Effects of computer support,collaboration, and time lag on performance self-efficacy and transfer of training: A longitudinal meta-analysis |
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| Institution: | 1. TUM School of Education, Technical University of Munich, Schellingstr. 33, D-80799 Munich, Germany;2. Centre for Learning Research, University of Turku, Assistentinkatu 5, FI-20014 Turku, Finland;1. Graduate Institute of Science Education, National Taiwan Normal University, Taiwan;2. Science Education Center, National Taiwan Normal University, Taiwan;3. Graduate Institute of Curriculum and Instruction, Tamkang University, Taiwan;4. Department of Earth Sciences, National Taiwan Normal University, Taiwan;1. Australian Catholic University, Institute for Learning Sciences & Teacher Education, 115 Victoria Parade, Fitzroy, VIC, 3065, Australia;2. University of Oxford, Department of Education, 15 Norham Gardens, Oxford, OX2 6PY, UK;3. Monash University, Faculty of Education, Wellington Road, Clayton, Victoria, 3800, Australia;4. Deakin University, Faculty of Arts and Education, SoE Arts and Education, 75 Pidgons Road, Waurn Ponds, Victoria, 3216, Australia;5. Health and Social Care Improvement and Implementation Science, Health and Social Care Unit, 553 St Kilda Road, School of Public Health and Preventive Medicine Monash University, Melbourne, VIC, 3004, Australia;1. University of Michigan – Flint, 2145 Riverfront Ctr W., Flint, MI 48502, USA;2. Copenhagen Business School, Howitzvej 60, 2000 Frederiksberg, Denmark;3. The University of Virginia, 125 Ruppel Dr, Charlottesville, VA 22903, USA |
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| Abstract: | This meta-analysis (29 studies, k = 33, N = 4158) examined the longitudinal development of the relationship between performance self-efficacy and transfer before and after training. A specific focus was on training programs that afforded varying degrees of computer-supported collaborative learning (CSCL). Consistent with social cognitive theory, results suggested positive population correlation estimates between self-efficacy and transfer before (ρ = 0.31) and after (ρ = 0.39) training, and thus a small but positive increase. Three boundary conditions were estimated. First, effect sizes were higher in trainings with rather than without computer support. Second, effect sizes were higher in trainings without rather than with collaboration. Third, time lag had marginal effects. These findings are discussed in terms of their implications for theories of complex social and computer-mediated learning environments and their practical significance for scaffolding technology-enhanced learning and interaction. |
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