Uso de una app móvil para evaluar la calidad de la enseñanza superior

  1. Arceo Vacas, Alfredo
  2. Niño González, José Ignacio
  3. Álvarez Sánchez, Sergio 1
  1. 1 Universidad Complutense de Madrid
    info

    Universidad Complutense de Madrid

    Madrid, España

    ROR 02p0gd045

Journal:
Prisma Social: revista de investigación social

ISSN: 1989-3469

Year of publication: 2019

Issue Title: La Investigación en la Educación Superior y su Impacto Social

Issue: 27

Pages: 65-85

Type: Article

More publications in: Prisma Social: revista de investigación social

Abstract

Universities belonging to the European Higher Education Area -EHEA- need procedures to assess the quality of their titles. In this sense, much has been discussed about the most adequate methods to measure the satisfaction of students, as well as about how useful this variable is in reality. Taking into account the increasing demand for mobile learning applications -the so-called m-learning-, a new app to assess the quality of teaching was tested, employing neuroscientific methods to find out the emotions experienced by 22 students of the degree in Advertising and Public Relations from Complutense University. Consequently, the employed set of tecniques included registering the travel of the gaze (eye tracking), the facial expressions and the dermoelectric response of the skin. The results reflect a huge acceptance of the app. When screenshots were showed, the students payed attention to the most important areas, regardless of their genre or the academic year they were in. In addition, they conceded high ratings in the questionnaire, something that evidences how inclined they are towards this kind of tools.

Funding information

La presente investigación es resultado del proyecto de innovación docente "Desarrollo de una App para el Grado de Publicidad y Relacones Públicas como Sistema de Evaluación y Mejora Continua de la Calidad", por lo que ha contado con la financiación del programa Innova-Docencia de la Universidad Complutense.

