Empirical Model for Mobile Learning and their Factors. Case Study: Universities located in the Urban City of Guadalajara, México

• Mejía Trejo, Juan; Titular Research Professor of Marketing and International Business Department at Universidad de Guadalajara-CUCEA. Dean of Phd. in Administrative Sciences juanmejiatrejo@hotmail.com; jmejia@cucea.udg.mx ; Sánchez Gutiérrez, José ^[1] ; Vázquez Ávila, Guillermo ^[2]
  1. [1] Chief of Marketing and International Business Department at Universidad de Guadalajara-CUCEA. Chair and President of Red Internacional de Investigadores en Competitividad (RIICO). SNI Level I CONACYT Member
  2. [2] Titular Research Professor of Marketing and International Business Department at Universidad de Guadalajara-CUCEA.Red Internacional de Investigadores en Competitividad (RIICO). SNI Level I CONACYT Member
• Localización: Apertura: Revista de Innovación Educativa, ISSN-e 2007-1094, ISSN 1665-6180, Vol. 7, Nº. 2, 2015 (Ejemplar dedicado a: Mixtura de modalidades educativas / Octubre 2015 - marzo 2016), págs. 20-39
• Idioma: inglés
• Enlaces
  • Texto completo (pdf)
• Resumen

  • Information and communication technologies (ICT) are producing new and innovative teaching-learning processes. The research question we focused on is: Which is the empirical model and the factors for mobile learning at universities located within the Metropolitan Zone of Guadalajara, in Jalisco, México? Our research is grounded on a documentary study that chose variables used by specialists in m-learning using Analytic Hierarchy Process (AHP). The factors discovered were three: Technology (TECH); Contents Teaching-Learning Management and Styles (CTLMS); and Professor and Student Role (PSR). We used 13 dimensions and 60 variables. 20 professors and 800 students in social sciences courses participated in the study; they came from 7 universities located in the Urban City of Guadalajara, during 2013-2014 school cycles (24 months). We applied questionnaires and the data were analyzed by structural equations modeling (SEM), using EQS 6.1 software. The results suggest that there are 9/60 variables that have the most influence to improve the interaction with m-Learning model within the universities.

