022.100495
Lu, W. Y., & Fan, S. C. (2023). Developing a weather prediction project-based machine learning course in facilitating AI learning among high school students. Computers and Education: Artificial Intelligence, 5, 100154. https://doi.org/10.1016/J.CAEAI.2023.100154
Markauskaite, L., Marrone, R., Poquet, O., Knight, S., Martinez-Maldonado, R., Howard, S., Tondeur, J., De Laat, M., Buckingham Shum, S., Gašević, D., & Siemens, G. (2022). Rethinking the entwinement between artificial intelligence and human learning: What capabilities do learners need for a world with AI? Computers and Education: Artificial Intelligence, 3, 100056. https://doi.org/10.1016/J.CAEAI.2022.100056
Marr, D. (1977). Artificial intelligence—A personal view. Artificial Intelligence, 9(1), 37–48. https://doi.org/10.1016/0004-3702(77)90013-3
Martín-Núñez, J. L., Ar, A. Y., Fernández, R. P., Abbas, A., & Radovanović, D. (2023). Does intrinsic motivation mediate perceived artificial intelligence (AI) learning and computational thinking of students during the COVID-19 pandemic? Computers and Education: Artificial Intelligence, 4, 100128. https://doi.org/10.1016/J.CAEAI.2023.100128
McGrath, C., Cerratto Pargman, T., Juth, N., & Palmgren, P. J. (2023). University teachers’ perceptions of responsibility and artificial intelligence in higher education - An experimental philosophical study. Computers and Education: Artificial Intelligence, 4, 100139. https://doi.org/10.1016/J.CAEAI.2023.100139
Molenaar, I. (2022). The concept of hybrid human-AI regulation: Exemplifying how to support young learners’ self-regulated learning. Computers and Education: Artificial Intelligence, 3, 100070. https://doi.org/10.1016/J.CAEAI.2022.100070
Nazaretsky, T., Mejia-Domenzain, P., Swamy, V., Frej, J., & Käser, T. (2025). The critical role of trust in adopting AI-powered educational technology for learning: An instrument for measuring student perceptions. Computers and Education: Artificial Intelligence, 8, 100368. https://doi.org/10.1016/J.CAEAI.2025.100368
Ouyang, F., & Jiao, P. (2021a). Artificial intelligence in education: The three paradigms. Computers and Education: Artificial Intelligence, 2, 100020. https://doi.org/10.1016/J.CAEAI.2021.100020
Ouyang, F., & Jiao, P. (2021b). Artificial intelligence in education: The three paradigms. Computers and Education: Artificial Intelligence, 2, 100020. https://doi.org/10.1016/J.CAEAI.2021.100020
Prentice, C., Weaven, S., & Wong, I. K. A. (2020). Linking AI quality performance and customer engagement: The moderating effect of AI preference. International Journal of Hospitality Management, 90, 102629. https://doi.org/10.1016/J.IJHM.2020.102629
Renz, A., Krishnaraja, S., & Gronau, E. (2020). Demystification of Artificial Intelligence in Education – How much AI is really in the Educational Technology? International Journal of Learning Analytics and Artificial Intelligence for Education (IJAI), 2(1), 14. https://doi.org/10.3991/ijai.v2i1.12675
Risko, E. F., & Gilbert, S. J. (2016). Cognitive Offloading. Trends in Cognitive Sciences, 20(9), 676–688. https://doi.org/10.1016/J.TICS.2016.07.002
Rosser, A., & Fahmi, M. (2018). The political economy of teacher management reform in Indonesia. International Journal of Educational Development, 61, 72–81. https://doi.org/10.1016/J.IJEDUDEV.2017.12.005
Ryan, R. M., & Deci, E. L. (2000). Self-determination theory and the facilitation of intrinsic motivation, social development, and well-being. American Psychologist, 55(1), 68–78. https://doi.org/10.1037/0003-066X.55.1.68
Soori, M., Arezoo, B., & Dastres, R. (2023). Artificial intelligence, machine learning and deep learning in advanced robotics, a review. Cognitive Robotics, 3, 54–70. https://doi.org/10.1016/J.COGR.2023.04.001