Bibliographic References

  • Adhami, M. (2013). Using neuromarketing to discover how we really feel about apps. International Journal of Mobile Marketing, 8(1), pp. 95-103. Recuperado de https://www.warc.com/content/article/ijmm/using_neuromarketing_to_discover_how_we_really_feel_about_apps/100341
  • Bell, L., Vogt, J., Willemse, C., Routledge, T., Butler, L. T. y Sakaki, M. (2018). Beyond self-report: A review of physiological and neuroscientific methods to investigate consumer behavior. Frontiers in Psychology, 9, pp. 1-16. doi: 10.3389/fpsyg.2018.01655
  • Bomhold, C. R. (2013). Educational use of smart phone technology: A survey of mobile phone application use by undergraduate university students. Program: Electronic Library and Information Systems, 47(4), pp. 424–436. doi: 10.1108/PROG-01-2013-0003
  • Busemeyer, J. R. y Rapoport, A. (1988). Psychological models of deferred decision making. Journal of Mathematical Psychology, 32(2), pp. 91-134. doi: 10.1016/0022-2496(88)90042-9
  • Cartocci, G., Cherubino, P., Rossi, D., Modica, E., Maglione, A. G., Di Flumeri, G y Babiloni, F. (2016). Gender and age related effects while watching TV advertisements: An EEG study. Computational Intelligence and Neuroscience, 2016, pp. 1-10. doi: 10.1155/2016/3795325
  • Clayson, D. E. (2009). Student evaluations of teaching: Are they related to what students learn? A meta-analysis and review of the literature. Journal of Marketing Education, 31(1), pp. 16-30. doi: 10.1177/0273475308324086
  • Cohen, M. X. (2017). Where does EEG come from and what does it mean? Trends in Neuroscience, 40(4), pp. 208-218. doi: 10.1016/j.tins.2017.02.004
  • Comisión Europea/EACEA/Eurydice (2018). The European Higher Education Area in 2018: Bologna process implementation report. Luxemburgo: Oficina de Publicaciones de la Unión Europea.
  • Couwenberg, L. E., Boksem, M. A. S., Dietvorst, R. C., Worm, L., Verbeke, W. J. M. I. y Smidts, A. (2017). Neural responses to functional and experiential ad appeals: Explaining ad effectiveness. International Journal of Research in Marketing, 34(2), pp. 355-366. doi: 10.1016/j.ijresmar.2016.10.005
  • Crompton, H. (2013). A historical overview of m-learning: Toward learner-centered education. En Z. L. Berge, ZL y L. Y. Muilenburg (Eds.), Handbook of Mobile Learning (pp. 3-14). Nueva York: Routledge.
  • Cuesta, U., Martínez-Martínez, L. y Cuesta, V. (2017). Neuromarketing olfativo: Análisis del electroencefalograma y las respuestas psicofisiológicas provocadas por diferentes olores. Madrid: Tecnos.
  • Cuesta, U., Martínez-Martínez, L. y Niño, J. I. (2018). A case-study in neuromarketing: Analysis of the influence of music on advertising effectiveness through eye-tracking, facial emotion and GSR. European Journal of Social Science Education and Research, 5(2), 84-92. doi: 10.2478/ejser-2018-0035
  • D’Apollonia, S. y Abrami, P. C. (1997). Navigating student ratings of instruction. The American Psychologist, 52(11), pp. 1198–1208. doi: 10.1037/0003-066X.52.11.1198
  • Fang, J., Zhao, Z., Wen, Ch. y Wang, R. (2017). Design and performance attributes driving mobile travel application engagement. International Journal of Information Management, 37(4), pp. 269-283. doi: 10.1016/j.ijinfomgt.2017.03.003
  • Fueyo, A. (2004). Evaluación de titulaciones, centros y profesorado en el proceso de convergencia europea: ¿De qué calidad y de qué evaluación hablamos? Revista Interuniversitaria de Formación de Profesorado, 18(3), pp. 207-219. Recuperado de https://www.aufop.com/aufop/uploaded_files/articulos/1212408107.pdf
  • Fugate, D. L. (2015). Neuromarketing: A layman's look at neuroscience and its potential application to marketing practice. Journal of Consumer Marketing, 24(7), pp. 385-394. doi: 10.1108/07363760710834807
  • García-Berro, E., Dapia, F., Amblás, G., Bugeda, G. y Roca, S. (2009). Estrategias e indicadores para la evaluación de la docencia en el marco del EEES. Revista de Investigación en Educación, 6(1), pp. 142-152. Recuperado de https://upcommons.upc.edu/bitstream/handle/2117/28115/55.pdf?sequence=1yisAllowed=y
  • Gaye, F. H. (2015). Neuroscience: The study of the nervous system and its functions. Daedalus, 144(1), pp. 5-9. Recuperado de https://www.amacad.org/sites/default/files/daedalus/downloads/15_Winter_Daedalus.pdf
  • Glover, G. H. (2011). Overview of functional magnetic resonance imaging. Neurosurgery Clinics of North America, 22(2), pp. 133-139. doi: 10.1016/j.nec.2010.11.001
  • Goodrich, K. (2014). The gender gap: Brain-processing differences between the sexes shape attitudes about online advertising. Journal of Advertising Research, 1(2014), pp. 32-43. doi: 10.2501/JAR-54-1-032-043
  • Harley, J. M. (2016). Measuring emotions: A survey of cutting edge methodologies used in computer-based learning environment research. En S. Y. Tettegah y M. Gartmeier (Eds.), Emotions, Technology, Design, and Learning (pp. 89-114). Londres y San Diego, California: Academic Press.
  • Hashemi, M., Azizinezhad, M., Najafi, V. y Nesari, A. J. (2011). What is mobile learning? Challenges and capabilities. Procedia: Social and Behavioral Sciences, 30(2011), pp. 2477-2481. doi: 10.1016/j.sbspro.2011.10.483
  • Jaén, A. y Sirignano, F. M. (2016). El aprendizaje cooperativo como estrategia didáctica para la adquisición de competencias en el EEES. Propuesta y reflexión sobre una experiencia. Hekademos: Revista Educativa Digital, 19(año IX), pp. 7-19. Recuperado de http://www.hekademos.com/hekademos/media/articulos/19/01.pdf
