Students’ Use Intention and Behavior Toward Knowledge Forum: A Survey Study from the Perspective of Diffusion of Innovation Theory

  • Yibo Fan
  • Shuhong GongEmail author
Conference paper
Part of the Communications in Computer and Information Science book series (CCIS, volume 1048)


Numerous studies have been conducted on knowledge forum (KF), however, the majority of these studies are on the application of KF. Few studies investigated the factors that affect the wide use of knowledge forum from the perspective of Diffusion of Innovation Theory (DIT). The aim of this study is to investigate students’ use intention and behavior on knowledge forum using DIT and extended Technology Acceptance Model (TAM). An online survey was administered to a sample of 150 students who had been using the knowledge forum. Exploratory factor analysis using Amos was utilized to examine the fitness and the construct validity of the research model. Structural equation modeling (SEM) was adopted to examine whether the factor loadings for the 8 elements were significant and whether the estimates for each of them were in a reasonable range. The research findings have implications for the development, management, and spread of KF in practice.


Knowledge forum Knowledge building Use intention Diffusion of innovation theory 


  1. Van Aalst, J., Chan, C.K.K., Taylor, P., Van Aalst, J., Chan, C.K.K.: Student-directed assessment of knowledge building using electronic portfolios. JSTOR 16(2), 175–220 (2017)Google Scholar
  2. Barrett, P.: Structural equation modelling: adjudging model fit. Personality Individ. Differ. 42(5), 815–824 (2007)MathSciNetCrossRefGoogle Scholar
  3. Bereiter, C., Scardamalia, M.: Learning to work creatively with knowledge. In: De Corte, E., Verschaffel, L., Entwistle, N., van Merriënboer, J. (eds.) Powerful Learning Environments: Unravelling Basic Components and Dimensions. Pergamon/Elsevier Science Ltd., Oxford (2003)Google Scholar
  4. Bereiter, C., Scardamalia, M.: Knowledge building and knowledge creation: one concept, two hills to climb. In: Tan, S.C., So, H.J., Yeo, J. (eds.) Knowledge Creation in Education, pp. 35–52. Springer, Singapore (2014). Scholar
  5. Camarero, C., Rodríguez, J., San José, R.: An exploratory study of online forums as a collaborative learning tool. Online Inf. Rev. 36(4), 568–585 (2012). Scholar
  6. Cheng, G.: Exploring factors influencing the acceptance of visual programming environment among boys and girls in primary schools. Comput. Hum. Behav. 92, 361–372 (2019).
  7. Chin, W.W.: The partial least squares approach to structural equation modeling. In: Marcoulides, G.A. (ed.) Modern Methods for Business Research, pp. 295–336. Erlbaum, Mahwah (1998)Google Scholar
  8. Davis, F.D.: Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Q. 13(3), 319–340 (1989)CrossRefGoogle Scholar
  9. Davis, F.D., Bagozzi, R.P., Warshaw, P.R.: User acceptance of computer technology: a comparison of two theoretical models. Manage. Sci. 35(8), 982–1003 (1989)CrossRefGoogle Scholar
  10. Deng, X., Doll, W.J., Hendrickson, A.R., Scazzero, J.A.: A multi-group analysis of structural invariance: an illustration using the technology acceptance model. Inf. Manag. 42, 745–759 (2005). Scholar
  11. DeVellis, R.F.: Scale Development: Theory and Applications, 4th edn. Sage Publications, Thousand Oaks (2016)Google Scholar
  12. Elyazgi, M.G., Nilashi, M., Ibrahim, O., Rayhan, A., Elyazgi, S.: Evaluating the factors influencing E-book technology acceptance among school children using TOPSIS technique. J. Soft Comput. Decis. Support Syst. 3(2), 11–25 (2016)Google Scholar
  13. Fishbein, M., Ajzen, I.: Belief, Attitude, Intention and Behavior: An Introduction to Theory and Research. Addison-Wesley, Reading (1975)Google Scholar
  14. Helitzer, D., Heath, D., Maltrud, K., Sullivan, E., Alverson, D.: Assessing or predicting adoption of telehealth using the diffusion of innovations theory: a practical example from a rural program in New Mexico. Telemed. J. E-Health 9(2), 179–187 (2003). Scholar
  15. Hong, H.Y., Scardamalia, M., Messina, R., Teo, C.L.: Fostering sustained idea improvement with principle-based knowledge building analytic tools. Comput. Educ. 89, 91–102 (2015). Scholar
