An evaluation of interactive tabletops in elementary mathematics education

  • Alexander T. JacksonEmail author
  • Bradley J. Brummel
  • Cody L. Pollet
  • David D. Greer
Research Article


This research examined the effect that a relatively new Computer Supported Collaborative Learning (CSCL) device, specifically an interactive tabletop, has on elementary students’ attitudes toward collaborative technologies, mathematical achievement, and the gender gap in mathematics. Prior research has shown many positive effects of CSCL technologies on mathematics education, such as increased math performance and an increased interest in math. Further, previous research has shown inconsistent results regarding gender differences in mathematics and has not examined the effect that CSCL technology has on the gender gap. Therefore, the effects of interactive tabletops on math performance, attitudes, and gender differences were examined. This study was conducted using a sample of 53 elementary students. The technology was brought to the classroom twice each week for an entire academic semester. To obtain a more accurate understanding of the influence of the CSCL technology, both self-report data and performance data were collected. Specifically, changes in students’ attitudes and reactions and changes in cognitive learning were measured. The results show that students learn and react favorably towards interactive tabletops. Implications for future research are discussed.


Computer Supported Collaborative Learning Mathematics Elementary students Gender differences Interactive tabletops 



This material is based on research sponsored by Defense Advanced Research Projects Agency (DARPA) under agreement number FA8750-09-1-0208. The U.S. Government is authorized to reproduce and distribute reprints for Governmental purposes notwithstanding any copyright notation thereon. The views and conclusions contained herein are those of the authors and should not be interpreted as necessarily representing the official policies or endorsements, either expressed or implied, of DARPA or the U.S. Government. The authors would like to thank Joseph Mazzola, Courtney Nelson, Kelsey Parker, Lauren Robertson, and Mathias Simmons for their helpful comments and suggestions. The authors would also like to thank Annalise Brady and Liang Kong for their contributions in designing the educational game and providing technical support.


