Factores determinantes de adopción de blended learning en educación superiorAdaptación del modelo UTAUT*

  1. Martín García, Antonio Víctor
  2. García del Dujo, Ángel
  3. Muñoz Rodríguez, José Manuel
Revista:
Educación XX1: Revista de la Facultad de Educación

ISSN: 1139-613X 2174-5374

Año de publicación: 2014

Volumen: 17

Número: 2

Páginas: 217-240

Tipo: Artículo

DOI: 10.5944/EDUCXX1.17.2.11489 DIALNET GOOGLE SCHOLAR lock_opene-spacio editor

Otras publicaciones en: Educación XX1: Revista de la Facultad de Educación

Resumen

El estudio analiza el uso de metodología combinada (b-learning) en educación superior, utilizando como marco teórico el modelo UTAUT (Unified Theory of Acceptance and Use of Technology). A partir de un muestreo estratificado, se contó con una muestra de 445 profesores universitarios. Se utilizó el programa AMOS.16 para el tratamiento de los datos, con análisis factorial confirmatorio (CFA) para evaluar las propiedades críticas de las escalas utilizadas y validar el modelo de medición, así como ecuaciones de regresión lineal para valorar el efecto tanto de los constructos teóricos del modelo (Expectativa de Resultados, Expectativa de Esfuerzo, Influencia Social y Condiciones Facilitadoras), como del efecto de las variables moderadoras consideradas en el estudio (Edad, Sexo, Categoría Profesional y Rama de Conocimiento) sobre la intención de uso de b-learning. Los resultados ponen de manifiesto que UTAUT es un modelo útil para explicar la intención de los profesores de utilizar la metodología docente combinada, mostrando un poder predictivo del conjunto de variables independientes sobre la Intención Conductual del 35% de la varianza (R2=.349, p<0,000). Los datos indican que la Expectativa de Resultados (?=.413, p<0,001), las Condiciones Facilitadoras (?=.15, p<0,001) y la Influencia Social (?=.14, p<0,001) fueron factores determinantes de la intención conductual de usar b-learning. Por otro lado se observó que las variables Sexo, Edad y Categoría Profesional moderan la intensidad del efecto de los factores ER, CF e IS sobre IC, mientras que la variable Rama de Conocimiento modera la intensidad del efecto de ER e IS sobre la intención (IC). Las conclusiones destacan el aporte de este tipo de estudios para conocer mejor el proceso de implementación de la metodología combinada de cara a acelerarlo en los entornos universitarios.

