Artificial intelligence and its impact on the methodological strategy of research-based learning
DOI:
https://doi.org/10.55813/gaea/jessr/v4/n2/106Abstract
This study examines the influence of artificial intelligence (AI) on inquiry-based learning (IBL), highlighting both its potential benefits and associated challenges. Using a qualitative literature review approach, recent academic articles were analyzed to assess how AI is transforming ABI methodological strategies. The results show that AI can significantly personalize learning, automate administrative and research tasks, and improve feedback and evaluation processes. However, these advantages come with substantial challenges, such as technological limitations, teacher training needs, and profound ethical and social issues. The discussion highlights how AI is redefining roles in education, changing the role of the teacher from a transmitter of knowledge to a facilitator of learning, and how this requires an adaptive and reflective pedagogical approach. In addition, the need to address the ethical implications of AI to ensure that its integration fosters an education that is equitable and respectful of students' privacy and autonomy is highlighted. It is emphasized that, although AI offers remarkable opportunities to enhance ABI, its implementation must be meticulously managed to optimize benefits and minimize risks.
Downloads
Download data is not yet available.
References
Annuš, N. (2024). Education in the Age of Artificial Intelligence. TEM Journal, 404–413. https://doi.org/10.18421/tem131-42
Bailenson, J. N. (2021). Nonverbal Overload: A Theoretical Argument for the Causes of Zoom Fatigue. Technology, Mind, and Behavior, 2(1). https://doi.org/10.1037/tmb0000030
Bates, A. W. (Tony). (2015). Teaching in a Digital Age: Guidelines for designing teaching and learning for a digital age. In Umn.edu. https://open.umn.edu/opentextbooks/textbooks/221
Bonilla Bonilla, M.A., Góngora Cheme, R.K., Casanova-Villalba, C.I., y Guamán Chávez, R.E. (Coordinadores). (2023). Libro de memorias. I Simposio de investigadores emergentes en cien-cia y tecnología. Religación Press. https://doi.org/10.46652/ReligacionPress.115
Carpenter, P. (2020). Challenges and Opportunities in Academic HPC Systems Research in 2030. Sc19.Supercomputing.org. https://sc19.supercomputing.org/proceedings/bof/bof_pages/bof197.html
Casanova-Villalba, C. I., Herrera-Sánchez, M. J. & Rivadeneira-Moreira, J. C. (2023). Spin-offs en el mundo académico: ¿Cómo se traducen en impacto tangible?. In Libro de memorias. I Simposio de investigadores emergentes en cien-cia y tecnología. Religación Press. https://doi.org/10.46652/ReligacionPress.115.p5
EDUCAUSE. (2019). 2019 Horizon Report. EDUCAUSE. https://library.educause.edu/resources/2019/4/2019-horizon-report
Ertmer, P. A., & Ottenbreit-Leftwich, A. T. (2010). Teacher technology change: How knowledge, confidence, beliefs, and culture intersect. Journal of Research on Technology in Education, 42(3), 255–284. https://doi.org/10.1080/15391523.2010.10782551
Ethical Use of Information Technology in Higher Education. (2022). In EAI/Springer Innovations in Communication and Computing. Springer International Publishing. https://doi.org/10.1007/978-981-16-1951-9
Eubanks, V. (2018). VIRTUAL POORHOUSE : how the fear of poverty is shaping our digital destiny.
