Andamiaje docente para la construcción del conocimiento en el aula de investigación educativa
DOI:
https://doi.org/10.5944/ried.27.2.38969Palabras clave:
enseñanza, innovación educativa, investigación educativa, aprendizaje en grupo, tecnología de la educación, aprendizaje asistido por ordenadorResumen
La Construcción del Conocimiento es un modelo educativo que se caracteriza por su énfasis en la responsabilidad colectiva de los estudiantes para mejorar las ideas colectivas. Estudios previos han demostrado los beneficios de la Construcción del Conocimiento en la enseñanza de las ciencias. Este estudio implementa esta pedagogía en el campo de la investigación educativa y persigue dos objetivos: i) analizar la calidad de las contribuciones de los estudiantes al participar en un entorno colaborativo para mejorar las ideas, y ii) examinar los andamios utilizados por los docentes durante la implementación. Se utilizó un diseño de investigación mixta que incluyó enfoques cualitativos y cuantitativos para recopilar datos. Los participantes fueron 59 estudiantes del grado de educación social inscritos en un curso de investigación-acción. Los datos sobre la calidad del discurso se recopilaron a partir de las entradas o notas elaboradas por los estudiantes en la plataforma Foro del Conocimiento, mientras que los datos sobre los andamios docentes, tal como los percibieron los estudiantes, se obtuvieron a través de entrevistas. Los resultados de este estudio revelan que la mayoría de las contribuciones del alumnado son de alta calidad, aunque se observa una distribución ligeramente desigual en la participación. Además, este estudio amplía nuestra comprensión de los andamios de enseñanza que respaldan la construcción del conocimiento del alumnado en materia de investigación educativa, y ofrece andamios docentes que pueden aplicarse en diversos contextos de aprendizaje constructivista que persigan fomentar la autonomía del alumnado para colaborar en la creación de conocimiento.
Descargas
Citas
Bereiter, C., & Scardamalia, M. (2016). “Good Moves” in knowledge-creating dialogue. QWERTY, 11, 2 (2016), 12-26.
Biggs, J. B. (2011). Teaching for quality learning at university. Open University Press/McGraw Hill.
Böttcher, F., & Thiel, F. (2018). Evaluating research-oriented teaching: a new instrument to assess university students’ research competences. Higher Education, 75, 91-110. https://doi.org/10.1007/s10734-017-0128-y
Cacciamani, S., Perrucci, V., & Fujita, N. (2021). Promoting students’ collective cognitive responsibility through concurrent, embedded, and transformative assessment in blended higher education courses. Technology, Knowledge, and Learning, 26(4), 1169-1194. https://doi.org/10.1007/s10758-021-09535-0
Cai, H., & Gu, X. (2022). Factors that influence the different levels of individuals’ understanding after collaborative problem solving: the effects of shared representational guidance and prior knowledge. Interactive Learning Environments, 30(4), 695-706, https://doi.org/10.1080/10494820.2019.1679841
Chan, C., Tsui, M., Chan, M., & Hong, H. (2002). Applying the structure of the observed learning outcomes (SOLO) taxonomy on student's learning outcomes: An empirical study. Assessment & Evaluation in Higher Education, 27(6), 511-527. https://doi.org/10.1080/0260293022000020282
Chen, B., & Hong, H.-Y. (2016). Schools as knowledge building organizations: thirty years of design research. Educational Psychologist, 51(2), 266–288. https://doi.org/10.1080/00461520.2016.1175306
Chen, J., Wang, M., Kirschner, P., & Tsai, C. C. (2018). The role of collaboration, computer use, learning environments, and supporting strategies in CSCL: A meta-analysis. Review of Educational Research, 88(6), 799-843. https://doi.org/10.3102/0034654318791584
Chen, J., Wang, M., Kirschner, P., & Tsai, C. C. (2019). A metaanalysis examining the moderating effects of educational level and subject area on CSCL effectiveness. Knowledge Management & E-Learning, 11(4), 409-427. https://doi.org/10.34105/j.kmel.2019.11.022
Chen, D., Zhang, Y., Luo, H., Zhu, Z., Ma, J., & Lin, Y. (2024). Effects of group awareness support in CSCL on students’ learning performance: A three-level meta-analysis. International Journal of Computer-Supported Collaborative Learning, 1-33. https://doi.org/10.1007/s11412-024-09418-3
