Looking for the “More Knowledgeable Other” through Learning Analytics


Δημοσιευμένα: Φεβ 10, 2020
Ροδάνθη Τσώνη
Βασίλειος Βερύκιος
Περίληψη

Long-tested pedagogical theories can provide the basis to analyze and interpret students’ interactions in distance learning environments. Through this lens, useful conclusions can be drawn from students’ data that could help to improve the teaching and learning process. In this paper, a number of forum posts were analyzed and the role of tutors and students was scrutinized through the use of network visualization. It was found that certain students have a central positive role in the discussion forum although tutors have the main burden of answering and keeping the interaction alive. These students can act as the more knowledgeable other and support their peers. Further research in order to gain insight into students’ interaction and promote collaboration, is proposed.

Λεπτομέρειες άρθρου
  • Ενότητα
  • Άρθρα
Βιογραφικά Συγγραφέων
Ροδάνθη Τσώνη, Ελληνικό Ανοικτό Πανεπιστήμιο

Υποψήφια διδάκτορας

Σχολή Θετικών Επιστημών και Τεχνολογίας

Βασίλειος Βερύκιος, Ελληνικό Ανοικτό Πανεπιστήμιο

Καθηγητής

Σχολή Θετικών Επιστημών και Τεχνολογίας

Αναφορές
Bliss J., Cooper G., Κολιόπουλος Δ., Κουλαϊδής Β., Ραβάνης Κ., Solomon J., Τσατσαρώνη Α., Χατζηνικήτα Β., Χρηστίδου Β. (2001). Διδακτική των Φυσικών Επιστημών. Τόμος Α'. Πάτρα: ΕΑΠ
Cela, K. L., Sicilia, M. Á., & Sánchez, S. (2015). Social network analysis in e-learning environments: A preliminary systematic review. Educational Psychology Review, 27(1), 219-246.
Chiru, C. G., Rebedea, T., & Erbaru, A. (2014). Using PageRank for Detecting the Attraction between Participants and Topics in a Conversation. In WEBIST (1) (pp. 294-301).
Chiu, T. K., & Hew, T. K. (2018). Factors influencing peer learning and performance in MOOC asynchronous online discussion forum. Australasian Journal of Educational Technology, 34(4).
Crossley, S., Dascalu, M., McNamara, D. S., Baker, R., & Trausan-Matu, S. (2017). Predicting success in massive open online courses (MOOCs) using cohesion network analysis. Philadelphia, PA: International Society of the Learning Sciences.
Cui, W., Xue, Z., & Thai, K. P. (2019). Performance comparison of an AI-based Adaptive Learning System in China. In 2018 Chinese Automation Congress (CAC) (pp. 3170-3175). IEEE.
Ferguson, R., & Shum, S. B. (2012). Social learning analytics: five approaches. In Proceedings of the 2nd international conference on learning analytics and knowledge (pp. 23-33). ACM.
Fincham, E., Gaševic, D., & Pardo, A. (2018). From Social Ties to Network Processes: Do Tie Definitions Matter? Journal of Learning Analytics, 5(2), 9-28.
Gkontzis, A. F., Karachristos, C. V., Lazarinis, F., Stavropoulos, E. C., & Verykios, V. S. (2017a). Assessing Student Performance by Learning Analytics Dashboards. 9th International Conference in Open and Distance Learning, 9(1A), 101-115.
Gkontzis, A. F., Karachristos, C. V., Panagiotakopoulos, C. T., Stavropoulos, E. C., & Verykios, V. S. (2017b). Sentiment Analysis to Track Emotion and Polarity in Student Fora. In Proceedings of the 21st Pan-Hellenic Conference on Informatics (p. 39). ACM.
Hernández-García, Á., González-González, I., Jiménez-Zarco, A. I., & Chaparro-Peláez, J. (2016). Visualizations of online course interactions for social network learning analytics. International Journal of Emerging Technologies in Learning (iJET), 11(07), 6-15.
Jagadish, D. (2014). Grouping in collaborative e-learning environment based on interaction among students. In 2014 International Conference on Recent Trends in Information Technology (pp. 1-5). IEEE.
Joksimovic, S., Jovanovic, J. M., Kovanovic, V., Gasevic, D., Milikic, N. M., Zouaq, A., & van Staalduinen, J. P. (2019). Comprehensive analysis of discussion forum participation: from speech acts to discussion dynamics and course outcomes. IEEE Transactions on Learning Technologies.
Kop, R., & Hill, A. (2008). Connectivism: Learning theory of the future or vestige of the past?. The International Review of Research in Open and Distributed Learning, 9(3).
Kyritsi, K. H., Zorkadis, V., Stavropoulos, E. C., & Verykios, V. S. (2018). Privacy Issues in Learning Analytics. Blended and Online Learning, 218.
Nouri, J., Ebner, M., Ifenthaler, D., Saqr, M., Malmberg, J., Khalil, M., ... & Berthelsen, U. D. (2019). Efforts in Europe for Data-Driven Improvement of Education–A Review of Learning Analytics Research in Six Countries. International Journal of Learning Analytics and Artificial Intelligence for Education, 1(1), 8-27.
Schaffer, J., Huynh, B., O'Donovan, J., Höllerer, T., Xia, Y., & Lin, S. (2016). An analysis of student behavior in two massive open online courses. In Proceedings of the 2016 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (pp. 380-385). IEEE Press.
Shunk, H. D. (2010). Θεωρίες Μάθησης. Μια εκπαιδευτική προσέγγιση. Αθήνα: Μεταίχμιο
Sun, B., Wang, M., & Guo, W. (2018). The influence of grouping/non-grouping strategies upon student interaction in online forum: A social network analysis. In 2018 International Symposium on Educational Technology (ISET) (pp. 173-177). IEEE.
Sundararajan, B. (2010). Emergence of the most knowledgeable other (mko): Social network analysis of chat and bulletin board conversations in a CSCL system. Electronic Journal of e-Learning, 8(2), 191-208.
Sweet, M., & Michaelsen, L. K. (2007). How group dynamics research can inform the theory and practice of postsecondary small group learning. Educational Psychology Review, 19(1), 31-47.
Tan, J. P. L., & Koh, E. (2017). Situating learning analytics pedagogically: Towards an ecological lens.
Traxler, A., Gavrin, A., & Lindell, R. (2018). Networks identify productive forum discussions. Physical Review Physics Education Research, 14(2), 020107
Tsoni R., Samaras C., Paxinou E., Panagiotakopoulos C., andVerykios, V.S. (2019). From Analytics to Cognition: Expanding the Reach of Data in Learning. In Proc. of CSEDU 2019
Tsoni, R., Stavropoulos, E. C., & Verykios, V. S. (2019). Leveraging Learning Analytics with the Power of Words. The Envisioning Report for Empowering Universities, 24.
Tudge, J. R. H. & Scrimsher, S. (2003). “Lev Vygotsky on education. A cultural, historical, interpersonal and individual approach to development”. Στο
Zimmerman, B. J. & Shunk, D. H. (επιμ.). Educational Psychology: A Century of Contributions. Manwah, NJ: Erlbaum
Vu, D., Pattison, P., & Robins, G. (2015). Relational event models for social learning in MOOCs. Social Networks, 43, 121-135.
Vygotsky, L. S. (1978). Mind in society: The development of higher
psychological processes. Cambridge, MA: Harvard University Press.
Wilson, T., Wiebe, J., & Hoffmann, P. (2005). Recognizing contextual polarity in phrase-level sentiment analysis. In Proceedings of Human Language Technology Conference and Conference on Empirical Methods in Natural Language Processing.