Implicações das palavras e do timing das mensagens nas discussões em linha com estudantes de graduação
DOI:
https://doi.org/10.5944/ried.25.2.32810Palavras-chave:
discussão, aprendizagem social, uso didáctico do computador, tecnologia educativa, análise de redes, universidadeResumo
O objectivo deste estudo era testar a relação entre a extensão e o atraso das mensagens nas discussões em linha com a influência estudante-estudante e o desempenho académico na universidade. Foram concebidos fóruns no Moodle e foram realizadas discussões assíncronas em linha com estudantes do primeiro ano de Ciências da Educação. Obtivemos contagens de palavras do sistema de gestão de aprendizagem, considerámos o atraso semanal para a publicação de mensagens no fórum e tirámos as notas dos estudantes pelo seu sucesso académico. Para obter um indicador de influência, realizámos uma análise da rede social a partir das interacções nas discussões. Calculámos então a centralidade eigenvectorial para cada estudante após o debate ter terminado. Os resultados mostraram uma baixa correlação monotónica entre as notas e o comprimento dos mensagens ou o atraso no envio. Havia uma ligeira tendência para alcançar mais centralidade eigenvector quanto mais tempo levava afixar uma mensagem e quando as mensagens eram mais sintéticas. No entanto, não havia valores de coeficiente para inferir uma associação substantiva. O nível de correlação detectado para as classificações foi significativo, especialmente para a centralidade eigenvector. Discutimos as limitações do estudo, a necessidade de mais investigação e as implicações para a prática educacional.
Downloads
Referências
Abe, J. A. A. (2020). Big five, linguistic styles, and successful online learning. The Internet and Higher Education, 45, 1-9. https://doi.org/10.1016/j.iheduc.2019.100724
Abu Talib, M., Bettayeb, A. M., & Omer, R. I. (2021). Analytical study on the impact of technology in higher education during the age of COVID-19: Systematic literature review. Education and Information Technologies, 26, 6719–6746. https://doi.org/10.1007/s10639-021-10507-1
Ahuja, R., Khan, D., Symonette, D., Pan, S., Stacey, S., & Engel, D. (2020). Towards the Automatic Assessment of Student Teamwork. Companion of the 2020 ACM International Conference on Supporting Group Work, 143-146. https://doi.org/10.1145/3323994.3369894
Al-Dheleai, Y. M., Tasir, Z., & Jumaat, N. F. (2020). Depicting Students’ Social Presence on Social Networking Site in Course-Related Interaction. SAGE Open, 10(1), 1-8. https://doi.org/10.1177/2158244019899094
Almatrafi, O., & Johri, A. (2019). Systematic Review of Discussion Forums in Massive Open Online Courses (MOOCs). IEEE Transactions on Learning Technologies, 12(3), 413-428. https://doi.org/10.1109/TLT.2018.2859304
Amastini, F., Sari Kaunang, C. P., Nefiratika, A., Sensuse, D. I., & Lusa, S. (2020). Collaborative Learning in Virtual Learning Environment using Social Network Analysis: Case study Universitas Terbuka. In Institute of Advanced Engineering and Science (Ed.), 2020 7th International Conference on Electrical Engineering, Computer Sciences and Informatics (EECSI) (pp. 262-269). IEEE. https://doi.org/10.23919/EECSI50503.2020.9251904
Andresen, M. A. (2009). Asynchronous discussion forums: success factors, outcomes, assessments, and limitations. Journal of Educational Technology & Society, 12(1), 249-257. https://www.jstor.org/stable/jeductechsoci.12.1.249
Assunção, H., Lin, S. W., Sit, P. S., Cheung, K. C., Harju-Luukkainen, H., Smith, T., Maloa, B., Álvares Duarte Bonini Campos, J., Ilic, I. S., Esposito, G., Francesca, F. M., & Marôco, J. (2020). University Student Engagement Inventory (USEI): Transcultural Validity Evidence Across Four Continents. Frontiers in Psychology, 10, 1-12. https://doi.org/10.3389/fpsyg.2019.02796
Ausubel, D. P., Novak, J. D., & Hanesian, H. (1968). Educational psychology: a cognitive view. Holt, Rinehart and Winston.
Bandura, A. (1986). Social Foundations of Thought and Action: A Social Cognitive Theory. Prentice-Hall, Inc.
