Abstract
Touch technologies have become ubiquitous, motivating researchers to explore their potential - especially in collaborative scenarios. Studies on collaboration using joint visual spaces like multi-touch tables have demonstrated positive effects on performance. Yet, factors like prior knowledge and preferences, resulting in cognitive biases, were neglected although they are likely to put additional demands on collaboration. Whether touch technology can support its users in mastering the resulting challenges remains an open issue. To address this issue, we employed a hidden-profile paradigm (e.g., Schulz-Hardt and Mojzisch 2012) to investigate whether the affordances of specific support functions realized in a collaboration support kit on a multi-touch table help to overcome established pitfalls of collaboration (prior preferences and discussion biases). The collaboration support kit comprised a joint space and private spaces. It allowed participants to push information from the private into the joint space, to jointly sort information within the joint space, and it provided automatic functions like merging information. To replicate traditional hidden-profile studies, triads in a standard hidden-profile condition (n = 25) exchanged information in a discussion; triads in the condition with collaboration support kit (n = 29) were additionally provided with the aforementioned functions. Our results revealed that groups with collaboration support kit available showed greater discussion intensity, more balanced discussions, more indicators of mutual understanding, and better decision performance than standard hidden-profile groups. This is original evidence that affordances of a multi-touch table with interactive support functions can be used to overcome biases from prior preferences and to enhance collaboration.
Similar content being viewed by others
Notes
The Organization for Economic Cooperation and Development (OECD) recognized the need to understand collaboration skills by including CPS in their latest Program for International Student Assessment (PISA) in 2015 (OECD 2017). In PISA 2015, CPS was assessed by implementing a standardized computer supported human-agent interaction, where a student was to solve the curriculum-independent tasks in collaboration with one or more computer-simulated agents using pre-defined messages (OECD 2017). In general, at each step, the student could choose the most adequate messages out of two to seven alternatives. When a message was sent, the computerized agent replied accordingly and a new set of messages to choose from was presented to the student. This circle repeated itself until the student came to the solution. It is important to note that students received guidance from one of the agents if their choice was not conducive to reach the solution. Therefore, every student ended up solving the task, only the paths to the solution differed. Summing up, in order to measure collaborative skills, PISA developed a scripted, highly standardized paradigm, yielding a reliable assessment approach. Still, this procedure comes with issues of reduced external validity because this kind of collaboration with computer agents does not directly compare to collaboration with actual persons (Greiff et al. 2013).
For the discussion bias measure according to Stasser, Vaughan, and Stewart (2000) the introduction/repetition rate for shared information was divided by the sum of the rate of introduced/repeated shared and unshared information. For this measure a value of .5 (range 0 to 1) indicates an unbiased discussion, larger values indicate a stronger bias towards shared information.
When comparing the decision quality in the CSK condition to that of the standard HP condition after participants saw the merged information, adding the condition predictor (AIC: 70.83) to the intercept model (AIC: 69.27) did not improve goodness-of-fit, χ2(1) = 0.44, p = .507. That is, having been presented with the merged information, the groups in the standard HP condition were as likely to decide for the best candidate as groups in the CSK condition. Specifically, the chance to make the right decision was nearly identical (OR = 1.48) in this analysis.
References
Antle, A. N. (2012). Knowledge gaps in hands-on tangible interaction research. In Proceedings of the 14th ACM International Conference on Multimodal Interaction - ICMI ’12 (pp. 233–240). doi:https://doi.org/10.1145/2388676.2388726.
Aronson, E., Blaney, N., Stephin, C., Sikes, J., & Snapp, M. (1978). The jigsaw classroom. Beverly Hills: Sage Publishing Company.
Baltes, B. B., Dickson, M. W., Sherman, M. P., Bauer, C. C., & LaGanke, J. S. (2002). Computer-mediated communication and group decision making: A meta-analysis. Organizational Behavior and Human Decision Processes, 87(1), 156–179. https://doi.org/10.1006/obhd.2001.2961.
Barron, B. (2003). When smart groups fail. The Journal of the Learning Sciences, 12(3), 307–359. https://doi.org/10.1207/S15327809JLS1203_1.
Brodbeck, F. C., Kerschreiter, R., Mojzisch, A., & Schulz-Hardt, S. (2007). Group decision-making under conditions of distributed knowledge: The information asymmetries model. Academy of Management Review, 32(2), 459–479. https://doi.org/10.5465/AMR.2007.24351441.