  1. Alvarez, K., Salas, E., & Garofano, C. M. (2004). An integrated model of training evaluation and effectiveness. Human Resource Development Review, 3(4), 385–416. doi: 10.1177/1534484304270820.CrossRefGoogle Scholar
  2. Arroyo, I., Royer, J. M., & Woolf, B. P. (2011). Using an intelligent tutor and math fluency training to improve math performance. International Journal of Artificial Intelligence in Education, 21, 135–152. doi: 10.3233/jai-2011-020.Google Scholar
  3. Beltran, D. O., Das, K. K., & Fairlie, R. W. (2008). Are computers good for children? The effects of home computers on educational outcomes. Centre for Economic Policy Research, Research School of Economics, Australian National University.Google Scholar
  4. Chan, C. K. K., & Van Aalst, J. (2004). Learning, assessment and collaboration in computer-supported environments. In J. W. Strijbos, P. A. Kirschner, & R. L. Martens (Eds.), What we know about CSCL: And implementing it in higher education (pp. 87–112). USA: Kluwer Academic Publishers.CrossRefGoogle Scholar
  5. Cho, H., Gay, G., Davidson, B., & Ingraffea, A. (2007). Social networks, communication styles, and learning performance in a CSCL community. Computers & Education, 49(2), 309–329. doi: 10.1016/j.compedu.2005.07.003.CrossRefGoogle Scholar
  6. Coleman-Martin, M. B., Heller, K. W., Cihak, D. F., & Irvine, K. L. (2005). Using computer-assisted instruction and the nonverbal reading approach to teach word identification. Focus on Autism & Other Developmental Disabilities, 20(2), 80–90.CrossRefGoogle Scholar
  7. Crombie, G., Sinclair, N., Silverthorn, N., Byrne, B. M., DuBois, D. L., & Trinneer, A. (2005). Predictors of young adolescents? Math grades and course enrollment intentions: Gender similarities and differences. Sex Roles, 52(5–6), 351–367. doi: 10.1007/s11199-005-2678-1.CrossRefGoogle Scholar
  8. Daft, R. L., & Lengel, R. H. (1984). Information richness: A new approach to managerial behavior and organization design. In B. M. Staw & L. L. Cummings (Eds.), Research in organizational behavior (Vol. 6, pp. 191–233). Greenwich, CT: JAI Press Inc.Google Scholar
  9. Diekman, A. B., Brown, E. R., Johnston, A. M., & Clark, E. K. (2010). Seeking congruity between goals and roles: A new look at why women opt out of science, technology, engineering, and mathematics careers. [Research Support, U.S. Gov’t, Non-P.H.S.]. Psychological Science, 21(8), 1051–1057. doi: 10.1177/0956797610377342.CrossRefGoogle Scholar
  10. Dillenbourg, P., & Evans, M. (2011). Interactive tabletops in education. International Journal of Computer Supported Collaborative Learning, 6, 491–514. doi: 10.1007/s11412-011-9127-7.CrossRefGoogle Scholar
  11. Ding, N., Bosker, R. J., & Harskamp, E. G. (2011). Exploring gender and gender pairing in the knowledge elaboration processes of students using computer-supported collaborative learning. Computers & Education, 56(2), 325–336. doi: 10.1016/j.compedu.2010.06.004.CrossRefGoogle Scholar
  12. Duhon, G. J., House, S. H., & Stinnett, T. A. (2012). Evaluating the generalization of math fact fluency gains across paper and computer performance modalities. Journal of School Psychology, 50(3), 335–345. doi: 10.1016/j.jsp.2012.01.003.CrossRefGoogle Scholar
  13. Evans, M. A., Feenstra, E., Ryon, E., & McNeill, D. (2011). A multimodal approach to coding discourse: Collaboration, distributed cognition, and geometric reasoning. International Journal of Computer-Supported Collaborative Learning, 6(2), 253–278. doi: 10.1007/s11412-011-9113-0.CrossRefGoogle Scholar
  14. Francescato, D., Porcelli, R., Mebane, M., Cuddetta, M., Klobas, J., & Renzi, P. (2006). Evaluation of the efficacy of collaborative learning in face-to-face and computer-supported university contexts. Computers in Human Behavior, 22(2), 163–176. doi: 10.1016/j.chb.2005.03.001.CrossRefGoogle Scholar
  15. Gomez, E. A., Wu, D., & Passerini, K. (2010). Computer-supported team-based learning: The impact of motivation, enjoyment and team contributions on learning outcomes. Computers & Education, 55(1), 378–390. doi: 10.1016/j.compedu.2010.02.003.CrossRefGoogle Scholar
  16. Gress, C. L. Z., Fior, M., Hadwin, A. F., & Winne, P. H. (2010). Measurement and assessment in computer-supported collaborative learning☆. Computers in Human Behavior, 26(5), 806–814. doi: 10.1016/j.chb.2007.05.012.CrossRefGoogle Scholar
  17. Groff, J., & Mouza, C. (2008). A framework for addressing challenges to classroom technology use. AACE Journal, 16(1), 21–46.Google Scholar
  18. Groves, S. (n.d.). District Benchmark Assessment Program. Retrieved from
  19. Gweon, G., Rosé, C. P., Albright, E., & Cui, Y. (2006). Help providers and help receivers in a computer supported collaborative learning environment. Paper presented at the Computer Supported Cooperative Work, Banff, Alberta, Canada.Google Scholar
  20. 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. doi: 10.1007/s11412-011-9131-y.CrossRefGoogle Scholar
