Notes
We use the term “minoritized” to refer to people who are marginalized by systemic and long-standing inequities. When discussing equity, word choice matters and shifts over time. Following Paris (2012) and Harper (2012), we prefer “minoritized” to “minorities” to highlight that it is harmful systems, rather than the individuals those systems disenfranchise, that are to blame for inequitable circumstances. Furthermore, in various global contexts, this term is meant to signify a wide range of historical and longstanding inequities (e.g., caste-based discrimination), although we encourage naming these specific oppressions when they can be clearly demarcated.
References
Alavi, H. S., & Dillenbourg, P. (2012). An ambient awareness tool for supporting supervised collaborative problem solving. IEEE Transactions on Learning Technologies, 5(3), 264-274.
Agarwal, P., & Sengupta-Irving, T. (2019). Integrating power to advance the study of connective and productive disciplinary engagement in mathematics and science. Cognition and Instruction, 37(3), 349–366.
Ahn, J., Campos, F., Hays, M., & DiGiacomo, D. (2019). Designing in context: Reaching beyond usability in learning analytics dashboard design. Journal of Learning Analytics, 6(2), 70–85.
Baghaei, N., Mitrovic, A., & Irwin, W. (2007). Supporting collaborative learning and problem-solving in a constraint-based CSCL environment for UML class diagrams. International Journal of Computer-Supported Collaborative Learning, 2(2), 159–190. https://doi.org/10.1007/s11412-007-9018-0.
Bakhtin, M. M. (1981). The dialogic imagination: Four essays. Austin: University of Texas Press.
Bang, M., & Vossoughi, S. (Eds.). (2016). Participatory design research and educational justice: Studying learning and relations within social change making [Special issue]. Cognition and Instruction, 34(3), 173–193.
Bell, P., Van Horne, K., & Cheng, B. H. (Eds.). (2017). Designing learning environments for equitable disciplinary identification [Special issue]. Journal of the Learning Sciences, 26(3), 367–375.
Benjamin, R. (2019). Race after technology: Abolitionist tools for the new jim code. John Wiley and Sons.
Biesta, G. (2013). Interrupting the politics of learning. Power and Education, 5(1), 4–15.
Blikstein, P., & Worsley, M. (2016). Multimodal learning analytics and education data mining: Using computational technologies to measure complex learning tasks. Journal of Learning Analytics, 3(2), 220–238.
Calabrese Barton, A., & Tan, E. (2010). We be burnin'! Agency, identity, and science learning. The Journal of the Learning Sciences, 19(2), 187–229.
Chzhen, Y., Gromada, A., Rees, G., Cuesta, J., & Bruckauf, Z. (2018). An unfair start: Inequality in children's education in rich countries, Innocenti Report Card no. 15. Florenc: UNICEF Office of Research.
Dillenbourg, P., Prieto, L. P., and Olsen, J. K. (2018). Classroom orchestration. In International Handbook of the Learning Sciences (pp. 180-190). Routledge.
Duncan, G. A. (2000). Urban pedagogies and the celling of adolescents of color, Social Justice., 27(3 (81), 29–42.
Eberle, J. (2018). Apprenticeship learning. In F. Fischer, C. E. Hmelo‐Silver, S. R. Goldman, & P. Reimann (Eds.), International handbook of the learning sciences (pp. 44-53). New York: Routledge.
Engle, R. A., & Conant, F. R. (2002). Guiding principles for fostering productive disciplinary engagement: Explaining an emergent argument in a community of learners classroom. Cognition and Instruction, 20(4), 399–483.
Esmonde, I. (2009). Mathematics learning in groups: Analyzing equity in two cooperative activity structures. The Journal of the Learning Sciences, 18(2), 247–284.
Esmonde, I., & Booker, A. N. (2017). Power and privilege in the learning sciences; critical and sociocultural theories of learning. New York, NY: Routledge.
Evans, A., Davis, K., & Wobbrock, J. (2019). Adaptive support for collaboration on tabletop computers. In K. Lund, G. P. Niccolai, E. Lavoué, C. E. Hmelo-Silver, G. Gweon, & M. Baker (Eds.), A wide Lens: Combining embodied, enactive, extended, and embedded learning in collaborative settings, Proceedings of 13th International Conference on Computer Supported Collaborative Learning (CSCL) 2019 (Vol. 1, pp. 176–183). Lyon, France: International Society of the Learning Sciences.
