Aulas inteligentes y rendimiento académico en estudiantes de Medicina de la Universidad Privada Abierta Latinoamericana, Cochabamba, Bolivia
Palabras clave:
Tecnología Educacional, Educación Médica, Estudiantes de Medicina, Rendimiento Académico, PercepciónResumen
Introducción: Las aulas inteligentes representan una estrategia de innovación educativa orientada a integrar recursos tecnológicos, interacción pedagógica y ambientes de aprendizaje más dinámicos. Sin embargo, su utilidad percibida y su relación con el rendimiento académico requieren evidencia contextualizada en educación médica. El objetivo fue evaluar la utilidad percibida de las aulas inteligentes y su asociación con el rendimiento académico en estudiantes de Medicina de una universidad privada de Cochabamba, Bolivia. Métodos: Estudio observacional, analítico, comparativo y transversal en 153 estudiantes de Medicina, distribuidos en aula inteligente n = 77 y aula tradicional n = 76. Se aplicó un cuestionario estructurado con ítems tipo Likert para evaluar uso tecnológico, motivación, participación, aprendizaje percibido, satisfacción/recomendación, innovación docente y utilidad global. El rendimiento académico fue medido mediante la nota final autorizada. Se emplearon comparaciones entre grupos, tamaños de efecto, modelos lineales ajustados y regresión logística para alta utilidad percibida. Resultados: Los estudiantes del aula inteligente presentaron medias superiores en todas las dimensiones perceptuales. Las mayores diferencias correspondieron a uso tecnológico d = 1.149 y utilidad global d = 0.887. La proporción de alta utilidad percibida fue mayor en el aula inteligente que en el aula tradicional 75.3% vs. 51.3%, manteniéndose significativa tras ajustar por edad y sexo OR ajustado = 2.57; IC95%: 1.24-5.30; p = 0.011. No se observó una asociación robusta entre tipo de aula y nota final. Discusión: Las aulas inteligentes se asociaron con una mejor percepción de utilidad educativa, aunque sin evidencia consistente de mejora en el rendimiento académico.
Citas
UNESCO. Global Education Monitoring Report 2023: Technology in education: A tool on whose terms? Paris: UNESCO; 2023. Disponible en: https://www.unesco.org/gem-report/en/technology
Alfoudari AM, Durugbo CM, Aldhmour FM. Exploring quality attributes of smart classrooms from the perspectives of academics. Educ Inf Technol (Dordr). 2023 Mar 24:1-43. doi: 10.1007/s10639-022-11452-3.
García-Tudela PA, Prendes-Espinosa P, Solano-Fernández IM. The Spanish experience of future classrooms as a possibility of smart learning environments. Heliyon. 2023 Jul 22;9(8):e18577. doi: 10.1016/j.heliyon.2023.e18577
Ma Y, Zuo M, Gao R, Yan Y, Luo H. Interrelationships among College Students' Perceptions of Smart Classroom Environments, Perceived Usefulness of Mobile Technology, Achievement Emotions, and Cognitive Engagement. Behav Sci (Basel). 2024 Jul 4;14(7):565. doi: 10.3390/bs14070565.
Yang Y, Yan Z, Zhu J, Guo W, Wu J, Huang B. The development and validation of the Student Self-feedback Behavior Scale. Front Psychol. 2025 Jan 6; 15:1495684. doi: 10.3389/fpsyg.2024.1495684.
Jin S, Peng L. Classroom perception in higher education: The impact of spatial factors on student satisfaction in lecture versus active learning classrooms. Front Psychol. 2022 Sep 27; 13:941285. doi: 10.3389/fpsyg.2022.941285.
Delungahawatta T, Dunne SS, Hyde S, Halpenny L, McGrath D, O'Regan A, Dunne CP. Advances in e-learning in undergraduate clinical medicine: a systematic review. BMC Med Educ. 2022 Oct 7;22(1):711. doi: 10.1186/s12909-022-03773-1.
Abdull Mutalib AA, Md Akim A, Jaafar MH. A systematic review of health sciences students' online learning during the COVID-19 pandemic. BMC Med Educ. 2022 Jul 3;22(1):524. doi: 10.1186/s12909-022-03579-1.
Tabatabaeichehr M, Babaei S, Dartomi M, Alesheikh P, Tabatabaee A, Mortazavi H, et al. Medical students’ satisfaction level with e-learning during the COVID-19 pandemic and its related factors: a systematic review. Journal of Educational Evaluation for Health Professions. 2022; 19:37. doi:10.3352/jeehp.2022.19.37
Tudor Car L, Poon S, Kyaw BM, Cook DA, Ward V, Atun R, et al. Digital education for health professionals: an evidence map, conceptual framework, and research agenda. Journal of Medical Internet Research. 2022;24(3):e31977. doi:10.2196/31977
Kim HY, Kim EY. Effects of medical education program using virtual reality: a systematic review and meta-analysis. International Journal of Environmental Research and Public Health. 2023;20(5):3895. doi:10.3390/ijerph20053895
Spaic D, Bukumiric Z, Rajovic N, Markovic K, Savic M, Milin-Lazovic J, et al. The flipped classroom in medical education: systematic review and meta-analysis. Journal of Medical Internet Research. 2025;27: e60757. doi:10.2196/60757
García-Martín J, García-Sánchez JN. The digital divide of know-how and use of digital technologies in higher education: The case of a college in Latin America in the COVID-19 era. International Journal of Environmental Research and Public Health. 2022;19(6):3358. doi:10.3390/ijerph19063358
Ndibalema P. Constraints of transition to online distance learning in Higher Education Institutions during COVID-19 in developing countries: A systematic review. E-Learning and Digital Media. 2022 Jun 8;19(6):595–618. doi: 10.1177/20427530221107510.