Block, P., Hoffman, M., Raabe, I. J., Dowd, J. B., Rahal, C., Kashyap, R., & Mills, M. C. (2020). Social network-based distancing strategies to flatten the COVID-19 curve in a post-lockdown world. Nature Human Behaviour, 4(6), 588-596. https://doi.org/10.1038/s41562-020-0898-6
Bonacich, P. (1972). Factoring and weighting approaches to status scores and clique identification. The Journal of Mathematical Sociology, 2(1), 113-120. https://doi.org/10.1080/0022250X.1972.9989806
Bond, M., Buntins, K., Bedenlier, S., Zawacki-Richter, O., & Kerres, M. (2020). Mapping research in student engagement and educational technology in higher education: a systematic evidence map. International Journal of Educational Technology in Higher Education, 17, 1-30. https://doi.org/10.1186/s41239-019-0176-8
Bouchard, M. (2020). Collaboration and Boundaries in Organized Crime: A Network Perspective. Crime and Justice, 49, 425-469. https://doi.org/10.1086/708435
Brooks, C. F., & Bippus, A. M. (2012). Underscoring the Social Nature of Classrooms by Examining the Amount of Virtual Talk across Online and Blended College Courses. European Journal of Open, Distance and E-Learning2, 1, 1-8. https://eric.ed.gov/?id=EJ979602
Burcher, M., & Whelan, C. (2018). Social network analysis as a tool for criminal intelligence: understanding its potential from the perspectives of intelligence analysts. Trends in Organized Crime, 21(3), 278-294. https://doi.org/10.1007/s12117-017-9313-8
Campbell, M., Gibson, W., Hall, A., Richards, D., & Callery, P. (2008). Online vs. face-to-face discussion in a web-based research methods course for postgraduate nursing students: A quasi-experimental study. International Journal of Nursing Studies, 45(5), 750-759. https://doi.org/10.1016/j.ijnurstu.2006.12.011
Chávez, J., Montaño, R., & Barrera, R. (2016). Structure and content of messages in an online environment: An approach from participation. Computers in Human Behavior, 54, 560-568. https://doi.org/10.1016/j.chb.2015.08.046
Chen, N.-S., Kinshuk, Wei, C.-W., & Liu, C.-C. (2011). Effects of matching teaching strategy to thinking style on learner’s quality of reflection in an online learning environment. Computers & Education, 56(1), 53-64. https://doi.org/10.1016/j.compedu.2010.08.021
Chen, Z., Jiao, J., & Hu, K. (2021). Formative Assessment as an Online Instruction Intervention. International Journal of Distance Education Technologies, 19(1), 50-65. https://doi.org/10.4018/IJDET.20210101.oa1
Choi, H. J., & Johnson, S. D. (2005). The Effect of Context-Based Video Instruction on Learning and Motivation in Online Courses. American Journal of Distance Education, 19(4), 215-227. https://doi.org/10.1207/s15389286ajde1904_3
da Silva, L. F. C., Barbosa, M. W., & Gomes, R. R. (2019). Measuring Participation in Distance Education Online Discussion Forums Using Social Network Analysis. Journal of the Association for Information Science and Technology, 70(2), 140-150. https://doi.org/10.1002/asi.24080
Diestel, R. (2017). Graph Theory (5th ed.). Springer. https://doi.org/10.1007/978-3-662-53622-3
Dommett, E. J. (2019). Understanding student use of twitter and online forums in higher education. Education and Information Technologies, 24(1), 325-343. https://doi.org/10.1007/s10639-018-9776-5
Fehrman, S., & Watson, S. L. (2020). A Systematic Review of Asynchronous Online Discussions in Online Higher Education. American Journal of Distance Education, 1-14. https://doi.org/10.1080/08923647.2020.1858705
Gao, F., Zhang, T., & Franklin, T. (2013). Designing asynchronous online discussion environments: Recent progress and possible future directions. British Journal of Educational Technology, 44(3), 469-483. https://doi.org/10.1111/j.1467-8535.2012.01330.x
García-Álvarez, M. T., Novo-Corti, I., & Varela-Candamio, L. (2018). The effects of social networks on the assessment of virtual learning environments: A study for social sciences degrees. Telematics and Informatics, 35(4), 1005-1017. https://doi.org/10.1016/j.tele.2017.09.013
Garcia-Garcia, F. J., Moctezuma-Ramírez, E., Molla-Esparza, C., & López-Francés, I. (2021). Strategies based on social network analysis for enhancing the learning climate at universities. Research in Education and Learning Innovation Archives, 27, 33-46. https://doi.org/10.7203/realia.27.18960
Greco, P., & Piaget, J. (1959). Apprentissage et connaissance. P.U.F.