Ferguson, R., & Clow, D. (n.d.). Where is the evidence? A call to action for learning analytics Conference or Workshop Item Where is the evidence? A call to action for learning analytics. 56–65. https://doi.org/10.1145/3027385.3027396
Fjeld, J., Achten, N., Hilligoss, H., Nagy, A., & Srikumar, M. (2020). Principled Artificial Intelligence: Mapping Consensus in Ethical and Rights-Based Approaches to Principles for AI. SSRN Electronic Journal. https://doi.org/10.2139/ssrn.3518482
Giroux, F., Couture, L., Lasbareille, C., Boasen, J., Stagg, C. J., Fleming, M. K., Sylvain Sénécal, & Pierre-Majorique Léger. (2022). Usability Evaluation of Assistive Technology for ICT Accessibility: Lessons Learned with Stroke Patients and Able-Bodied Participants Experiencing a Motor Dysfunction Simulation. Lecture Notes in Information Systems and Organisation, 349–359. https://doi.org/10.1007/978-3-031-13064-9_35
Goksel, N., & Bozkurt, A. (2019). Artificial Intelligence in Education. Handbook of Research on Learning in the Age of Transhumanism, 224–236. https://doi.org/10.4018/978-1-5225-8431-5.ch014
He, J., Baxter, S. L., Xu, J., Xu, J., Zhou, X., & Zhang, K. (2019). The practical implementation of artificial intelligence technologies in medicine. Nature Medicine, 25(1), 30–36. https://doi.org/10.1038/s41591-018-0307-0
Herrera-Enríquez, G., Herrera-Sánchez, M., Casanova-Villalba, C., Puyol-Cortez, J., Mendoza-Armijos, H, (2021). Manual para Elaboración del Plan de Titulación como Conclusión de Carrera. Editorial Grupo Compás.
Herrera-Sánchez, M. J., Casanova-Villalba, C. I., Bravo Bravo, I. F., & Barba Mosquera, A. E. (2023). Estudio comparativo de las desigualdades en el tecnoestrés entre instituciones de educación superior en América Latina y Europa. Código Científico Revista De Investigación, 4(2), 1288–1303. https://doi.org/10.55813/gaea/ccri/v4/n2/287
Holmes, W., Bialik, M., & Fadel, C. (2019). Artificial intelligence in education : promises and implications for teaching and learning. The Center For Curriculum Redesign.
Holmes, W., Luckin, R., Ucl Knowledge Lab, & Al, E. (2016). Intelligence unleashed : an argument for AI in education. Pearson.
Ifenthaler, D., & Yau, J. Y.-K. (2020). Utilising learning analytics to support study success in higher education: a systematic review. Educational Technology Research and Development, 68(4), 1961–1990. https://doi.org/10.1007/s11423-020-09788-z
Igbokwe, I. C. (2023). Application of Artificial Intelligence (AI) in Educational Management. International Journal of Scientific and Research Publications, 13(3). https://doi.org/10.29322/ijsrp.13.03.2023.p13536
Ipperciel, D. (2022). What Should the Future of Learning Look Like? Looking Back, Looking Forward. International Journal of Higher Education, 11(5), 51. https://doi.org/10.5430/ijhe.v11n5p51
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
Jobin, A., Ienca, M., & Vayena, E. (2019). The global landscape of AI ethics guidelines. Nature Machine Intelligence, 1(9), 389–399. https://www.nature.com/articles/s42256-019-0088-2
Justice, C., Rice, J., Warry, W., Inglis, S., Miller, S., & Sammon, S. (2006). Inquiry in Higher Education: Reflections and Directions on Course Design and Teaching Methods. Innovative Higher Education, 31(4), 201–214. https://doi.org/10.1007/s10755-006-9021-9
Khritish Swargiary, & Roy, K. (2023). Leveraging Artificial Intelligence for Enhanced Project Completion in Education. https://doi.org/10.32388/adg6h8
