Abstract
The quality of teachers’ knowledge about how people learn influences students’ learning outcomes. Similarly, the quality of students’ knowledge about how they learn influences their engagement in self-regulated learning and consequently, their learning achievement. There is a gap between research findings that support these two premises and teaching–learning practices in classrooms. In this paper we describe attempts to reduce this gap. In Study 1 we surveyed early adolescent students’ cognitive and metacognitive strategy use and demonstrated that students’ cognitive and metacognitive strategy knowledge has substantial room for improvement. In Studies 2 and 3 we collaborated with teachers to embed explicit cognitive and metacognitive strategy instruction, using learning protocols, into regular class lessons. Studies 2 and 3 showed that the learning protocols slipped readily into teachers’ typical lesson designs, scaffolded teachers’ delivery of strategy instruction, and scaffolded some students’ acquisition of strategy knowledge, although progress was sometimes slow. Recommendations are presented for supporting teachers and students to engage with cognitive and metacognitive strategy instruction.
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Notes
The Year 7 students were temporarily attending the secondary schools as part of the transition program.
The Index of Educational Disadvantage was developed using a combination of Education Department and Australian Bureau of Statistics data. It groups all schools into one of seven ranks of educational disadvantage based on four measures: parental income; parental education and occupation; Aboriginality; and student mobility.
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Acknowledgments
This project was funded by an Australian Research Council Linkage Grant 2007–2009. Partners in the grant included Flinders University, the South Australian Department of Education and Children’s Services, Aberfoyle Park High School, Blackwood High School, Christies Beach High School and Flagstaff Primary School. Approval for this project was granted by the Flinders University Social and Behavioural Research Ethics Committee and the South Australian Department of Education and Children’s Services.
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Appendix
Confirmatory factor analysis (CFA) of the cognitive and metacognitive factors
Missing values were replaced using normal expectation–maximisation in PASW 17.0. Split-half analysis provided support for each of the one factor congeneric models. CFA of the Cognitive factor suggested that two items, q.14 & q.15 (i.e. “I draw pictures or diagrams to help me understand this subject” and “I make up questions that I try to answer about this subject”) had poor loadings on the latent factor and would probably be reflective of another sub-factor. While a re-specification of the model with q.14 & q.15 loading separately onto a separate factor suggested that this would be a better model, the reliability of each of the two sub- factors was inadequate for further statistical analyses using these factors as two composite variables (two-item factor Coefficient H = .60; three-item factor Coefficient H = .71). A decision was made to keep the more reliable (Coefficient H = .76) 5-item cognitive factor for use in further statistical analyses. Each of the composite variables were calculated using factor score coefficients and rescaling them to sum to 1 before using them to weight participant responses for each item. Weighted item responses were then summed accordingly to obtain a composite factor score for use in subsequent analyses. Further details about the CFA can be obtained from the authors.
Confirmatory factor analysis of metacognitive items
I think about my thinking, to check if I understand the ideas in this subject. When I don’t understand something in this subject I go back over it again. I organise my time to manage my learning in this subject. I make plans for how to do the activities in this subject. I make a note of things that I don’t understand very well in this subject, so that I can follow them up. When I have finished an activity in this subject I look back to see how well I did. |
Coefficient H = .82 (adequate reliability) Chi-square (7, 1388) = 23.9, p < .0012 CFI = .991, TLI = .981, RMSEA = .042 |
Confirmatory factor analysis of cognitive items
I draw pictures or diagrams to help me understand this subject. I make up questions that I try to answer about this subject. When I am learning something new in this subject, I think back to what I already know about it. I practise things over and over until I know them well in this subject. I discuss what I am doing in this subject with others. |
Coefficient H = .74 (adequate reliability) Chi-square (4, 1388) = 8.6, p < .07 CFI = .995, TLI = .989, RMSEA = .029 |
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Askell-Williams, H., Lawson, M.J. & Skrzypiec, G. Scaffolding cognitive and metacognitive strategy instruction in regular class lessons. Instr Sci 40, 413–443 (2012). https://doi.org/10.1007/s11251-011-9182-5
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DOI: https://doi.org/10.1007/s11251-011-9182-5