Diseño y validación del cuestionario sobre Percepciones y actitudes hacia el aprendizaje por dispositivos móviles
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Palabras clave

Cuestionario
actitud
percepción
dispositivo móvil
aprendizaje

Cómo citar

Seifert, T., Hervás-Gómez, C., & Toledo-Morales, P. (2018). Diseño y validación del cuestionario sobre Percepciones y actitudes hacia el aprendizaje por dispositivos móviles. Pixel-Bit. Revista De Medios Y Educación, (54), 45–64. https://doi.org/10.12795/pixelbit.2019.i54.03

Resumen

El propósito de este estudio ha sido desarrollar un instrumento válido y fiable para evaluar el aprendizaje mediante el uso de dispositivos móviles a partir de las  percepciones y actitudes de estudiantes universitarios. Fueron examinados estudios que utilizaron cuestionarios para investigar diferentes aspectos del uso de dispositivos móviles en el proceso de enseñanza y aprendizaje, permitiéndonos su análisis crear el cuestionario para nuestro estudio. El análisis de datos estadísticos verificó la validez y fiabilidad del Cuestionario sobre Percepciones y Actitudes hacia el Aprendizaje Móvil (CPAAM). La fiabilidad del cuestionario quedó demostrada al obtener un Alpha de Cronbach de 0,915. La validez de constructo con el análisis factorial dio como resultando cuatro dimensiones en el CPAAM. Por lo tanto, el cuestionario es una herramienta de valoración de ágil y fácil aplicación de las percepciones y actitudes que futuros docentes tienen del uso de dispositivos móviles como instrumento de enseñanza y aprendizaje.

https://doi.org/10.12795/pixelbit.2019.i54.03
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Citas

Berrios, L., & Buxarrais, R. (2003). Las tecnologías de la información y la comunicación (TIC) y los adolescentes. Recuperado de http://www.oei.es/historico/valores2/monografias/monografia05/reflexion05.htm

Chao, H. C, Lai, C. F., Chen, S. Y., & Huang, Y. M. (2013). A M-learning content recommendation service by exploiting mobile social interactions. IEEE Transactions on Learning Technologies, 7 (3), 221–230. https://doi.org/10.1109/TLT.2014.2323053

Christensen, R., & Knezek, G. (2017). Readiness for integrating mobile learning in the classroom: Challenges, preferences and possibilities. Computers in Human Behavior, 76, 112-121. https://doi.org/10.1016/j.chb.2017.07.014

Ferrando, P. J. & Anguiano-Carrasco, C. (2010). El análisis factorial como técnica de investigación en psicología. Papeles del Psicólogo, 31(1), 18-33. Recuperado de http://www.redalyc.org/pdf/778/77812441003.pdf

Gezgin, D.M., Adnan, M., & Acar Guvendir, M. (2018). Mobile learning according to students of Computer Engineering and Computer Education: A comparison of attitudes. Turkish Online Journal of Distance Education, 19 (1), 4-17. https://doi.org/10.17718/tojde.382653

Hao, S., Dennen, V. P., & Mei, L. (2016). Influential factors for mobile learning acceptance among Chinese users. Educational Technology Research and Development, 65(1), 101–123. https://doi.org/10.1007/s11423-016-9465-2

Hefetz, A., & Liberman, G. (2017). The Factor Analysis Procedure for Exploration: A Short Guide with Examples. Culture and Education, 29(3), 526-562. https://doi.org/10.1080/11356405.2017.1365425

Hernández, R., Fernández, C., & Baptista; P. (2003). Metodología de la Investigación. México, D.F.: McGraw-Hill.

Kärki, T., Keinänen, H., Tuominen, A., Hoikkala, M., Matikainen, E., & Maijala, H. (2018). Meaningful learning with mobile devices: pre-service class teachers’ experiences of mobile learning in the outdoors. Technology, Pedagogy and Education, 27 (2), 251-263. https://doi.org/10.1080/1475939X.2018.1430061

Khaddage, F., & Knezek, G. (2013). Introducing a mobile learning attitude scale for higher education, in WCCE 2013: Learning while we are connected: Proceedings of the IFIP Computers in Education 2013 World Conference, Nicolaus Copernicus University Press, Torun, Italy, pp. 226-235.