Habermass, J. (1984). Theory of Communicative Action. Volume One: Reason and the Rationalization of Society. Beacon Press.
Hammond, M. (2019). A Review of Recent Papers on Online Discussion in Teaching and Learning in Higher Education. Journal of Asynchronous Learning Networks, 9(3), 9-23. https://doi.org/10.24059/olj.v9i3.1782
He, X., & Meghanathan, N. (2016). Correlation of Eigenvector Centrality to Other Centrality Measures: Random, Small-World and Real-World Networks. Proceedings of the 8th International Conference on Networks and Communications (NeCoM), 9-18. https://doi.org/10.5121/csit.2016.61202
Hew, K. F., & Cheung, W. S. (2008). Attracting student participation in asynchronous online discussions: A case study of peer facilitation. Computers and Education, 51(3), 1111-1124. https://doi.org/10.1016/j.compedu.2007.11.002
Hülsmann, T., & Shabalala, L. (2016). Workload and interaction: Unisa’s signature courses – a design template for transitioning to online DE? Distance Education, 37(2), 224-236. https://doi.org/10.1080/01587919.2016.1191408
Jan, S. K., & Vlachopoulos, P. (2019). Social Network Analysis: A Framework for Identifying Communities in Higher Education Online Learning. Technology, Knowledge and Learning, 24(4), 621-639. https://doi.org/10.1007/s10758-018-9375-y
Jeong, A., & Chiu, M. M. (2020). Production blocking in brainstorming arguments in online group debates and asynchronous threaded discussions. Educational Technology Research and Development, 68, 3097-3114. https://doi.org/10.1007/s11423-020-09845-7
Jivet, I., Scheffel, M., Schmitz, M., Robbers, S., Specht, M., & Drachsler, H. (2020). From students with love: An empirical study on learner goals, self-regulated learning and sense-making of learning analytics in higher education. The Internet and Higher Education, 47. https://doi.org/10.1016/j.iheduc.2020.100758
Junus, K., Suhartanto, H., R-Suradujono, B. S. H., Santoso, H. B., & Sadita, L. (2019). The Community of Inquiry Model Training Using the Cognitive Apprenticeship Approach to Improve Students’ Learning Strategy in the Asynchronous Discussion Forum. The Journal of Educators Online, 16(1), 1-17. https://doi.org/10.9743/jeo.2019.16.1.7
Lahuerta-Otero, E., Cordero-Gutiérrez, R., & Izquierdo-Álvarez, V. (2019). Using Social Media to Enhance Learning and Motivate Students in the Higher Education Classroom. In L. Uden, D. Liberona, G. Sanchez, & S. Rodríguez-González (Eds.), Communications in Computer and Information Science (pp. 351-361). Springer. https://doi.org/10.1007/978-3-030-20798-4_30
Law, J., Barny, D., & Poulin, R. (2020). Patterns of peer interaction in multimodal L2 digital social reading. Language Learning and Technology, 24(2), 70-85. https://doi.org/10125/44726
Lee, D., Rothstein, R., Dunford, A., Berger, E., Rhoads, J. F., & DeBoer, J. (2021). “Connecting online”: The structure and content of students’ asynchronous online networks in a blended engineering class. Computers & Education, 163, 1-18. https://doi.org/10.1016/j.compedu.2020.104082
Lin, Y., Yu, R., & Dowell, N. (2020). LIWCs the Same, Not the Same: Gendered Linguistic Signals of Performance and Experience in Online STEM Courses. In I. I. Bittencourt, M. Cukurova, K. Muldner, R. Luckin, & E. Millán (Eds.), Artificial Intelligence in Education. 21st International Conference, AIED 2020, Ifrane, Morocco, July 6-10, 2020, Proceedings, Part I (pp. 333-345). Springer. https://doi.org/10.1007/978-3-030-52237-7_27
Maguire, R., Egan, A., Hyland, P., & Maguire, P. (2017). Engaging students emotionally: the role of emotional intelligence in predicting cognitive and affective engagement in higher education. Higher Education Research and Development, 36(2), 343-357. https://doi.org/10.1080/07294360.2016.1185396
Mazzolini, M., & Maddison, S. (2007). When to jump in: The role of the instructor in online discussion forums. Computers and Education, 49(2), 193-213. https://doi.org/10.1016/j.compedu.2005.06.011
