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PolyCAFe—automatic support for the polyphonic analysis of CSCL chats

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International Journal of Computer-Supported Collaborative Learning Aims and scope Submit manuscript

Abstract

Chat conversations and other types of online communication environments are widely used within CSCL educational scenarios. However, there is a lack of theoretical and methodological background for the analysis of collaboration. Manual assessing of non-moderated chat discussions is difficult and time-consuming, having as a consequence that learning scenarios have not been widely adopted, neither in formal education nor in informal learning contexts. An analysis method of collaboration and individual participation is needed. Moreover, computer-support tools for the analysis and assessment of these conversations are required. In this paper, we start from the “polyphonic framework” as a theoretical foundation suitable for the analysis of textual and even gestural interactions within collaborative groups. This framework exploits the notions of dialogism, inter-animation and polyphony for assessing interactions between participants. The basics of the polyphonic framework are discussed and a systematic presentation of the polyphonic analysis method is included. Then, we present the PolyCAFe system, which provides tools that support the polyphonic analysis of chat conversations and online discussion forums of small groups of learners. Natural Language Processing (NLP) is used in order to identify topics, semantic similarities and links between utterances. The detected links are then used to build a graph of utterances, which forms the central element for the polyphonic analysis and for providing automatic feedback and support to both tutors and learners. Social Network Analysis is used for computing quantitative measures for the interactions between participants. Two evaluation experiments have been undertaken with PolyCAFe. Learners find the system useful and efficient. In addition to these advantages, tutors reflecting on the conversation can provide quicker manual feedback.

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Notes

  1. The analysis of this response pair is due to Gerry Stahl (Personal communication, December 19, 2013).

References

  • Adams, P.H., & Martell, C.H. (2008). Topic detection and extraction in chat. In IEEE Int. Conf. on Semantic Computing (ICSC 2008) (pp. 581–588). Santa Clara: IEEE.

  • Avouris, N., Fiotakis, G., Kahrimanis, G., Margaritis, M., & Komis, V. (2007). Beyond logging of fingertip actions: Analysis of collaborative learning using multiple sources of data. Journal of Interactive Learning Research, 18(2), 231–250.

    Google Scholar 

  • Bakhtin, M.M. (1981). The dialogic imagination: Four essays (trans: Emerson, C. & Holquist, M.). Austin and London: The University of Texas Press.

  • Bakhtin, M.M. (1984). Problems of Dostoevsky’s poetics (Emerson, C., Trans. C. Emerson Ed.). Minneapolis: University of Minnesota Press.

  • Bakhtin, M.M. (1986). Speech genres and other late essays (trans: McGee, V.W.). Austin: University of Texas

  • Bereiter, C. (2002). Education and mind in the knowledge age. Mahwah: Lawrence Erlbaum Associates.

    Google Scholar 

  • Berlanga, A.J., Van Rosmalen, P., Trausan-Matu, S., Monachesi, P., & Burek, G. (2009). The language technologies for lifelong learning project. In 9th IEEE Int. Conf. on Advanced Learning Technologies (ICALT 2009) (pp. 624–625). Riga: IEEE.

  • Blei, D. M., Ng, A. Y., & Jordan, M. I. (2003). Latent Dirichlet allocation. Journal of Machine Learning Research, 3(4–5), 993–1022.

    Google Scholar 

  • Brandes, U. (2001). A faster algorithm for betweenness centrality. Journal of Mathematical Sociology, 25(2), 163–177.

    Article  Google Scholar 

  • Budanitsky, A., & Hirst, G. (2006). Evaluating WordNet-based measures of lexical semantic relatedness. Computational Linguistics, 32(1), 13–47.

    Article  Google Scholar 

  • Cazden, C. B. (1993). Vygotsky, Hymes, and Bakhtin: From word to utterance and voice. In E. A. Forman, N. Minick, & C. A. Stone (Eds.), Contexts for learning: Sociocultural dynamics in children’s development (pp. 197–212). Oxford: Oxford University Press.

    Google Scholar 

  • Chiru, C. G., & Trausan-Matu, S. (2012). Identification and classification of the most important moments from students’ collaborative discourses. In S. A. Cerri, W. J. Clancey, G. Papadourakis, & K. Panourgia (Eds.), 11th Int. Conf. on Intelligent Tutoring Systems (ITS 2012) (pp. 330–339). Chania: Springer.