Bronckart, J. P. (1995). Theories of action, speech, natural language, and discourse. In Sociocultural studies of mind (pp. 75–91). Cambridge: CUP.
Clark, H. H., & Brennan, S. E. (1991). Grounding in communication. Perspectives on Socially Shared Cognition, 13(1991), 127–149. https://doi.org/10.1037/10096-006.
Cohen, J. (1960). A coefficient of agreement for nominal scales. Educational and Psychosocial Measurement, 20(1), 37–46. https://doi.org/10.1177/001316446002000104.
Deiglmayr, A., & Spada, H. (2010a). Collaborative problem-solving with distributed information: The role of inferences from interdependent information. Group Processes & Intergroup Relations, 13(3), 361–378. https://doi.org/10.1177/1368430209342259.
Deiglmayr, A., & Spada, H. (2010b). Developing adaptive collaboration support: The example of an effective training for collaborative inferences. Educational Psychology Review, 22(1), 103–113. https://doi.org/10.1007/s10648-010-9119-6.
Deiglmayr, A., & Spada, H. (2011). Training for fostering knowledge co-construction from collaborative inference-drawing. Learning and Instruction, 21(3), 441–451. https://doi.org/10.1016/j.learninstruc.2010.06.004.
DeLuca, D., Gasson, S., & Kock, N. (2006). Adaptations that virtual teams make so that complex tasks can be performed using simple e-collaboration technologies. International Journal of E-Collaboration, 2(3), 64–89. https://doi.org/10.4018/jec.2006070104.
Dervin, B. (2003). Chaos, order, and sense-making: A proposed theory for information design. In B. Dervin, L. Foreman-Wernet, & E. Lauterbach (Eds.), Sense-making methodology reader selected writings of Brenda Dervin (pp. 325–340). Cresskill: Hampton.
Dillenbourg, P., & Evans, M. (2011). Interactive tabletops in education. International Journal of Computer-Supported Collaborative Learning, 6(4), 491–514. https://doi.org/10.1007/s11412-011-9127-7.
Dillenbourg, P., & Fischer, F. (2007). Computer-supported collaborative learning: The basics. Zeitschrift für Berufs- und Wirtschaftspädagogik, 21, 111–130. https://doi.org/10.1002/9781118766804.wbiect195.
Dillenbourg, P., & Traum, D. (2006). Sharing solutions: Persistence and grounding in multimodal collaborative problem solving. The Journal of the Learning Sciences, 15(1), 121–151. https://doi.org/10.1207/s15327809jls1501_9.
Fiore, S. M., & Schooler, J. W. (2004). Process mapping and shared cognition: Teamwork and the development of shared problem models. In E. E. Salas & S. M. Fiore (Eds.), Team cognition: Understanding the factors that drive process and performance (pp. 133–152). Washington, DC: American Psychological Association. https://doi.org/10.1037/10690-007.
Fischer, F., Bruhn, J., Gräsel, C., & Mandl, H. (2002). Fostering collaborative knowledge construction with visualization tools. Learning and Instruction, 12(2), 213–232. https://doi.org/10.1016/S0959-4752(01)00005-6.
Garrison, D. R., Anderson, T., & Archer, W. (2001). Critical thinking, cognitive presence, and computer conferencing in distance education. American Journal of Distance Education, 15(1), 7–23. https://doi.org/10.1080/08923640109527071.
Greiff, S., Holt, D. V., & Funke, J. (2013). Perspectives on problem solving in educational assessment: Analytical, interactive, and collaborative problem solving. The Journal of Problem Solving, 5(2), 71–91. https://doi.org/10.7771/1932-6246.1153
Greitemeyer, T., & Schulz-Hardt, S. (2003). Preference-consistent evaluation of information in the hidden profile paradigm: Beyond group-level explanations for the dominance of shared information in group decisions. Journal of Personality and Social Psychology, 84(2), 322–339. https://doi.org/10.1037/0022-3514.84.2.322.
Greitemeyer, T., Schulz-Hardt, S., & Frey, D. (2003). Präferenzkonsistenz und Geteiltheit von Information. Zeitschrift für Sozialpsychologie, 34(1), 9–23. https://doi.org/10.1024//0044-3514.34.1.9.
Gweon, Kane, & Rosé. (2011). Facilitating knowledge transfer between groups through idea co-construction processes. In INGroup (pp. 1–4).
