Enhancing Abstract Reasoning through AI and Reading for Emotion: Insights from Indonesian Pre-Service English Teachers
(1) Universitas Islam Negeri Siber Syekh Nurjati Cirebon
(2) Universitas Islam Negeri Siber Syekh Nurjati Cirebon
(3) Universitas Islam Negeri Siber Syekh Nurjati Cirebon
(*) Corresponding Author
Abstract
This study explores the integration of Artificial Intelligence (AI) and the "Reading for Emotion" approach to enhance abstract reasoning skills among Indonesian pre-service English teachers at UIN Cyber Syekh Nurjati Cirebon. The research addresses a critical issue in teacher education: the necessity for effective strategies that foster deeper comprehension and critical analysis of academic texts. Existing literature emphasizes the role of emotions in learning, indicating that traditional cognitive approaches may overlook essential emotional dimensions. The primary aim of this research is to examine how pre-service English teachers utilize Reading for Emotion and Aesthetics to improve their understanding and critical analysis of academic papers. This aligns with Lian (2017) and Lian (2024) that transformative learning must begin with students reflecting on their relationship with the world, rather than merely performing tasks. Using a qualitative case study method, data were gathered from 10 participants via questionnaires and 3 informants through interviews throughout the third semester. The findings indicate that emotional engagement significantly enhances students' comprehension and analytical skills, suggesting that understanding emotions is crucial for effective learning. This research contributes to the discourse on innovative pedagogical strategies in teacher education, highlighting the need for further exploration of emotional approaches in academic contexts.
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Alan, S., & Turkum, B. (2024). Abstract reasoning, theory of mind, and character development in the school. Journal of Economic Behavior & Organization, 221, 307-326.
Anderson, L. W., & Krathwohl, D. R. (2001). A taxonomy for learning, teaching, and assessing: A revision of Bloom's taxonomy of educational objectives: complete edition. Addison Wesley Longman, Inc.
Andrew, L. (2022). Hidden impacts and stereotypes of technology in language learning: 2nd Presidential Keynote Address–18th AsiaCALL International Conference. AsiaCALL Online Journal, 13(4), 1-6.
Aspers, P., & Corte, U. (2021). What is qualitative in research? Qualitative Sociology, 1-10.
Baxter, P., & Jack, S. (2008). Qualitative case study methodology: Study design and implementation for novice researchers. The qualitative report, 13(4), 544-559.
Budiana, A. (2022). Impact of abstract reasoning skills on language teaching. Journal of Linguistic and English Teaching.
Cattell, R. B. (1963). Theory of fluid and crystallized intelligence: A critical experiment. Journal of Educational Psychology, 54(1), 1-22.
Conklin, W. (2011). Higher-order thinking skills to develop 21st-century learners. Teacher Created Materials.
Creswell, J. W., & Creswell, J. D. (2017). Research design: Qualitative, quantitative, and mixed methods approaches. Sage publications.
Damasio, A. & Immordino-Yang, H. (2007). We feel, therefore we learn: The relevance of affective and social neuroscience to education, International Mind, Brain, and Education Society, 1(1), 3-10. doi:10.1111/j.1751-228X.2007.00004.x.
Helyanti, N. D., Bumela, L., & Ikawati, L. (2022). Kurikulum Merdeka reimagined: Adopting story science for English literacy learning in Indonesian middle school. ELT Echo: The Journal of English Language Teaching in Foreign Language Context, 7(2), 202.
Holmes, W., & Porayska-Pomsta, K. (2023). The ethics of artificial intelligence in education. Routledge Taylor.
Huffcutt, A. I., Weekley, J. A., Wiesner, W. H., Degroot, T. G., & Jones, C. (2001). Comparison of situational and behavior description interview questions for higher‐level positions. Personnel Psychology, 54(3), 619-644.