    Chapter  Google Scholar 

  • Confucius. (2003). Analects. Indianapolis: Hackett Publishing Company, Inc.

    Google Scholar 

  • Cormen, T. H., Leiserson, C. E., Rivest, R. L., & Stein, C. (Eds.). (2009). Introduction to algorithms (3rd ed.). Cambridge: MIT Press.

    Google Scholar 

  • Dascalu, M., Chioasca, E. V., & Trausan-Matu, S. (2008). ASAP – an advanced system for assessing chat participants. In D. Dochev, M. Pistore, & P. Traverso (Eds.), 13th Int. Conf. on Artificial Intelligence: Methodology, Systems, and Applications (AIMSA 2008) (pp. 58–68). Varna: Springer.

    Chapter  Google Scholar 

  • Dascalu, M., Rebedea, T., & Trausan-Matu, S. (2010a). A deep insight in chat analysis: Collaboration, evolution and evaluation, summarization and search. In D. Dochev & D. Dicheva (Eds.), 14th Int. Conf. on Artificial Intelligence: Methodology, Systems, Applications (AIMSA 2010) (pp. 191–200). Varna: Springer.

    Chapter  Google Scholar 

  • Dascalu, M., Trausan-Matu, S., & Dessus, P. (2010b). Utterances assessment in chat conversations. Research in Computing Science, 46, 323–334.

    Google Scholar 

  • Dascalu, M., Rebedea, T., Trausan-Matu, S., & Armitt, G. (2011). PolyCAFe: Collaboration and utterance assessment for online CSCL conversations. In H. Spada, G. Stahl, N. Miyake, & N. Law (Eds.), 9th Int. Conf. on Computer-Supported Collaborative Learning (CSCL 2011) (pp. 781–785). Hong Kong: ISLS.

    Google Scholar 

  • Dascalu, M., Dessus, P., Trausan-Matu, S., Bianco, M., & Nardy, A. (2013). ReaderBench, an environment for analyzing text complexity and reading strategies. In H. C. Lane, K. Yacef, J. Mostow, & P. Pavlik (Eds.), 16th Int. Conf. on Artificial Intelligence in Education (AIED 2013) (pp. 379–388). Memphis: Springer.

    Chapter  Google Scholar 

  • Dong, A. (2006). Concept formation as knowledge accumulation: A computational linguistics study. AIE EDAM: Artificial Intelligence for Engineering Design, Analysis, and Manufacturing, 20(1), 35–53.

    Google Scholar 

  • Dowell, J., & Gladisch, T. (2007). Design of argument diagramming for case-based group learning. ACM International Conference Proceeding Series, 250, 99–105.

    Google Scholar 

  • Dowell, J., Tscholl, M., Gladisch, T., & Asgari-Targhi, M. (2009). Argumentation scheme and shared online diagramming in case-based collaborative learning. In 9th Int. Conf. on Computer supported collaborative learning (CSCL’09) (pp. 567–575). Rhodes: ISLS.

  • Eastman, J. K., & Swift, C. O. (2002). Enhancing collaborative learning: Discussion boards and chat rooms as project communication tools. Business Communication Quarterly, 65(3), 29–41.

    Article  Google Scholar 

  • Freeman, L. (1977). A set of measures of centrality based on betweenness. Sociometry, 40(1), 35–41.

    Article  Google Scholar 

  • Fuks, H., & Pimentel, M. (2009). Studying response-structure confusion in VMT. In G. Stahl (Ed.), Studying virtual math teams (pp. 373–397). Boston: Springer.

    Chapter  Google Scholar 

  • Harrer, A., Hever, R., & Ziebarth, S. (2007). Empowering researchers to detect interaction patterns in e-collaboration. In R. Luckin, K. R. Koedinger, & J. E. Greer (Eds.), 13th Int. Conf. on Artificial Intelligence in Education (AIED 2007) (pp. 503–510). Los Angeles: Frontiers in Artificial Intelligence and Applications.

    Google Scholar 

  • Hmelo-Silver, C.E., Chernobilsky, E., & Masto, O. (2006). Analyzing collaborative learning: Multiple approaches to understanding processes and outcomes. In 7th Int. Conf. of the Learning Sciences (ICLS ’06) (pp. 1061–1062). Bloomington, IN, USA.