Krstić, L., Aleksić, V., & Krstić, M. (2022). Artificial Intelligence in Education: A Review. Proceedings TIE 2022. https://doi.org/10.46793/tie22.223k
Loor Giler, J. L., Lorenzo Benítez, R., & Herrera Navas, C. D. (2021). Manual de actividades didácticas para el desarrollo de la comprensión lectora en estudiantes de subnivel de básica media. Journal of Economic and Social Science Research, 1(1), 15–37. https://doi.org/10.55813/gaea/jessr/v1/n1/18
Ma, W., Adesope, O. O., Nesbit, J. C., & Liu, Q. (2014). Intelligent tutoring systems and learning outcomes: A meta-analysis. Journal of Educational Psychology, 106(4), 901–918. https://doi.org/10.1037/a0037123
Madrid-Gómez, K. E., Arias-Huánuco, . J. M., Zevallos-Parave, Y., Alfaro-Saavedra, M. N., Camposano-Córdova, A. I., & Yaulilahua-Huacho, R. (2023). Estrategias activas para el aprendizaje autónomo: Un enfoque en Alumnos de Secundaria. Editorial Grupo AEA. https://doi.org/10.55813/egaea.l.2022.53
Madrid-Gómez, K. E., Arias-Huánuco, J. M., Zevallos-Parave, Y., Camposano-Córdova, A. I., & Yaulilahua-Huacho, M. (2023). Entre el Autoconocimiento y la Autoestima: Explorando el Programa “Súbete a mi Auto” en el ámbito Universitario. Editorial Grupo AEA. https://doi.org/10.55813/egaea.l.2022.54
Madrid-Gómez, K. E., Herrera-Aponte, M. B., Arias-Huánuco, J. M., Zevallos-Parave, Y., Camposano-Córdova, A. I., & LLancari-Choccelahua, R. B. (2023). Interacciones Familiares y Autoestima: Un Estudio entre Estudiantes de Secundaria. Editorial Grupo AEA. https://doi.org/10.55813/egaea.l.2022.52
Mittelstadt, B., & Floridi, L. (2016). The Ethics of Biomedical Big Data. In Law, governance and technology series. Springer International Publishing. https://doi.org/10.1007/978-3-319-33525-4
Muneeba Anis. (2024). Teacher Professional Development in the Digital Age: Addressing the Evolving Needs Post-covid. International Journal for Multidisciplinary Research, 6(1). https://doi.org/10.36948/ijfmr.2024.v06i01.12386
Nicolae Moroianu, Silvia-Elena Iacob, & Alexandra Maria Constantin. (2023). Artificial Intelligence in Education: a Systematic Review. Sciendo EBooks, 906–921. https://doi.org/10.2478/9788367405546-084
Pacheco-Altamirano, A. M., Camposano-Córdova, A. I., Torres-Acevedo, C. L., Oré-Rojas, J. J., Gavidia-Anticona, J. A., Yauri-Huiza, Y., & Rojas-Quispe, Ángel E. (2023). Comprendiendo la Lectura: Del Nivel Literal al Crítico en Estudiantes de EBA. Editorial Grupo AEA. https://doi.org/10.55813/egaea.l.2022.40
Parisa Tadi, Anienie Veldsman, & Sadeghi, A. (2023). Professional Development in Online Teaching and Learning at Tertiary Level During Pandemic: A Quest for Student’s Care. Pacific Journal of Technology Enhanced Learning, 4(3), 9–19. https://doi.org/10.24135/pjtel.v4i3.151
Phillips, M. (2016). Digital Technology, Schools and Teachers’ Workplace Learning. In Palgrave Macmillan UK eBooks. Palgrave Macmillan. https://doi.org/10.1057/978-1-137-52462-1
Popenici, S. A. D., & Kerr, S. (2017). Exploring the impact of artificial intelligence on teaching and learning in higher education. Research and Practice in Technology Enhanced Learning, 12(1). https://doi.org/10.1186/s41039-017-0062-8
Puyol-Cortez, J. L., & Mina-Bone, S. G. (2022). Explorando el liderazgo de los profesores en la educación superior: un enfoque en la UTELVT Santo Domingo. Journal of Economic and Social Science Research, 2(2), 16–28. https://doi.org/10.55813/gaea/jessr/v2/n2/49
Reich, J., & Mizuko , I. (2017). From Good Intentions to Real Outcomes: Equity by Design in Learning Technologies. Digital Media and Learning Research Hub.