Chevrier, M., Muis, K. R., Trevors, G. J., Pekrun, R., & Sinatra, G. M. (2019). Exploring the antecedents and consequences of epistemic emotions. Learning and instruction, 63, 101209. https://doi.org/10.1016/j.learninstruc.2019.05.006
Ciraso-Calí, A., Martínez-Fernández, J. R., París-Mañas, G., Sánchez-Martí, A., & García-Ravidá, L. B. (2022). The research competence: acquisition and development among undergraduates in education sciences. Frontiers in Education, 7. https://doi.org/10.3389/feduc.2022.836165
Coll Salvador, C., Díaz Barriga Arceo, F., Engel Rocamora, A., & Salinas Ibáñez, J. (2023). Evidencias de aprendizaje en prácticas educativas mediadas por tecnologías digitales. RIED-Revista Iberoamericana de Educación a Distancia, 26(2), 9-25. https://doi.org/10.5944/ried.26.2.37293
Creswell, J. W., & Guetterman, T. C. (2021). Educational research: planning, conducting, and evaluating quantitative and qualitative research (Sixth, global edition). Pearson.
Earley, M. A. (2014). A synthesis of the literature on research methods education. Teaching in Higher Education, 19(3), 242-253. https://doi.org/10.1080/13562517.2013.860105
Endres, T., Lovell, O., Morkunas, D., Rieß, W., & Renkl, A. (2023). Can prior knowledge increase task complexity? – Cases in which higher prior knowledge leads to higher intrinsic cognitive load. British Journal of Educational Psychology, 93(2), 305-3017. https://doi.org/10.1111/bjep.12563
Fernández-Miranda, M., Dios-Castillo, C. A., Sosa-Córdova, D. M., & Camilo-Cépeda, A. (2022). Inverted method and didactic model: a motivating perspective of virtual learning in pandemic contexts. Bordón. Revista de Pedagogía, 74(3), 11-33. https://doi.org/10.13042/Bordon.2022.92677
Finelli, C. J., & Borrego, M. J. (2020). Evidence-based strategies to reduce student resistance to active learning. In J. J. Mintzes & E. M. Walter (Eds.), Active learning in college science: The case for evidence-based practice. (pp. 943-952). Springer Nature. https://doi.org/10.1007/978-3-030-33600-4_58
García Peñalvo, F. J., Llorens-Largo, F., & Vidal, J. (2024). The new reality of education in the face of advances in generative artificial intelligence. [La nueva realidad de la educación ante los avances de la inteligencia artificial generativa]. RIED-Revista Iberoamericana de Educación a Distancia, 27(1), pp. 9-39. https://doi.org/10.5944/ried.27.1.37716
Gess, C., Geiger, C., & Ziegler, M. (2018). Social-scientific research competency. European Journal of Psychological Assessment, 35(5), 737-750. https://doi.org/10.1027/1015-5759/a000451
Gussen L., Schumacher F., Großmann N., Ferreira González L., Schlüter, K., & Großschedl, J. (2023) Supporting pre-service teachers in developing research competence. Frontiers in Education, 8. https://doi.org/10.3389/feduc.2023.1197938
Gutiérrez-Braojos, C., Daniela, L., Montejo-Gámez, J., & Aliaga, F. (2022). Developing and comparing indices to evaluate community knowledge building in an educational research course. Sustainability, 14, 10603. https://doi.org/10.3390/su141710603
Gutiérrez-Braojos, C., Montejo-Gámez, J., Ma, L., Chen, B., de Escalona-Fernández, M. M., Scardamalia, M., & Bereiter, C. (2018). Exploring collective cognitive responsibility through the emergence and flow of forms of engagement in a knowledge building community. In L. Daniela (Ed.), Didactics of smart pedagogy (pp. 213-232). Cham: Springer. https://doi.org/10.1007/978-3-030-01551-0_11
Gutiérrez-Braojos, C., Montejo Gámez, J., Poza Vílches, F., & Marín-Jiménez, A. (2020). Evaluación de la investigación sobre la pedagogía Construcción de Conocimiento: un enfoque metodológico mixto. RELIEVE - Revista Electrónica De Investigación Y Evaluación Educativa, 26(1). https://doi.org/10.7203/relieve.26.1.16671
Gutiérrez-Braojos, C., Rodríguez-Domínguez, C., Daniela, L., & Carranza-García, F. (2023). An analytical dashboard of collaborative activities for the knowledge building. Technology, Knowledge and Learning, 1-27. https://doi.org/10.1007/s10758-023-09644-y
Holmes, K. (2005). Analysis of asynchronous online discussion using the SOLO Taxonomy. Australian Journal of Educational & Developmental Psychology, 5, 117-127.