Harris, A., Rick, J., Bonnett, V., Yuill, N., Fleck, R., Marshall, P., & Rogers, Y. (2009). Around the table: Are multiple-touch surfaces better than single-touch for children’s collaborative interactions? In CSCL 2009 Proceedings (pp. 335–344). doi:https://doi.org/10.3115/1600053.1600104.
Higgins, S. E., Mercier, E., Burd, E., & Hatch, A. (2011). Multi-touch tables and the relationship with collaborative classroom pedagogies: A synthetic review. International Journal of Computer-Supported Collaborative Learning, 6(4), 515–538. https://doi.org/10.1007/s11412-011-9131-y.
Higgins, S., Mercier, E., Burd, L., & Joyce-Gibbons, A. (2012). Multi-touch tables and collaborative learning. British Journal of Educational Technology, 43(6), 1041–1054. https://doi.org/10.1111/j.1467-8535.2011.01259.x.
Hinsz, V. B., Tindale, R. S., & Vollrath, D. A. (1997). The emerging conceptualization of groups as information processors. Psychological Bulletin, 121(1), 43–64. https://doi.org/10.1037/0033-2909.121.1.43.
Hollenbeck, J. R., Ilgen, D. R., Sego, D. J., Hedlund, J., Major, D. A., & Phillips, J. (1995). Multilevel theory of team decision-making: Decision performance in teams incorporating distributed expertise. Journal of Applied Psychology, 80(2), 292–316. https://doi.org/10.1037/0021-9010.80.2.292.
Kaplan, F., DoLenh, S., Bachour, K., Kao, G. Y. I., Gault, C., & Dillenbourg, P. (2009). Interpersonal computers for higher education. In P. Dillenbourg, J. Huang, & M. Cherubini (Eds.), Collaborative artefacts and interactive furniture (pp. 1–17). Computer-Supported Collaborative Learning Series, Springer US.
Kharrufa, A. S., Olivier, P., & Leat, D. (2009). Digital mysteries: Designing for learning at the tabletop digital mysteries. In Computing Science. Newcastle upon Tyne: University of Newcastle upon Tyne.
Kirschner, P. A., & Kreijns, K. (2005). Enhancing sociability of computer-supported collaborative learning environments. In R. Bromme, F. W. Hesse, & H. Spada (Eds.), Barriers and biases in computer-mediated knowledge communication (pp. 169–191). US: Springer. https://doi.org/10.1007/0-387-24319-4_8.
Kolbe, M. (2007). Explizite Prozesskoordination von Entscheidungsfindungsgruppen. Georg-August-Universität Göttingen.
Landis, J. R., & Koch, G. G. (1977). The measurement of observer agreement for categorical data. Biometrics, 33(1), 159–174. https://doi.org/10.2307/2529310.
Leat, D., & Nichols, A. (2000). Brains on the table: Diagnostic and formative assessment through observation. Assessment in Education: Principles, Policy & Practice, 7(1), 103–121. https://doi.org/10.1080/713613327.
Lightle, J. P., Kagel, J. H., & Arkes, H. R. (2009). Information exchange in group decision making: The hidden profile problem reconsidered. Management Science, 55(4), 568–581. https://doi.org/10.1287/mnsc.1080.0975.
Lu, L., Yuan, Y., & McLeod, P. (2012). Twenty-five years of hidden profiles in group decision making: A meta-analysis. Personality and Social Psychology Review, 16(1), 54–75. https://doi.org/10.1177/1088868311417243.
Maquil, V., Tobias, E., Anastasiou, D., Mayer, H., & Latour, T. (2017). COPSE : Rapidly instantiating problem solving activities based on tangible tabletop interfaces. Proceedings of the ACM on Human-Computer Interaction, 1(1), 1–16. https://doi.org/10.1145/3095808.
Martin, L., & Schwartz, D. L. (2009). Prospective adaptation in the use of external representations. Cognition and Instruction, 27(4), 370–400. https://doi.org/10.1080/07370000903221775.
Mayer, R. E., & Wittrock, M. C. (2006). Problem solving. In P. A. Alexaner & P. H. Winne (Eds.), Handbook of Educational Psychology (pp. 287–303). New York: Routledge.
McGrath, J. (1984). Groups: Interaction and Performance. Englewood Cliffs: Prentice-Hall.