Southworth, J., Migliaccio, K., Glover, J., Glover, J. N., Reed, D., McCarty, C., Brendemuhl, J., & Thomas, A. (2023). Developing a model for AI Across the curriculum: Transforming the higher education landscape via innovation in AI literacy. Computers and Education: Artificial Intelligence, 4, 100127. https://doi.org/10.1016/J.CAEAI.2023.100127
Su, J., & Zhong, Y. (2022). Artificial Intelligence (AI) in early childhood education: Curriculum design and future directions. Computers and Education: Artificial Intelligence, 3, 100072. https://doi.org/10.1016/J.CAEAI.2022.100072
Suthers, D. D. (2012). Computer-Supported Collaborative Learning. In Encyclopedia of the Sciences of Learning (pp. 719–722). Springer US. https://doi.org/10.1007/978-1-4419-1428-6_389
Sweller, J. (1988a). Cognitive load during problem solving: Effects on learning. Cognitive Science, 12(2), 257–285. https://doi.org/10.1016/0364-0213(88)90023-7
Sweller, J. (1988b). Cognitive load during problem solving: Effects on learning. Cognitive Science, 12(2), 257–285. https://doi.org/10.1016/0364-0213(88)90023-7
Tan, S. C., Lee, A. V. Y., & Lee, M. (2022). A systematic review of artificial intelligence techniques for collaborative learning over the past two decades. Computers and Education: Artificial Intelligence, 3, 100097. https://doi.org/10.1016/J.CAEAI.2022.100097
van Dijk, J. A. G. M. (2006). Digital divide research, achievements and shortcomings. Poetics, 34(4–5), 221–235. https://doi.org/10.1016/J.POETIC.2006.05.004
Vygotsky, L. (1987). Zone of proximal development. Mind in Society: The Development of Higher Psychological Processes, 5291(157), 3.
Wei, Y., Lu, W., Cheng, Q., Jiang, T., & Liu, S. (2022). How humans obtain information from AI: Categorizing user messages in human-AI collaborative conversations. Information Processing & Management, 59(2), 102838. https://doi.org/10.1016/J.IPM.2021.102838
Wixted, J. T. (2024). Atkinson and Shiffrin’s (1968) influential model overshadowed their contemporary theory of human memory. Journal of Memory and Language, 136, 104471. https://doi.org/10.1016/J.JML.2023.104471
Wu, R., & Yu, Z. (2024). Do AI chatbots improve students learning outcomes? Evidence from a meta-analysis. British Journal of Educational Technology, 55(1), 10–33. https://doi.org/10.1111/bjet.13334
Xu, L. J., Wu, J., Zhu, J. D., & Chen, L. (2025). Effects of AI-assisted dance skills teaching, evaluation and visual feedback on dance students’ learning performance, motivation and self-efficacy. International Journal of Human-Computer Studies, 195, 103410. https://doi.org/10.1016/J.IJHCS.2024.103410
Yu, W., Wong, C. Y., Chavez, R., & Jacobs, M. A. (2021). Integrating big data analytics into supply chain finance: The roles of information processing and data-driven culture. International Journal of Production Economics, 236, 108135. https://doi.org/10.1016/J.IJPE.2021.108135
Zhang, H., Chai, J., & Li, C. (2024). On innovative strategies of youth sports teaching and training based on the internet of things and artificial intelligence technology from the perspective of humanism. Learning and Motivation, 86, 101969. https://doi.org/10.1016/J.LMOT.2024.101969
Alalwan, N., Cheng, L., Al-Samarraie, H., Yousef, R., Ibrahim Alzahrani, A., & Sarsam, S. M. (2020). Challenges and Prospects of Virtual Reality and Augmented Reality Utilization among Primary School Teachers: A Developing Country Perspective. Studies in Educational Evaluation, 66, 100876. https://doi.org/10.1016/J.STUEDUC.2020.100876
Bajaj, R., & Sharma, V. (2018). Smart Education with artificial intelligence based determination of learning styles. Procedia Computer Science, 132, 834–842. https://doi.org/10.1016/J.PROCS.2018.05.095
Banabilah, S., Aloqaily, M., Alsayed, E., Malik, N., & Jararweh, Y. (2022). Federated learning review: Fundamentals, enabling technologies, and future applications. Information Processing & Management, 59(6), 103061. https://doi.org/10.1016/J.IPM.2022.103061