Reimers, A., & Schleicher, F. M. (2020). A Framework to Guide an Education Response to the COVID-19 Pandemic of 2020. Organisation for Economic Co-Operation and Development.
Rios-Campos, C., Vega, S. M. Z., Tejada-Castro, M. I., Viteri, J. D. C. L., Zambrano, E. O. G., Gamarra, J. M. B., Núñez, J. B., & Vara, F. E. O. (2023). Ethics of artificial intelligence. South Florida Journal of Development, 4(4), 1715–1729. https://doi.org/10.46932/sfjdv4n4-022
Salvi, Ms. R., & Singh, Dr. R. (2023). Artificial Intelligence and Human Society. International Journal of Social Science and Human Research, 6(09). https://doi.org/10.47191/ijsshr/v6-i9-13
Selbst, A. D., Boyd, D., Friedler, S. A., Venkatasubramanian, S., & Vertesi, J. (2019). Fairness and Abstraction in Sociotechnical Systems. Proceedings of the Conference on Fairness, Accountability, and Transparency - FAT* ’19. https://doi.org/10.1145/3287560.3287598
Silva Alvarado, J. C., & Herrera Navas, C. D. (2022). Estudio de Kahoot como recurso didáctico para innovar los procesos evaluativos pospandemia de básica superior de la Unidad Educativa Iberoamericano. Journal of Economic and Social Science Research, 2(4), 15–40. https://doi.org/10.55813/gaea/jessr/v2/n4/23
Terrazo-Luna, E. G., Riveros-Anccasi, D., Torres-Acevedo, C. L., Rojas-Quispe, A. E., Cencho Pari, A., Coronel-Capani, J., & Yaulilahua-Huacho, R. (2023). Habilidades Perceptivas: Mejorando el Aprendizaje Remoto en Estudiantes de 5 años. Editorial Grupo AEA. https://doi.org/10.55813/egaea.l.2022.30
Torres-Torres, O. L. (2024). Evaluación de Genially como herramienta didáctica en la práctica docente de la educación a distancia. Journal of Economic and Social Science Research, 4(1), 1–18. https://doi.org/10.55813/gaea/jessr/v4/n1/82
Turkle, S. (2011). Alone Together: Why We Expect More from Technology and Less from Each Other. Basic Books.
Wachter, S., Mittelstadt, B., & Floridi, L. (2017). Transparent, explainable, and accountable AI for robotics. Science Robotics, 2(6), eaan6080. https://doi.org/10.1126/scirobotics.aan6080
Williamson, B. (2017). Big Data in Education: The digital future of learning, policy and practice. https://doi.org/10.4135/9781529714920
Wilson, J., & Andrada, G. N. (2016). Using Automated Feedback to Improve Writing Quality. Advances in Higher Education and Professional Development Book Series, 679–704. https://doi.org/10.4018/978-1-4666-9441-5.ch026
Yildiz Durak, H. (2021). Preparing pre-service teachers to integrate teaching technologies into their classrooms: Examining the effects of teaching environments based on open-ended, hands-on and authentic tasks. Education and Information Technologies, 26(5), 5365–5387. https://doi.org/10.1007/s10639-021-10511-5
Zawacki-Richter, O., & Latchem, C. (2018). Exploring four decades of research in Computers & Education. Computers & Education, 122, 136–152. https://doi.org/10.1016/j.compedu.2018.04.001
Zawacki-Richter, O., Marín, V. I., Bond, M., & Gouverneur, F. (2019). Systematic review of research on artificial intelligence applications in higher education – where are the educators? International Journal of Educational Technology in Higher Education, 16(1). Springeropen. https://doi.org/10.1186/s41239-019-0171-0
Zhang, K., & Aslan, A. B. (2021). AI technologies for education: Recent research & future directions. Computers and Education: Artificial Intelligence, 2(100025), 100025. https://doi.org/10.1016/j.caeai.2021.100025
Zhang, L., Wang, S., & Liu, B. (2018). Deep Learning for Sentiment Analysis : A Survey. ArXiv (Cornell University). https://doi.org/10.48550/arxiv.1801.07883
