Journal of Computing in Higher Education

, Volume 27, Issue 3, pp 215–239 | Cite as

Assessing learners’ perceived readiness for computer-supported collaborative learning (CSCL): a study on initial development and validation

  • Yao Xiong
  • Hyo-Jeong SoEmail author
  • Yancy Toh


The main purpose of this study was to develop an instrument that assesses university students’ perceived readiness for computer-supported collaborative learning (CSCL). Assessment in CSCL research had predominantly focused on measuring “after-collaboration” outcomes and “during-collaboration” behaviors while “before-collaboration” assessment was rarely studied. Given the nature of high learner agency and self-directness necessary in CSCL contexts, it was assumed that a sufficient level of student readiness for CSCL could promote positive attitudes and behaviors during the collaborative learning process and subsequent learning outcomes. Considering the importance of a before-collaboration status, this study proposes the new notion of students’ readiness for CSCL (SR-CSCL) and presents a set of criteria to theoretically define and empirically measure the perceived level of SR-CSCL. Drawing on prior research on CSCL and readiness issues, we developed the SR-CSCL instrument with a three-dimensional framework consisting of: (a) motivation for collaborative learning, (b) prospective behaviors for collaborative learning and (c) online learning aptitude. The SR-CSCL instrument was validated with the university students in China in the pilot study (N = 120) and the main study (N = 295). Overall, the results showed some evidence of reliability and validity for the proposed instrument. This study presents an empirical assessment tool that can help instructors and researchers better understand and investigate how to assess and increase students’ readiness levels in order to enhance their learning experiences in CSCL environments.


Readiness CSCL Collaboration Online learning 



This research was conducted as the master’s thesis of the first author at the National Institute of Education, Nanyang Technological University, Singapore.

Compliance with ethical standards

Conflict of interest

We declare that there are no potential conflicts of interest.

Ethical approval

We complied with the ethical standards of research involving human subjects.

Informed consent

Informed consent was obtained from all individual participants included in the study.


