Cuestionarios de e-autoevaluación y e-feedback: una aplicación en Moodle
Cuestionarios de e-autoevaluación y e-feedback: una aplicación en Moodle
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Resumen
En los entornos Learning Management System (LMS), uno de los recursos de aprendizaje mejor valorados por los estudiantes es la utilización de cuestionarios de autoevaluación (quizzes) en los que se incluyen procesos automáticos de feedback a las respuestas en tiempo real. El uso de estos sistemas facilita el desarrollo de competencias conceptuales y procedimentales. Los objetivos de este estudio fueron conocer si esta herramienta y si su frecuencia de uso incrementaban los resultados de aprendizaje y la satisfacción del estudiante con el proceso de enseñanza. Para ello se realizó un estudio longitudinal a lo largo de dos cursos académicos. Se trabajó con una muestra de 179 estudiantes de Ciencias de la Salud en la Plataforma Moodle v.3.1. En el análisis de los datos se aplicaron técnicas cuantitativas y cualitativas. Los resultados indican que cuando las preguntas de autoevaluación se insertan dentro de videos instruccionales, los aprendices obtienen mejores resultados y experimentan un mayor grado de satisfacción. Además, los estudiantes de ambos grupos (experimental y control) consideraron que la inserción de videos en el LMS facilitó su comprensión conceptual y respetó su ritmo de aprendizaje. La inclusión del feedback automático, en tiempo real (tanto dentro de los videos como en los cuestionarios de autoevaluación) fue valorada como una buena técnica de personalización del aprendizaje.
Citas
ATLAS.ti. Software of Qualitative Data Analysis (Version 8). Atlas.ti. Berlin. Germany.
Cerezo, R., Sánchez-Santillan, M., Paule-Ruiz, M.P., y Núñez, J.C. (2016). Students’ LMS
interaction patterns and their relationship with achievement: a case study in higher
education. Computer and Education, 96, 42-54. doi: 10.1016/j.compedu.2016.02.006
Churches, A. (2009). La Taxonomía de Bloom para la Era Digital. Recuperado de
http://eduteka.icesi.edu.co/articulos/TaxonomiaBloomDigital.
Cloude, E.B., Taub M., y Azevedo R. (2018) Investigating the Role of Goal Orientation:
Metacognitive and Cognitive Strategy Use and Learning with Intelligent Tutoring
Systems. En R. Nkambou., R. Azevedo., y J. Vassileva (Eds.), Intelligent Tutoring
Systems. ITS 2018. Lecture Notes in Computer Science (Vol. 10858, pp.44-53).
Cham: Springer. doi: 10.1007/978-3-319-91464-0_5
D. Hacker, J. Dunlosky, A. Graesser (Eds.), Handbook of Metacognition in Education (pp. 299-
315). New York: Routledge.
Friese, S. (2017). ATLAS.ti. 8 Windows Quick Tour. Software for Qualitative and Mixed Methods
Data Analysis. Berlin: Scientific Software Development GmbH.
Harley, J.M., Taub, M., Azevedo, R., y Bouchet, F. (2018). “Let’s Set Up Some Subgoals”:
Understanding Human-Pedagogical Agent Collaborations and Their Implications for
Learning and Prompt and Feedback Compliance. IEEE Transactions on Learning
Technologies, 11(1), 54-66 doi: 10.1109/TLT.2017.2756629
Hattie, J., y Gan, M (2011). Instructions based on feedback. En R.E. Mayer y P. A. Alexander,
Handbook of Research on Learning and Instruction: Educational Psychology Handbook
series (pp. 249-271). New York: Routledge.
Hattie, J., y Timperley, H. (2007). The power of feedback. Review of Educational Research, 77,
(81–112). doi: 10.3102/003465430298487
Lau, C., Sinclair, J., Taub, M., Azevedo, R., y Jang, E.E. (2017). Transitioning Self-Regulated
Learning Profiles in Hypermedia-learning Environments. Proceedings of the Seventh
International Learning Analytics & Knowledge Conference. LAK,'17 (pp. 198-202).
Vancouver: Canada. doi: 10.1145/3027385.3027443.
Price, M.J., Mudrick, N.V., Taub, M., y Azevedo, R. (2018). The Role of Negative Emotions and
Emotion Regulation on Self-Regulated Learning with MetaTutor. En R. Nkambou.,
Azevedo R., J. Vassileva (Eds.), Intelligent Tutoring Systems. ITS 2018. Lecture Notes in
Computer Science (Vol. 10858, pp. 170-179). Springer: Cham
Sáiz, M.C. (2018), E- Project Based Learning en Terapia Ocupacional: una aplicación en la
asignatura “Estimulación Temprana. Servicio de Publicaciones de la Universidad de
Burgos, Burgos.
Sáiz, M. C., y Marticorena, R. (2016). Metacognition. Self-Regulation and Feedback for ObjectOriented
Programming Problem-Solving. En J. Benson (Ed.), Metacognition: Theory.
Performance and Current Research (pp. 43-94). New York: Nova.