Hong, H. Y., & Scardamalia, M. (2014). Community knowledge assessment in a knowledge building environment. Computers & Education, 71. 279-288. https://doi.org/10.1016/j.compedu.2013.09.009
Järvelä, S., Gašević, D., Seppänen, T., Pechenizkiy, M., & Kirschner, P. A. (2020). Bridging learning sciences, machine learning and affective computing for understanding cognition and affect in collaborative learning. British Journal of Educational Technology, 51(6), 2391– 2406. https://doi.org/10.1111/bjet.12917
Järvelä, S., Nguyen, A., Vuorenmaa, E., Malmberg, J., & Järvenoja, H. (2023). Predicting regulatory activities for socially shared regulation to optimize collaborative learning. Computers in Human Behavior, 144, 107737. https://doi.org/10.1016/j.chb.2023.107737
Jiao, Q. G., DaRos-Voseles, D. A., Collins., K. M. T., & Onwuegbuzie, A. J. (2011). Academic procrastination and the performance of graduate-level cooperative groups in research methods courses. Journal of the Scholarship of Teaching and Learning, 11, 119–138.
Johnson, R. B., Onwuegbuzie, A. J., & Turner, L. A. (2007). Toward a definition of mixed methods research. Journal of Mixed Methods Research, 1(2), 112-133. https://doi.org/10.1177/1558689806298224
Khan, S., & Krell, M. (2019). Scientific reasoning competencies: a case of preservice teacher education. Canadian Journal of Science, Mathematics and Technology Education, 19, 446-464. https://doi.org/10.1007/s42330-019-00063-9
Khanlari, A. (2019). Knowledge Building in robotics for math education. Knowledge Building Summer Institute: Knowledge Building Practices and Technology for Global Hubs of Innovation. March 27-20.
Khanlari, A., Zhu, G., & Scardamalia, M. (2019). Knowledge building analytics to explore crossing disciplinary and grade-level boundaries. Journal of Learning Analytics, 60(3), 60-75. https://doi.org/10.18608/jla.2019.63.9
Laferrière, T., & Lamon, M. (2010). Knowledge Building / Knowledge Forum®: The transformation of classroom discourse. In M. S. Khine e I. M. Saleb (Eds.), New Science of Learning: Cognition, Computers and Collaboration in Education (pp. 485-502). Springer. https://doi.org/10.1007/978-1-4419-5716-0_24
Lister, R., Simon, B., Thompson, E., Whalley, J. L., & Prasad, C. (2006). Not seeing the forest for the trees: novice programmers and the SOLO taxonomy. ACM SIGCSE Bulletin, 38(3), 118-122. https://doi.org/10.1145/1140123.1140157
Liu, R., Wang, L., Koszalka, T. A., & Wan, K. (2022). Effects of immersive virtual reality classrooms on students' academic achievement, motivation, and cognitive load in science lessons. Journal of Computer Assisted Learning, 38, 1422-1433. https://doi.org/10.1111/jcal.12688
Ma, J., Zhou, X., Chen, R., & Dong, X. (2019). Does ambidextrous leadership motivate work crafting? International Journal of Hospitality Management, 77, 159-168. https://doi.org/10.1016/j.ijhm.2018.06.025
Ma, L., & Scardamalia, M. (2022). Teachers as designers in knowledge building innovation networks. In M.-C. Shanahan, B. Kim, M. A. Takeuchi, K. Koh, A. P. Preciado-Babb & P. Sengupta (Eds.), The Learning Sciences in Conversation (pp. 107-120). Routledge. https://doi.org/10.4324/9781003089728-13
Madison, A., Michael P., Finelli, C., Graham, M., Borrego, M., & Husman, J. (2022). Explanation and Facilitation Strategies Reduce Student Resistance to Active Learning. College Teaching, 70(4), 530-540. https://doi.org/10.1080/87567555.2021.1987183
McKeown, J., Hmelo-Silver, C. E., Jeong, H., Hartley, K., Faulkner, R., & Emmanuel, N. (2017). A Meta-Synthesis of CSCL Literature in STEM Education. In B. K. Smith, M. Borge, E. Mercier & K. Y. Lim (Eds.), Making a Difference: Prioritizing Equity and Access in CSCL, 12th International Conference on Computer Supported Collaborative Learning (CSCL) 2017, Volume 1. International Society of the Learning Sciences.
