An Approach for Assessing Large Online Communities in Informal Learning Environments
Resumo
Online Learning Communities (OLC), supported by social web technologies, have proved to be beneficial for collaborative knowledge building, mainly in informal environments. There is an increasing interest in assessing online Social Learning (SL) in these communities. However, there is no agreement on how their performance can be measured. This paper presents an approach which combines structure and discourse analyses to assess large online communities used in SL. Its objective is to identify conditions and behavioral patterns associated to learning. The results point out a set of quantitative features which shows that participation and ongoing collaboration have a fundamental role for knowledge creation and sharing.Referências
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Bholowalia, P. and Kumar, A. (2014). Ebk-means: A clustering technique based on elbow method and k-means in wsn. Int. J. of Computer App., v. 105, n. 9, p. 79.
Cowan, J. E. and Menchaca, M. P. (2014). Investigating value creation in a community of practice with social network analysis in a hybrid online graduate education program. Distance Education, v. 35, n. 1, p. 43–74.
De Laat, M. and Prinsen, F. (2014). Social Learning Analytics: Navigating the Changing Settings of Higher Education. n. 2014, p. 51–60.
Ferreira, M., Rolim, V., Mello, R. F., et al. (2020). Towards Automatic Content Analysis of Social Presence in Transcripts of Online Discussions. In Proceedings of the 10th International Conference on Learning Analytics and Knowledge.
Garrison, D. R., Anderson, T. and Archer, W. (2010). The first decade of the community of inquiry framework. Internet and Higher Ed., v. 13, n. 1–2, p. 5–9.
Gruzd, A., Paulin, D. and Haythornthwaite, C. (2016). Analyzing Social Media and Learning Through Content and Social Network Analysis: A Faceted Methodological Approach. Journal of Learning Analytics, v. 3, n. 3, p. 46–71.
Hafeez, K., Alghatas, F. M., Foroudi, P., Nguyen, B. and Gupta, S. (2018). Knowledge sharing by entrepreneurs in a virtual community of practice (VCoP). Information Technology and People,
Hartigan, J. A. and Wong, M. A. (1979). Algorithm as 136: A k-means clustering algorithm. Journal of the Royal Statistical Society, v. 28, n. 1, p. 100–108.
Haythornthwaite, C., Kumar, P., Gruzd, A., et al. (2018). Learning in the wild : coding for learning and practice on Reddit. Learning, Media and Technology, v. 9884.
Jan, S. K. (2019). Investigating VCoP with social network analysis: guidelines from a systematic review of research. Int. J. of Web Based Communities, v. 15, n. 1, p. 25.
Joksimovic, S., Gasevic, D., Kovanovic, V., Riecke, B. E. and Hatala, M. (2015). Social presence in online discussions as a process predictor of academic performance. Journal of Computer Assisted Learning, v. 31, n. 6, p. 638–654.
Nistor, N., Derntl, M. and Klamma, R. (2015). Learning Analytics : Trends and Issues of the Empirical Research of the Years 2011 – 2014. Design for Teaching and Learning in a Networked World, v. 4, p. 453–459.
Palazuelos, C., García-Saiz, D. and Zorrilla, M. (2013). Social network analysis and data mining: An application to the E-learning context. Lecture Notes in Computer Science, v. 8083 LNAI, p. 651–660.
Pennebaker, J. W., Boyd, R. L., Jordan, K. and Blackburn, K. (2015). The development and psychometric properties of LIWC2015.
Wenger, E., Trayner, B. and De Laat, M. (2011). Promoting and assessing value creation in communities and networks: a conceptual framework. v. 18
Weninger, T. (2014). An exploration of submissions and discussions in social news: Mining collective intelligence of Reddit. Social Network Analysis and Mining, v. 4, n. 1, p. 173–192.
Publicado
24/11/2020
Como Citar
SILVA, Rogério Ferreira da; GIMENES, Itana Maria de Souza; MALDONADO, José Carlos.
An Approach for Assessing Large Online Communities in Informal Learning Environments. In: SIMPÓSIO BRASILEIRO DE INFORMÁTICA NA EDUCAÇÃO (SBIE), 31. , 2020, Online.
Anais [...].
Porto Alegre: Sociedade Brasileira de Computação,
2020
.
p. 642-651.
DOI: https://doi.org/10.5753/cbie.sbie.2020.642.