Fischer, F., Kollar, I., Weinberger, A., Stegmann, K., Wecker, C., & Zottmann, J. (2013). Collaboration scripts in computer-supported collaborative learning. In C. E. Hmelo-Silver, C. A. Chinn, C. K. K. Chan, & A. M. O’Donnell (Eds.), International handbook of collaborative learning (pp. 403–419). New York: Routledge.
Freire, P. (1972). Pedagogy of the oppressed (M. B. Ramos, Trans. New York, NY: Herder and Herder.
Gerard, L., Kidron, A., & Linn, M. C. (2019). Guiding collaborative revision of science explanations. International Journal of Computer-Supported Collaborative Learning, 14(3), 291–324.
Glazewski, K. D., & Hmelo-Silver, C. E. (2019). Scaffolding and supporting use of information for ambitious learning practices. Information and Learning Sciences, 120(1/2), 39–58.
Gutiérrez, R. (2009). Embracing the inherent tensions in teaching mathematics from an equity stance. Democracy and Education, 18(3), 9–16.
Gutiérrez, K. D., & Jurow, A. S. (2016). Social design experiments: Toward equity by design. Journal of the Learning Sciences, 25(4), 565–598.
Hakkarainen, K. (2009). A knowledge-practice perspective on technology-mediated learning. International Journal of Computer-Supported Collaborative Learning, 4(2), 213–231.
Harper, S. R. (2012). Race without racism: How higher education researchers minimize racist institutional norms. The Review of Higher Education, 36(1), 9–29.
Hmelo-Silver, C. E. (2004). Problem-based learning: What and how do students learn? Educational Psychology Review, 16, 235–266.
Hod, Y., Sagy, O., Kali, Y., & Taking Citizen Science to School. (2018). The opportunities of networks of research-practice partnerships and why CSCL should not give up on large-scale educational change. International Journal of Computer Supported Collaborative Learning, 13(4), 457–466.
Holstein, K., McLaren, B. M., & Aleven, V. (2018). Student learning benefits of a mixed-reality teacher awareness tool in AI-enhanced classrooms, In Proceedings of the 19th International Conference on Artificial Intelligence in Education (AIED 2018). (pp. 154–168). Cham: Springer.
Jeong, H., & Hmelo-Silver, C. E. (2016). Seven affordances of CSCL technology: How can technology support collaborative learning. Educational Psychologist, 51, 247–265.
Ladson-Billings, G. (1995). Toward a theory of culturally relevant pedagogy. American Educational Research Journal, 32(3), 465-491.
Louie, N. (2020). Agency discourse and the reproduction of hierarchy in mathematics instruction. Cognition and Instruction, 38(1), 1-26.
Nasir, N. I. S. (2020). Teaching for equity: Where developmental needs meet racialized structures. Applied Developmental Science, 24(2), 146–150.
Noble, S. U. (2018). Algorithms of oppression: How search engines reinforce racism. New York: New York University Press.
Oakes, J. (1992). Can tracking research inform practice? Technical, normative, and political considerations. Educational Researcher, 21(4), 12–21.
Olsen, J.K., Aleven, V., and Rummel, N. (2015). Predicting student performance in a collaborative learning environment. In Proceedings of the 8th International Conference on Educational Data Mining. (pp. 211-217).
Olsen, J. K., Rummel, N., & Aleven, V. (2019). It is not either or: An initial investigation into combining collaborative and individual learning using an ITS. International Journal of Computer-Supported Collaborative Learning, 14(3), 353–381. https://doi.org/10.1007/s11412-019-09307-0.
Papert, S. (1980). Mindstorms: Children, computers, and powerful ideas. Inc: Basic Books.
Paris, D. (2012). Culturally sustaining pedagogy: A needed change in stance, terminology, and practice. Educational Researcher, 41(3), 93–97.
Philip, T. M., Olivares-Pasillas, M. C., & Rocha, J. (2016). Becoming racially literate about data and data-literate about race: Data visualizations in the classroom as a site of racial-ideological micro-contestations. Cognition and Instruction, 34(4), 361–388.