  • Javor, A., Koller, M., Lee, N., Chamberlain, L. y Ransmayr, G. (2013). Neuromarketing and consumer neuroscience: contributions to neurology. BMC Neurology, 13(1), pp. 1-12. doi: 10.1186/1471-2377-13-13
  • Jenaro, C., Castaño, R., Martín, M. E. y Flores, N. (2018). Rendimiento académico en educación superior y su asociación con la participación activa en la plataforma Moodle. Cultura y Educación, 34(2018), pp. 177-198. doi: 10.15581/004.34.177-198
  • Lee, N., Broderick, A. J. y Chamberlain, L. (2007). What is “neuromarketing”? A discussion and agenda for future research. International Journal of Psychophysiology, 63(2), pp. 199-204. doi: 10.1016/j.ijpsycho.2006.03.007
  • Lee, N., Chamberlain, L. y Brandes, L. (2018). Welcome to the jungle! The neuromarketing literatura through the eyes of a newcomer. European Journal of Marketing, 52(1-2), pp. 4-38. doi: 10.1108/EJM-02-2017-0122
  • Leite, F. P. y Ratcliff, R. (2010). Modeling reaction time and accuracy of multiple-alternative decisions. Attention, Perception, y Psychophysics, 72(1), pp. 246-273. doi: 10.3758/APP.72.1.246
  • Marsh, H. W. (2007). Students’ evaluations of university teaching: A multidimensional perspective. En R. P. Perry y J. C. Smart (Eds.), The scholarship of teaching and learning in Higher Education: An evidence based perspective (pp. 319–384). Nueva York: Springer.
  • Muñoz-Leiva, F., Hernández-Méndez, J. y Gómez-Carmona, D. (2019). Measuring advertising effectiveness in Travel 2.0 websites through eye-tracking technology. Physiology & Behavior, 200, pp. 83-95. doi: 10.1016/j.physbeh.2018.03.002
  • Palés-Argullós, J., Nolla-Domenjó, M., Oriol-Bosch, A. y Gual, A. (2010). Proceso de Bolonia (I): Educación orientada a competencias. Educación Médica, 13(3), pp. 1575-1813. doi: 10.33588/fem.133.564
  • Penny, A. R. y Coe, R. (2004). Effectiveness of consultation on student ratings feedback: A meta-analysis. Review of Educational Research, 74(2), 215-253. doi: 10.3102/00346543074002215
  • Plassmann, H., Ramsøy, T. Z. y Milosavljevic, M. (2012). Branding the brain: A critical review and outlook. Brand Insights from Psychological and Neurophysiological Perspectives, 22(1), pp. 18-36. doi: 10.1016/j.jcps.2011.11.010
  • Plassmann, H., Venkatraman, V., Huettel, S. y Yoon C. (2015). Consumer Neuroscience: Applications, Challenges, and Possible Solutions. Journal of Marketing Research, 52(4), pp. 427-435. doi: 10.1509/jmr.14.0048
  • Pozo, C., Bretones, B., Martos, M. J. y Alonso, E. (2011). Evaluación de la actividad docente en el Espacio Europeo de Educación Superior: un estudio comparativo de indicadores de calidad en universidades europeas. Revista Española de Pedagogía, 248(69), pp. 145-163. Recuperado de https://revistadepedagogia.org/wp-content/uploads/2011/01/248-008.pdf
  • Rampl, L. V., Opitz, C., Welpe, I. M. y Kenning, P. (2016). The role of emotions in decision-making on employer brands: Insights from functional magnetic resonance imaging (fMRI). Marketing Letters, 27(2), pp. 361-374. doi: 10.1007/s11002-014-9335-9
  • Rebollo, M. Á., García, R., Barragán, R., Buzón, O. y Ruiz, E. (2012). Tecnologías para la coeducación y la igualdad: Valoración del profesorado de una herramienta web. Educación XXI, 15(1), pp. 87-111. doi: 10.5944/educxx1.15.1.151
  • Reisenzein, R., Studtmann, M. y Horstmann, G. (2013). Coherence between emotion and facial expression: Evidence from laboratory experiments. Emotion Review, 5(1), pp. 16-23. doi: 10.1177/1754073912457228
  • Sánchez-Elvira, A., López-González, M. A. y Fernández-Sánchez, M. V. (2010). Análisis de las competencias genéricas en los nuevos títulos de grado del EEES en las universidades españolas. Red U - Revista de Docencia Universitaria, 8(1), pp. 35-73. doi: 10.4995/redu.2010.6217
  • Shimojo, S., Simion, C., Shimojo, E. y Scheier, C. (2003). Gaze bias both reflects and influences preference. Nature neuroscience, 6(12), pp. 1317-1322. doi: 10.1038/nn1150
  • Simion, C. y Shimojo, S. (2007). Interrupting the cascade: Orienting contributes to decision making even in the absence of visual stimulation. Perception y Psychophysics, 69(4), pp. 591-595. doi: 10.3758/bf03193916
  • Spooren, P., Brockx, B. y Mortelmans, D. (2013). On the validity of student evaluation of teaching: The state of the art. Review of Educational Research, 83(4), pp. 598-642. doi: 10.3102/0034654313496870
  • Stapenhurst, T. (2009). The benchmarking book: A how-to-guide to best practice for managers and practitioners. Oxford: Butterworth-Heinemann.
  • Vázquez-Cano, E. (2014). Mobile distance learning with smartphones and apps in Higher Education. Educational Sciences: Theory y Practice, 14(4), pp. 1505-1520. doi: 10.12738/estp.2014.4.2012
  • Vila-López, N. y Küster-Boluda, I. (2019). Consumers’ physiological and verbal responses towards product packages: Could these responses anticipate product choices? Physiology y Behavior, 200, pp. 166-173. doi: 10.1016/j.physbeh.2018.03.003
  • Wai, I. S. H., Ng, S. S. Y., Chiu, D. K. W., Ho, K. K. W. y Lo, P. (2018). Exploring undergraduate students’ usage pattern of mobile apps for education. Journal of Librarianship and Information Science, 50(1), pp. 34-47. doi: 10.1177/0961000616662699
  • Wright, S. L. y Jenkins-Guarnieri, S. L. (2012). Student evaluations of teaching: combining the meta-analyses and demonstrating further evidence for effective use. Assessment y Evaluation in Higher Education, 37(6), pp. 683-699. doi: 10.1080/02602938.2011.563279
  • Yániz, C. (2006). Planificar la enseñanza universitaria para el desarrollo de competencias. Educatio Siglo XXI: Revista de la Facultad de Educación, 24(1), pp. 17-34. Recuperado de https://revistas.um.es/educatio/article/view/151/134