Use of ICT and artificial intelligence as psycho-pedagogical strategies to strengthen critical reading in students with specific educational needs
DOI:
https://doi.org/10.71112/jcqx1318Keywords:
Artificial intelligence, ICT, critical reading, specific educational needs, psycho-pedagogical strategiesAbstract
The study analyzed the use of Information and Communication Technologies (ICT) and artificial intelligence as psycho-pedagogical strategies to strengthen critical reading skills in students with specific educational needs. It employed a quantitative approach with a non-experimental, cross-sectional, and descriptive-correlational design. Participants included 100 students from the upper levels of General Basic Education and the Unified General Baccalaureate at a public educational institution in Ecuador. Data were collected using a structured 20-item questionnaire, organized into four dimensions and administered using a five-point Likert scale. The results showed favorable assessments regarding the educational use of ICT, artificial intelligence, inclusive psycho-pedagogical strategies, and critical reading. Furthermore, positive associations were observed among these variables, highlighting the combined integration of ICT and artificial intelligence with critical reading. The study concluded that these tools served as pertinent resources to support inclusive learning processes, provided they were utilized through planned, responsible psycho-pedagogical mediation aimed at fostering analysis, reflection, and critical evaluation of information by the participating students.
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Besekar, S., Jogdand, S., & Naqvi, W. (2024). Sample size in educational research: A rapid synthesis. F1000Research, 12, 1291. https://doi.org/10.12688/f1000research.141173.3 DOI: https://doi.org/10.12688/f1000research.141173.2
Essel, H. B., Vlachopoulos, D., Tachie-Menson, A., Johnson, E. E., & Ebeheakey, A. K. (2024). ChatGPT effects on cognitive skills of undergraduate students: Receiving instant responses from AI-based conversational large language models (LLMs). Computers and Education: Artificial Intelligence, 6, 100198. https://doi.org/10.1016/j.caeai.2023.100198 DOI: https://doi.org/10.1016/j.caeai.2023.100198
Fitas, R. (2025). Inclusive education with AI: Supporting special needs and tackling language barriers. AI and Ethics, 5, 5729–5757. https://doi.org/10.1007/s43681-025-00824-3 DOI: https://doi.org/10.1007/s43681-025-00824-3
Flowers, J. (2024). Review of participatory research assent procedures in school psychology. Psychology in the Schools. https://doi.org/10.1002/pits.23112 Wiley Online Library DOI: https://doi.org/10.1002/pits.23112
Gallud, J. A., Carreño, M., Tesoriero, R., Sandoval, A., Lozano, M. D., Durán, I., & Cosio, R. (2023). Technology-enhanced and game-based learning for children with special needs: A systematic mapping study. Universal Access in the Information Society, 22, 227–240. https://doi.org/10.1007/s10209-021-00824-0 DOI: https://doi.org/10.1007/s10209-021-00824-0
Huang, J., & Wang, Y. (2023). Examining Chinese social sciences graduate students’ understanding of research ethics: Implications for their research ethics education. Humanities and Social Sciences Communications, 10, 487. https://doi.org/10.1057/s41599-023-02000-6 DOI: https://doi.org/10.1057/s41599-023-02000-6
Kusmaryono, I., Wijayanti, D., & Maharani, H. R. (2022). Number of response options, reliability, validity, and potential bias in the use of the Likert scale education and social science research: A literature review. International Journal of Educational Methodology, 8(4), 625–637. https://doi.org/10.12973/ijem.8.4.625 DOI: https://doi.org/10.12973/ijem.8.4.625
Lee, C. C., & Low, M. Y. H. (2024). Using genAI in education: The case for critical thinking. Frontiers in Artificial Intelligence, 7, 1452131. https://doi.org/10.3389/frai.2024.1452131 DOI: https://doi.org/10.3389/frai.2024.1452131
Mikropoulos, T. A., & Iatraki, G. (2023). Digital technology supports science education for students with disabilities: A systematic review. Education and Information Technologies, 28, 3911–3935. https://doi.org/10.1007/s10639-022-11317-9 DOI: https://doi.org/10.1007/s10639-022-11317-9
Msafiri, M. M., Kangwa, D., & Cai, L. (2023). A systematic literature review of ICT integration in secondary education: What works, what does not, ¿and what next? Discover Education, 2, Article 44. https://doi.org/10.1007/s44217-023-00070-x DOI: https://doi.org/10.1007/s44217-023-00070-x
Niloy, A. C., Bari, M. A., Sultana, J., Chowdhury, R., Raisa, F. M., Islam, A., Mahmud, S., Jahan, I., Sarkar, M., Akter, S., Nishat, N., Afroz, M., Sen, A., Islam, T., Tareq, M. H., & Hossen, M. A. (2024). Why do students use ChatGPT? Answering through a triangulation approach. Computers and Education: Artificial Intelligence, 6, 100208. https://doi.org/10.1016/j.caeai.2024.100208 DOI: https://doi.org/10.1016/j.caeai.2024.100208
