The Relationship Between Student Self-confidence, AI Support, and Academic Achievement: A Study in the Psychology of Motivation and Learning
Abstract
This research explores the relationship between student self-confidence, artificial intelligence (AI) support, and academic achievement in the psychology of motivation and learning. In this digital era, AI technology is increasingly used in education to facilitate teaching-learning. This research examines How AI support can affect students' self-confidence and how it affects their academic performance. Data are collected from 80 students at STPK ST. Yohanes Rasul Jayapura, Thomas Aquinas College of Agriculture 100 people, and Papua International University 20 people, 120 via questionnaire. The research results show that students' self-confidence and AI support are essential in improving academic performance. Implementing AI technology in education not only helps deliver lesson material but also contributes to improving students' self-confidence. Therefore, schools and institutions of education recommend using AI technology as a learning strategy to maximize potential student academics.
Downloads
References
Alfaiz, A., Hidayat, H., Yandri, H., Sari, A. T. L., Sendayu, F. S., Suarja, S., & Arjoni, A. (2021). Identification of Perceived Self-Efficacy to Predict Student’s Awareness in Career Readiness. Islamic Guidance and Counseling Journal, 4(1), 124–132. https://doi.org/10.25217/IGCJ.V4I1.933
Almasri, F. (2022). Simulations to Teach Science Subjects: Connections Among Students’ Engagement, Self-Confidence, Satisfaction, and Learning Styles. Education and Information Technologies, 27(5), 7161–7181. https://doi.org/10.1007/S10639-022-10940-W/TABLES/5
Arini, M., & Wahyudin, A. Y. (2022). Students’ Perception On Questionning Technique In Improving Speaking Skill Ability at English Education Study Program. Journal of Arts and Education, 1(2), 2022. https://doi.org/10.33365/JAE.V2I1.70
Bear, G. G., & Soltys, A. (2020). Developing Social and Emotional Competencies and Self-Discipline. In Improving School Climate. Routledge. https://doi.org/10.4324/9781351170482-4
Buehl, D. (2023). Classroom Strategies for Interactive Learning. Classroom Strategies for Interactive Learning, 1–260. https://doi.org/10.4324/9781032680842/CLASSROOM-STRATEGIES-INTERACTIVE-LEARNING-DOUG-BUEHL
Castonguay, A., Farthing, P., Davies, S., Vogelsang, L., Kleib, M., Risling, T., & Green, N. (2023). Revolutionizing nursing education through Ai integration: A reflection on the disruptive impact of ChatGPT. Nurse Education Today, 129, 105916. https://doi.org/10.1016/J.NEDT.2023.105916
Collie, R. J. (2022). Perceived social-emotional competence: A multidimensional examination and links with social-emotional motivation and behaviors. Learning and Instruction, 82, 101656. https://doi.org/10.1016/J.LEARNINSTRUC.2022.101656
Dai, Y., Liu, A., & Lim, C. P. (2023). Reconceptualizing ChatGPT and generative AI as a student-driven innovation in higher education. Procedia CIRP, 119, 84–90. https://doi.org/10.1016/J.PROCIR.2023.05.002
Duli, N. (2019). Metodologi Penelitian Kuantitatif: Beberapa Konsep Dasar Untuk Penulisan Skripsi & Analisis Data Dengan SPSS. Deepublish.
Fesenmaier, D. R., & Wöber, K. (2023). AI, ChatGPT and the university. Annals of Tourism Research, 101, 103578. https://doi.org/10.1016/J.ANNALS.2023.103578
Gamage, K. A. A., Dehideniya, D. M. S. C. P. K., & Ekanayake, S. Y. (2021). The Role of Personal Values in Learning Approaches and Student Achievements. Behavioral Sciences 2021, Vol. 11, Page 102, 11(7), 102. https://doi.org/10.3390/BS11070102
García-Martínez, I., Pérez-Navío, E., Pérez-Ferra, M., & Quijano-López, R. (2021). Relationship between Emotional Intelligence, Educational Achievement and Academic Stress of Pre-Service Teachers. Behavioral Sciences 2021, Vol. 11, Page 95, 11(7), 95. https://doi.org/10.3390/BS11070095
Guo, W., Bai, B., Zang, F., Wang, T., & Song, H. (2023). Influences of motivation and grit on students’ self-regulated learning and English learning achievement: A comparison between male and female students. System, 114, 103018. https://doi.org/10.1016/J.SYSTEM.2023.103018
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
Han, J., Wang, Y., Qian, J., & Shi, M. (2023). Delving into the role of creativity on meaning in life: A multiple mediation model. Heliyon, 9(6), e16566. https://doi.org/10.1016/J.HELIYON.2023.E16566
Herrera Granda, A., Yepes, S. M., Montes Granada, W. F., & Alvarez Salazar, J. (2022). Students’ self-perception of social, emotional, and intercultural competences in a public higher education institution in Colombia. Journal for Multicultural Education, 17(1), 70–82. https://doi.org/10.1108/JME-02-2022-0032
