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22-07-2019 | Long Paper

Using multimodal learning analytics to study collaboration on discussion groups

A social network approach

Authors: Fabian Riquelme, Roberto Munoz, Roberto Mac Lean, Rodolfo Villarroel, Thiago S. Barcelos, Victor Hugo C. de Albuquerque

Published in: Universal Access in the Information Society | Issue 3/2019

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Abstract

Nowadays, companies and organizations require highly competitive professionals that have the necessary skills to confront new challenges. However, current evaluation techniques do not allow detection of skills that are valuable in the work environment, such as collaboration, teamwork, and effective communication. Multimodal learning analytics is a prominent discipline related to the analysis of several modalities of natural communication (e.g., speech, writing, gestures, sight) during educational processes. The main aim of this work is to develop a computational environment to both analyze and visualize student discussion groups working in a collaborative way to accomplish a task. ReSpeaker devices were used to collect speech data from students, and the collected data were modeled by using influence graphs. Three centrality measures were defined, namely permanence, persistence, and prompting, to measure the activity of each student and the influence exerted between them. As a proof of concept, we carried out a case study made up of 11 groups of undergraduate students that had to solve an engineering problem with everyday materials. Thus, we show that our system allows to find and visualize nontrivial information regarding interrelations between subjects in collaborative working groups; moreover, this information can help to support complex decision-making processes.

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Airasian, P., Gallagher, T., Engemann, J.: Classroom Assessment: Concepts and Applications. McGraw-Hill, New York (2006)

Akareem, H.S., Hossain, S.S.: Determinants of education quality: What makes students’ perception different? Open Rev. Educ. Res. 3(1), 52–67 (2016). https://doi.org/10.1080/23265507.2016.1155167 CrossRef

Andrade, A., Delandshere, G., Danish, J.A.: Using multimodal learning analytics to model student behavior: a systematic analysis of epistemological framing. J. Learn. Anal. 3(2), 282–306 (2016). https://doi.org/10.18608/jla.2016.32.14 CrossRef

Bellon, J.J., Bellon, E.C., Blank, M.A.: Teaching from a Research Knowledge Base: A Development and Renewal Process. Merrill, New York (1992)CrossRef

Blikstein, P.: Multimodal learning analytics. In: Suthers, D., Verbert, K. (eds.) Third Conference on Learning Analytics and Knowledge, LAK ’13, Leuven, Belgium, April 8–12, 2013, pp. 102–106. ACM (2013). https://doi.org/10.1145/2460296.2460316

Blikstein, P., Worsley, M.: Multimodal learning analytics and education data mining: using computational technologies to measure complex learning tasks. J. Learn. Anal. 3(2), 220–238 (2016). https://doi.org/10.18608/jla.2016.32.11 CrossRef

Chen, L., Feng, G., Leong, C.W., Joe, J., Kitchen, C., Lee, C.M.: Designing an automated assessment of public speaking skills using multimodal cues. J. Learn. Anal. 3(2), 261–281 (2016). https://doi.org/10.18608/jla.2016.32.13 CrossRef

Cukurova, M., Luckin, R., Mavrikis, M., Millán, E.: Machine and human observable differences in groups’ collaborative problem-solving behaviours. In: Lavoué, É., Drachsler, H., Verbert, K., Broisin, J., Pérez-Sanagustín, M. (eds.) Data Driven Approaches in Digital Education—12th European Conference on Technology Enhanced Learning, EC-TEL 2017, Tallinn, Estonia, September 12–15, 2017, Proceedings, Lecture Notes in Computer Science, vol. 10474, pp. 17–29. Springer, (2017). https://doi.org/10.1007/978-3-319-66610-5_2

Dillenbourg, P.: What Do You Mean by Collaborative Learning?. Elsevier, Oxford (1999)

10.

Elrehail, H., Emeagwali, O.L., Alsaad, A., Alzghoul, A.: The impact of transformational and authentic leadership on innovation in higher education: the contingent role of knowledge sharing. Telemat. Inform. 35(1), 55–67 (2018). https://doi.org/10.1016/j.tele.2017.09.018 CrossRef

11.