• Referencias bibliográficas
  • Bloom (2009). Eduteka Bloom’s Digital. Eduteka: USA
  • Brazuelo, Francisco & Gallego, Domingo. (2011). Mobile Learning. Los dispositivos móviles como recurso educativo. Sevilla: Eduforma.
  • Cabero, Julio. (2012) Tendencias para el aprendizaje digital: de los contenidos cerrados al diseño de materiales centrado en las actividades....
  • Carroll, John & Rosson, Mary. (2005). Getting around the task-artifact cycle: How to make claims and design by scenario. ACM Transactions...
  • Driscoll, Marcy. (2005). Psychology of learning for instruction (3rd ed.). Boston, MA: Pearson Allyn & Bacon.
  • Fernández, Miguel. (1988). La profesionalización del docente. Madrid: Escuela Española.
  • Dussel, Inés & Quevedo, Luis. (2010). Educación y nuevas tecnologías: los desafíos pedagógicos ante el mundo digital. VI Foro Latinoamericano...
  • Forrester Research Portal (2015). Forrester Research Portal Recuperado de https://www.forrester.com/home/
  • Gallego, Alejandro & Martínez, Eva. (1999). Estilos de aprendizaje y e-learning. Hacia un mayor rendimiento académico, núm. 7, pp.1-10....
  • Garrison, D. & Anderson, T. (2003). E-learning in the 21st Century: A Framework to Research and Practice. NY: Routledge/Falmer.
  • Hernández-Sampieri, Roberto; Fernández-Collado, Carlos; y Baptista-Lucio, Pilar. (2010). Metodología de la Investigación (5ª.Ed.). México:...
  • Honey, Peter & Mumford, Alan. (1992). The Manual of Learning Styles. Maidenhead, Berkshire: Peter Honey, Ardingly House.
  • ISO/IEC 7498-1 (1996). Information Technology-Open Systems Interconnection- Basic Reference Model: The Basic Model. Recuperado de http://www.ecma-international.org/activities/Communications/TG11/s020269e.pdf
  • Kaganer, Evgeny; Giordano, Gabriel; Brion, Sebastien & Tortoriello, Marco. (2013). Media Tablets for Mobile Learning. Communications of...
  • Kaptelinin, Victor & Nardi, Bonnie. (2006). Acting with technology: Activity theory and interaction design. Cambridge, MA: MIT Press.
  • Keegan, Desmond. (2005). Mobile Learning: The Next Generation of Learning. Report, Distance Education International. Recuperado de www.cin.ufpe.br/~mlearning/intranet/m-learning/book.doc
  • Marcelo, Carlos; Puente, D.; Ballesteros, Miguel Ángel y Palazón, A. (2002). E-learning-teleformación. Diseño, desarrollo y evaluación de...
  • Matos, J. (1995). El paradigma sociocultural de L.S. Vygotsky y su aplicación en la educación. Heredia, Costa Rica: Universidad Nacional.
  • Moll, L. (1993). Vygotsky y la educación. Buenos Aires: Editorial Aique.
  • Ramírez-Montoya, María Soledad. (2008). Dispositivos de mobile learning para ambientes virtuales: implicaciones en el diseño y la enseñanza....
  • Ng, Wan & Nicholas, Howard. (2013). A framework for sustainable mobile learning in schools. BJET British Journal of Educational Technology,...
  • Ngai, E., Poon, J. & Chan, Y. (2007). Empirical Examination of the Adoption of WebCT Using TAM. Computers and Education, vol. 48, núm....
  • O’Malley, Claire; Vavoula, Giasemi; Glew, Jp; Taylor, Josie; Sharples, Mike; Lefrere, Paul; et. al. (2005). Guidelines for learning/teaching/tutoring...
  • Saaty, Thomas. (1997). Decision Making for Leaders: The Analytic Hierarchy Process for Decisions in a Complex World. Pittsburgh, PA: RWS.
  • Shneiderman, Ben & Plaisant, Catherine. (2005). Designing the user interface: Strategies for effective human-computer interaction. (4th....
  • Tirri, H. (2003). Promises and challenges of mobile learning. In Kynäslahti & P. Seppälä (Eds.). Mobile learning (pp.23-28). Helsinki:...
  • Traxler, John & Kukulska-Hulme, Agnes. (2005). Evaluating Mobile Learning: Reflections on Current Practice. mLearn 2005: Mobile technology:...
  • Woodill, Gary. (2011). The Mobile Learning Edge: Tools and Technologies for Developing Your Teams. USA: McGraw-Hill.
  • EQS 6 Software References
  • Anderson , J. & Gerbing, D. (1988). Structural equation modeling in practice: A review and recommended two-step approach. Psychological...
  • Bentler, Peter M. (1990). Comparative fit indexes in structural models. Psychological Bulletin, vol. 107, núm. 2, pp. 238-246, DOI: http://dx.doi.org/10.1037//0033-2909.107.2.238
  • Bentler, Peter. (2006). EQS 6 Structural Equations Program Manual. Encion, CA: Multivariate Software Inc. Recuperado de http://www.econ.upf.edu/~satorra/CourseSEMVienna2010/EQSManual.pdf
  • Bentler, P. & Bonnet, D. (1980). Significance tests and goodness of fit in the analysis of covariance structures. Psychological Bulletin,...
  • Bagozzi, Richard P. & YI, Youjae. (1988). On the evaluation of structural equation models. Journal of the Academy of Marketing Science,...
  • Brown, Timothy. (2006). Confirmatory Factor Analysis for Applied Research. New York: The Guilford Press.
  • Byrne, Barbara. (2006). Structural Equation Modeling with EQS, Basic Concepts, Applications, and Programming. London: LEA Publishers.
  • Chau, PYK. (1997). Reexamining a model for evaluating information center success using a structural equation modeling approach. Decision Sciences,...
  • Fornell, Caes & Larcker, David. (1981). Evaluating Structural Equation Models with Unobservable Variables and Measurement Error. Journal...
  • Hair, Joseph; Black, William; Babin, Barry & Anderson, Rolph. (2010). Multivariate Data Analysis. (7th ed). New Jersey: Prentice Hall.
  • Hatcher, Larry. (1994). A Step by Step Approach to Using the SAS System for Factor Analysis and Structural Equation Modeling. USA. Cary, NC:...
  • Heck, R. (1998). Factor analysis: exploratory and confirmatory approaches. In Marcoulides, George. (Ed.). Modern Methods for Business Research....
  • Nunnally, Jum. & Bernsstein Ira. (1994). Psychometric Theory. New York: McGraw-Hill.
  • Satorra, Albert & Bentler, Peter. (1988). Scaling corrections for Chi-square Statistics in Covariance Structure Analysis. 1998 Proceedings...