Müller, F. A., & Wulf, T. (2020). Technology-supported management education: a systematic review of antecedents of learning effectiveness. International Journal of Educational Technology in Higher Education, 17, 1-33. https://doi.org/10.1186/s41239-020-00226-x
Negre, C. F. A., Morzan, U. N., Hendrickson, H. P., Pal, R., Lisi, G. P., Loria, J. P., Rivalta, I., Ho, J., & Batista, V. S. (2018). Eigenvector centrality for characterization of protein allosteric pathways. Proceedings of the National Academy of Sciences, 115(52), E12201-E12208. https://doi.org/10.1073/pnas.1810452115
Newman, M. E. J. (2010). Networks: An Introduction. Oxford University Press. https://doi.org/10.1093/acprof:oso/9780199206650.001.0001
Onyema, E. M., Deborah, E. C., Alsayed, A. O., Noorulhasan, Q., & Sanober, S. (2019). Online Discussion Forum as a Tool for Interactive Learning and Communication. International Journal of Recent Technology and Engineering, 8(4), 4852-4859. https://doi.org/10.35940/ijrte.D8062.118419
Pulford, B. D. (2011). The influence of advice in a virtual learning environment. British Journal of Educational Technology, 42(1), 31-39. https://doi.org/10.1111/j.1467-8535.2009.00995.x
Saadatdoost, R., Sim, A. T. H., Jafarkarimi, H., & Mei Hee, J. (2015). Exploring MOOC from education and Information Systems perspectives: a short literature review. Educational Review, 67(4), 505-518. https://doi.org/10.1080/00131911.2015.1058748
Sachdeva, C., & Gilbert, S. J. (2020). Excessive use of reminders: Metacognition and effort-minimisation in cognitive offloading. Consciousness and Cognition, 85, 1-14. https://doi.org/10.1016/j.concog.2020.103024
Sanganyado, E., & Nkomo, S. (2018). Incorporating Sustainability into Engineering and Chemical Education Using E-Learning. Education Sciences, 8(2), 1-11. https://doi.org/10.3390/educsci8020039
Saqr, M., Viberg, O., & Vartiainen, H. (2020). Capturing the participation and social dimensions of computer-supported collaborative learning through social network analysis: which method and measures matter? International Journal of Computer-Supported Collaborative Learning, 15(2), 227-248. https://doi.org/10.1007/s11412-020-09322-6
Schmitz, B., & Hanke, K. (2021). Engage me: Learners’ expectancies and teachers’ efforts in designing effective online classes. Journal of Computer Assisted Learning. https://doi.org/10.1111/jcal.12636
Sellke, T., Bayarri, M. J., & Berger, J. O. (2001). Calibration of ρ Values for Testing Precise Null Hypotheses. The American Statistician, 55(1), 62-71. https://doi.org/10.1198/000313001300339950
Silk, M. J., Croft, D. P., Delahay, R. J., Hodgson, D. J., Boots, M., Weber, N., & McDonald, R. A. (2017). Using Social Network Measures in Wildlife Disease Ecology, Epidemiology, and Management. BioScience, 67(3), 245-257. https://doi.org/10.1093/biosci/biw175
Smet, M. De, Keer, H. Van, Wever, B. De, & Valcke, M. (2010). Cross-age peer tutors in asynchronous discussion groups: Exploring the impact of three types of tutor training on patterns in tutor support and on tutor characteristics. Computers & Education, 54(4), 1167-1181. https://doi.org/10.1016/j.compedu.2009.11.002
Stephens, G. C., Rees, C. E., & Lazarus, M. D. (2019). How does Donor Dissection Influence Medical Students’ Perceptions of Ethics? A Cross-Sectional and Longitudinal Qualitative Study. Anatomical Sciences Education, 12(4), 332–348. https://doi.org/10.1002/ase.1877
Sun, J., & Tang, J. (2011). A Survey of Models and Algorithms for Social Influence Analysis. In C. C. Aggarwal (Ed.), Social Network Data Analytics (pp. 177-214). Springer. https://doi.org/10.1007/978-1-4419-8462-3_7
Thomas, J. (2013). Exploring the use of asynchronous online discussion in health care education: A literature review. Computers and Education, 69, 199-215. https://doi.org/10.1016/j.compedu.2013.07.005
Tirado Morueta, R., Maraver López, P., Hernando Gómez, Á., & Harris, V. W. (2016). Exploring social and cognitive presences in communities of inquiry to perform higher cognitive tasks. The Internet and Higher Education, 31, 122-131. https://doi.org/10.1016/j.iheduc.2016.07.004