Philip, T. M., Bang, M., & Jackson, K. (2018). Articulating the “how,” the “for what,” the “for whom,” and the “with whom” in concert: A call to broaden the benchmarks of our scholarship. Cognition and Instruction, 36(2), 83–88.
Politics of Learning Writing Collective. (2017). The learning sciences in a new era of US nationalism. Cognition and Instruction, 35(2), 91–102.
Prieto, L. P., Sharma, K., Dillenbourg, P., and Jesús, M. (2016). Teaching analytics: Towards automatic extraction of orchestration graphs using wearable sensors. In Proceedings Of The Sixth International Conference On Learning Analytics and Knowledge (pp. 148-157).
Ramey, K. and Stevens, R. (2019). Girls as experts, helpers, organizers, and leaders: Designing for Equitable Access and participation in CSCL environments. In Lund, K., Niccolai, G. P., Lavoué, E., Gweon, C. H., and Baker, M. (Eds.), A wide lens: combining embodied, enactive, extended, and embedded learning in collaborative settings, Proceedings of 13th International Conference on Computer Supported Collaborative Learning (CSCL) 2019, Volume 1 (pp. 368–375). Lyon, France: International Society of the Learning Sciences.
Rau, M. A., Bowman, H. E., & Moore, J. W. (2017). An adaptive collaboration script for learning with multiple visual representations in chemistry. Computers and Education, 109, 38–55.
Reinholz, D. L., & Shah, N. (2018). Equity analytics: A methodological approach for quantifying participation patterns in mathematics classroom discourse. Journal for Research in Mathematics Education, 49(2), 140–177.
Resnick, L. B., Asterhan, C. A., & Clarke, S. N. (2015). Socializing intelligence through academic talk and dialogue. Washington, DC: American Educational Research Association.
Roschelle, J. (1992). Learning by collaborating: Convergent conceptual change. The Journal of the Learning Sciences, 2(3), 235–276.
Rummel, N., Walker, E., & Aleven, V. (2016). Different futures of adaptive collaborative learning support. International Journal of Artificial Intelligence in Education, 26(2), 784–795.
Savery, J. R. (2015). Overview of problem-based learning: Definitions and distinctions. In A. Walker, H. Leary, C. E. Hmelo-Silver, & P. A. Ertmer (Eds.), Essential readings in problem-based learning: Exploring and extending the legacy of Howard S. barrows (pp. 5–15). Lafayette: Purdue University Press.
Schwarz, B. B., Prusak, N., Swidan, O., Livny, A., Gal, K., & Segal, A. (2018). Orchestrating the emergence of conceptual learning: A case study in a geometry class. International Journal of Computer-Supported Collaborative Learning, 13(2), 189–211.
Sfard, A., & Cobb, P. (2014). Research in mathematics education: What can it teach us about human learning? In K. Sawyer (Ed.), The Cambridge handbook of the learning sciences (pp. 545–563). Cambridge University Press.
Slotta, J. D., Quintana, R. M., & Moher, T. (2018). Collective inquiry in communities of learners. In F. Fischer, C. Hmelo-Silver, S. Goldman, & P. Reimann (Eds.), International handbook of the learning sciences. New York: Routledge.
Stahl, G., Koschmann, T., & Suthers, D. (2014). Computer-supported collaborative learning. In K. Sawyer (Ed.), The Cambridge handbook of the learning sciences (pp. 479–500). Cambridge University Press.
Star, S. L. (1989). The structure of ill-structured solutions: Boundary objects and heterogeneous distributed problem solving. In L. Gasser & M. Huhns (Eds.), Distributed artificial intelligence (pp. 37–54). San Mateo, CA: Morgan Kaufmann.
Suthers, D. D. (2006). Technology affordances for intersubjective meaning making: A research agenda for CSCL. International Journal of Computer-Supported Collaborative Learning, 1(3), 315–337.
Swartz, E. (2003). Teaching white preservice teachers: Pedagogy for change. Urban Education, 38(3), 255–278.