McLeod, S. (2019). Constructivism as a theory for teaching and learning. Educational Technology, 40(6), 12-28. https://doi.org/10.47747/ijets.v2i1.586
Murtonen, M. (2015). University students' understanding of the concepts empirical, theoretical, qualitative and quantitative research. Teaching in Higher Education, 20(7), 684-698. https://doi.org/10.1080/13562517.2015.1072152
Murtonen, M., & Salmento, H. (2019). Broadening the theory of scientific thinking for higher education. In M. Murtonen & K. Balloo (Eds.), Redefining scientific thinking for higher education: higher-order thinking, evidence-based reasoning and research skills (pp. 3-29). Palgrave Macmillan. https://doi.org/10.1007/978-3-030-24215-2_1
Nind, M., Michelle Holmes, M., Michela Insenga, M., Sarah Lewthwaite, S., & Cordelia Sutton, C. (2020). Student perspectives on learning research methods in the social sciences. Teaching in Higher Education, 25(7), 797-811. https://doi.org/10.1080/13562517.2019.1592150
Palacios-Ortega, A., Pascual-López, V., & Moreno-Mediavilla, D. (2022). The role of new technologies in STEM education. Bordón. Revista de Pedagogía, 74(4), 11-21. https://doi.org/10.13042/Bordon.2022.96550
Pekrun, R., Cusack, A., Murayama, K., Elliot, A. J., & Thomas, K. (2014). The power of anticipated feed-back: Effects on students’ achievement goals and achievement emotions. Learning and Instruction, 29, 115-124. https://doi.org/10.1016/j.learninstruc.2013.09.002
Popper, K. (1972). Objective Knowledge. An Evolutionary Approach. Oxford U.P.
Puntambekar, S., Gnesdilow, D., Dornfeld Tissenbaum, C., Narayanan, N. H., & Rebello, N. S. (2021). Supporting middle school students’ science talk: a comparison of physical and virtual labs. Journal of Research in Science Teaching, 58(3), 392-419. https://doi.org/10.1002/tea.21664
Radkowitsch, A., Vogel, F., & Fischer, F. (2020). Good for learning, bad for motivation? A meta-analysis on the effects of computer-supported collaboration scripts. International Journal of Computer-Supported Collaborative Learning, 15, 5-47. https://doi.org/10.1007/s11412-020-09316-4
Rannikmäe, M., Holbrook, J., & Soobard, R. (2020). Social constructivism - Jerome Bruner. In B. Akpan & T. J. Kennedy (Eds.), Science education in theory and practice: an introductory guide to learning theory, (pp. 259-275). https://doi.org/10.1007/978-3-030-43620-9_18
Rousseau, R., Zhang, L., & Sivertsen, G. (2023). Using the weighted Lorenz curve to represent balance in collaborations: the BIC indicator. Scientometrics, 128, 609-622. https://doi.org/10.1007/s11192-022-04533-0
Salgado-Orellana, N., Berrocal de-Luna, E., & Gutiérrez-Braojos, C. (2021). A scientometric study of doctoral theses on the Roma in the Iberian Peninsula during the 1977-2018 period. Scientometrics, 126, 437-458. https://doi.org/10.1007/s11192-020-03723-y
Scardamalia, M. (2002). Collective cognitive responsibility for the advancement of knowledge. In B. Smith (Ed.), Liberal Education in a Knowledge Society (pp. 67-98). Open Court.