Lai, CL., Hwang, GJ., Liang, JC., & Tsai, C.C. (2016). Differences between mobile learning environmental preferences of high school teachers and students in Taiwan: a structural equation model analysis. Educational Technology Research and Development, 64 (3), 533-554. https://doi.org/10.1007/s11423-016-9432-y

Moreira, F., Ferreira, M. J., Santos, C. P., & Durão, N. (2017). Evolution and use of mobile devices in higher education: A case study in portuguese higher education institutions between 2009/2010 and 2014/2015. Telematics and Informatics, 34 (6), 838-852. https://doi.org /10.1016/j.tele.2016.08.010

Muthén, B. (1984). A general structural equation model with dichotomous, ordered categorical, and continuous latent variable indicators. Psychometrika, 49 (1), 115-132. Retrieved from https://www.statmodel.com/download/Article_011.pdf

Muthén, L. K., & Muthén, B. O. (2017). Mplus User’s Guide. Eight Edition. Los Angeles, CA: Muthén & Muthén.

Sánchez-García, J.M. & Toledo-Morales, P. (2017). Tecnologías convergentes para la enseñanza: Realidad Aumentada, BYOD, Flipped Classroom. Revista de Educación a Distancia, 55, 1-15. https://doi.org/10.6018/red/55/8

Sarrab, M., Al Shibli, I., & Badursha, N. (2016). An Empirical Study of Factors Driving the Adoption of Mobile Learning in Omani Higher Education. International Review of Research in Open and Distributed Learning, 17 (4), 331-349. http://www.irrodl.org/index.php/irrodl/article/view/2614/3791

Sarrab, M. K., Elbasir, M. H., & Alnaeli, S. M. (2016). Towards a quality model of technical aspects for mobile learning services: An empirical investigation. Computers in Human Behavior, 55 (PartA), 100-112. https://doi.org/10.1016/j.chb.2015.09.003

Sarrab, M. K., Alzahrani, A. A., Alalwan, N. A., & Alfarraj, O. M. (2014). From tradicional learning into mobile learning in education at the university level: undergraduate students perspective. International Journal of Mobile Learning and Organisation, 8 (3/4), 167-186. https://doi.org/10.1504/IJMLO.2014.067014

Schnall, R., Cho, H., & Liu, J. (2018). Health Information Technology Usability Evaluation Scale (Health-ITUES) for Usability Assessment of Mobile Health Technology: Validation Study. JMIR Mhealth Uhealth, 6 (1), 1-11. https://doi.org/10.2196/mhealth.8851.

Siouli, S., Dratsiou, I., Tsitouridou,M., Kartsidis, P., Spachos, D., & Bamidis, P. D. (2017). Evaluating the AffectLecture Mobile App within an Elementary School Class Teaching Process. IEEE 30th International Symposium on Computer-Based Medical Systems (CBMS), Thessaloniki, Greece, (pp. 481-485). https://doi.org/10.1109/CBMS.2017.56

Souppaya, M. & Scarfone, K (2016). Guide to Enterprise Telework, Remote Access, and Bring Your Own Device (BYOD) Security. Draft SP 800-46 Revision 2. The National Institute of Standards and Technology (NIST). http://doi.org/10.6028/NIST.SP.800-46r2

Venkatesh, V., Morris, M.G., Davis, G.B. & Davis, F.D. (2003). User Acceptance of Information Technology: Toward a Unified View. MIS Quarterly, 27 (3), 425-478. https://doi.org/10.2307/30036540

Yao-Ting, S., Kuo-En, C., & Tzu-Chien, L. (2016). The effects of integrating mobile devices with teaching and learning on students’ learning performance: A meta-analysis and research synthesis. Computers & Education, 94, 252–275. https://doi.org/10.1016/j.compedu.2015.11.008

Zhu, Q., Guo, W., & Hu, Y. (2012). Mobile learning in higher education. Students´ acceptance of mobile learning in three top Chinese universities, (June), 79. JIBS, Business Informatics. Recuperado de http://www.diva-portal.org/smash/get/diva2:536882/FULLTEXT01.pdf

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