Ishartono, N., Faiziyah, N., Sutarni, S., Putri, A. B., Fatmasari, L. W. S., Sayuti, M., Rahmaniati, R., & Yunus, M. M. (2021). Visual, Auditory, and Kinesthetic Students: How They Solve PISA-Oriented Mathematics Problems? Journal of Physics: Conference Series, 1720(1), 012012. https://doi.org/10.1088/1742-6596/1720/1/012012
Khanshan, S. K., & Yousefi, M. H. (2020). The relationship between self-efficacy and instructional practice of in-service soft disciplines, hard disciplines and EFL teachers. Asian-Pacific Journal of Second and Foreign Language Education, 5(1), 1–20. https://doi.org/10.1186/S40862-020-0080-8/TABLES/8
Khogali, H. O., & Mekid, S. (2023). The blended future of automation and AI: Examining some long-term societal and ethical impact features. Technology in Society, 73, 102232. https://doi.org/10.1016/J.TECHSOC.2023.102232
Lim, W. M., Gunasekara, A., Pallant, J. L., Pallant, J. I., & Pechenkina, E. (2023). Generative AI and the future of education: Ragnarök or reformation? A paradoxical perspective from management educators. The International Journal of Management Education, 21(2), 100790. https://doi.org/10.1016/J.IJME.2023.100790
Malik, A. R., Pratiwi, Y., Andajani, K., Numertayasa, I. W., Suharti, S., Darwis, A., & Marzuki. (2023). Exploring Artificial Intelligence in Academic Essay: Higher Education Student’s Perspective. International Journal of Educational Research Open, 5, 100296. https://doi.org/10.1016/J.IJEDRO.2023.100296
Meeter, M., Bele, T., Hartogh, C. den, Bakker, T., Vries, R. E. de, & Plak, S. (2020). College students’ motivation and study results after COVID-19 stay-at-home orders. https://doi.org/10.31234/OSF.IO/KN6V9
Nuraniza, S. (2022). Pengaruh Self Control dan Self Confidence Terhadap Hasil Belajar PAI Siswa Kelas XI di SMA Negeri 1 Grogol Kediri [IAIN Kediri]. https://etheses.iainkediri.ac.id/6077/
Pence, P. L. (2022). Student satisfaction and self-confidence in learning with virtual simulations. Teaching and Learning in Nursing, 17(1), 31–35. https://doi.org/10.1016/J.TELN.2021.07.008
Sethi, J., & Scales, P. C. (2020). Developmental relationships and school success: How teachers, parents, and friends affect educational outcomes and what actions students say matter most. Contemporary Educational Psychology, 63, 101904. https://doi.org/10.1016/J.CEDPSYCH.2020.101904
Stavropoulou, G., Stamovlasis, D., & Gonida, S. E. (2023). Probing the effects of perceived teacher goals and achievement-goal orientations on students’ self-efficacy, cognitive and metacognitive strategies in writing: A person-centered approach. Learning and Motivation, 82, 101888. https://doi.org/10.1016/J.LMOT.2023.101888
Steele, J. L. (2023). To GPT or not GPT? Empowering our students to learn with AI. Computers and Education: Artificial Intelligence, 5, 100160. https://doi.org/10.1016/J.CAEAI.2023.100160
Wardani, A. D., Gunawan, I., Kusumaningrum, D. E., Benty, D. D. N., Sumarsono, R. B., Nurabadi, A., & Handayani, L. (2020). Student Learning Motivation: A Conceptual Paper. 275–278. https://doi.org/10.2991/ASSEHR.K.201112.049
Yilmaz, R., & Karaoglan Yilmaz, F. G. (2023a). The effect of generative artificial intelligence (AI)-based tool use on students’ computational thinking skills, programming self-efficacy and motivation. Computers and Education: Artificial Intelligence, 4, 100147. https://doi.org/10.1016/J.CAEAI.2023.100147
Yilmaz, R., & Karaoglan Yilmaz, F. G. (2023b). The effect of generative artificial intelligence (AI)-based tool use on students’ computational thinking skills, programming self-efficacy and motivation. Computers and Education: Artificial Intelligence, 4, 100147. https://doi.org/10.1016/J.CAEAI.2023.100147
Copyright (c) 2023 Evaristus Silitubun

This work is licensed under a Creative Commons Attribution 4.0 International License.
Authors who publish with this journal agree to the following terms:
1) Authors retain copyright and grant the journal the right to first publication, with the work simultaneously licensed under the Creative Commons Attribution that allows the sharing of articles published with the acknowledgement of authorship and the initial publication in this magazine.
2) The authors are authorized to make additional contracts separately for distribution of the version of the work published in this journal (for example, publication in an institutional repository or as a chapter of the book), as long as there is recognition of authorship and initial publication in this journal.
3) Authors are authorized and encouraged to publish and distribute their work online (for example, in institutional repositories or on their personal pages) at any time before or during the editorial process, as it increases the impact and reference of the published work.