  16. Hu, L., Bentler, P.M.: Cutoff criteria for fit indexes in covariance structure analysis: conventional criteria versus new alternatives. Struct. Equ. Model. Multi. J. 6(1), 1–55 (1999). Scholar
  17. Kenny, D.A.: Measuring model fit (2014).
  18. Lee, E.Y.C., Chan, C.K.K., Van Aalst, J.: Students assessing their own collaborative knowledge building. Int. J. Comput. Support. Collaborative Learn. 1(1), 57–87 (2006). Scholar
  19. Moore, G.C., Benbasat, I.: Integrating Diffusion of Innovations and Theory of Reasoned Action models to predict utilization of information technology by end-users. In: Kautz, K., Pries-Heje, J. (eds.) Diffusion and Adoption of Information Technology, 1st edn., pp. 132–146. Chapman and Hall, London (1996)CrossRefGoogle Scholar
  20. Mustonen-Ollila, E., Lyytinen, K.: Why organizations adopt information system process innovations: a longitudinal study using diffusion of innovation theory. Inform. Syst. J. 13(3), 275–297 (2003). Scholar
  21. Norton, J.A., Bass, F.M.: A diffusion theory model of adoption and substitution for successive generations of high-technology products. Manage. Sci. 33(9), 1069–1086 (1987)CrossRefGoogle Scholar
  22. Piaget, J.: The Origins of Intelligence in Children. International Universities Press, New York (1952)CrossRefGoogle Scholar
  23. Piaget, J.: The Construction of Reality in the Child. Routledge and Kegan Paul, London (1957)Google Scholar
  24. Rogers, E.M.: Diffusion of Innovations, 5th edn. Free Press, New York (2003)Google Scholar
  25. Scardamalia, M.: Collective cognitive responsibility for the advancement of knowledge. In: Smith, B. (ed.) Liberal Education in a Knowledge Society, pp. 76–98. Open Court, Chicago (2002)Google Scholar
  26. Scardamalia, M.: CSILE/knowledge forum. In: Kovalchick, A., Dawson, K. (eds.) Education and Technology: An Encyclopedia, pp. 183–192. ABC-Clio Inc., Santa Barbara (2003)Google Scholar
  27. Scardamalia, M., Bereiter, C.: Higher levels of agency for children in knowledge building: a challenge for the design of new knowledge media. J. Learn. Sci. 1(1), 37–68 (1991)CrossRefGoogle Scholar
  28. Scardamalia, M., Bereiter, C.: Knowledge building environments: extending the limits of the possible in education and knowledge work. Encycl. Distrib. Learn. 17(Suppl. 3, Learning Technology Innovation in Canada), 1–10 (2003).
  29. Scardamalia, M., Bereiter, C.: Knowledge building: theory, pedagogy, and technology. In: Sawyer, R.K. (ed.) Cambridge Handbook of the Learning Sciences, 1st edn., pp. 97–118. Cambridge University Press, New York.
  30. Scardamalia, M., Bereiter, C., McLean, R.S., Swallow, J., Woodruff, E.: Computer-supported intentional learning environments. J. Educ. Comput. Res. 5(1), 51–68 (1989)CrossRefGoogle Scholar
  31. Shroff, R.H., Deneen, C.C., Ng, E.M.W.: Analysis of the technology acceptance model in examining students’ behavioural intention to use an e- portfolio system. Australas. J. Educ. Technol. 27(4), 600–618 (2011)CrossRefGoogle Scholar
  32. Sivo, S.A.: Understanding how university student perceptions of resources affect technology acceptance in online learning courses. Australas. J. Educ. Technol. 34(4), 72–92 (2018)Google Scholar
  33. Tan, S.C., Seah, L.H.: Exploring relationship between students’ questioning behaviors and inquiry tasks in an online forum through analysis of ideational function of questions. Comput. Educ. 57(2), 1675–1685 (2011). Scholar
  34. Venkatesh, V., Davis, F.D.: A model of the antecedents of perceived ease of use: development and test. Decis. Sci. 27(3), 451–481 (1996). Scholar
  35. Yang, S., Kwok, D.: A study of students’ attitudes towards using ICT in a social constructivist environment. Australas. J. Educ. Technol. 33(5), 50–63 (2017)Google Scholar
  36. Zacharis, N.Z.: Predicting college students’ acceptance of podcasting as a learning tool. Interact. Technol. Smart Educ. 9(3), 171–183 (2012). Scholar
  37. Zhang, J., Scardamalia, M., Reeve, R., Messina, R.: Designs for collective cognitive responsibility in knowledge-building communities. J. Learn. Sci. 18(1), 7–44 (2009). Scholar

Copyright information

© Springer Nature Singapore Pte Ltd. 2019

Authors and Affiliations

  1. 1.College of EducationBoise State UniversityBoiseUSA
  2. 2.College of Journalism and CommunicationShandong Normal UniversityJinanPeople’s Republic of China

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