  • Holmer, T., Kienle, A., & Wessner, M. (2006). Explicit referencing in learning chats: Needs and acceptance. In W. Nejdl & K. Tochtermann (Eds.), First European Conference on Technology Enhanced Learning, EC-TEL 2006 (pp. 170–184). Crete: Springer.

    Google Scholar 

  • Jurafsky, D., & Martin, J. H. (2009). An introduction to natural language processing. Computational linguistics, and speech recognition (2nd ed.). London: Pearson Prentice Hall.

    Google Scholar 

  • Kent, J. T. (1983). Information gain and a general measure of correlation. Biometrika, 70(1), 163–173.

    Article  Google Scholar 

  • Koschmann, T. (1999). Toward a dialogic theory of learning: Bakhtin’s contribution to understanding learning in settings of collaboration. In C. M. Hoadley & J. Roschelle (Eds.), Int. Conf. on Computer Support for Collaborative Learning (CSCL’99) (pp. 308–313). Palo Alto: ISLS.

    Google Scholar 

  • Kumar, R., Chaudhuri, S., Howley, I., & Rosé, C.P. (2009). VMT-Basilica: An environment for rapid prototyping of collaborative learning environments with dynamic support. In 9th Int. Conf. on Computer supported collaborative learning (CSCL’09) (pp. 192–194). Rhodes: ISLS.

  • Landauer, T. K., & Dumais, S. T. (1997). A solution to Plato’s problem: The Latent Semantic Analysis theory of acquisition, induction and representation of knowledge. Psychological Review, 104(2), 211–240.

    Article  Google Scholar 

  • Landauer, T. K., Foltz, P. W., & Laham, D. (1998). An introduction to Latent Semantic Analysis. Discourse Processes, 25(2/3), 259–284.

    Article  Google Scholar 

  • Law, N., Lu, J., Leng, J., Yuen, J., & Lai, M. (2008). Understanding knowledge building from multiple perspectives. Utrecht, Netherland.

  • Ligorio, M. B., & Ritella, G. (2010). The collaborative construction of chronotopes during computer-supported collaborative professional tasks. International Journal of Computer-Supported Collaborative Learning, 5(4), 433–452.

    Article  Google Scholar 

  • Mahnkopf, C. S. (2002). Theory of polyphony. In C. S. Mahnkopf, F. Cox, & W. Schurig (Eds.), Polyphony and complexity (Vol. 1, p. 328). Hofheim: Wolke Verlags Gmbh.

    Google Scholar 

  • Manning, C. D., & Schütze, H. (1999). Foundations of statistical Natural Language Processing. Cambridge: MIT Press.

    Google Scholar 

  • Manning, C. D., Raghavan, P., & Schütze, H. (2008). Introduction to information retrieval (Vol. 1). Cambridge: Cambridge University Press.

    Book  Google Scholar 

  • Marková, I. (2003). Dialogicality and social representations. Cambridge: Cambridge University Press.

    Google Scholar 

  • Nelson, J., Perfetti, C., Liben, D., & Liben, M. (2012). Measures of text difficulty: Testing their predictive value for grade levels and student performance. Washington, DC: Council of Chief State School Officers.

    Google Scholar 

  • Newman, M. E. J. (2010). Networks: An introduction (1st ed.). Oxford: Oxford University Press.

    Book  Google Scholar 

  • Rebedea, T., Dascalu, M., Trausan-Matu, S., Banica, D., Gartner, A., Chiru, C. G., et al. (2010). Overview and preliminary results of using PolyCAFe for collaboration analysis and feedback generation. In M. Wolpers, P. Kirschner, M. Scheffel, S. Lindstaedt, & V. Dimitrova (Eds.), 5th European Conference on Technology Enhanced Learning (EC-TEL 2010) (pp. 420–425). Barcelona: Springer.

    Google Scholar 

  • Rebedea, T., Dascalu, M., Trausan-Matu, S., Armitt, G., & Chiru, C. G. (2011). Automatic assessment of collaborative chat conversations with PolyCAFe. In C. D. Kloos, D. Gillet, R. M. Crespo García, F. Wild, & M. Wolpers (Eds.), 6th European Conference of Technology Enhanced Learning (EC-TEL 2011) (pp. 299–312). Palermo: Springer.