Mercier, E. M., & Higgins, S. E. (2013). Collaborative learning with multi-touch technology: Developing adaptive expertise. Learning and Instruction, 25, 13–23. https://doi.org/10.1016/j.learninstruc.2012.10.004.
Mercier, E., & Higgins, S. (2014). Creating joint representations of collaborative problem solving with multi-touch technology. Journal of Computer Assisted Learning, 30(6), 497–510. https://doi.org/10.1111/jcal.12052.
Nowak, K. L., Watt, J., & Walther, J. B. (2006). The influence of synchrony and sensory modality on the person perception process in computer-mediated groups. Journal of Computer-Mediated Communication, 10(3). https://doi.org/10.1111/j.1083-6101.2005.tb00251.x.
OECD. (2017). Pisa 2015 collaborative problem solving framework. Retrieved from https://www.oecd.org/pisa/pisaproducts/pisa2015draftframeworks.htm.
Piper, A. M., & Hollan, J. D. (2009). Tabletop displays for small group study: Affordances of paper and digital materials. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (pp. 1227–1236). ACM. doi:https://doi.org/10.1145/1518701.1518885.
Ras, E., Krkovic, K., Greiff, S., Tobias, E., & Maquil, V. (2014). Moving towards the assessment of collaborative problem solving skills with a tangible user interface. TOJET: The Turkish Online Journal of Educational Technology, 13(4), 95–104.
R Core Team. (2017). A language and environment for statistical computing. Vienna, Austria: R Foundation for Statistical Computing. Retrieved from https://www.r-project.org/
Rick, J., & Keynes, M. (2009). Towards a classroom ecology of devices: Interfaces for collaborative scripts. In Workshop Proceedings of 8th International Conference on Computer Supported Collaborative Learning (CSCL2009): “Scripted vs. Free CS Collaboration: Alternatives and Paths for Adaptable and Flexible CS Scripted Collaboration” (p. 9). Retrieved from http://oro.open.ac.uk/19511/1/dt-cscl2009.pdf.
Rick, J., Marshall, P., & Yuill, N. (2011). Beyond one-size-fits-all:How interactive tabletops support collaborative learning. In Proceedings of the 10th International Conference on Interaction Design and Children - IDC ’11 (pp. 109–117). New York: ACM Press. doi:https://doi.org/10.1145/1999030.1999043.
Roschelle, J., & Teasley, S. D. (1995). The construction of shared knowledge in collaborative problem solving. In C. E. O’Melley (Ed.), Computer supported collaborative learning (pp. 69–97). Berlin: Springer. https://doi.org/10.1007/978-3-642-85098-1_5.
Rosen, Y. (2015). Computer-based assessment of collaborative problem solving: Exploring the feasibility of human-to-agent approach. International Journal of Artificial Intelligence in Education, 25(3), 380–406. https://doi.org/10.1007/s40593-015-0042-3.
Rummel, N., & Spada, H. (2005). Instructional support for collaboration in desktop videoconference settings. In R. Bromme, F. W. Hesse, & H. Spada (Eds.), Barriers and biases in computer-mediated knowledge communication, and how they may be overcome (pp. 59–84). New York: Springer US. https://doi.org/10.1007/0-387-24319-4_4.
Sassenberg, K., Landkammer, F., & Jacoby, J. (2014). The influence of regulatory focus and group vs. individual goals on the evaluation bias in the context of group decision making. Journal of Experimental Social Psychology, 54, 153–164. https://doi.org/10.1016/j.jesp.2014.05.009.
Scholten, L., van Knippenberg, D., Nijstad, B. a., & De Dreu, C. K. W. (2007). Motivated information processing and group decision-making: Effects of process accountability on information processing and decision quality. Journal of Experimental Social Psychology, 43(4), 539–552. https://doi.org/10.1016/j.jesp.2006.05.010.
Schulz-Hardt, S., & Mojzisch, A. (2012). How to achieve synergy in group decision making: Lessons to be learned from the hidden profile paradigm. European Review of Social Psychology, 23(1), 305–343. https://doi.org/10.1080/10463283.2012.744440.
Schulz-Hardt, S., Brodbeck, F. C., Mojzisch, A., Kerschreiter, R., & Frey, D. (2006). Group decision making in hidden profile situations: Dissent as a facilitator for decision quality. Journal of Personality and Social Psychology, 91(6), 1080–1093. https://doi.org/10.1037/0022-3514.91.6.1080.