Bhutoria, A. (2022). Personalized education and Artificial Intelligence in the United States, China, and India: A systematic review using a Human-In-The-Loop model. Computers and Education: Artificial Intelligence, 3, 100068. https://doi.org/10.1016/J.CAEAI.2022.100068
Chang, D. H., Lin, M. P.-C., Hajian, S., & Wang, Q. Q. (2023). Educational Design Principles of Using AI Chatbot That Supports Self-Regulated Learning in Education: Goal Setting, Feedback, and Personalization. Sustainability, 15(17), 12921. https://doi.org/10.3390/su151712921
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
Cheng, E. C. K., & Wang, T. (2023). Leading digital transformation and eliminating barriers for teachers to incorporate artificial intelligence in basic education in Hong Kong. Computers and Education: Artificial Intelligence, 5, 100171. https://doi.org/10.1016/J.CAEAI.2023.100171
Daniere, A. (1965). GARY S. BECKER. Human Capital: A Theoretical and Empirical Analysis, with Special Reference to Education. Pp. xvi, 187. New York: National Bureau of Economic Research, 1964. $5.00. The ANNALS of the American Academy of Political and Social Science, 360(1), 208–209. https://doi.org/10.1177/000271626536000153
Dwivedi, Y. K., Hughes, L., Ismagilova, E., Aarts, G., Coombs, C., Crick, T., Duan, Y., Dwivedi, R., Edwards, J., Eirug, A., Galanos, V., Ilavarasan, P. V., Janssen, M., Jones, P., Kar, A. K., Kizgin, H., Kronemann, B., Lal, B., Lucini, B., … Williams, M. D. (2021). Artificial Intelligence (AI): Multidisciplinary perspectives on emerging challenges, opportunities, and agenda for research, practice and policy. International Journal of Information Management, 57, 101994. https://doi.org/10.1016/J.IJINFOMGT.2019.08.002
Goldenthal, E., Park, J., Liu, S. X., Mieczkowski, H., & Hancock, J. T. (2021). Not All AI are Equal: Exploring the Accessibility of AI-Mediated Communication Technology. Computers in Human Behavior, 125, 106975. https://doi.org/10.1016/J.CHB.2021.106975
Gomez, C., Unberath, M., & Huang, C. M. (2023). Mitigating knowledge imbalance in AI-advised decision-making through collaborative user involvement. International Journal of Human-Computer Studies, 172, 102977. https://doi.org/10.1016/J.IJHCS.2022.102977
Grassini, S. (2023). Shaping the Future of Education: Exploring the Potential and Consequences of AI and ChatGPT in Educational Settings. Education Sciences, 13(7), 692. https://doi.org/10.3390/educsci13070692
Hamid, H., Zulkifli, K., Naimat, F., Che Yaacob, N. L., & Ng, K. W. (2023). Exploratory study on student perception on the use of chat AI in process-driven problem-based learning. Currents in Pharmacy Teaching and Learning, 15(12), 1017–1025. https://doi.org/10.1016/J.CPTL.2023.10.001
Hornberger, M., Bewersdorff, A., & Nerdel, C. (2023). What do university students know about Artificial Intelligence? Development and validation of an AI literacy test. Computers and Education: Artificial Intelligence, 5, 100165. https://doi.org/10.1016/J.CAEAI.2023.100165
Huang, A. Y. Q., Lu, O. H. T., & Yang, S. J. H. (2023). Effects of artificial Intelligence–Enabled personalized recommendations on learners’ learning engagement, motivation, and outcomes in a flipped classroom. Computers & Education, 194, 104684. https://doi.org/10.1016/J.COMPEDU.2022.104684
Jarrahi, M. H. (2018). Artificial intelligence and the future of work: Human-AI symbiosis in organizational decision making. Business Horizons, 61(4), 577–586. https://doi.org/10.1016/J.BUSHOR.2018.03.007
Labrague, L. J., Aguilar-Rosales, R., Yboa, B. C., & Sabio, J. B. (2023). Factors influencing student nurses’ readiness to adopt artificial intelligence (AI) in their studies and their perceived barriers to accessing AI technology: A cross-sectional study. Nurse Education Today, 130, 105945. https://doi.org/10.1016/J.NEDT.2023.105945
