La mejora de satisfacción de los estudiantes de grado de Relaciones Laborales y Recursos Humanos con el uso de las Ticsefectos de las estrategias de aprendizaje y de las experiencias de flujo

  1. Antonio José Carrasco Hernández 1
  2. Micaela Martínez Costa 1
  3. Daniel Jiménez Jiménez 1
  1. 1 Universidad de Murcia
    info

    Universidad de Murcia

    Murcia, España

    ROR https://ror.org/03p3aeb86

Journal:
Trabajo: Revista iberoamericana de relaciones laborales

ISSN: 1136-3819

Year of publication: 2015

Issue Title: La docencia en los estudios de Relaciones Laborales: nuevas propuestas

Issue: 33

Pages: 17-30

Type: Article

More publications in: Trabajo: Revista iberoamericana de relaciones laborales

Abstract

This paper attempts to investigate the effect of applying SAKAI in the degree of satisfaction of students in the learning process and learning strategies developed by the student. On the other hand, measure the effect of learning strategies on flow experience and student satisfaction, and the mediating effects of learning strategies on student satisfaction. The work was carried out on a sample of 127 students of the University of Murcia, from different subjects and courses.

Bibliographic References

  • Chin, W. W. (1998). The partial least squares approach to structural equation modeling. In G. A. Marcoulides (Ed.), (pp. 295-336). Mahwah, NJ: Lawrence Erlbaum Associate.
  • Csikszentmihalyi, M. (2013). Flow: The psychology of happiness. Random House.
  • Dansereau, D. (1985): A Learning strategy research@, en J. Segal, S. Chipman y R. Glaser (eds.) Thinking and learning skills, 1, 209-239, Hillsdale, N.J.: Lawrence Erlbaum Associates, Publishers.
  • Delone, W. H., y Mclean, E. R. (2003). The Delone and Mclean model of information systems success: a ten-year update. Journal of Management Information Systems, 19(4), 9–30.
  • Esteban-Millat, I., Martínez-López, F. J., Huertas-García, R., Meseguer, A., y RodríguezArdura, I. (2014). Modelling students’ flow experiences in an online learning environment. Computers & Education, 71, 111-123.
  • Fornell, C., y Larcker, D. F. (1981). Evaluating structural equation models with unobservable variables and measurement error. Journal of Marketing Research, XXVII(February), 39-50.
  • Graham, S., y Golan, S. (1991). Motivational influences on cognition: Task involvement, ego involvement, and depth of information processing. Journal of Educational Psychology, 83(2), 187.
  • Hair, J. F., Anderson, R. L., y Tatham, W. C. (2006). Multivariate data analysis. Upper Saddle River, NJ: Pearson.
  • Kiili, K. (2005). Content creation challenges and flow experience in educational games: The IT-Emperor case. The Internet and Higher Education, 8(3), 183-198.
  • Kim, K. J., y Bonk, C. J. (2006). The future of online teaching and learning in higher education: the survey says. Educause Quarterly, 29, 22–30.
  • Koufaris, M. (2002). Applying the technology acceptance model and flow theory to online consumer behavior. Information Systems Research, 3(2), 205–223.
  • Kuo, Y.-C., Walker, A. E., Schroder, K. E. E., y Belland, B. R. (2014). Interaction, Internet self-efficacy, and self-regulated learning as predictors of student satisfaction in online education courses. The Internet and Higher Education, 20(0), 35-50. doi: http://dx.doi.org/10.1016/j.iheduc.2013.10.001
  • Lee, E. (2001). The relations of motivation and cognitive strategies to flow experience. Journal of Educational Psychology, 15(3), 199–216.
  • Lee, Y. K., Tseng, S. P., Liu, F. J., y Liu, S. C. (2007). Antecedents of learner satisfaction toward e-learning. The Journal of American Academy of Business, Cambridge, 11, 161–168.
  • Liaw, S.S., y Huang, H.M. (2013). Perceived satisfaction, perceived usefulness and interactive learning environments as predictors to self-regulation in e-learning environments. Computers & Education, 60, 14-24.
  • Lindgaard, G., y Dudek, C. (2003). What is this evasive beast we call user satisfaction? Interacting with Computers, 15(3), 429–452.
  • Lowerison, G., Sclater, J., Schmid, R. F., y Abrami, P. C. (2006). Student perceived effectiveness of computer technology use in post-secondary classrooms. Computers & Education, 47(4), 465-489.
  • Massimini, F., y Delle Fave, A. (2000). Individual development in a bio-cultural perspective. American Psychologist, 55(1), 24.
  • Massimini, F., Csikszentmihalyi, M., y delle Fave, A. (1988). Flow and biocultural evolution. In M. Csikszentmikalyi, y I. S. Csikszentmihalyi (Eds.), Optimal experience: Psychological studies of low in consciousness (pp. 60–81). New York: Cambridge University Press.
  • Miles, J., y Shevlin, M. (2001). Applying regression and correlation. London: Sage Publications.
  • Motiwalla, L. F. (2007). Mobile learning: A framework and evaluation. Computers & Education, 49(3), 581-596.
  • Nunnally, J. C. (1978). Psychometric theory. New York: McGraw-Hill.
  • Pearce, J. M., Ainley, M., y Howard, S. (2005). The ebb and flow of online learning. Computers in human behavior, 21(5), 745-771.
  • Pekrun, R., Goetz, T., Titz, W., y Perry, R. P. (2002). Academic emotions in students’ self-regulated learning and achievement: A program of qualitative and quantitative research. Educational psychologist, 37(2), 91-105.
  • Pintrich, P. R. (1988). A process‐oriented view of student motivation and cognition. New directions for institutional research, 1988(57), 65-79.
  • Pintrich, P. R., y Garcia, T. (1994). Self-regulated learning in college students: Knowledge, strategies, and motivation. Student motivation, cognition, and learning, 113-133.
  • Podsakoff, P. M., y Organ, D. W. (1986). Self-reports in organizational research: Problems and prospects. Journal of Management, 12, 69-82.
  • Ringle, C. M., Wende, S., y Will, A. (2005). SmartPLS 2.0 (M3) beta. Sevillano, M.L. (2005): Estrategias innovadoras para una enseñanza de calidad, Madrid: Pearson Prentice Hall.
  • Shee, D., y Wang, Y. H. (2008). Multi-criteria evaluation of the web-based e-learning system: a methodology based on learner satisfaction and its applications. Computers & Education, 50, 894–905.
  • Somuncuoglu, Y., y Yildirim, A. (1999). Relationship between achievement goal orientations and use of learning strategies. The Journal of Educational Research, 92(5), 267-277.
  • Sternberg, R. J., y Davidson, J. E. (1995). The nature of insight. The MIT Press.
  • Sun, P. C., Tsai, R. J., Finger, G., Chen, Y. Y., y Yeh, D. (2008). What drives a successful e-learning? An empirical investigation of the critical factors influencing learner satisfaction. Computers & Education, 50, 1183–1202.
  • Virvou, M., y Katsionis, G. (2008). On the usability and likeability of virtual reality games for education: the case of VR-ENGAGE. Computers & Education, 50, 154–178.