PERCEPCIÓN DE LOS ESTUDIANTES ACERCA DE LOS EXÁMENES ONLINE CON CORRECCIÓN AUTOMÁTICA EN UNA EVALUACIÓN MIXTA: RETROALIMENTACIÓN PARA LA MEJORA

Autores/as

DOI:

https://doi.org/10.5944/educxx1.19559

Palabras clave:

Enseñanza superior, Retroalimentación (respuesta), Encuestas a los estudiantes, Entrevistas, Evaluación alternativa, Análisis estadístico.

Agencias Financiadoras:

Universitat Politècnica de València through the A25/14 Project (Convocatoria de Proyectos de Innovación y Convergencia de la UPV).

Resumen

El desarrollo de las tecnologías de la información y la comunicación ha
producido un incremento del uso de la Computer Based Assessment (CBA,
evaluación basada en ordenadores). en la educación superior. En la última
década, ha habido un debate sobre los exámenes online vs los escritos
tradicionales. El objetivo del presente estudio ha sido verificar si los estudiantes tienen prejuicios sobre los exámenes online con corrección automática, y si ese es el caso, determinar los motivos. El estudio se realizó en el contexto de una evaluación mixta que implicó a 1200 estudiantes matriculados en una asignatura de física de primer curso universitario. De entre ellos, 463 respondieron a una encuesta anónima. Del análisis cuantitativo de la encuesta surgieron tres factores (etiquetados «F1-Learning», «F2-Use of Tool» y «F3-Assessment»), y se estableció una escala aditiva. Hemos encontrado diferencias
significativas en el factor «F3-Assessment» en comparación con los otros
dos factores, lo que indica una menor aceptación de la herramienta para
la evaluación del estudiante. Parece ser que, a pesar de que los estudiantes están acostumbrados a los ordenadores, tienen una falta de confianza en los exámenes online. Para reforzar y matizar los resultados cuantitativos de la encuesta, incluimos una pregunta abierta y realizamos una entrevista a un pequeño grupo de 11 estudiantes. Aunque sus comentarios fueron en general positivos, especialmente sobre la facilidad de uso y sobre su utilidad para conocer el nivel alcanzado durante el proceso de aprendizaje, hubo algunas críticas sobre la claridad de las preguntas y el rigor del sistema de puntuación.
Estos dos factores, entre otros, podrían ser la causa de la peor percepción del factor «F3-Assessment» y el origen de las reticencias de los estudiantes a los exámenes online y a la corrección automática.

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Citas

Ardid, M., Gómez-Tejedor, J.A., Meseguer-Dueñas, J.M., Riera, J., & Vidaurre, A. (2015). Online exams for blended assessment. Study of Different application methodologies. Computers & Education, 81, 296-303. https://doi. org/10.1016/j.compedu. 2014.10.010

Bain, K. (2004). What do they know about how we learn? What the Best College Teachers Do. Cambridge, MA: Harvard University Press.

Ballantine, J., Guo, X., & Larres, P. (2015). Psychometric evaluation of the Student Authorship Questionnaire: a confirmatory factor analysis approach. Studies in Higher Education, 40(4), 596-609. https://doi.org/10.1080/03075 079.2013.835910

Barbeite, F.G., & Weiss, E.M. (2004). Computer self-efficacy and anxiety scales for an Internet sample: testing measurement equivalence of existing measures and development of new scales. Computers in Human Behavior, 20(1), 1-15.

Brill, J.M., & Galloway, C. (2007). Perils and promises: University instructors’ integration of technology in classroom-based practices. British Journal of Educational Technology, 38(1), 95-105. https://doi.org/10.1111/j.1467-8535.2006.00601.x

Carless, D. (2015). Exploring learningoriented assessment processes. higher Education, 69(6), 963-976. https://doi. org/10.1007s10734-014-9816-z

Chao, K.-J. J., Hung, I.-C. C., & Chen, N.-S. S. (2012). On the design of online synchronous assessments in a synchronous cyber classroom. journal of Computer Assisted Learning, 28(4), 379-395. https://doi.org /10.1111/j.1365-2729.2011.00463.x

Coenders, G., Satorra, A., & Saris, W. E. (1997). Alternative Approaches to Structural Modeling of Ordinal Data: A Monte Carlo Study. Structural Equation Modeling-a Multidisciplinary Journal, 4(4), 261-282.