Freeman, L.: Centrality in social networks: conceptual clarification. Soc. Netw. 1(3), 215–239 (1979). https://doi.org/10.1016/0378-8733(78)90021-7 CrossRef

12.

Gardner, H., Gardner, H.: The disciplined mind: Beyond facts and standardized tests, the K-12 education that every child deserves. Penguin books, New York (2000)

13.

Greller, W., Drachsler, H.: Translating learning into numbers: a generic framework for learning analytics. Educ. Technol. Soc. 15(3), 42–57 (2012)

14.

Joyce, B.R.: Student Achievement Through Staff Development, 3rd edn. Association for Supervision & Curriculum Development (2002)

15.

Klein, A., Ahlf, H., Sharma, V.: Social activity and structural centrality in online social networks. Telemat. Inform. 32(2), 321–332 (2015). https://doi.org/10.1016/j.tele.2014.09.008 CrossRef

16.

Langville, A.N., Meyer, C.D.: Survey: deeper inside pagerank. Internet Math. 1(3), 335–380 (2003). https://doi.org/10.1080/15427951.2004.10129091 CrossRefMATH

17.

McDonald, G.: Does size matter? The impact of student–staff ratios. J. High. Educ. Policy Manag. 35(6), 652–667 (2013). https://doi.org/10.1080/1360080x.2013.844668 CrossRef

18.

Molinero, X., Riquelme, F., Serna, M.J.: Star-shaped mediation in influence games. In: Cornelissen, K., Hoeksma, R., Hurink, J., Manthey, B. (eds.) 12th Cologne-Twente Workshop on Graphs and Combinatorial Optimization, Enschede, Netherlands, May 21–23, 2013., CTIT Workshop Proceedings, vol. WP 13–01, pp. 179–182 (2013)

19.

Molinero, X., Riquelme, F., Serna, M.J.: Power indices of influence games and new centrality measures for agent societies and social networks. In: Ramos, C., Novais, P., Nihan, C.E., Rodríguez, J.M.C. (eds.) Ambient Intelligence—Software and Applications—5th International Symposium on Ambient Intelligence, ISAmI 2014, Salamanca, Spain, June 4–6, 2014, Advances in Intelligent Systems and Computing, vol. 291, pp. 23–30. Springer (2014). https://doi.org/10.1007/978-3-319-07596-9_3

20.

Molinero, X., Riquelme, F., Serna, M.J.: Cooperation through social influence. Eur. J. Oper. Res. 242(3), 960–974 (2015). https://doi.org/10.1016/j.ejor.2014.11.006 MathSciNetCrossRefMATH

21.

Molinero, X., Riquelme, F., Serna, M.J.: Satisfaction and power in unanimous majority influence decision models. Electron. Notes Discrete Math. 68, 197–202 (2018). https://doi.org/10.1016/j.endm.2018.06.034 MathSciNetCrossRefMATH

22.

Mulryan-Kyne, C.: Teaching large classes at college and university level: challenges and opportunities. Teach. High. Educ. 15(2), 175–185 (2010). https://doi.org/10.1080/13562511003620001 CrossRef

23.

Muñoz-Soto, R., Villarroel, R., Barcelos, T.S., Souza, A., Merino, E., Guiñez, R., Silva, L.A.: Development of a software that supports multimodal learning analytics: a case study on oral presentations. J. UCS 24(2), 149–170 (2018)

24.

Ochoa, X., Worsley, M.: Augmenting learning analytics with multimodal sensory data. J. Learn. Anal. 3(2), 213–219 (2016). https://doi.org/10.18608/jla.2016.32.10 CrossRef

25.

Otte, E., Rousseau, R.: Social network analysis: a powerful strategy, also for the information sciences. J. Inf. Sci. 28(6), 441–453 (2002). https://doi.org/10.1177/016555150202800601 CrossRef

26.

Oviatt, S.: Problem solving, domain expertise and learning. In: Proceedings of the 15th ACM on International conference on multimodal interaction—ICMI ’13. ACM Press (2013). https://doi.org/10.1145/2522848.2533791

27.