Scardamalia, M. (2004). CSILE/Knowledge Forum. In A. Kovalchick & K. Dawson (Eds.), Education and technology: An encyclopedia (pp. 183-192). ABC-CLIO.
Scardamalia, M., & Bereiter, C. (1996). Computer support for knowledge-building communities. In T. Koschmann (Ed.), CSCL: Theory and practice of an emerging paradigm (pp. 249-268). Lawrence Erlbaum Associates.
Scardamalia, M., & Bereiter, C. (2021). Knowledge Building: advancing the state of community knowledge. In U. Cress, C. Rosé, A. F. Wise & J. Oshima (Eds.), International handbook of computer-supported collaborative learning. Computer-Supported Collaborative Learning Series, 19. Springer, Cham. https://doi.org/10.1007/978-3-030-65291-3_14
Schnaubert, L., & Vogel, F. (2022). Integrating collaboration scripts, group awareness, and self-regulation in computer-supported collaborative learning. International Journal of Computer-Supported Collaborative Learning, 17, 1-10. https://doi.org/10.1007/s11412-022-09367-9
Schrire, S. (2006). Knowledge building in asynchronous discussion groups: going beyond quantitative analysis. Computers & Education, 46, 49-70. https://doi.org/10.1016/j.compedu.2005.04.006
Slof, B., van Leeuwen, A., Janssen, J., & Kirschner, P. A. (2020). Mine, ours and yours, whose engagement and prior knowledge affects individual achievement from online collaborative learning? Journal Computer Assisted Learning, 37, 39-50. https://doi.org/10.1111/jcal.12466
Soliman, D., Costa, S., & Scardamalia, M. (2021). Knowledge building in online mode: Insights and reflections. Education Sciences, 11(8), 425. https://doi.org/10.3390/educsci11080425
Stahl, G. (2020). Theoretical investigations: philosophical foundations of group cognition. Springer International Publishing. https://doi.org/10.1007/978-3-030-49157-4
Stahl, G., Koschmann, T., & Suthers, D. (2006). Computer-supported collaborative learning: An historical perspective. In R. K. Sawyer (Ed.), Cambridge handbook of the learning sciences (pp. 409-426). Cambridge University Press. https://doi.org/10.1017/CBO9780511816833.025
Stahl, G., & Hakkarainen, K. (2021). Theories of CSCL. In U. Cress, C. Rose, A. F. Wise & J. Oshima (Eds.), International Handbook of Computer Supported Collaborative Learning (pp. 23-43). Springer. https://doi.org/10.1007/978-3-030-65291-3_2
Strauß, S., & Rummel, N. (2021). Promoting regulation of equal participation in online collaboration by combining a group awareness tool and adaptive prompts. But does it even matter? International Journal of Computer-Supported Collaborative Learning, 16(1), 67-104. https://doi.org/10.1007/s11412-021-09340-y
Svendsen, B., & Burner, T. (2023). Gifted Students and Gradeless Formative Assessment: A Case Study from Norway. Journal for the Education of the Gifted, 46(3), 259-275. https://doi.org/10.1177/01623532231180883
Sweller, J., van Merriënboer, J. J., & Paas, F. (2019). Cognitive architecture and instructional design: 20 years later. Educational Psychology Review, 31(2), 261-292. https://doi.org/10.1007/s10648-019-09465-5
Tammeleht, A., Koort, K., Rodríguez-Triana, M. J., & Löfström, E. (2022). Knowledge building process during collaborative research ethics training for researchers: experiences from one university. International Journal of Ethics Education, 7, 147-170. https://doi.org/10.1007/s40889-021-00138-y
Tan, S. C., Chan, C., Bielaczyc, K., Ma, L., Scardamalia, M., & Bereiter, C. (2021). Knowledge building: aligning education with needs for knowledge creation in the digital age. Educational Technology Research and Development, 69, 1-24. https://doi.org/10.1007/s11423-020-09914-x