Debuse, J.C.W., & Lawley, M. (2016). Benefits and drawbacks of Computerbased assessment and feedback systems: Student and educator perspectives. British Journal of Educational Technology, 47(2), 294-301. Https://doi.org/10.1111/bjet.12232

Ellis, R.A., Goodyear, P., Bliuc, A.-M., & Ellis, M. (2011). High school Students’ experiences of learning through research on the internet. Journal of Computer Assisted Learning, 27(6), 503-515. https://doi.org/10.1111/j.1365-2729.2011.00412.x

Espasa, A., & Meneses, J. (2010). Analysing feedback processes in an online teaching and learning environment: an exploratory study. Higher Education, 59(3), 277-292. https://doi.org/10.1007/s10734-009-9247-4

Gibbs, G. (1999). Using assessment strategically to change the way students learn. In Assessment Matters in Higher Education (pp. 41-53). https://doi.org/10.1007/s13398-014-0173-7.2

Gipps, C. V. (2005). What is the role for ICT-based assessment in universities? Studies in Higher Education, 30(2), 171-180. https://doi.org/10.1080/03075070500043176

Hair, J.F., Black, W.C., Babin, B.J., Anderson, R.E., & Tatham, R.L. (2010). Multivariate Data Analysis. Prentice Hall.

Hewson, C. (2012). Can online coursebased assessment methods be fair and equitable? Relationships between students’ preferences and performance within online and offline assessments. Journal of Computer Assisted Learning, 28(5), 488-498.

Hwang, W.-Y., Hsu, J.-L., Shadiev, R., Chang, C.-L., & Huang, Y.-M. (2015). Employing self-assessment, journaling, and peer sharing to enhance learning from an online course. Journal of Computing in Higher Education, 27(2), 114-133. https://doi.org/10.1007/s12528-015-9096-3

Jassó, J., Milani, A., & Pallottelli, S. (2008). Blended e-Learning: Survey of On-line Student Assessment. In 2008 19th International Conference on Database and Expert Systems Applications (pp. 626-630). IEEE. https://doi.org/10.1109/DEXA.2008.115

Jawaid, M., Moosa, F.A., Jaleel, F., & Ashraf, J. (2014). Computer Based Assessment (CBA): Perception of residents at Dow University of Health Sciences. Pakistan Journal of Medical Sciences, 30(4), 688-91. https://doi.org/10.12669/pjms.304.5444

Jordan, S., & Mitchell, T. (2009). e-Assessment for learning? The potential of short-answer free-text questions with tailored feedback. British Journal of Educational Technology, 40(2), 371-385. https://doi.org/10.1111/j.1467-8535.2008.00928.x

Joreskog, K.G. (1990). New Developments in Lisrel - Analysis of Ordinal Variables using Polychoric Correlations and Weighted Least-Squares. Quality & Quantity, 24(4), 387-404.

Jöreskog, K.G., & Sörbom, D. (1999). LISREL 8 user’s guide. Chicago: Scientific Software International. Kline, T.J.B. (2005). Psychological Testing A Practical Approach to Design and Evaluation. SAGE Publications, Inc.

Kuo, C.-Y., & Wu, H.-K. (2013). Toward an integrated model for designing assessment systems: An analysis of the current status of computer-based assessments in science. Computers & Education, 68, 388-403. https://doi. org/10.1016/j.compedu.2013.06.002

Lafuente, M., Remesal, A., & Álvarez Valdivia, I. M. (2014). Assisting learning in e-assessment: a closer look at educational supports. Assessment & Evaluation in Higher Education, 39(March 2015), 443-460. https://doi.org/10.1080/02602938.2013.848835

Lawton, D., Vye, N., Bransford, J., Sanders, E., Richey, M., French, D., & Stephens, R. (2012). Online Learning Based on Essential Concepts and Formative Assessment. Journal of Engineering Education, 101(2), 244-287. https://doi.org/10.1002/j.2168-9830.2012.tb00050.x

Lee, J. (2014). An Exploratory Study of Effective Online Learning: Assessing Satisfaction Levels of Graduate Students of Mathematics Education Associated with Human and Design Factors of an Online Course. International Review of Research in Open and Distance Learning, 15(1).