Oviatt, S., Cohen, A., Weibel, N.: Multimodal learning analytics. In: Proceedings of the 15th ACM on International conference on multimodal interaction—ICMI 13, pp. 563–568. ACM Press (2013). https://doi.org/10.1145/2522848.2533790

28.

Perera, J., Lee, N., Win, K., Perera, J., Wijesuriya, L.: Formative feedback to students: the mismatch between faculty perceptions and student expectations. Med. Teach. 30(4), 395–399 (2008). https://doi.org/10.1080/01421590801949966 CrossRef

29.

Picatoste, J., Pérez-Ortiz, L., Ruesga-Benito, S.M.: A new educational pattern in response to new technologies and sustainable development. Enlightening ICT skills for youth employability in the european union. Telemat. Inform. 35(4), 1031–1038 (2018). https://doi.org/10.1016/j.tele.2017.09.014 CrossRef

30.

Riquelme, F., Cantergiani, P.G.: Measuring user influence on twitter: a survey. Inf. Process. Manag. 52(5), 949–975 (2016). https://doi.org/10.1016/j.ipm.2016.04.003 CrossRef

31.

Schneider, J., Börner, D., van Rosmalen, P., Specht, M.: Do you know what your nonverbal behavior communicates? – studying a self-reflection module for the presentation trainer. In: Communications in Computer and Information Science, pp. 93–106. Springer International Publishing (2017). https://doi.org/10.1007/978-3-319-60633-0_8

32.

Scott, J.: Social Network Analysis, 4th edn. Sage Publications Ltd, New York (2017)

33.

Sedraz-Silva, J.C., Zambom, E., Lins-Rodrigues, R., Cavalcanti-Ramos, J.L., da Fonseca-de Souza, F.: Effects of learning analytics on students’ self-regulated learning in flipped classroom. IJICTE 14(3), 91–107 (2018). https://doi.org/10.4018/IJICTE.2018070108

34.

Siemens, G., Baker, R.S.J.d.: Learning analytics and educational data mining: towards communication and collaboration. In: Proceedings of the 2nd International Conference on Learning Analytics and Knowledge, LAK ’12, pp. 252–254. ACM, New York, NY, USA (2012). https://doi.org/10.1145/2330601.2330661

35.

Tinati, R., Carr, L., Hall, W., Bentwood, J.: Identifying communicator roles in twitter. In: Mille, A., Gandon, F.L., Misselis, J., Rabinovich, M., Staab, S. (eds.) Proceedings of the 21st World Wide Web Conference, WWW 2012, Lyon, France, April 16–20, 2012 (Companion Volume), pp. 1161–1168. ACM (2012). https://doi.org/10.1145/2187980.2188256

36.

Vieira, C., Goldstein, M.H., Purzer, Ş., Magana, A.J.: Using learning analytics to characterize student experimentation strategies in the context of engineering design. J. Learn. Anal. 3(3), 291–317 (2016). https://doi.org/10.18608/jla.2016.33.14 CrossRef

37.

Worsley, M., Blikstein, P.: Towards the development of learning analytics: Student speech as an automatic and natural form of assessment. In: Annual Meeting of the American Education Research Association (AERA) (2010)

38.

Worsley, M., Blikstein, P.: Reasoning strategies in the context of engineering design with everyday materials. J. Pre-Coll. Eng. Educ. Res. (J-PEER) 6(2), 5 (2017). https://doi.org/10.7771/2157-9288.1126

Title: Using multimodal learning analytics to study collaboration on discussion groups
A social network approach
Authors: Fabian Riquelme
Roberto Munoz
Roberto Mac Lean
Rodolfo Villarroel
Thiago S. Barcelos
Victor Hugo C. de Albuquerque
Publication date: 22-07-2019
Publisher: Springer Berlin Heidelberg
Published in: Universal Access in the Information Society / Issue 3/2019
Print ISSN: 1615-5289
Electronic ISSN: 1615-5297
DOI: https://doi.org/10.1007/s10209-019-00683-w

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