Enhancing learning outcomes in computer-based training via self-generated elaboration
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The present study investigated the utility of an instructional strategy known as the query method for enhancing learning outcomes in computer-based training. The query method involves an embedded guided, sentence generation task requiring elaboration of key concepts in the training material that encourages learners to ‘stop and think’ about the information already presented before proceeding to new concepts. This study also investigated the effect of varying the level of elaboration (low or high) prompted by the queries. Fifty-one undergraduate students from the general psychology department subject pool at a major university in the southeastern United States received instruction on the basic principles of flight via one of three versions of a computer-based tutorial (no query, low-level elaboration query, or high-level elaboration query). Participants had no prior knowledge or previous experience with the aviation domain. A one-way between-groups design was employed, with the query method serving as the independent variable and a sample size of 17 per condition. Dependent variables included knowledge organization, knowledge acquisition, and instructional efficiency. Overall, results showed that incorporating low-level elaboration queries into the training resulted in improved organization, integration, and application of task-relevant knowledge and higher instructional efficiency. High-level elaboration queries consistently failed to produce significantly better post-training outcomes, possibly due to the increased cognitive load imposed on learners during training. The discussion centers on theoretical and practical implications for promoting and assessing learning outcomes in computer-based training.
KeywordsCognitive load Instructional efficiency Knowledge acquisition Knowledge organization Self-generated elaboration
The views herein are those of the authors and do not necessarily reflect those of the organizations with which the authors are affiliated. The research reported in this paper is based upon the doctoral dissertation of Haydee M. Cuevas, University of Central Florida. Portions of this paper were presented at the Human Factors and Ergonomics Society 50th Annual Meeting. This research was partially supported by funding through Grant Number F49620-01-1-0214 from the Air Force Office of Scientific Research to Eduardo Salas, Stephen M. Fiore, and Clint A. Bowers.
- Chipman, S. F., Segal, J. W., & Glaser, R. (Eds.) (2013). Thinking and learning skills: Vol. 2: Research and open questions. New York, NY: Routledge–Taylor and Francis Group.Google Scholar
- Clark, R. C., Nguyen, F., & Sweller, J. (2006). Efficiency in learning: Evidence-based guidelines to manage cognitive load. San Francisco: Jossey-Bass.Google Scholar
- Cuevas, H. M., Fiore, S. M., Bowers, C. A., & Salas, E. (2004b). Using guided learner-generated instructional strategies to transform learning into a constructive cognitive and metacognitive activity. Proceedings of the 48th Annual Meeting of the Human Factors and Ergonomics Society, (pp. 1049–1053). Santa Monica, CA: Human Factors and Ergonomics Society.Google Scholar
- Fiore, S. M., & Salas, E. (Eds.). (2007). Toward a science of distributed learning. Washington, DC: American Psychological Association.Google Scholar
- Fonseca, B., & Chi, M. T. H. (2011). The self-explanation effect: A constructive learning activity. In R. E. Mayer & P. A. Alexander (Eds.), The handbook of research on learning and instruction (pp. 296–321). New York: Routledge—Taylor and Frances Group.Google Scholar
- Guilford, J. P., & Zimmerman, W. S. (1981). Manual of instructions and interpretations for the Guilford-Zimmerman Aptitude Survey (revised ed.). Palo Alto, CA: Consulting Psychological Press.Google Scholar
- Gully, S., & Chen, G. (2010). Individual differences, attribute-treatment interactions, and training outcomes. In S. W. J. Kozlowski & E. Salas (Eds.), Learning, training, and development in organizations (pp. 3–64). New York: Routledge–Taylor and Francis Group.Google Scholar
- Hermanson, D. R., Hermanson, H. M., & Tompkins, J. G, I. V. (1997). The impact of self-generated elaboration on students’ recall of finance concepts. Journal of Financial Education (Fall), 23, 27–34.Google Scholar
- Jeppesen Sanderson Training Systems. (1996a). Jeppesen Sanderson Private Pilot Exercises Book. Englewood, CO: Jeppesen Sanderson Inc.Google Scholar
- Jeppesen Sanderson Training Systems. (1996b). Jeppesen Sanderson Private Pilot Maneuvers Manual (6th ed.). Englewood, CO: Jeppesen Sanderson Inc.Google Scholar
- Jeppesen Sanderson Training Systems. (1996c). Jeppesen Sanderson Private Pilot Manual (15th ed.). Englewood, CO: Jeppesen Sanderson Inc.Google Scholar
- Kirwan, B., Evans, A., Donohoe, L., Kilner, A., Lamoureux, Atkinson, T. & MacKendrick, H. (1997). Human factors in the ATM system design life cycle. In Paper presented at the FAA/Eurocontrol ATM R&D Seminar, Paris, France, 16–20 June 1997. Retrieved from http://www.atmseminar.org/seminarContent/seminar1/papers/p_007_CDR.pdf. Accessed 19 Jan 2012.
- Mayer, R. E., Hegarty, M., Mayer, S., & Campbell, J. (2005). When static media promote active learning: Annotated illustrations versus narrated animations in multimedia instruction. Journal of Experimental Psychology: Applied, 11(4), 256–265.Google Scholar
- Paas, F. G. W. C., & van Merrienboer, J. J. G. (1993). The efficiency of instructional conditions: An approach to combine mental effort and performance measures. Human Factors, 35, 737–743.Google Scholar
- Salas, E., & Rosen, M. A. (2010). Experts at work: Principles for developing expertise in organizations. In S. W. J. Kozlowski & E. Salas (Eds.), Learning, training, and development in organizations (pp. 99–134). New York: Routledge–Taylor and Francis Group.Google Scholar
- Scielzo, S., Cuevas, H. M, & Fiore, S. M. (2005). Investigating individual differences and instructional efficiency in computer-based training environments. Proceedings of the Human Factors and Ergonomics Society 49th Annual Meeting (pp. 1251–1255). Santa Monica, CA: Human Factors and Ergonomics Society.Google Scholar
- Scielzo, S., Fiore, S. M., Cuevas, H. M., & Salas, E. (2004). Diagnosticity of mental models in cognitive and metacognitive processes: Implications for synthetic task environment training. In S. G. Schiflett, L. R. Elliott, E. Salas, & M. D. Coovert (Eds.), Scaled worlds: Development, validation, and applications (pp. 181–199). Aldershot, UK: Ashgate.Google Scholar