Liu, H., Peng, H., Song, X., Xu, C., & Zhang, M. (2022). Using AI chatbots to provide self-help depression interventions for university students: A randomized trial of effectiveness. Internet Interventions, 27, 100495. https://doi.org/10.1016/J.INVENT.2022.100495
Lu, W. Y., & Fan, S. C. (2023). Developing a weather prediction project-based machine learning course in facilitating AI learning among high school students. Computers and Education: Artificial Intelligence, 5, 100154. https://doi.org/10.1016/J.CAEAI.2023.100154
Markauskaite, L., Marrone, R., Poquet, O., Knight, S., Martinez-Maldonado, R., Howard, S., Tondeur, J., De Laat, M., Buckingham Shum, S., Gašević, D., & Siemens, G. (2022). Rethinking the entwinement between artificial intelligence and human learning: What capabilities do learners need for a world with AI? Computers and Education: Artificial Intelligence, 3, 100056. https://doi.org/10.1016/J.CAEAI.2022.100056
Marr, D. (1977). Artificial intelligence—A personal view. Artificial Intelligence, 9(1), 37–48. https://doi.org/10.1016/0004-3702(77)90013-3
Martín-Núñez, J. L., Ar, A. Y., Fernández, R. P., Abbas, A., & Radovanović, D. (2023). Does intrinsic motivation mediate perceived artificial intelligence (AI) learning and computational thinking of students during the COVID-19 pandemic? Computers and Education: Artificial Intelligence, 4, 100128. https://doi.org/10.1016/J.CAEAI.2023.100128
McGrath, C., Cerratto Pargman, T., Juth, N., & Palmgren, P. J. (2023). University teachers’ perceptions of responsibility and artificial intelligence in higher education - An experimental philosophical study. Computers and Education: Artificial Intelligence, 4, 100139. https://doi.org/10.1016/J.CAEAI.2023.100139
Molenaar, I. (2022). The concept of hybrid human-AI regulation: Exemplifying how to support young learners’ self-regulated learning. Computers and Education: Artificial Intelligence, 3, 100070. https://doi.org/10.1016/J.CAEAI.2022.100070
Nazaretsky, T., Mejia-Domenzain, P., Swamy, V., Frej, J., & Käser, T. (2025). The critical role of trust in adopting AI-powered educational technology for learning: An instrument for measuring student perceptions. Computers and Education: Artificial Intelligence, 8, 100368. https://doi.org/10.1016/J.CAEAI.2025.100368
Ouyang, F., & Jiao, P. (2021a). Artificial intelligence in education: The three paradigms. Computers and Education: Artificial Intelligence, 2, 100020. https://doi.org/10.1016/J.CAEAI.2021.100020
Ouyang, F., & Jiao, P. (2021b). Artificial intelligence in education: The three paradigms. Computers and Education: Artificial Intelligence, 2, 100020. https://doi.org/10.1016/J.CAEAI.2021.100020
Prentice, C., Weaven, S., & Wong, I. K. A. (2020). Linking AI quality performance and customer engagement: The moderating effect of AI preference. International Journal of Hospitality Management, 90, 102629. https://doi.org/10.1016/J.IJHM.2020.102629
Renz, A., Krishnaraja, S., & Gronau, E. (2020). Demystification of Artificial Intelligence in Education – How much AI is really in the Educational Technology? International Journal of Learning Analytics and Artificial Intelligence for Education (IJAI), 2(1), 14. https://doi.org/10.3991/ijai.v2i1.12675
Risko, E. F., & Gilbert, S. J. (2016). Cognitive Offloading. Trends in Cognitive Sciences, 20(9), 676–688. https://doi.org/10.1016/J.TICS.2016.07.002
Rosser, A., & Fahmi, M. (2018). The political economy of teacher management reform in Indonesia. International Journal of Educational Development, 61, 72–81. https://doi.org/10.1016/J.IJEDUDEV.2017.12.005
Ryan, R. M., & Deci, E. L. (2000). Self-determination theory and the facilitation of intrinsic motivation, social development, and well-being. American Psychologist, 55(1), 68–78. https://doi.org/10.1037/0003-066X.55.1.68