  1. AERA, APA, & NCME. (2014). Standards for educational and psychological testing. Washington, DC: AERA.Google Scholar
  2. Bandura, A. (1997). Self-efficacy: The exercise of control. New York: Macmillan.Google Scholar
  3. Barron, B. (2003). When smart groups fail. The Journal of the Learning Sciences, 12(3), 307–359.CrossRefGoogle Scholar
  4. Beebe, T. J., Harrison, P. A., Sharma, A., & Hedger, S. (2001). The community readiness survey development and initial validation. Evaluation Review, 25(1), 55–71.CrossRefGoogle Scholar
  5. Blair, C. (2002). School readiness: Integrating cognition and emotion in a neurobiological conceptualization of children’s functioning at school entry. American Psychologist, 57(2), 111.CrossRefGoogle Scholar
  6. Capdeferro, N., & Romero, M. (2012). Are online learners frustrated with collaborative learning experiences? International Review of Research in Open & Distance Learning, 13(2), 26–44.Google Scholar
  7. Carey, K. B., Purnine, D. M., Maisto, S. A., & Carey, M. P. (1999). Assessing readiness to change substance abuse: A critical review of instruments. Clinical Psychology: Science and Practice, 6(3), 245–266.Google Scholar
  8. Chow, A., & Law, N. (2005). Measuring motivation in collaborative inquiry-based learning contexts. Paper presented at the proceedings of th 2005 conference on Computer support for collaborative learning: Learning 2005: The next 10 years!Google Scholar
  9. Cook, D. A., & Beckman, T. J. (2006). Current concepts in validity and reliability for psychometric instruments: Theory and application. The American Journal of Medicine, 119(2), 166.e7–166.e16.CrossRefGoogle Scholar
  10. Cronbach, L. J., & Meehl, P. E. (1955). Construct validity in psychological tests. Psychological Bulletin, 52(4), 281–302.CrossRefGoogle Scholar
  11. Deutsch, M. (2011). Interdependence and psychological orientation: Cooperation and competition (pp. 23–40). New York: Springer.Google Scholar
  12. DeVellis, R. (2011). Scale development: Theory and applications (2nd ed.). California: Sage.Google Scholar
  13. Dillenbourg, P., Järvelä, S., & Fischer, F. (2009). The evolution of research on computer-supported collaborative learning. In N. Balacheff, S. Ludvigsen, & T. d. Jong (Eds.), Technology-enhanced learning (pp. 3–19). Berlin: Springer.CrossRefGoogle Scholar
  14. Downing, S. M., & Haladyna, T. M. (2006). Handbook of test development. Mahwah, NJ: Lawrence Erlbaum Associates Publishers.Google 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.CrossRefGoogle Scholar
  16. Gress, C. L., 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.CrossRefGoogle Scholar
  17. Harasim, L., Hiltz, S. R., Teles, L., & Turoff, M. (1995). Learning networks: A field guide to teaching and learning online. Cambridge, MA: MIT Press.Google Scholar
  18. Hu, L., & Bentler, P. M. (1999). Cutoff criteria for fit indexes in covariance structure analysis: Conventional criteria versus new alternatives. Structural Equation Modeling: A Multidisciplinary Journal, 6(1), 1–55.CrossRefGoogle Scholar
  19. Hung, M.-L., Chou, C., Chen, C.-H., & Own, Z.-Y. (2010). Learner readiness for online learning: Scale development and student perceptions. Computers & Education, 55(3), 1080–1090.CrossRefGoogle Scholar
  20. Johnson, D. W., & Johnson, R. T. (1999). Making cooperative learning work. Theory into Practice, 38(2), 67–73.CrossRefGoogle Scholar
  21. Kemery, E. R. (2000). Developing on-line collaboration. In A. Aggarwal (Ed.), Web-based learning and teaching technologies: Opportunities and challenges (pp. 227–245). Hershey, PA: Idea Group Inc.CrossRefGoogle Scholar
  22. Kerr, M. S., Rynearson, K., & Kerr, M. C. (2006). Student characteristics for online learning success. The Internet and Higher Education, 9(2), 91–105.CrossRefGoogle Scholar
  23. Kim, H. K., & Bateman, B. (2007). Student characteristics and participation patterns in online discussion. Paper presented at the Society for Information Technology & Teacher Education International Conference.Google Scholar
  24. Kline, R. B. (2011). Principles and practice of structural equation modeling (3rd ed.). New York: Guilford Press.Google Scholar
  25. Kolodner, J. L., Camp, P. J., Crismond, D., Fasse, B., Gray, J., Holbrook, J., & Ryan, M. (2003). Problem-based learning meets case-based reasoning in the middle-school science classroom: Putting learning by design into practice. The Journal of the Learning Sciences, 12(4), 495–547.CrossRefGoogle Scholar
  26. Koschmann, T. (2002). Dewey’s contribution to the foundations of CSCL research. Paper presented at the proceedings of the conference on computer support for collaborative learning: Foundations for a CSCL Community.Google Scholar
  27. Kreijns, K., Kirschner, P. A., & Vermeulen, M. (2013). Social aspects of CSCL environments: A research framework. Educational Psychologist, 48(4), 229–242.CrossRefGoogle Scholar
  28. Leach, D. J., Wall, T. D., Rogelberg, S. G., & Jackson, P. R. (2005). Team autonomy, performance, and member job strain: Uncovering the teamwork KSA link. Applied Psychology: An International Review, 54(1), 1–24.CrossRefGoogle Scholar
  29. Lei, P.-W., & Wu, Q. (2007). CTTITEM: SAS macro and SPSS syntax for classical item analysis. Behavior Research Methods, 39(3), 527–530.CrossRefGoogle Scholar
  30. Marcus, B. H., Rakowski, W., & Rossi, J. S. (1992). Assessing motivational readiness and decision making for exercise. Health Psychology, 11(4), 257.CrossRefGoogle Scholar
  31. McClough, A. C., & Rogelberg, S. G. (2003). Selection in teams: An exploration of the teamwork knowledge, skills, and ability test. International Journal of Selection & Assessment, 11(1), 56–66.CrossRefGoogle Scholar