Inter-American Development Bank. Higher Education Digital Transformation in Latin America and the Caribbean. Washington, DC: IDB; 2024. Disponible en: https://publications.iadb.org/publications/english/document/Higher-Education-Digital-Transformation-in-Latin-America-and-the-Caribbean.pdf
Lu K, Shi Y, Li J, Yang HH, Xu M. An investigation of college students’ learning engagement and classroom preferences under the smart classroom environment. SN Comput Sci. 2022; 3:205. doi: https://doi.org/10.1007/s42979-022-01093-1
Lu G, Xie K, Liu Q. What influences student situational engagement in smart classrooms: perception of the learning environment and students’ motivation. Br J Educ Technol. 2022;53(6):1665-1687. doi: https://doi.org/10.1111/bjet.13204
Hu Y, Huang J, Kong F. College students' learning perceptions and outcomes in different classroom environments: A community of inquiry perspective. Front Psychol. 2022 Dec 1; 13:1047027. doi: 10.3389/fpsyg.2022.1047027. PMID: 36532972; PMCID: PMC9751398.
Mao Q, Fang X, Jiang L, Zhu L. Enhancement or impediment? How university teachers’ use of smart classrooms might impact interaction quality. Sustainability. 2023;15(22):15826. doi: https://doi.org/10.3390/su152215826
Dai Z, Wang L, Peng X, Zhao L, Xiong J. A model for assessing student satisfaction with smart classroom environment in higher education. J Comput Assist Learn. 2024;40(6):2901-2916. doi: https://doi.org/10.1111/jcal.13045
Wang Y, Liu S, Pu L, Mao X, Shen S. College students’ learning experience and engagement in the smart classroom: the mediating role of self-efficacy in the background of COVID-19. SAGE Open. 2024;14(4). doi: https://doi.org/10.1177/21582440241285082
Chen C, Xiao LG. Human–computer interaction in smart classrooms: enhancing educational outcomes in Chinese higher education. Int J Hum Comput Interact. 2025;41(22):14379-14400. doi: https://doi.org/10.1080/10447318.2025.2483851
Romli MH, Cheema MS, Mehat MZ, Md Hashim NF, Abdul Hamid H. Exploring the effectiveness of technology-based learning on the educational outcomes of undergraduate healthcare students: an overview of systematic reviews protocol. BMJ Open. 2020 Nov 23;10(11):e041153. doi: 10.1136/bmjopen-2020-041153.
Kim JW, Myung SJ, Yoon HB, Moon SH, Ryu H, Yim JJ. How medical education survives and evolves during COVID-19: Our experience and future direction. PLoS One. 2020 Dec 18;15(12): e0243958. doi: 10.1371/journal.pone.0243958.
Erfannia L, Sharifian R, Yazdani A, Sarsarshahi A, Rahati R, Jahangiri S. Students' Satisfaction and e-Learning Courses in Covid-19 Pandemic Era: A Case Study. Stud Health Technol Inform. 2022 Jan 14;289:180-183. doi: 10.3233/SHTI210889.
McGee RG, Wark S, Mwangi F, et al. Digital learning of clinical skills and its impact on medical students’ academic performance: a systematic review. BMC Med Educ. 2024; 24:1477. doi: https://doi.org/10.1186/s12909-024-06471-2
Martinengo L, Ng MSP, Ng TDR, Ang YI, Jabir AI, Kyaw BM, et al. Spaced digital education for health professionals: systematic review and meta-analysis. J Med Internet Res. 2024;26:e57760. doi: https://doi.org/10.2196/57760
Naing C, Whittaker MA, Aung HH, Chellappan DK, Riegelman A. The effects of flipped classrooms to improve learning outcomes in undergraduate health professional education: a systematic review. Campbell Syst Rev. 2023;19(3):e1339. doi: https://doi.org/10.1002/cl2.1339
Mitchell AA, Ivimey-Cook ER. Technology-enhanced simulation for healthcare professionals: a meta-analysis. Front Med. 2023; 10:1149048. doi: https://doi.org/10.3389/fmed.2023.1149048
Pupic N, Ghaffari-zadeh A, Hu R, Singla R, Darras K, Karwowska A, et al. An evidence-based approach to artificial intelligence education for medical students: a systematic review. PLOS Digit Health. 2023;2(11):e0000255. doi: https://doi.org/10.1371/journal.pdig.0000255
Descargas
Archivos adicionales
Publicado
Cómo citar
Número
Sección
Licencia
Derechos de autor 2026 Multidisciplinary & Health Education Journal

Esta obra está bajo una licencia internacional Creative Commons Atribución-NoComercial-SinDerivadas 4.0.