Ogle, K., et al. (2023). Educator’s blueprint: A how-to guide on survey administration. AEM Education and Training. https://doi.org/10.1002/aet2.10906 Wiley Online Library DOI: https://doi.org/10.1002/aet2.10906
Ogunleye, B., Zakariyyah, K. I., Ajao, O., Olayinka, O., & Sharma, H. (2024). A systematic review of generative AI for teaching and learning practice. Education Sciences, 14(6), 636. https://doi.org/10.3390/educsci14060636 DOI: https://doi.org/10.3390/educsci14060636
Pagliara, S. M., Pia, M., Falchi, S., Zurru, A. L., Fenu, G., & Mura, A. (2024). The integration of artificial intelligence in inclusive education: A scoping review. Information, 15(12), 774. https://doi.org/10.3390/info15120774 DOI: https://doi.org/10.3390/info15120774
Romero Jeldres, M., Díaz Costa, E., & Faouzi Nadim, T. (2023). A review of Lawshe’s method for calculating content validity in the social sciences. Frontiers in Education, 8, 1271335. https://doi.org/10.3389/feduc.2023.1271335 DOI: https://doi.org/10.3389/feduc.2023.1271335
Stalmach, A., D’Elia, P., Di Sano, S., & Casale, G. (2023). Digital learning and self-regulation in students with special educational needs: A systematic review of current research and future directions. Education Sciences, 13(10), 1051. https://doi.org/10.3390/educsci13101051 DOI: https://doi.org/10.3390/educsci13101051
Styve, A., Virkki, O. T., & Naeem, U. (2024). Developing critical thinking practices interwoven with generative AI usage in an introductory programming course. 2024 IEEE Global Engineering Education Conference (EDUCON), 1–8. https://doi.org/10.1109/EDUCON60312.2024.10578746 DOI: https://doi.org/10.1109/EDUCON60312.2024.10578746
Tabernero-Sala, R., & Colón-Castillo, M. J. (2023). The promotion of critical reading through the digital environment: A study on the virtual epitexts used to promote children’s picturebooks. Frontiers in Psychology, 14, 1154513. https://doi.org/10.3389/fpsyg.2023.1154513 DOI: https://doi.org/10.3389/fpsyg.2023.1154513
Tang, K.-S., Cooper, G., Rappa, N., Cooper, M., Sims, C., & Nonis, K. (2024). A dialogic approach to transform teaching, learning & assessment with generative AI in secondary education: A proof of concept. Pedagogies: An International Journal, 19(3), 493–503. https://doi.org/10.1080/1554480X.2024.2379774 DOI: https://doi.org/10.1080/1554480X.2024.2379774
Wafudu, S. J., Kamin, Y. B., & Marcel, D. (2022). Validity and reliability of a questionnaire developed to explore quality assurance components for teaching and learning in vocational and technical education. Humanities and Social Sciences Communications, 9, 303. https://doi.org/10.1057/s41599-022-01306-1 Nature DOI: https://doi.org/10.1057/s41599-022-01306-1
Walter, Y. (2024). Embracing the future of artificial intelligence in the classroom: The relevance of AI literacy, prompt engineering, and critical thinking in modern education. International Journal of Educational Technology in Higher Education, 21, 15. https://doi.org/10.1186/s41239-024-00448-3 DOI: https://doi.org/10.1186/s41239-024-00448-3
Yamashita, T. (2022). Analyzing Likert scale surveys with Rasch models. Research Methods in Applied Linguistics, 1(3), 100022. https://doi.org/10.1016/j.rmal.2022.100022 DOI: https://doi.org/10.1016/j.rmal.2022.100022
Yarin, A. J., Encalada, I. A., Elias, J. W., Surichaqui, A. A., Sulca, R. E., & Pozo, F. (2022). Relationship between motivation and academic performance in Peruvian undergraduate students in the subject mathematics. Education Research International, 2022, Article 3667076. https://doi.org/10.1155/2022/3667076 DOI: https://doi.org/10.1155/2022/3667076
Yngve, M., Ekbladh, E., Lidström, H., & Hemmingsson, H. (2023). Information and communication technology to improve school participation among upper secondary school students with special educational needs. Scandinavian Journal of Occupational Therapy, 30(3), 311–321. https://doi.org/10.1080/11038128.2021.1998610 DOI: https://doi.org/10.1080/11038128.2021.1998610
Zakariya, Y. F. (2022). Cronbach’s alpha in mathematics education research: Its appropriateness, overuse, and alternatives in estimating scale reliability. Frontiers in Psychology, 13, 1074430. https://doi.org/10.3389/fpsyg.2022.1074430 DOI: https://doi.org/10.3389/fpsyg.2022.1074430
Zhai, C., Wibowo, S., & Li, L. D. (2024). The effects of over-reliance on AI dialogue systems on students’ cognitive abilities: A systematic review. Smart Learning Environments, 11, 28. https://doi.org/10.1186/s40561-024-00316-7 DOI: https://doi.org/10.1186/s40561-024-00316-7
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Copyright (c) 2026 María Isabel Sabando Guerrero, Brenda Cristina Calle Santistevan, Yadira Rocío Ordoñez Lapo, Noelia del Carmen Lupú Benavides, Janet Alexandra Bajaña Suárez (Autor/a)
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