Sáiz, M.C., Marticorena, R., García-Osorio, C.I., y Díez-Pastor, J.F. (2017). How do B-learning
and learning patterns influence learning outcomes? Frontiers in Psychology, 8(745), 1-
13. doi: 10.3389/fpsyg.2017.00745
Sáiz, M. C., y Montero, E. (2015). Metacognition, self-regulation and assessment in problemsolving
processes at university. A. Peña-Ayala (Ed.), In Metacognition: Fundaments,
Applications, and Trends (pp. 107-133). Cham: Springer. doi: 10.1007/978-3-319-
11062-2_5
Sinclair, J., Jang E.E., Azevedo R., Lau C., Taub M., y Mudrick N.V. (2018) Changes in Emotion
and Their Relationship with Learning Gains in the Context of MetaTutor. En R.
Nkambou., R. Azevedo., y J. Vassileva. (Eds.), Intelligent Tutoring Systems. ITS 2018.
Lecture Notes in Computer Science (Vol. 10858, pp.202-211). Cham: Springer. doi.
10.1007/978-3-319-91464-0_20
Saeed, N., Yang, Y., y Sinnappan, S. (2009). Emerging Web Technologies in Higher Education: A
Case of Incorporating Blogs, Podcasts and Social Bookmarks in a Web Programming
Course based on Students’ Learning Styles and Technology Preferences. Educational
Technology & Society, 12(4), 98-109. Recuperado de https://goo.gl/wuA1e
Statistical Package for the Social Sciences (SPSS) (Version 24). IBM. Madrid. Spain:
Taub, M., y Azevedo, R. (2016) Using Eye-Tracking to Determine the Impact of Prior Knowledge
on Self-Regulated Learning with an Adaptive Hypermedia-Learning Environment. En A.
Micarelli., J. Stamper., y K. Panourgia (Eds.), Intelligent Tutoring Systems. ITS 2016.
Lecture Notes in Computer Science (Vol. 9684, pp.34-47). Cham: Springer. doi:
10.1007/978-3-319-39583-8_4
Taub, M., Azevedo, R., Mudrick, N.V., Clodfelter, E., y Bouchet, F. (2014). Can Scaffolds from
Pedagogical Agents Influence Effective Completion of Sub-Goals during Learning with
a Multi-Agent Hypermedia-Learning Environment? Learning and becoming in practice:
The International Conference of the Learning Sciences (ICLS). International Society of
the Learning Sciences, 2 (pp.1052-1056). Boulder, CO: United States.
Taub M., Mudrick N.V., Rajendran R., Dong Y., Biswas G., y Azevedo R. (2018). How Are
Students’ Emotions Associated with the Accuracy of Their Note Taking and
Summarizing During Learning with ITSs? En R. Nkambou., R. Azevedo., y J. Vassileva
(Eds.), Intelligent Tutoring Systems. ITS 2018. Lecture Notes in Computer Science (Vol.
10858, pp.233-242). Cham: Springer. doi: 10.1007/978-3-319-91464-0_23
Zimmerman, B.J., y Moylan, A. (2009). Self-regulation: Where metacognition and motivation
intersect. En D. J. Hacker, J. Dunlosky, & A. C. Graesser (Eds.), The educational
psychology series. Handbook of metacognition in education (pp. 299-315). New York,
NY, US: Routledge/Taylor & Francis Group.
Cerezo, R., Sánchez-Santillan, M., Paule-Ruiz, M.P., y Núñez, J.C. (2016). Students’ LMS
interaction patterns and their relationship with achievement: a case study in higher
education. Computer and Education, 96, 42-54. doi: 10.1016/j.compedu.2016.02.006
Churches, A. (2009). La Taxonomía de Bloom para la Era Digital. Recuperado de
http://eduteka.icesi.edu.co/articulos/TaxonomiaBloomDigital.
Cloude, E.B., Taub M., y Azevedo R. (2018) Investigating the Role of Goal Orientation:
Metacognitive and Cognitive Strategy Use and Learning with Intelligent Tutoring
Systems. En R. Nkambou., R. Azevedo., y J. Vassileva (Eds.), Intelligent Tutoring
Systems. ITS 2018. Lecture Notes in Computer Science (Vol. 10858, pp.44-53).
Cham: Springer. doi: 10.1007/978-3-319-91464-0_5
D. Hacker, J. Dunlosky, A. Graesser (Eds.), Handbook of Metacognition in Education (pp. 299-
315). New York: Routledge.
Friese, S. (2017). ATLAS.ti. 8 Windows Quick Tour. Software for Qualitative and Mixed Methods
Data Analysis. Berlin: Scientific Software Development GmbH.
Harley, J.M., Taub, M., Azevedo, R., y Bouchet, F. (2018). “Let’s Set Up Some Subgoals”:
Understanding Human-Pedagogical Agent Collaborations and Their Implications for
Learning and Prompt and Feedback Compliance. IEEE Transactions on Learning
Technologies, 11(1), 54-66 doi: 10.1109/TLT.2017.2756629
Hattie, J., y Gan, M (2011). Instructions based on feedback. En R.E. Mayer y P. A. Alexander,
Handbook of Research on Learning and Instruction: Educational Psychology Handbook
series (pp. 249-271). New York: Routledge.
