International Science Index


Role of Feedbacks in Simulation-Based Learning

Abstract:Feedback is a vital element for improving student learning in a simulation-based training as it guides and refines learning through scaffolding. A number of studies in literature have shown that students’ learning is enhanced when feedback is provided with personalized tutoring that offers specific guidance and adapts feedback to the learner in a one-to-one environment. Thus, emulating these adaptive aspects of human tutoring in simulation provides an effective methodology to train individuals. This paper presents the results of a study that investigated the effectiveness of automating different types of feedback techniques such as Knowledge-of-Correct-Response (KCR) and Answer-Until- Correct (AUC) in software simulation for learning basic information technology concepts. For the purpose of comparison, techniques like simulation with zero or no-feedback (NFB) and traditional hands-on (HON) learning environments are also examined. The paper presents the summary of findings based on quantitative analyses which reveal that the simulation based instructional strategies are at least as effective as hands-on teaching methodologies for the purpose of learning of IT concepts. The paper also compares the results of the study with the earlier studies and recommends strategies for using feedback mechanism to improve students’ learning in designing and simulation-based IT training.
[1] McCrea, F., Gay, R., & Bacon, R. (2000). Riding the big waves: A white paper on B2B e-learning industry. San Francisco, CA: Thomas Weisel.
[2] Bell, B., Kanar, A. M., & Kozlowski, S. J. (2008). Current issues and future directions in simulation-based training. Ithaca, NY: Center for Advanced Human Resources. Cornell University.
[3] Chen, D. (2003). Uncovering the provisos behind flexible learning. Educational Technology and Society, 6(2), 25-30.
[4] Sancristobal, E., Castro, M., Martin, S., & Tawkif, M. (2011, April). Remote labs as learning services in the educational arena. Paper presented at the Global Engineering Education Conference, Amman, Jordan.
[5] Gillet, D., Ngoc, A. V., & Rekik, Y. (2005). Collaborative web-based experimentation in flexible engineering education. IEEE Transactions on Education, 48(4), 696-704.
[6] Schiflett, S. G., Elliott, L. R., Salas, E., & Coovert, M. D., (Eds.). (2004). Scaled worlds: Development validation, and application. Surrey, England, Ashgate Publishing Limited, 75-99.
[7] Steele-Johnson, D., & Hyde, B. G. (1997). Advanced technologies in training: Intelligent tutoring systems and virtual reality. In M. A. Quiñones & A. Ehrenstein (Eds.), Training for a rapidly changing workplace: Applications of psychological research, (pp. 225-248). Washington, DC: American Psychological Association.
[8] Clariana, R. B., Ross, S. M., & Morrison, G. R. (1991). The effects of different feedback strategies using computer-administered multiplechoice questions as instruction. Educational Technology Research and Development, 39(2), 5-17.
[9] Institute for Creative Technologies. (2009). Intelligent guided experiential learning: Tutoring for practice. Retrieved from
[10] Cuevas, H. M., Fiore, S. M., Bowers, C. A., & Salas, E. (2004). Fostering constructive cognitive and metacognitive activity in computerbased complex task training environments. Computers in Human Behavior, 20(2), 225-241.
[11] Azevedo, R., & Bernard, R. M. (1995). A meta analysis of the effects of feedback in computer-based instruction. Journal of Educational Computer Research, 13(2), 111-127.
[12] Morrison, G. R., Ross, S. M., Gopalakrishnan, M., & Casey, J. (1995). The effects of feedback and incentives on achievement in computerbased instruction. Contemporary Educational Psychology, 20(1), 32-50.
[13] Clariana, R. B. (1993). A Review of Multiple-Try Feedback in Traditional and Computer-Based Instruction. Journal of Computer- Based Instruction, 20, 67-74.
[14] Clariana, R. B. (1990). A comparison of answer-until-correct feedback and knowledge-of- correct-response feedback under two conditions of contextualization. Journal of Computer-Based Instruction, 17(4), 125- 129.
[15] Moreno, R. (2004). Decreasing cognitive load for novice students: Effects of explanatory versus corrective feedback in discovery-based multimedia. Instructional Science, 32(1-2), 99-113.
[16] Agina, A. M., Komers, P., & Steehouder, M. (2011). The effect of the nonhuman external regulator’s AUC versus KCR task feedback on children’s behavioral regulation during learning tasks. Computers in Human Behavior, 27(5), 1710‐1723.
[17] Kalyuga, S. (2006). Assessment of learners’ organized knowledge structures in adaptive learning environments. Applied Cognitive Psychology, 20(3), 333-342.
[18] Wood, D., Bruner, J. S., & Ross, G. (1976). The role of tutoring in problem solving. Journal of Child Psychology and Psychiatry, 17(2), 89-100.
[19] Sherin, B., Reiser, B. J., & Edelson, D. (2004). Scaffolding analysis: Extending the scaffolding metaphor to learning artifacts. Journal of Learning Sciences, 13(3), 387-421.
[20] Jackson, S. L., Krajcik, J., & Soloway, E. (1998). The design of guided learner-adaptable scaffolding in interactive learning environments. Proceeding of the SIGCHI Conference on Human Factors in Computer Systems (pp. 187-194). New York, NY: Addison-Wesley Publishing.
[21] Hannafin, M. J. & Hooper, S. R. (1993). Learning principles. In M. L. Fleming & W. H. Levie (Eds.), Instructional message design: Principles from the behavioral and cognitive sciences (pp. 191-231). Englewood Cliffs, NJ: Educational Technology Publications.
[22] Linton, F. (2000). The Intranet: An Open Learning Environment. Retrieved from http:// 2000/paper/poster4/ws2-poster-4.htm
[23] Jaehnig, W., & Miller, M. L. (2007). Feedback types in programmed instructions: A systematic review, Psychological Record, 57(2), 219- 232.
[24] Bruning, R., & Mason, B. J. (2001). Providing feedback in computerbased instruction: What the research tells us. Retrieved from MasonBruning
[25] Narciss, S. (2008). Feedback strategies for interactive learning tasks. In J. M. Spector, M. D. Merrill, J. Van Merriënboer, & M. P. Driscoll (Eds.), Handbook of research on educational communications and technology (pp. 125-144). New York, NY: Lawrence Erlbaum.
[26] Corter, J., Nickerson, J., Esche, S., Chassapis, C., Im, S., & Ma, J. (2007). Constructing reality: A study of remote, hands-on, and simulated laboratories. ACM Transactions on Computer-Human Interaction, 14(2), 17-37.
[27] Tavakol, M., & Dennick, R. (2011). Making sense of Cronbach's alpha. International Journal of Medical Education, 2, 53-55.