    Google Scholar 

  • Sacks, O. (2007). Musicophilia: Tales of music and the brain. New York: Vintage Books.

    Google Scholar 

  • Scardamalia, M. (2002). Collective cognitive responsibility for the advancement of knowledge. In B. Smith & C. Bereiter (Eds.), Liberal education in a knowledge society (pp. 67–98). Chicago: Open Court Publishing.

    Google Scholar 

  • Shannon, C. E. (1948). A mathematical theory of communication. The Bell System Technical Journal, 27, 379–423. 623–656.

    Article  Google Scholar 

  • Stahl, G. (2006). Group cognition. Computer support for building collaborative knowledge. Cambridge: MIT Press.

    Google Scholar 

  • Stahl, G. (2009a). Studying virtual math teams. New York: Springer.

    Book  Google Scholar 

  • Stahl, G. (2009b). The VMT vision. In G. Stahl (Ed.), Studying virtual math teams (pp. 17–29). New York: Springer.

    Chapter  Google Scholar 

  • Stahl, G. (2013). Translating Euclid: Designing a human-centered mathematics. San Rafael, CA: Morgan & Claypool Publishers. http://gerrystahl.net/elibrary/euclid.

  • Strijbos, J. W. (2009). A multidimensional coding scheme for VMT. In G. Stahl (Ed.), Studying virtual math teams (pp. 399–419). Boston: Springer.

    Chapter  Google Scholar 

  • Suthers, D., & Desiato, C. (2012). Exposing chat features through analysis of uptake between contributions. In 45th Hawaii International Conference on System Sciences (pp. 3368–3377). Maui, HI: IEEE.

  • Tannen, D. (2007). Talking voices: Repetition, dialogue, and imagery in conversational discourse (2nd ed.). Cambridge: Cambridge University Press.

    Book  Google Scholar 

  • Teplovs, C. (2008). The knowledge space visualizer: A tool for visualizing online discourse. In Workshop on A Common Framework for CSCL Interaction Analysis, ICLS 2008 (pp. 12). Utrecht, Netherland.

  • Trausan-Matu, S. (2010a). Automatic support for the analysis of online collaborative learning chat conversations. In P. M. Tsang, S. K. S. Cheung, V. S. K. Lee, & R. Huang (Eds.), 3rd Int. Conf. on Hybrid Learning (pp. 383–394). Beijing: Springer.

    Chapter  Google Scholar 

  • Trausan-Matu, S. (2010b). Computer support for creativity in small Groups using chats. Annals of the Academy of Romanian Scientists, Series on Science and Technology of Information, 3(2), 81–90.

    Google Scholar 

  • Trausan-Matu, S. (2010c). The polyphonic model of hybrid and collaborative learning. In F. L. Wang, J. Fong, & R. C. Kwan (Eds.), Handbook of research on hybrid learning models: Advanced tools, technologies, and applications (pp. 466–486). Hershey: Information Science Publishing.

    Google Scholar 

  • Trausan-Matu, S. (2012). Repetition as artifact generation in polyphonic CSCL chats. In Third Int. Conf. on Emerging Intelligent Data and Web Technologies (pp. 194–198). IEEE.

  • Trausan-Matu, S. (2013). Collaborative and differential utterances, pivotal moments, and polyphony. In D. Suthers, K. Lund, C. P. Rosé, C. Teplovs, & N. Law (Eds.), Productive multivocality in the analysis of group interactions (Computer-supported collaborative learning series, Vol. 15, pp. 123–139). New York: Springer.

    Chapter  Google Scholar 

  • Trausan-Matu, S., & Rebedea, T. (2009). Polyphonic inter-animation of voices in VMT. In G. Stahl (Ed.), Studying virtual math teams (pp. 451–473). Boston: Springer.

    Chapter  Google Scholar 

  • Trausan-Matu, S., & Rebedea, T. (2010). A polyphonic model and system for inter-animation analysis in chat conversations with multiple participants. In A. F. Gelbukh (Ed.), 11th Int. Conf. Computational Linguistics and Intelligent Text Processing (CICLing 2010) (pp. 354–363). Iasi: Springer.

    Chapter  Google Scholar 

  • Trausan-Matu, S., & Stahl, G. (2007). Polyphonic inter-animation of voices in chats. In CSCL’07 Workshop on Chat Analysis in Virtual Math Teams (pp. 12). New Brunwick: ISLS.