Hattie, J., y Timperley, H. (2007). The power of feedback. Review of Educational Research, 77,
(81–112). doi: 10.3102/003465430298487
Lau, C., Sinclair, J., Taub, M., Azevedo, R., y Jang, E.E. (2017). Transitioning Self-Regulated
Learning Profiles in Hypermedia-learning Environments. Proceedings of the Seventh
International Learning Analytics & Knowledge Conference. LAK,'17 (pp. 198-202).
Vancouver: Canada. doi: 10.1145/3027385.3027443.
Price, M.J., Mudrick, N.V., Taub, M., y Azevedo, R. (2018). The Role of Negative Emotions and
Emotion Regulation on Self-Regulated Learning with MetaTutor. En R. Nkambou.,
Azevedo R., J. Vassileva (Eds.), Intelligent Tutoring Systems. ITS 2018. Lecture Notes in
Computer Science (Vol. 10858, pp. 170-179). Springer: Cham
Sáiz, M.C. (2018), E- Project Based Learning en Terapia Ocupacional: una aplicación en la
asignatura “Estimulación Temprana. Servicio de Publicaciones de la Universidad de
Burgos, Burgos.
Sáiz, M. C., y Marticorena, R. (2016). Metacognition. Self-Regulation and Feedback for ObjectOriented
Programming Problem-Solving. En J. Benson (Ed.), Metacognition: Theory.
Performance and Current Research (pp. 43-94). New York: Nova.
Sáiz, M.C., Marticorena, R., García-Osorio, C.I., y Díez-Pastor, J.F. (2017). How do B-learning
and learning patterns influence learning outcomes? Frontiers in Psychology, 8(745), 1-
13. doi: 10.3389/fpsyg.2017.00745
Sáiz, M. C., y Montero, E. (2015). Metacognition, self-regulation and assessment in problemsolving
processes at university. A. Peña-Ayala (Ed.), In Metacognition: Fundaments,
Applications, and Trends (pp. 107-133). Cham: Springer. doi: 10.1007/978-3-319-
11062-2_5
Sinclair, J., Jang E.E., Azevedo R., Lau C., Taub M., y Mudrick N.V. (2018) Changes in Emotion
and Their Relationship with Learning Gains in the Context of MetaTutor. En R.
Nkambou., R. Azevedo., y J. Vassileva. (Eds.), Intelligent Tutoring Systems. ITS 2018.
Lecture Notes in Computer Science (Vol. 10858, pp.202-211). Cham: Springer. doi.
10.1007/978-3-319-91464-0_20
Saeed, N., Yang, Y., y Sinnappan, S. (2009). Emerging Web Technologies in Higher Education: A
Case of Incorporating Blogs, Podcasts and Social Bookmarks in a Web Programming
Course based on Students’ Learning Styles and Technology Preferences. Educational
Technology & Society, 12(4), 98-109. Recuperado de https://goo.gl/wuA1e
Statistical Package for the Social Sciences (SPSS) (Version 24). IBM. Madrid. Spain:
Taub, M., y Azevedo, R. (2016) Using Eye-Tracking to Determine the Impact of Prior Knowledge
on Self-Regulated Learning with an Adaptive Hypermedia-Learning Environment. En A.
Micarelli., J. Stamper., y K. Panourgia (Eds.), Intelligent Tutoring Systems. ITS 2016.
Lecture Notes in Computer Science (Vol. 9684, pp.34-47). Cham: Springer. doi:
10.1007/978-3-319-39583-8_4
Taub, M., Azevedo, R., Mudrick, N.V., Clodfelter, E., y Bouchet, F. (2014). Can Scaffolds from
Pedagogical Agents Influence Effective Completion of Sub-Goals during Learning with
a Multi-Agent Hypermedia-Learning Environment? Learning and becoming in practice:
The International Conference of the Learning Sciences (ICLS). International Society of
the Learning Sciences, 2 (pp.1052-1056). Boulder, CO: United States.
Taub M., Mudrick N.V., Rajendran R., Dong Y., Biswas G., y Azevedo R. (2018). How Are
Students’ Emotions Associated with the Accuracy of Their Note Taking and
Summarizing During Learning with ITSs? En R. Nkambou., R. Azevedo., y J. Vassileva
(Eds.), Intelligent Tutoring Systems. ITS 2018. Lecture Notes in Computer Science (Vol.
10858, pp.233-242). Cham: Springer. doi: 10.1007/978-3-319-91464-0_23
Zimmerman, B.J., y Moylan, A. (2009). Self-regulation: Where metacognition and motivation
intersect. En D. J. Hacker, J. Dunlosky, & A. C. Graesser (Eds.), The educational
psychology series. Handbook of metacognition in education (pp. 299-315). New York,
NY, US: Routledge/Taylor & Francis Group.