Zhao, Y. (2017). What works may hurt: Side effects in education. Journal of Educational Change, 18(1), 1–19. https://doi.org/10.1007/s10833-016-9294-4
Bailenson, J. N. (2021). Nonverbal Overload: A Theoretical Argument for the Causes of Zoom Fatigue. Technology, Mind, and Behavior, 2(1). https://doi.org/10.1037/tmb0000030
Bates, A. W. (Tony). (2015). Teaching in a Digital Age: Guidelines for designing teaching and learning for a digital age. In Umn.edu. https://open.umn.edu/opentextbooks/textbooks/221
Bonilla Bonilla, M.A., Góngora Cheme, R.K., Casanova-Villalba, C.I., y Guamán Chávez, R.E. (Coordinadores). (2023). Libro de memorias. I Simposio de investigadores emergentes en cien-cia y tecnología. Religación Press. https://doi.org/10.46652/ReligacionPress.115
Carpenter, P. (2020). Challenges and Opportunities in Academic HPC Systems Research in 2030. Sc19.Supercomputing.org. https://sc19.supercomputing.org/proceedings/bof/bof_pages/bof197.html
Casanova-Villalba, C. I., Herrera-Sánchez, M. J. & Rivadeneira-Moreira, J. C. (2023). Spin-offs en el mundo académico: ¿Cómo se traducen en impacto tangible?. In Libro de memorias. I Simposio de investigadores emergentes en cien-cia y tecnología. Religación Press. https://doi.org/10.46652/ReligacionPress.115.p5
EDUCAUSE. (2019). 2019 Horizon Report. EDUCAUSE. https://library.educause.edu/resources/2019/4/2019-horizon-report
Ertmer, P. A., & Ottenbreit-Leftwich, A. T. (2010). Teacher technology change: How knowledge, confidence, beliefs, and culture intersect. Journal of Research on Technology in Education, 42(3), 255–284. https://doi.org/10.1080/15391523.2010.10782551
Ethical Use of Information Technology in Higher Education. (2022). In EAI/Springer Innovations in Communication and Computing. Springer International Publishing. https://doi.org/10.1007/978-981-16-1951-9
Eubanks, V. (2018). VIRTUAL POORHOUSE : how the fear of poverty is shaping our digital destiny.
Ferguson, R., & Clow, D. (n.d.). Where is the evidence? A call to action for learning analytics Conference or Workshop Item Where is the evidence? A call to action for learning analytics. 56–65. https://doi.org/10.1145/3027385.3027396
Fjeld, J., Achten, N., Hilligoss, H., Nagy, A., & Srikumar, M. (2020). Principled Artificial Intelligence: Mapping Consensus in Ethical and Rights-Based Approaches to Principles for AI. SSRN Electronic Journal. https://doi.org/10.2139/ssrn.3518482
Giroux, F., Couture, L., Lasbareille, C., Boasen, J., Stagg, C. J., Fleming, M. K., Sylvain Sénécal, & Pierre-Majorique Léger. (2022). Usability Evaluation of Assistive Technology for ICT Accessibility: Lessons Learned with Stroke Patients and Able-Bodied Participants Experiencing a Motor Dysfunction Simulation. Lecture Notes in Information Systems and Organisation, 349–359. https://doi.org/10.1007/978-3-031-13064-9_35
Goksel, N., & Bozkurt, A. (2019). Artificial Intelligence in Education. Handbook of Research on Learning in the Age of Transhumanism, 224–236. https://doi.org/10.4018/978-1-5225-8431-5.ch014
He, J., Baxter, S. L., Xu, J., Xu, J., Zhou, X., & Zhang, K. (2019). The practical implementation of artificial intelligence technologies in medicine. Nature Medicine, 25(1), 30–36. https://doi.org/10.1038/s41591-018-0307-0
Herrera-Enríquez, G., Herrera-Sánchez, M., Casanova-Villalba, C., Puyol-Cortez, J., Mendoza-Armijos, H, (2021). Manual para Elaboración del Plan de Titulación como Conclusión de Carrera. Editorial Grupo Compás.