Scoular, C., Care, E., & Hesse, F. W. (2017). Designs for operationalizing collaborative problem solving for automated assessment. Journal of Educational Measurement, 54(1), 12–35. https://doi.org/10.1111/jedm.12130.
Shen, C., Ryall, K., Forlines, C., Esenther, A., Vernier, F. D., Everitt, K., et al. (2009). Collaborative tabletop research and evaluation. In P. Dillenbourg, J. Huang, & M. Cherubini (Eds.), Interactive Artifacts and Furniture Supporting Collaborative Work and Learning (pp. 1–17). US: Springer. https://doi.org/10.1007/978-0-387-77234-9_7.
Slavin, R. E. (2011). Instruction based on cooperative learning. In R. E. Mayer & P. A. Alexander (Eds.), Handbook of research on learning and instruction (pp. 344–360). New York: Taylor & Francis.
Stahl, G., Koschmann, T., & Suthers, D. (2006). Computer-supported collaborative learning: An historical perspective. In R. K. Sawyer (Ed.), Cambridge handbook of the learning sciences (pp. 409–426). Cambridge: Cambridge University Press.
Stasser, G., & Birchmeier, Z. (2003). Group creativity and collective choice. In P. B. Paulus & B. A. Nijstad (Eds.), Group creativity: Innovation through collaboration (pp. 85–109). New York: Oxford University Press.
Stasser, G., & Titus, W. (1985). Pooling of unshared information in group decision making: Biased information sampling during discussion. Journal of Personality and Social Psychology, 48(6), 1467–1478. https://doi.org/10.1037/0022-3514.48.6.1467.
Stasser, G., Vaughan, S. I., & Stewart, D. D. (2000). Pooling unshared information: The benefits of knowing how access to information is distributed among group members. Organizational Behavior and Human Decision Processes, 82(1), 102–116. https://doi.org/10.1006/obhd.2000.2890.
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. https://doi.org/10.1007/s11412-006-9660-y.
Suthers, D. D., & Hundhausen, C. D. (2003). An experimental study of the effects of representational guidance on collaborative learning processes. The Journal of the Learning Sciences, 12(2), 183–218. https://doi.org/10.1207/S15327809JLS1202_2.
Suthers, D. D., Vatrapu, R., Medina, R., Joseph, S., & Dwyer, N. (2008). Beyond threaded discussion: Representational guidance in asynchronous collaborative learning environments. Computers in Education, 50(4), 1103–1127. https://doi.org/10.1016/j.compedu.2006.10.007.
Swaab, R. I., Galinsky, A. D., Medvec, V., & Diermeier, D. A. (2012). The communication orientation model: Explaining the diverse effects of sight, sound, and synchronicity on negotiation and group decision-making outcomes. Personality and Social Psychology Review, 16(1), 25–53. https://doi.org/10.1177/1088868311417186.
Teasley. (1997). Talking about reasoning: How important is the peer in peer collaboration? In Discourse, tools and reasoning (pp. 361–384). Berlin: Springer.
Tversky, A., & Kahneman, D. (1974). Judgment under uncertainty: Heuristics and biases. Science, 185(4157), 1124–1131.
Weaver, K., Garcia, S. M., Schwarz, N., & Miller, D. T. (2007). Inferring the popularity of an opinion from its familiarity: A repetitive voice can sound like a chorus. Journal of Personality and Social Psychology, 92(5), 821–833. https://doi.org/10.1037/0022-3514.92.5.821.
Weinberger, A., & Fischer, F. (2006). A framework to analyze argumentative knowledge construction in computer-supported collaborative learning. Computers in Education, 46(1), 71–95. https://doi.org/10.1016/j.compedu.2005.04.003.
Wittenbaum, G. M., Hollingshead, A. B., & Botero, I. C. (2004). From cooperative to motivated information sharing in groups: Moving beyond the hidden profile paradigm. Communication Monographs, 71(3), 286–310. https://doi.org/10.1080/0363452042000299894.
Author information
Authors and Affiliations
Corresponding author
Rights and permissions
About this article
Cite this article
Bause, I.M., Brich, I.R., Wesslein, AK. et al. Using technological functions on a multi-touch table and their affordances to counteract biases and foster collaborative problem solving. Intern. J. Comput.-Support. Collab. Learn 13, 7–33 (2018). https://doi.org/10.1007/s11412-018-9271-4
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s11412-018-9271-4