  32. McVay, M. (2000). How to be a successful distance learning student: Learning on the Internet. New York: Pearson Custom Pub.Google Scholar
  33. Miyake, N. (2007). Computer supported collaborative learning. In R. Andrews & C. Haythornthwaite (Eds.), The SAGE handbook of e-learning research (pp. 248–265). Los Angeles, CA: Sage.Google Scholar
  34. Nardi, B. A. (2005). Beyond bandwidth: Dimensions of connection in interpersonal communication. Computer Supported Cooperative Work (CSCW), 14(2), 91–130.CrossRefGoogle Scholar
  35. Olson, G. M., Teasley, S., Bietz, M. J., & Cogburn, D. L. (2002). Collaboratories to support distributed science: The example of international HIV/AIDS research. Paper presented at the proceedings of the 2002 annual research conference of the South African institute of computer scientists and information technologists on enablement through technology.Google Scholar
  36. Padilla-Meléndez, A., Garrido-Moreno, A., & Del Aguila-Obra, A. R. (2008). Factors affecting e-collaboration technology use among management students. Computers & Education, 51(2), 609–623.CrossRefGoogle Scholar
  37. Paraskeva, F., Mysirlaki, S., & Papagianni, A. (2010). Multiplayer online games as educational tools: Facing new challenges in learning. Computers & Education, 54(2), 498–505.CrossRefGoogle Scholar
  38. Phielix, C., Prins, F. J., & Kirschner, P. A. (2010). Awareness of group performance in a CSCL-environment: Effects of peer feedback and reflection. Computers in Human Behavior, 26(2), 151–161.CrossRefGoogle Scholar
  39. Pillay, H., Irving, K., & Tones, M. (2007). Validation of the diagnostic tool for assessing tertiary students’ readiness for online learning. Higher Education Research & Development, 26(2), 217–234.CrossRefGoogle Scholar
  40. Prinsen, F., Volman, M. L., & Terwel, J. (2007). The influence of learner characteristics on degree and type of participation in a CSCL environment. British Journal of Educational Technology, 38(6), 1037–1055.CrossRefGoogle Scholar
  41. Rummel, N., Spada, H., & Hauser, S. (2009). Learning to collaborate while being scripted or by observing a model. International Journal of Computer-Supported Collaborative Learning, 4(1), 69–92.CrossRefGoogle Scholar
  42. Ryan, R. M., & Deci, E. L. (2000). Intrinsic and extrinsic motivations: Classic definitions and new directions. Contemporary Educational Psychology, 25(1), 54–67.CrossRefGoogle Scholar
  43. Schoor, C., & Bannert, M. (2011). Motivation in a computer-supported collaborative learning scenario and its impact on learning activities and knowledge acquisition. Learning and Instruction, 21(4), 560–573.CrossRefGoogle Scholar
  44. Shi, Y., Frederiksen, C. H., & Muis, K. R. (2013). A cross-cultural study of self-regulated learning in a computer-supported collaborative learning environment. Learning and Instruction, 23, 52–59.CrossRefGoogle Scholar
  45. Shumar, W., & Renninger, K. (2002). Introduction: On conceptualizing community. In K. A. Renninger & W. Shumar (Eds.), Building virtual communities (pp. 1–19). Cambridge: Cambridge University Press.CrossRefGoogle Scholar
  46. Smith, P. J. (2005). Learning preferences and readiness for online learning. Educational Psychology, 25(1), 3–12.CrossRefGoogle Scholar
  47. Smith, P. J., Murphy, K. L., & Mahoney, S. E. (2003). Towards identifying factors underlying readiness for online learning: An exploratory study. Distance Education, 24(1), 57–67.CrossRefGoogle Scholar
  48. Snedecor, G., & Cochran, W. (1989). Statistical methods (8th ed.). Ames, IA: Iowa State University Press.Google Scholar
  49. Stahl, G. (2011). A view of computer-supported collaborative learning research today. Paper presented at the 2011 international conference on collaboration technologies and systems (CTS).Google Scholar
  50. 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 (Vol. 2006). Cambridge: Cambridge University Press.Google Scholar
  51. Stevens, M., & Campion, M. A. (1994). The knowledge, skill, and ability requirements for teamwork: Implications for human resource management. Journal of Management, 20(2), 503–530.CrossRefGoogle Scholar
  52. Stevens, M., & Campion, M. A. (1999). Staffing work teams: Development and validation of a selection test for teamwork settings. Journal of Management, 25(2), 207–228.CrossRefGoogle Scholar
  53. Tabachnick, B. G., & Fidell, L. S. (2001). Using multivariate statistics (4th ed.). Needham Heights, MA: Allyn and Bacon.Google Scholar
  54. Valtonen, T., Kukkonen, J., Dillon, P., & Väisänen, P. (2009). Finnish high school students’ readiness to adopt online learning: Questioning the assumptions. Computers & Education, 53(3), 742–748.CrossRefGoogle Scholar
  55. Vonderwell, S. (2004). Online learning: Student role and readiness. Turkish Online Journal of Educational Technology, 3(3), 38–42.Google Scholar
  56. Watkins, R., Leigh, D., & Triner, D. (2004). Assessing readiness for e-learning. Performance Improvement Quarterly, 17(4), 66–79.CrossRefGoogle Scholar
  57. Xie, K., Debacker, T. K., & Ferguson, C. (2006). Extending the traditional classroom through online discussion: The role of student motivation. Journal of Educational Computing Research, 34(1), 67–89.CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media New York 2015

Authors and Affiliations

  1. 1.The Pennsylvania State UniversityUniversity ParkUSA
  2. 2.Department of Creative IT EngineeringPohang University of Science and TechnologyPohangKorea
  3. 3.National Institute of EducationNanyang Technological UniversitySingaporeSingapore

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