Herrera-Sánchez, M. J., Casanova-Villalba, C. I., Bravo Bravo, I. F., & Barba Mosquera, A. E. (2023). Estudio comparativo de las desigualdades en el tecnoestrés entre instituciones de educación superior en América Latina y Europa. Código Científico Revista De Investigación, 4(2), 1288–1303. https://doi.org/10.55813/gaea/ccri/v4/n2/287
Holmes, W., Bialik, M., & Fadel, C. (2019). Artificial intelligence in education : promises and implications for teaching and learning. The Center For Curriculum Redesign.
Holmes, W., Luckin, R., Ucl Knowledge Lab, & Al, E. (2016). Intelligence unleashed : an argument for AI in education. Pearson.
Ifenthaler, D., & Yau, J. Y.-K. (2020). Utilising learning analytics to support study success in higher education: a systematic review. Educational Technology Research and Development, 68(4), 1961–1990. https://doi.org/10.1007/s11423-020-09788-z
Igbokwe, I. C. (2023). Application of Artificial Intelligence (AI) in Educational Management. International Journal of Scientific and Research Publications, 13(3). https://doi.org/10.29322/ijsrp.13.03.2023.p13536
Ipperciel, D. (2022). What Should the Future of Learning Look Like? Looking Back, Looking Forward. International Journal of Higher Education, 11(5), 51. https://doi.org/10.5430/ijhe.v11n5p51
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
Jobin, A., Ienca, M., & Vayena, E. (2019). The global landscape of AI ethics guidelines. Nature Machine Intelligence, 1(9), 389–399. https://www.nature.com/articles/s42256-019-0088-2
Justice, C., Rice, J., Warry, W., Inglis, S., Miller, S., & Sammon, S. (2006). Inquiry in Higher Education: Reflections and Directions on Course Design and Teaching Methods. Innovative Higher Education, 31(4), 201–214. https://doi.org/10.1007/s10755-006-9021-9
Khritish Swargiary, & Roy, K. (2023). Leveraging Artificial Intelligence for Enhanced Project Completion in Education. https://doi.org/10.32388/adg6h8
Krstić, L., Aleksić, V., & Krstić, M. (2022). Artificial Intelligence in Education: A Review. Proceedings TIE 2022. https://doi.org/10.46793/tie22.223k
Loor Giler, J. L., Lorenzo Benítez, R., & Herrera Navas, C. D. (2021). Manual de actividades didácticas para el desarrollo de la comprensión lectora en estudiantes de subnivel de básica media. Journal of Economic and Social Science Research, 1(1), 15–37. https://doi.org/10.55813/gaea/jessr/v1/n1/18
Ma, W., Adesope, O. O., Nesbit, J. C., & Liu, Q. (2014). Intelligent tutoring systems and learning outcomes: A meta-analysis. Journal of Educational Psychology, 106(4), 901–918. https://doi.org/10.1037/a0037123
Madrid-Gómez, K. E., Arias-Huánuco, . J. M., Zevallos-Parave, Y., Alfaro-Saavedra, M. N., Camposano-Córdova, A. I., & Yaulilahua-Huacho, R. (2023). Estrategias activas para el aprendizaje autónomo: Un enfoque en Alumnos de Secundaria. Editorial Grupo AEA. https://doi.org/10.55813/egaea.l.2022.53