  21. Hwang, W.-Y., Chen, N.-S., & Hsu, R.-L. (2006). Development and evaluation of multimedia whiteboard system for improving mathematical problem solving. Computers & Education, 46(2), 105–121. doi: 10.1016/j.compedu.2004.05.005.CrossRefGoogle Scholar
  22. Hyde, J. S. (1981). How large are cognitive gender differences: A meta-analysis using ω2 and d. American Psychologist, 36(8), 892–901.CrossRefGoogle Scholar
  23. Jones, M. H., Audley-Piotrowski, S. R., & Kiefer, S. M. (2012). Relationships among adolescents’ perceptions of friends’ behaviors, academic self-concept, and math performance. Journal of Educational Psychology, 104(1), 19–31. doi: 10.1037/a0025596.CrossRefGoogle Scholar
  24. Kang, H. W., & Zentall, S. S. (2011). Computer-generated geometry instruction: A preliminary study. Educational Technology Research and Development, 59(6), 783–797. doi: 10.1007/s11423-011-9186-5.CrossRefGoogle Scholar
  25. Kennedy, D. M., Vozdolska, R. R., & McComb, S. A. (2010). Team decision making in computer-supported cooperative work: How initial computer-mediated or face-to-face meetings set the stage for later outcomes. Decision Sciences, 41(4), 933–954.CrossRefGoogle Scholar
  26. Knowledge Adventure. (2010). Math Blaster. Torrance, CA: Knowledge Holdings, Incorporated.Google Scholar
  27. Kock, N., Garza, V., & Rangel, M. (2009). Media naturalness reduction and compensatory channel expression: A study of online and face-to-face sections of the same course. Paper presented at the International Conference on Information Resources Management.Google Scholar
  28. Kolloffel, B., Eysink, T. H. S., & Jong, T. (2011). Comparing the effects of representational tools in collaborative and individual inquiry learning. International Journal of Computer-Supported Collaborative Learning, 6(2), 223–251. doi: 10.1007/s11412-011-9110-3.CrossRefGoogle Scholar
  29. Kraiger, K. (2008). Transforming our models of learning and development: Web-based instruction as enabler of third-generation instruction. Industrial and Organizational Psychology, 1, 454–467.CrossRefGoogle Scholar
  30. Kreijns, K., Kirschner, P. A., & Jochems, W. (2003). Identifying the pitfalls for social interaction in computer-supported collaborative learning environments: A review of the research. Computers in Human Behavior, 19, 335–353.CrossRefGoogle Scholar
  31. Lever, J. (1978). Sex differences in the complexity of children’s play and games. American Sociological Review, 43(4), 471–483.CrossRefGoogle Scholar
  32. Lindberg, S. M., Hyde, J. S., Petersen, J. L., & Linn, M. C. (2010). New trends in gender and mathematics performance: A meta-analysis. Psychological Bulletin, 136(6), 1123–1135. doi: 10.1037/a0021276.CrossRefGoogle Scholar
  33. Liu, O. L., & Wilson, M. (2009). Gender differences in large-scale math assessments: PISA trend 2000 and 2003. Applied Measurement in Education, 22(2), 164–184. doi: 10.1080/08957340902754635.CrossRefGoogle Scholar
  34. Maccoby, E. E., & Jacklin, C. N. (1974). The psychology of sex differences. Stanford, CA: Stanford University Press.Google Scholar
  35. Marjanovic, O. (1999). Learning and teaching in a synchronous collaborative environment. Journal of Computer Assisted Learning, 15, 129–138.CrossRefGoogle Scholar
  36. McGraw, R., Lubienski, S. T., & Strutchens, M. E. (2006). A closer look at gender in NAEP mathematics achievement and affect data: Intersections with achievement, race/ethnicity, and socioeconomic status. Journal for Research in Mathematics Education, 37(2), 129–150.Google Scholar
  37. Miller, D., Glover, D., & Averis, D. (2004). Motivation: The contribution of interactive whiteboards to teaching and learning in mathematics. Retrieved from
  38. Mohammed, A. A., & Kanpolat, Y. E. (2010). Effectiveness of computer-assisted instruction on enhancing the classification skill in second-graders at risk for learning disabilities. Electronic Journal of Research in Educational Psychology, 8(3), 1115–1130.Google Scholar
  39. Ota, K. R., & DuPaul, G. J. (2002). Task engagement and mathematics performance in children with attention-deficit hyperactivity disorder: Effects of supplemental computer instruction. School Psychology Quarterly, 17(3), 242–257.CrossRefGoogle Scholar
  40. Prinsen, F., Volman, M., Terwel, J., & Vandeneeden, P. (2009). Effects on participation of an experimental CSCL-programme to support elaboration: Do all students benefit? Computers & Education, 52(1), 113–125. doi: 10.1016/j.compedu.2008.07.001.CrossRefGoogle Scholar
  41. Richtel, M. (2011). In classroom of future, stagnant scores. The New York Times. Google Scholar
  42. Rick, J., Marshall, P., & Yuill, N. (2011). Beyond one-size-fits-all: How interactive tabletops support collaborative learning. Paper presented at the 5th International Symposium on Intelligent Distributed Computing, Delft, the Netherlands.Google Scholar