Soori, M., Arezoo, B., & Dastres, R. (2023). Artificial intelligence, machine learning and deep learning in advanced robotics, a review. Cognitive Robotics, 3, 54–70. https://doi.org/10.1016/J.COGR.2023.04.001
Southworth, J., Migliaccio, K., Glover, J., Glover, J. N., Reed, D., McCarty, C., Brendemuhl, J., & Thomas, A. (2023). Developing a model for AI Across the curriculum: Transforming the higher education landscape via innovation in AI literacy. Computers and Education: Artificial Intelligence, 4, 100127. https://doi.org/10.1016/J.CAEAI.2023.100127
Su, J., & Zhong, Y. (2022). Artificial Intelligence (AI) in early childhood education: Curriculum design and future directions. Computers and Education: Artificial Intelligence, 3, 100072. https://doi.org/10.1016/J.CAEAI.2022.100072
Suthers, D. D. (2012). Computer-Supported Collaborative Learning. In Encyclopedia of the Sciences of Learning (pp. 719–722). Springer US. https://doi.org/10.1007/978-1-4419-1428-6_389
Sweller, J. (1988a). Cognitive load during problem solving: Effects on learning. Cognitive Science, 12(2), 257–285. https://doi.org/10.1016/0364-0213(88)90023-7
Sweller, J. (1988b). Cognitive load during problem solving: Effects on learning. Cognitive Science, 12(2), 257–285. https://doi.org/10.1016/0364-0213(88)90023-7
Tan, S. C., Lee, A. V. Y., & Lee, M. (2022). A systematic review of artificial intelligence techniques for collaborative learning over the past two decades. Computers and Education: Artificial Intelligence, 3, 100097. https://doi.org/10.1016/J.CAEAI.2022.100097
van Dijk, J. A. G. M. (2006). Digital divide research, achievements and shortcomings. Poetics, 34(4–5), 221–235. https://doi.org/10.1016/J.POETIC.2006.05.004
Vygotsky, L. (1987). Zone of proximal development. Mind in Society: The Development of Higher Psychological Processes, 5291(157), 3.
Wei, Y., Lu, W., Cheng, Q., Jiang, T., & Liu, S. (2022). How humans obtain information from AI: Categorizing user messages in human-AI collaborative conversations. Information Processing & Management, 59(2), 102838. https://doi.org/10.1016/J.IPM.2021.102838
Wixted, J. T. (2024). Atkinson and Shiffrin’s (1968) influential model overshadowed their contemporary theory of human memory. Journal of Memory and Language, 136, 104471. https://doi.org/10.1016/J.JML.2023.104471
Wu, R., & Yu, Z. (2024). Do AI chatbots improve students learning outcomes? Evidence from a meta-analysis. British Journal of Educational Technology, 55(1), 10–33. https://doi.org/10.1111/bjet.13334
Xu, L. J., Wu, J., Zhu, J. D., & Chen, L. (2025). Effects of AI-assisted dance skills teaching, evaluation and visual feedback on dance students’ learning performance, motivation and self-efficacy. International Journal of Human-Computer Studies, 195, 103410. https://doi.org/10.1016/J.IJHCS.2024.103410
Yu, W., Wong, C. Y., Chavez, R., & Jacobs, M. A. (2021). Integrating big data analytics into supply chain finance: The roles of information processing and data-driven culture. International Journal of Production Economics, 236, 108135. https://doi.org/10.1016/J.IJPE.2021.108135
Zhang, H., Chai, J., & Li, C. (2024). On innovative strategies of youth sports teaching and training based on the internet of things and artificial intelligence technology from the perspective of humanism. Learning and Motivation, 86, 101969. https://doi.org/10.1016/J.LMOT.2024.101969
Published
2025-04-30
How to Cite
Auna, H., Polamolo, C., Auna, I., Ma’ruf, A. R., & Darojat, A. (2025). Economic Education Students’ Perspectives on AI Utilization in Learning: A Descriptive Study. Pedagogi: Jurnal Ilmu Pendidikan, 25(1), 206-216. https://doi.org/https://doi.org/10.24036/pedagogi.v25i1.2496
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Articles
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