Immordino-Yang, M. H. (2016). Emotion, sociality, and the brain’s default mode network: Insights for educational practice and policy. Policy Insights from the Behavioral and Brain Sciences, 3(2), 211-219.
Immordino-Yang, M. H., Darling-Hammond, L., & Krone, C. (2018). The Brain Basis for Integrated Social, Emotional, and Academic Development: How Emotions and Social Relationships Drive Learning. Aspen Institute.
Indriyani, S., & Sudimantara, L. B. (2023). Incorporating CEFR Principles in Developing a Hypertext Poetry Learning Platform for High School Students. Intensive Journal, 6(2), 39-58.
Knott, E., Rao, A. H., Summers, K., & Teeger, C. (2022). Interviews in the social sciences. Nature Reviews Methods Primers, 2(1), 73.
Kohnke, L., Zou, D., & Zhang, R. (2021). Pre-Service Teachers’ Perceptions of Emotions and Self-Regulatory Learning in Emergency Remote Learning. Sustainability, 13(13), 7111. https://doi.org/10.3390/su13137111
Lange, J., Heerdink, M. W., & Van Kleef, G. A. (2022). Reading emotions, reading people:
Emotion perception and inferences drawn from perceived emotions. Current opinion in psychology, 43, 85-90.
Lian, A. (2023). Integrating ChatGPT into L2-Learning: Implications for Research, Policy and Practice. 7.
Lian, A. (2024). Integrating AI and Neuroscience in L2 Literacy Education: Advancing Emotional Literacy and Social Equity through ChatGPT and the Reading for Emotional Model. In International Conference on Education and Innovation (ICEI) (Vol. 1, No. 1, pp. ii-ii). Link video: https://youtu.be/18BuwVZtrMc?si=CSwUm24NSNPIEsC4
Lian, A.B. (2017). Reading for emotion with ICT tools. In Chen, W. et al. (Eds.) (2017). Proceedings of the 25th International Conference on Computers in Education. (Internationally refereed proceedings) New Zealand: Asia-Pacific Society for Computers in Education.
Lian, A. (2021). Team teaching with overseas partners in the days of the “New normal”: A better way to introduce innovation and build local expertise. Advances in Social Science, Education and Humanities Research, 246- 258. https://doi.org/10.2991/assehr.k.211224.024
OECD, (2019). PISA 2018 Assessment and Analytical Framework. Paris: OECD Publishing. http://doi.org/10.1787/b25efab8-en
OECD, (2023). PISA 2022 Assessment and Analytical Framework. Paris: OECD Publishing. https://www.oecd.org/publication/pisa-2022-results/country-notes/indonesia- c2e1ae0e/
OpenAI, Achiam, J., Adler, S., Agarwal, S., Ahmad, L., Akkaya, I., Aleman, F. L., Almeida, D., Altenschmidt, J., Altman, S., Anadkat, S., Avila, R., Babuschkin, I., Balaji, S., Balcom, V., Baltescu, P., Bao, H., Bavarian, M., Belgum, J., … Zoph, B. GPT-4 Technical Report, 4, 1–100. http://arxiv.org/abs/2303.08774
Panksepp, J. (1998). Affective Neuroscience: The Foundations of Human and Animal Emotions. New York: Oxford University Press.
Pekrun, R., & Linnenbrink-Garcia, L. (2014). International handbook of emotions in education. Routledge.
Ramachandran, V. S., & Hirstein, W. (1999). The science of art: A neurological theory of aesthetic experience. Journal of Consciousness Studies, 6(6-7), 15-51.
Rosenberg, E. L., & Ekman, P. (2020). What the face reveals: Basic and applied studies of spontaneous expression using the Facial Action Coding System (FACS). Oxford University Press.
Sudimantara, L. B. (2023). Perspectives and experiences of Indonesian pre-service English teachers in developing digital learning resources. English Review: Journal of English Education, 11(2), 609-628. https://doi.org/10.25134/erjee.v11i3.7919
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