Likert, R. (1932). A technique for the measurement of attitudes. Archives of Psychology, 22, 1-55. Retrieved from http://www.sciepub.com/reference/113453

Llamas-Nistal, M., Fernández-Iglesias, M. J., González-Tato, J., & Mikic-Fonte, F. A. (2013). Blended e-assessment: Migrating classical exams to the digital world. Computers & Education, 62, 72-87. https://doi.org/10.1016/j.compedu.2012.10.021

Muthen, B., & Kaplan, D. (1992). A Comparison of some Methodologies for the Factor-Analysis of Nonnormal Likert Variables - a Note on the Size of the Model. British Journal of Mathematical & Statistical Psychology, 45, 19-30.

Netemeyer, R. G., Bearden, W. O., & Sharma, S. (2003). Scaling procedures: issues and applications. In Thousand Oaks (p. 219-261 Chap. 10). https://doi.org/10.4135/9781412985772

Nicol, D., Thomson, A., & Breslin, C. (2014). Rethinking feedback practices in higher education: a peer review perspective. Assessment & Evaluation in Higher Education, 39(1), 102-122. https://doi.org/10.1080/02602938.2013.795518

Noyes, J.M., & Garland, K.J. (2008). Computer- vs. paper-based tasks: Are they equivalent? Ergonomics, 51(9), 1352-1375.

Pacheco-Venegas, N.D., López, G., & Andrade-Aréchiga, M. (2015). Conceptualization, development and implementation of a web-based system for automatic evaluation of mathematical expressions. Computers & Education, 88, 15-28. https: / /doi .org/10.1016/ j.compedu.2015.03.021

Rosen, Y., & Tager, M. (2014). Making Student Thinking Visible through a Concept Map in Computer-Based Assessment of Critical Thinking. Journal of Educational Computing Research, 50(2), 249-270. https://doi.org/10.2190/EC.50.2.f

Roth, P.L. (1994). Missing Data - A Conceptual Review for Applied Psychologists. Personnel Psychology, 47(3), 537-560. https://doi.org/10.1111/j.1744-6570.1994.tb01736.x

Schermelleh-Engel, K., Moosbrugger, H., & Müller, H. (2003). Evaluating the Fit of Structural Equation Models: Tests of Significance and Descriptive Goodness-of-Fit Measures. Methods of Psychological Research Online, 8(2), 23-74. https://doi.org/10.1002/0470010940

Smaill, C.R. (2005). The implementation and evaluation of OASIS: A webbased learning and assessment tool for large classes. Ieee Transactions on Education, 48(4), 658-663.

Smith, J. G., & Suzuki, S. (2015). Embedded blended learning within an Algebra classroom : a multimedia capture experiment. Journal of Computer Assisted Learning, 31, 133-147. https://doi.org/10.1111/jcal.12083

Sun, P.-C., Tsai, R.J., Finger, G., Chen, Y.-Y., & Yeh, D. (2008). What drives a successful e-Learning? An empirical investigation of the critical factors influencing learner satisfaction. Computers & Education, 50(4), 1183-1202.

Wilson, M., & Scalise, K. (2006). Assessment to improve learning in higher education: The BEAR assessment system. Higher Education, 52(4), 635-663.

Xiong, Y., So, H.-J., & Toh, Y. (2015). Assessing learners’ perceived readiness for computer-supported collaborative learning (CSCL): a study on initial development and validation. Journal of Computing in Higher Education, 27(3), 215-239. https://doi.org/10.1007/s12528-015-9102-9

Yang-Wallentin, F., Joreskog, K.G., & Luo, H. (2010). Confirmatory Factor Analysis of Ordinal Variables With Misspecified Models. Structural Equation Modeling-a Multidisciplinary Journal, 17(3), 392-423.

Yuan, J., & Kim, C. (2015). Effective Feedback Design Using Free Technologies. Journal of Educational Computing Research, 52(3), 408-434.

Zlatovic´, M., Balaban, I., & Kermek, D. (2015). Using online assessments to stimulate learning strategies and achievement of learning goals. Computers & Education, 91, 32-45. https://doi.org/10.1016/j.compedu.2015.09.012

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Publicado

2018-05-31

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Estudios