Madrid-Gómez, K. E., Arias-Huánuco, J. M., Zevallos-Parave, Y., Camposano-Córdova, A. I., & Yaulilahua-Huacho, M. (2023). Entre el Autoconocimiento y la Autoestima: Explorando el Programa “Súbete a mi Auto” en el ámbito Universitario. Editorial Grupo AEA. https://doi.org/10.55813/egaea.l.2022.54
Madrid-Gómez, K. E., Herrera-Aponte, M. B., Arias-Huánuco, J. M., Zevallos-Parave, Y., Camposano-Córdova, A. I., & LLancari-Choccelahua, R. B. (2023). Interacciones Familiares y Autoestima: Un Estudio entre Estudiantes de Secundaria. Editorial Grupo AEA. https://doi.org/10.55813/egaea.l.2022.52
Mittelstadt, B., & Floridi, L. (2016). The Ethics of Biomedical Big Data. In Law, governance and technology series. Springer International Publishing. https://doi.org/10.1007/978-3-319-33525-4
Muneeba Anis. (2024). Teacher Professional Development in the Digital Age: Addressing the Evolving Needs Post-covid. International Journal for Multidisciplinary Research, 6(1). https://doi.org/10.36948/ijfmr.2024.v06i01.12386
Nicolae Moroianu, Silvia-Elena Iacob, & Alexandra Maria Constantin. (2023). Artificial Intelligence in Education: a Systematic Review. Sciendo EBooks, 906–921. https://doi.org/10.2478/9788367405546-084
Pacheco-Altamirano, A. M., Camposano-Córdova, A. I., Torres-Acevedo, C. L., Oré-Rojas, J. J., Gavidia-Anticona, J. A., Yauri-Huiza, Y., & Rojas-Quispe, Ángel E. (2023). Comprendiendo la Lectura: Del Nivel Literal al Crítico en Estudiantes de EBA. Editorial Grupo AEA. https://doi.org/10.55813/egaea.l.2022.40
Parisa Tadi, Anienie Veldsman, & Sadeghi, A. (2023). Professional Development in Online Teaching and Learning at Tertiary Level During Pandemic: A Quest for Student’s Care. Pacific Journal of Technology Enhanced Learning, 4(3), 9–19. https://doi.org/10.24135/pjtel.v4i3.151
Phillips, M. (2016). Digital Technology, Schools and Teachers’ Workplace Learning. In Palgrave Macmillan UK eBooks. Palgrave Macmillan. https://doi.org/10.1057/978-1-137-52462-1
Popenici, S. A. D., & Kerr, S. (2017). Exploring the impact of artificial intelligence on teaching and learning in higher education. Research and Practice in Technology Enhanced Learning, 12(1). https://doi.org/10.1186/s41039-017-0062-8
Puyol-Cortez, J. L., & Mina-Bone, S. G. (2022). Explorando el liderazgo de los profesores en la educación superior: un enfoque en la UTELVT Santo Domingo. Journal of Economic and Social Science Research, 2(2), 16–28. https://doi.org/10.55813/gaea/jessr/v2/n2/49
Reich, J., & Mizuko , I. (2017). From Good Intentions to Real Outcomes: Equity by Design in Learning Technologies. Digital Media and Learning Research Hub.
Reimers, A., & Schleicher, F. M. (2020). A Framework to Guide an Education Response to the COVID-19 Pandemic of 2020. Organisation for Economic Co-Operation and Development.