  43. Rinn, A. N., McQueen, K. S., Clark, G. L., & Rumsey, J. L. (2008). Gender differences in gifted adolescents’ math/verbal self-concepts and math/verbal achievement: Implications for the STEM fields. Journal for the Education of the Gifted, 32(1), 34–53.Google Scholar
  44. Robinson, J. P., & Lubienski, S. T. (2011). The development of gender achievement gaps in mathematics and reading during elementary and middle school: Examining direct cognitive assessments and teacher ratings. American Educational Research Journal, 48(2), 268–302. doi: 10.3102/0002831210372249.CrossRefGoogle Scholar
  45. Rogers, Y., Lim, Y., Hazlewood, W., & Marshall, P. (2009). Equal opportunities: Do shareable interfaces promote more group participation than single user displays? Human-Computer Interaction, 24(1), 79–116. doi: 10.1080/07370020902739379.CrossRefGoogle Scholar
  46. Rogers, Y., & Lindley, S. (2004). Collaborating around vertical and horizontal large interactive displays: Which way is best? Interacting with Computers, 16(6), 1133–1152. doi: 10.1016/j.intcom.2004.07.008.CrossRefGoogle Scholar
  47. Rosselli, M., Ardila, A., Matute, E., & Inozemtseva, O. (2009). Gender differences and cognitive correlates of mathematical skills in school-aged children. Child Neuropsychology: A Journal on Normal and Abnormal Development in Childhood and Adolescence, 15(3), 216–231. doi: 10.1080/09297040802195205.Google Scholar
  48. Scafidi, T., & Bui, K. (2010). Gender similarities in math performance from middle school through high school. Journal of Instructional Psychology, 37(3), 252–255.Google Scholar
  49. Schellens, T., & Valcke, M. (2005). Collaborative learning in asynchronous discussion groups: What about the impact on cognitive processing? Computers in Human Behavior, 21(6), 957–975. doi: 10.1016/j.chb.2004.02.025.CrossRefGoogle Scholar
  50. Segal, A. (2012). Do gestural interfaces promote thinking? Embodied interaction: Congruent gestures and direct touch promote performance in math. Dissertation Abstracts International, 72(7-B), 4340–4478.Google Scholar
  51. Seo, Y.-J., & Bryant, D. P. (2009). Analysis of studies of the effects of computer-assisted instruction on the mathematics performance of students with learning disabilities. Computers & Education, 53(3), 913–928. doi: 10.1016/j.compedu.2009.05.002.CrossRefGoogle Scholar
  52. Shin, Y., & Song, K. (2011). Role of face-to-face and computer-mediated communication time in the cohesion and performance of mixed-mode groups. Asian Journal of Social Psychology, 14(2), 126–139. doi: 10.1111/j.1467-839X.2010.01341.x.CrossRefGoogle Scholar
  53. Stahl, G., Koschmann, T., & Suthers, D. D. (2006). Computer-supported collaborative learning. In R. Sawyer (Ed.), The Cambridge handbook of: The learning sciences (pp. 409–425). New York, NY: Cambridge University Press.Google Scholar
  54. Starcic, A. I., & Zajc, M. (2011). An interactive tangible user interface application for learning addition concepts. British Journal of Educational Technology, 42(6), E131–E135. doi: 10.1111/j.1467-8535.2011.01217.x.CrossRefGoogle Scholar
  55. Swan, K. (2004). Learning online: A review of current research on issues of interface, teaching presence and learner characteristics. In J. Bourne & J. C. Moore (Eds.), Elements of quality online education, into the mainstream (pp. 63–79). Needham, MA: Sloan Center for Online Education.Google Scholar
  56. Torff, B., & Tirotta, R. (2010). Interactive whiteboards produce small gains in elementary students’ self-reported motivation in mathematics. Computers & Education, 54(2), 379–383. doi: 10.1016/j.compedu.2009.08.019.CrossRefGoogle Scholar
  57. van Langen, A., Bosker, R., & Dekkers, H. (2006). Exploring cross-national differences in gender gaps in education. Educational Research and Evaluation, 12(2), 155–177. doi: 10.1080/13803610600587016.CrossRefGoogle Scholar
  58. Watt, H. M. G. (2008). What motivates females and males to pursue sex-stereotyped careers? In H. M. G. Watt & J. S. Eccles (Eds.), Gender and occupational outcomes: Longitudinal assessments of individual, social, and cultural influences (pp. 87–113). Washington, DC: American Psychological Association.CrossRefGoogle Scholar
  59. Wolfram, S. (2012). Mathematica for primary and secondary education: Wolfram Research, Incorporated. Retrieved from
  60. Zhang, D., & Nunamaker, J. F. (2003). Powering E-learning in the new millennium: An overview of E-learning and enabling technology. Information Systems Frontiers, 5(2), 207–218.CrossRefGoogle Scholar

Copyright information

© Association for Educational Communications and Technology 2013

Authors and Affiliations

  • Alexander T. Jackson
    • 1
    Email author
  • Bradley J. Brummel
    • 2
  • Cody L. Pollet
    • 3
  • David D. Greer
    • 4
  1. 1.Kansas State UniversityManhattanUSA
  2. 2.Department of PsychologyThe University of TulsaTulsaUSA
  3. 3.The Institute for Information SecurityThe University of TulsaBartlesvilleUSA
  4. 4.The Institute for Information SecurityThe University of TulsaTulsaUSA

Personalised recommendations