Valente, T. W., Coronges, K., Lakon, C., & Costenbader, E. (2008). How Correlated Are Network Centrality Measures? Connections (Toronto, Ont.), 28(1), 16-26. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2875682/
Vázquez-Cano, E., Meneses, E. L., & Sánchez-Serrano, J. L. S. (2015). Analysis of social worker and educator’s areas of intervention through multimedia concept maps and online discussion forums in higher education. Electronic Journal of E-Learning, 13(5), 333-346. https://academic-publishing.org/index.php/ejel/article/view/1936
Vovk, V. G. (1993). A Logic of Probability, with Application to the Foundations of Statistics. Journal of the Royal Statistical Society: Series B (Methodological), 55(2), 317-341. https://doi.org/10.1111/j.2517-6161.1993.tb01904.x
Vygotsky, L. S. (1978). Mind in Society. The Development of Higher Psychological Processes. Harvard University Press. https://doi.org/10.2307/j.ctvjf9vz4
Wang, P. Y., & Yang, H. C. (2012). Using collaborative filtering to support college students’ use of online forum for English learning. Computers and Education, 59(2), 628-637. https://doi.org/10.1016/j.compedu.2012.02.007
Yapici, İ. Ü., & Akbayin, H. (2012). The Effect of Blended Learning Model on High School Students’ Biology Achievement and on their Attitudes towards the Internet. The Turkish Online Journal of Educational Technology, 11(2), 228-237. http://www.tojet.net/articles/v11i2/11224.pdf
Yoo, J., & Kim, J. (2012). Predicting Learner’s Project Performance with Dialogue Features in Online Q&A Discussions. In S. A. Cerri, W. J. Clancey, G. Papadourakis, & K. Panourgia (Eds.), Intelligence Tutoring Systems. 11th International Conference, ITS 2012 Chania, Crete, Greece, June 14-18, 2012 Proceedings. Springer. https://doi.org/10.1007/978-3-642-30950-2_74
Yoo, J., & Kim, J. (2014). Can Online Discussion Participation Predict Group Project Performance? Investigating the Roles of Linguistic Features and Participation Patterns. International Journal of Artificial Intelligence in Education, 24(1), 8-32. https://doi.org/10.1007/s40593-013-0010-8
Zou, W., Hu, X., Pan, Z., Li, C., Cai, Y., & Liu, M. (2021). Exploring the relationship between social presence and learners’ prestige in MOOC discussion forums using automated content analysis and social network analysis. Computers in Human Behavior, 115, 1-17. https://doi.org/10.1016/j.chb.2020.106582
Publicado
Como Citar
Edição
Secção
Licença
Direitos de Autor (c) 2022 Inmaculada López-Francés, Fran J. Garcia-Garcia, Bernardo Gargallo López, Cristian Molla-Esparza
Este trabalho encontra-se publicado com a Licença Internacional Creative Commons Atribuição 4.0.
As obras que são publicadas neste revista estão sujeitas ao seguintes termos:
1. Os autores cedem de forma não exclusiva os direitos de exploração dos trabalhos aceitos para sua publicação a "RIED. Revista Iberoamericana de Educação a Distância", garantem à revista o direito de ser a primeira publicação do trabalho e permitem que a revista distribua os trabalhos publicados sob a licença de indicada no ponto 2.
2. As obras são publicadas na edição eletrônica da revista sob uma licença Creative Commons Atribuição 4.0 Internacional (CC BY 4.0). Podem copiar e redistribuir o material em qualquer suporte ou formato, adaptar, remixar, transformar, e criar a partir do material para qualquer fim, mesmo que comercial. Você deve atribuir o devido crédito, fornecer um link para a licença, e indicar se foram feitas alterações. Você pode fazê-lo de qualquer forma razoável, mas não de uma forma que sugira que o licenciante o apoia ou aprova o seu uso.
3. Condições de auto-arquivo. Permite-se e incentava-se aos autores difundir eletronicamente a versõ OnlineFirst (versão avaliada e aceita para publicação) de su obra antes de sua publicação, sempre com referência a sua publicação na RIED, já que favorece sua circulação e difusão mais cedo e com isso um possível aumento em sua citação e alcance entre a comunidade acadêmica. Color RoMEO: verde.