Tan, S. C., Chen, W., & Chua, B. L. (2023). Leveraging generative artificial intelligence based on large language models for collaborative learning. Learning, Research and Practice, 9(2), 125-134. https://doi.org/10.1080/23735082.2023.2258895
Tarchi, C., Chuy, M., Donoahue, Z., Stephenson, C., Messina, R., & Scardamalia, M. (2013). Knowledge building and knowledge forum: getting started with pedagogy and technology. LEARNing Landscapes, 6(2), 385-407. https://doi.org/10.36510/learnland.v6i2.623
Teo, C. L., & Tan, S. C. (2023). Supporting knowledge building with digital technologies: From computer supported collaborative learning to analytics and artificial intelligence. In S. Y. L. Chye & B. L. Chua (Eds.), Pedagogy and Psychology in Digital Education (pp. 137-157). https://doi.org/10.1007/978-981-99-2107-2_8
Tharayil, S., Borrego, M., Prince, M., Nguyen, K. A., Shekhar, P., Finelli, C. J., & Waters, C. (2018). Strategies to mitigate student resistance to active learning. International Journal of STEM Education, 5, 1-16. https://doi.org/10.1186/s40594-018-0102-y
Tucker, T., Shehab, S., & Mercier, E. (2020). Using the Gini coefficient to characterize the distribution of group problem-solving processes in collaborative tasks. In M. Gresalfi e I. S. Horn (Eds.), 14th International Conference of the Learning Sciences: The Interdisciplinarity of the Learning Sciences, ICLS 2020 - Conference Proceedings (pp. 1761-1762). (Computer-Supported Collaborative Learning Conference, CSCL; Vol. 3). International Society of the Learning Sciences (ISLS). https://doi.org/10.22318/icls2020.1761
Van de Pol, J., Mercer, N., & Volman, M. (2019). Scaffolding student understanding in small-group work: Students’ uptake of teacher support in subsequent small-group interaction. Journal of the Learning Sciences, 28(2), 206-239. https://doi.org/10.1080/10508406.2018.1522258
Vandiver, D. M., & Walsh, J. A. (2010). Assessing autonomous learning in research methods courses: Implementing the student-driven research project. Active Learning in Higher Education, 11(1), 31-42. https://doi.org/10.1177/1469787409355877
Vygotsky, L. S. (1978). Mind in society: Development of higher psychological processes. Harvard University Press.
Yang, Y., Yuan, K., Feng, X., Li, X., & van Aalst, J. (2022). Fostering low‐achieving students' productive disciplinary engagement through knowledge‐building inquiry and reflective assessment. British Journal of Educational Technology, 53(6), 1511-1529. https://doi.org/10.1111/bjet.13267
Yang, Y., Zhu, G., Sun, D., & Chan, C. K. K. (2022). Collaborative analytics-supported reflective assessment for scaffolding pre-service teachers’ collaborative inquiry and knowledge building. International Journal of Computer-Supported Collaborative Learning, 17(2), 249-292. https://doi.org/10.1007/s11412-022-09372-y
Zhang, N., Liu, Q., Zhu, J., Wang, Q., & Xie, K. (2020). Analysis of temporal characteristics of collaborative knowledge construction in teacher workshops. Technology Knowledge and Learning, 25, 323-336. https://doi.org/10.1007/s10758-019-09422-9
Zheng, L., Zhong, L., Niu, J., Long, M., & Zhao, J. (2021). Effects of personalized intervention on collaborative knowledge building, group performance, socially shared metacognitive regulation, and cognitive load in computer-supported collaborative learning. Educational Technology & Society, 24(3), 174-193. https://www.jstor.org/stable/27032864
Zhu, G., & Lin, F. (2023). Teachers scaffold student discourse and emotions in knowledge building classrooms. Interactive Learning Environments, 31, 1-18. https://doi.org/10.1080/10494820.2023.2172046
