Implications of Message Length and Delay in Undergraduate Online Discussions

  1. Inmaculada López-Francés 1
  2. Fran J. Garcia-Garcia 1
  3. Bernardo Gargallo López 1
  4. Cristian Molla-Esparza 2
  1. 1 University of Valencia, España
  2. 2 International University of La Rioja (Spain), España
Revista:
RIED: revista iberoamericana de educación a distancia

ISSN: 1138-2783

Any de publicació: 2022

Volum: 25

Número: 2

Pàgines: 259-276

Tipus: Article

Altres publicacions en: RIED: revista iberoamericana de educación a distancia

Resum

This study aimed at verifying the association of message length and delay in university online discussions with academic achievement and students’ influence on their classmates. Forums in Moodle were designed, and asynchronous online discussions with first-year undergraduate students of Educational Sciences were conducted. We gained word count from the learning management system, the weekly delay in posting a message to the forum was regarded, and we assumed the students’ grades to know their academic success. To obtain an indicator of influence, we conducted a social network analysis from the interactions that emerged from the online discussions. Then, we calculated the eigenvector centrality of each student once the debate had been completed. Results showed a low monotonic association between grades and the message words or the delay in posting. There was a slight trend to achieve more eigenvector centrality since students took more time to send a message and when messages were more synthetic. However, we did not obtain values in the coefficients that would allow us to infer a relevant association. The level of correlation detected for the grades was significant and, above all, regarding eigenvector centrality. We discussed the limitations of this study, the need for more research, and the implications for educational practice.

Referències bibliogràfiques

  • 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. 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