Referencias bibliográficas

  • Azjen, I., From intentions to actions: A theory of planned behavior (1985) Action-control: From cognition of behavior, pp. 11-39. , En J. Kuhl y J. Beckman (Eds.), Heidelberg: Springer
  • Azjen, I., The theory of planned behavior (1991) Organizational Behavior and Human Decision Process, 50 (2), pp. 179-211
  • Ajzen, I., Perceived Behavioral Control, Self-Efficacy, Locus of Control, and the Theory of Planned Behavior (2002) Journal of Applied Social Psychology, 32, pp. 665-683
  • Ajzen, I., Fishbein, M., (1980) Understanding attitudes and predicting social behaviour., , Englewood Cliffs, NJ: Prentice-Hall
  • Aldás Manzano, J., Curras Pérez, R., Ruiz Mafé, C., Sanz Blas, S., Factores determinantes de la lealtad en el comercio electrónico B2C. Aplicación a la compra de billetes de avión (2010) Revista Española de Investigación de Marketing ESIC, 14 (2), pp. 113-142
  • Assi Moreno, V., Bassalo da Silva, J.M., (2009) Aplicação do Modelo UTAUT a Processos de Adoção de Sistemas ERP: Um Estudo Longitudinal, , http://www.aedb.br/seget/artigos09/443_UTAUT%20-%20revisado.pdf, Faculdades Ibmec-RJ Faculdades Ibmec-RJ. Recuperado de
  • Baggozzi, R., Yi, Y., On the evaluation of structural equation models (1998) Academy of Marketing Science, 16 (1), pp. 79-94
  • Bhattacherjee, A., Premkumar, G., Understanding Changes in Belief and Attitude Toward Information Technology Usage: A Theoretical Model and Longitudinal Test (2004) MIS Quarterly, 28 (2), pp. 351-370
  • Birch, A., Irvine, V., Preservice teachers' acceptance of ICT integration in the classroom: Applying the UTAUT model (2009) Educational Media International, 46 (4), pp. 295-315
  • Bollen, K.A., (1989) Structural Equations with Latent Variables, , New York: Wiley
  • Bollen, K.A., Long, J.S., (1993) Testins structural equation models, , Newbury Park, CA: Sage
  • Castañeda, J.A., Frías, D., Muñoz, F., Rodríguez, M.A., Extrinsic and instrinsic motivation in the use of the internet as a tourist information source (2007) International Journal of Internet Marketing and Advertising, 4 (1), pp. 37-52
  • Chin, W.W., (1998) The partial least squares approach to structural equation modeling, pp. 195-336. , En: G. A. Marcoulides (Ed.) Modern methods for business research,. Mahwah, NJ: Erlbaum
  • Compeau, D., Higgins, C., Huff, S., Social Cognitive Theory and Individual Reactions to computing Technology: A longitudinal Study (1999) MIS Quarterly, 23 (2), pp. 145-158
  • Davis, F.D., Perceived usefulness, perceived ease of use, and user acceptance of information technology (1989) MIS Quarterly, 1 (3), pp. 319-340
  • Davis, F.D., Baggozzi, R.P., Warshaw, P.R., Extrinsic and intrinsic motivation to use computers in the workplace (1992) Journal of Applied Social Psychology, 22, pp. 1111-1132
  • Davis, F.D., Bagozzi, R.P., Warshaw, P.R., User acceptance of computer technology: A comparison of two theoretical models (1989) Management Science, 35. , 982-100
  • Davis, S., Wiedenbeck, S., The mediating effects of intrinsic motivation, ease of use and usefulness percepetions on performance in first-time and subsequent computer users (2001) Interacting with Computers, 13, pp. 549-580
  • Featherman, M., Pavlou, P., Predicting e-services adoption: A perceived risk facets perspective (2003) International Journal of Human-Computer Studies. Zhang and Dillon Special Issue on HCI and MIS, 59 (4), pp. 451-474
  • Fishbein, M., Ajzen, I., (1975) Belief, Attitude, Intention and Behavior: An Introduction to Theory and Research, , Reading MA: Addison-Wesley
  • Gefen, D., Karahanna, E., Straub, D., Inexperience and Experience with online stores: The Importance of TAM and Trust (2003) IEEE Transactions on Engineering Management, 50 (3), pp. 307-321
  • Hair, J., Anderson, R., Tatham, R., Black, W., (1999) Análisis multivariante, , 5.a ed. Madrid: Prentice Hall
  • Kline, R.B., (2005) Principles and practice of structural equation modeling, , 2nd ed. New York: Guilford Press
  • Lévy Mangin, J., Varela Mallou, J., (2006) Modelización con estructuras de covarianzas en ciencias sociales, , (ed.), Madrid: Netbiblo
  • Marchewka, T.J., Kurt Kostiwa, K., An Application of the UTAUT Model for Understanding Student Perceptions Using Course Management Software (2007) Communications of the IIMA, 7 (2), pp. 93-104
  • Moon, J.W., Kim, Y.G., Extending de TAM for a world-wide-web context (2001) Information y Management, 38 (4), pp. 217-230
  • Nunnally, J.C., (1978) Psychometric theory, , New York: McGraw-Hill
  • Nurosis, M., (1993) SPSS. Statistical Data Analysis, , Chicago, IL: SPSS Inc
  • Olivier, R.L., A cognitive model of the antecedents and consequences of satisfaction decisions (1980) Journal of Marketing Research, 17, pp. 460-469
  • Rogers, E., (1995) Diffusion of innovations, , (4th ed). New York: Free Press
  • Sánchez, M.J., Roldán, J.L., Web acceptance and usage model: A comparison between goal-directed and experiencial web users (2005) Internet Research, 15, pp. 21-48
  • Taylor, S., Todd, P., Understanding information technology usage: A test of competing models (1995) Information Systems Research, 6 (2), pp. 144-176
  • Teo, T., Examining the intention to use technology among pre-service teachers: An integration of the Technology Acceptance Model and Theory of Planned Behavior (2012) Interactive Learning Environments, 20 (1), pp. 3-18
  • Terzis, V., Economide, A.A., The acceptance and use of computer based assesment (2011) Computer y Education, 56 (4), pp. 1032-1044
  • Thompson, R.L., Higgins, C.A., Howell, J.M., Personal Computing: Toward a Conceptual Model of Utilization (1991) MIS Quarterly, 15, pp. 124-143
  • Venkatesh, V., Davis, F.D., A theoretical extension of the technology acceptance model: Four longitudinal field studies (2000) Management Science, 46 (2), pp. 186-204
  • Venkatesh, V., Morris, M.G., Davis, G.B., Davis, F.D., User acceptance of information technology: Toward a unified view (2003) MIS Quarterly, 27 (3), pp. 425-478
  • Venkatesh, V., Bala, H., Technology Acceptance Model 3 and a Research Agenda on Interventions (2008) Decision Sciences, 39 (2), pp. 273-315
  • Venkatesh, V., Thong, J.Y., Xu, X., Consumer acceptance and use of information technology. Extending the Unified Theory of Acceptance and Use of Technology (2012) MIS Quarterly, 36 (1), pp. 157-178
  • West, G.S., Finch, F.J., Curan, J.P., (1995) Structural equation models with nonnormal variables: Problems and remedies, pp. 56-75. , En R. H. Hoyle (Ed) Structural equation modeling: Concepts, issues, and applications,. CA: Sage, Thousand Oaks, Vol. 9
  • Wong, K.T., Timothy, T., Russo, S., Interactive Whiteboard Acceptance: Applicability of the UTAUT Model to Student Teachers (2012) The Asia-Pacific Education Researcher, 22 (1), pp. 1-10
  • Zhou, T., Lu, Y., Wang, B., Integrating TTF and UTAUT to explain mobile banking user adoption (2010) Computers in Human Behavior, 26 (4), pp. 760-767