Rios-Campos, C., Vega, S. M. Z., Tejada-Castro, M. I., Viteri, J. D. C. L., Zambrano, E. O. G., Gamarra, J. M. B., Núñez, J. B., & Vara, F. E. O. (2023). Ethics of artificial intelligence. South Florida Journal of Development, 4(4), 1715–1729. https://doi.org/10.46932/sfjdv4n4-022
Salvi, Ms. R., & Singh, Dr. R. (2023). Artificial Intelligence and Human Society. International Journal of Social Science and Human Research, 6(09). https://doi.org/10.47191/ijsshr/v6-i9-13
Selbst, A. D., Boyd, D., Friedler, S. A., Venkatasubramanian, S., & Vertesi, J. (2019). Fairness and Abstraction in Sociotechnical Systems. Proceedings of the Conference on Fairness, Accountability, and Transparency - FAT* ’19. https://doi.org/10.1145/3287560.3287598
Silva Alvarado, J. C., & Herrera Navas, C. D. (2022). Estudio de Kahoot como recurso didáctico para innovar los procesos evaluativos pospandemia de básica superior de la Unidad Educativa Iberoamericano. Journal of Economic and Social Science Research, 2(4), 15–40. https://doi.org/10.55813/gaea/jessr/v2/n4/23
Terrazo-Luna, E. G., Riveros-Anccasi, D., Torres-Acevedo, C. L., Rojas-Quispe, A. E., Cencho Pari, A., Coronel-Capani, J., & Yaulilahua-Huacho, R. (2023). Habilidades Perceptivas: Mejorando el Aprendizaje Remoto en Estudiantes de 5 años. Editorial Grupo AEA. https://doi.org/10.55813/egaea.l.2022.30
Torres-Torres, O. L. (2024). Evaluación de Genially como herramienta didáctica en la práctica docente de la educación a distancia. Journal of Economic and Social Science Research, 4(1), 1–18. https://doi.org/10.55813/gaea/jessr/v4/n1/82
Turkle, S. (2011). Alone Together: Why We Expect More from Technology and Less from Each Other. Basic Books.
Wachter, S., Mittelstadt, B., & Floridi, L. (2017). Transparent, explainable, and accountable AI for robotics. Science Robotics, 2(6), eaan6080. https://doi.org/10.1126/scirobotics.aan6080
Williamson, B. (2017). Big Data in Education: The digital future of learning, policy and practice. https://doi.org/10.4135/9781529714920
Wilson, J., & Andrada, G. N. (2016). Using Automated Feedback to Improve Writing Quality. Advances in Higher Education and Professional Development Book Series, 679–704. https://doi.org/10.4018/978-1-4666-9441-5.ch026
Yildiz Durak, H. (2021). Preparing pre-service teachers to integrate teaching technologies into their classrooms: Examining the effects of teaching environments based on open-ended, hands-on and authentic tasks. Education and Information Technologies, 26(5), 5365–5387. https://doi.org/10.1007/s10639-021-10511-5
Zawacki-Richter, O., & Latchem, C. (2018). Exploring four decades of research in Computers & Education. Computers & Education, 122, 136–152. https://doi.org/10.1016/j.compedu.2018.04.001
Zawacki-Richter, O., Marín, V. I., Bond, M., & Gouverneur, F. (2019). Systematic review of research on artificial intelligence applications in higher education – where are the educators? International Journal of Educational Technology in Higher Education, 16(1). Springeropen. https://doi.org/10.1186/s41239-019-0171-0
Zhang, K., & Aslan, A. B. (2021). AI technologies for education: Recent research & future directions. Computers and Education: Artificial Intelligence, 2(100025), 100025. https://doi.org/10.1016/j.caeai.2021.100025
Zhang, L., Wang, S., & Liu, B. (2018). Deep Learning for Sentiment Analysis : A Survey. ArXiv (Cornell University). https://doi.org/10.48550/arxiv.1801.07883
Zhao, Y. (2017). What works may hurt: Side effects in education. Journal of Educational Change, 18(1), 1–19. https://doi.org/10.1007/s10833-016-9294-4
Downloads
Published
2024-04-30
Issue
Section
Articles
License
Copyright (c) 2024 Piedra-Castro, Wilson Iván, Burbano-Buñay, Erika Silvana, Tamayo-Verdezoto, Jhonny Junior, Moreira-Alcívar, Elvin Fray
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
How to Cite
Piedra-Castro, W. I., Burbano-Buñay, E. S., Tamayo-Verdezoto, J. J., & Moreira-Alcívar, E. F. (2024). Artificial intelligence and its impact on the methodological strategy of research-based learning. Journal of Economic and Social Science Research, 4(2), 178-196. https://doi.org/10.55813/gaea/jessr/v4/n2/106