  • Trausan-Matu, S., Stahl, G., & Zemel, A. (2005). Polyphonic inter-animation in collaborative problem solving chats. Philadelphia: Drexel University, http://mathforum.org/wikis/uploads/Stefan_Interanimation.doc.

  • Trausan-Matu, S., Stahl, G., & Sarmiento, J. (2006). Polyphonic support for collaborative learning. In Y. A. Dimitriadis, I. Zigurs, & E. Gómez-Sánchez (Eds.), Groupware: Design, implementation, and use, (CRIWG 2006) (pp. 132–139). Medina del Campo: Springer.

    Chapter  Google Scholar 

  • Trausan-Matu, S., Rebedea, T., Dragan, A., & Alexandru, C. (2007a). Visualisation of learners’ contributions in chat conversations. In J. Fong & F. L. Wang (Eds.), Blended learning (pp. 217–226). Singapour: Pearson/Prentice Hall.

    Google Scholar 

  • Trausan-Matu, S., Stahl, G., & Sarmiento, J. (2007b). Supporting polyphonic collaborative learning. Indiana University Press, E-service Journal, 6(1), 58–74.

    Google Scholar 

  • Trausan-Matu, S., Dessus, P., Lemaire, B., Mandin, S., Villiot-Leclercq, E., Rebedea, T., et al. (2008). Deliverable D5.1 LTfLL – Support and feedback design. Heerlen: OUNL, Research report of the LTfLL Project.

  • Trausan-Matu, S., Dessus, P., Rebedea, T., Mandin, S., Villiot-Leclercq, E., Dascalu, M., et al. (2009). Deliverable D5.2 LTfLL – Learning support and feedback. http://dspace.ou.nl/handle/1820/2251.

  • Trausan-Matu, S., Rebedea, T., & Dascalu, M. (2010). Analysis of discourse in collaborative learning chat conversations with multiple participants. In D. Tufis & C. Forascu (Eds.), Multilinguality and interoperability in language processing with emphasis on Romanian (pp. 313–330). Bucharest: Editura Academiei.

    Google Scholar 

  • Trausan-Matu, S., Dascalu, M., & Dessus, P. (2012). Textual complexity and discourse structure in computer-supported collaborative learning. In S. A. Cerri, W. J. Clancey, G. Papadourakis, & K. Panourgia (Eds.), 11th Int. Conf. on Intelligent Tutoring Systems (ITS 2012) (pp. 352–357). Chania: Springer.

    Chapter  Google Scholar 

  • Vygotsky, L. S. (1978). Mind in society. Cambridge: Harvard University Press.

    Google Scholar 

  • Webern, A. (1963). The path to the new music. Pennsylvania: Theodore Presser Co.

    Google Scholar 

  • Zemel, A., Xhafa, F., & Çakir, M. P. (2009). Combining coding and conversation analysis of VMT chats. In G. Stahl (Ed.), Studying virtual math teams (pp. 421–450). New York, NY: Springer.

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Acknowledgments

The authors wish to express their thanks to the anonymous reviewers for their extensive and very useful comments. We would like to mention the thoughtful advice of Gerry Stahl. We would also like to thank Alexandru Gartner, Dan Banica and the students and tutors who participated in the validation and verification experiments. The research presented here has been partially performed under a Fulbright Scholar post-doc grant (awarded to Stefan Trausan-Matu) and was also supported by the FP7 ICT STREP project LTfLL (http://www.ltfll-project.org/) and by project FP7-REGPOT-2010-1, nr. 264207, ERRIC.

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  1. Department of Computer Science and Engineering, University “Politehnica” of Bucharest, 313 Splaiul Independetei, Bucharest, Romania

    Stefan Trausan-Matu, Mihai Dascalu & Traian Rebedea

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  1. Stefan Trausan-Matu
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  2. Mihai Dascalu
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  3. Traian Rebedea
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Correspondence to Stefan Trausan-Matu.

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Trausan-Matu, S., Dascalu, M. & Rebedea, T. PolyCAFe—automatic support for the polyphonic analysis of CSCL chats. Intern. J. Comput.-Support. Collab. Learn. 9, 127–156 (2014). https://doi.org/10.1007/s11412-014-9190-y

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