Tabak, I. (2004). Synergy: A complement to emerging patterns of distributed scaffolding. Journal of the Learning Sciences, 13, 305–336.
Taylor, K. H. (2018). The role of public education in place-re making: From a retrospective walk through my hometown to a call to action. Cognition and Instruction, 36(3), 188–198.
Tchounikine, P. (2019). Learners’ agency and CSCL technologies: Towards an emancipatory perspective. International Journal of Computer-Supported Collaborative Learning, 14(2), 237–250.
Tegos, S., Demetriadis, S., Papadopoulos, P. M., & Weinberger, A. (2016). Conversational agents for academically productive talk: A comparison of directed and undirected agent interventions. International Journal of Computer-Supported Collaborative Learning, 11(4), 417–440.
Tissenbaum, M., & Slotta, J. (2019). Supporting classroom orchestration with real-time feedback: A role for teacher dashboards and real-time agents. International Journal of Computer-Supported Collaborative Learning, 14(3), 325–351.
UNESCO. (2014). Global citizenship education: Preparing learners for the challenges of the twenty-first century. Paris: Unesco. Retrieved from http://unesdoc.unesco.org/images/0022/002277/227729E.pdf.
Uttamchandani, S. (2018). Equity in the learning sciences: Recent themes and pathways. In J. Kay & R. Luckin (Eds.), International conference of the learning sciences (ICLS) 2018, volume 1 (pp. 480–487). London, UK: International Society of the Learning Sciences.
van Aalst, J. (2009). Distinguishing knowledge-sharing, knowledge-construction, and knowledge-creation discourses. International Journal of Computer-Supported Collaborative Learning, 4(3), 259–287.
van Leeuwen, A. (2015). Learning analytics to support teachers during synchronous CSCL: Balancing between overview and overload. Journal of learning Analytics, 2(2), 138–162.
van Leeuwen, A., Rummel, N., & van Gog, T. (2019). What information should CSCL teacher dashboards provide to help teachers interpret CSCL situations? International Journal of Computer-Supported Collaborative Learning, 14(3), 261–289.
Vossoughi, S., & Gutiérrez, K. D. (2017). Critical pedagogy and sociocultural theories. In I. Esmonde & A. N. Booker (Eds.), Power and privilege in the learning sciences: Critical and sociocultural theories of learning. New York, NY: Routledge.
Walker, E., Rummel, N., & Koedinger, K. R. (2011). Designing automated adaptive support to improve student helping behaviors in a peer tutoring activity. International Journal of Computer-Supported Collaborative Learning, 6(2), 279–306.
Wang, H. C., Rosé, C. P., & Chang, C. Y. (2011). Agent-based dynamic support for learning from collaborative brainstorming in scientific inquiry. International Journal of Computer-Supported Collaborative Learning, 6(3), 371–395.
Wise, A. F., & Schwarz, B. B. (2017). Visions of CSCL: Eight provocations for the future of the field. International Journal of Computer-Supported Collaborative Learning, 12(4), 423–467.
Zhang, J. (2013). Collaboration, technology, and culture. In C. E. Hmelo-Silver, C. A. Chinn, C. K. K. Chan, & A. M. O’Donnell (Eds.), International handbook of collaborative learning (pp. 495–508). Philadelphia: Taylor and Francis.
Zhang, J., Tao, D., Chen, M. H., Sun, Y., Judson, D., & Naqvi, S. (2018). Co-organizing the collective journey of inquiry with idea thread mapper. Journal of the Learning Sciences, 27(3), 390–430.
Acknowledgements
This research was funded by the National Science Foundation under grant DGE #1547731 to the third author. The opinions, findings, and conclusions or recommendations expressed are those of the author(s) and do not necessarily reflect the views of the National Science Foundation.
Author information
Authors and Affiliations
Corresponding author
Additional information
Publisher’s note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Rights and permissions
About this article
Cite this article
Uttamchandani, S., Bhimdiwala, A. & Hmelo-Silver, C.E. Finding a place for equity in CSCL: ambitious learning practices as a lever for sustained educational change. Intern. J. Comput.-Support. Collab. Learn 15, 373–382 (2020). https://doi.org/10.1007/s11412-020-09325-3
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s11412-020-09325-3