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Targeting points of high working memory load: Expertise reversal effects. Paul Ayres (p.ayres@unsw.edu.au) School of Education, University of New South Wales 3rd International CLT Conference Heerlen, NL 2 March 2009. The trouble with brackets. Ayres (2001) -3(-4 - 5x) - 3(-3x - 4)
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Targeting points of high working memory load: Expertise reversal effects Paul Ayres(p.ayres@unsw.edu.au)School of Education, University of New South Wales3rd International CLT Conference Heerlen, NL 2 March 2009
The trouble with brackets Ayres (2001) • -3(-4 - 5x) - 3(-3x - 4) • Op 1Op 2Op 3Op 4 –3(–4) -3(–5x) -3(-3x) -3(-4) • Op-2 > Op-1, Op-4 > Op-3, Br-2 > Br-1
Evidence of WM load causing errors • Verbal protocols (Ayres, 2001) • Dual tasks (Ayres, 2001) • Subjective measures within problems (Ayres, 2006: L & I)
What would be helpful instruction? • For novices this is fairly complex domain- high in element interactivity • Need to deal with Intrinsic CL • Isolating elements (Pollock, Chandler & Sweller, 2002) • Pollock et al. proposed a two stage learning experience. During the first phase, learning is conducted element-by-element, leading to some partial schemas being acquired.
Ayres (2006 Appl. Cog. Psych.) • Complete Group 5 (3x - 4) - 2 (4x - 7) = 5 * 3x + 5 * -4 - 2 * 4x - 2 * -7 = 15 x - 20 - 8x + 14 • Single (isolated) Group -5 (3x - 4) - 2 (4x - 7) = -5 * 3x = - 15x
Results • Expertise reversal effect • For students with below mathematical ability the isolated strategy was effective. • For students with above average mathematical ability it was not effective- CL measures suggested low engagement. • However, the error profiles remained • Hypothesis: extra practice at points of greatest WM load will lead to greater learning.
The present study: Targeting strategy • 90 grade 8 students: 47 above average in math ability, 43 below average. • Equal group:Isolatedsingle calculations equally distributed over four operations during acquisition • Targeted group: Isolatedsingle calculations : three times as many on operations 2 and 4 compared with 1 and 3. Design • Acquisition phase: 4 pairs of worked examples (16 calculations). Study one- complete one alternation. • A nine-point self-rating scale (see van Gog & Paas, 2008) • Test phase: 8 complete bracket expansion tasks.
Statistical tests Acquisition: Ability F < 1 ; Strategy: F < 1 • Interaction: F= 4.0, p < 0.05; no simple effects CL measures: All F < 1 Test scores: Ability F=5.0, p < 0.03; Strategy F < 1 Interaction F = 4.4, p < 0.04 Simple effects High ability t < 1; Low ability t = 1.97, p = 0.055 Efficiency: All F < 1
Summary • Expertise reversal effects present again • Students with above average mathematical ability benefited from a targeting approach, but students below average didn’t. • For the latter it is plausible that the targeting format was too far removed from the full problems to be meaningful.
Exp 2 • Exact test of relevant mathematical ability (2 groups) • Full worked example group added (3 x 2 Design) • Transfer questions • Same design • Acquisition • CL measures (Difficulty- see van Gog & Paas) • Test • Transfer
Analysis Acquisition: Strategy F < 1 ; Interaction: F < 1 • Ability: F= 15.5, p < 0.001 CL measures: Ability F = 15.6, p <0.001 Strategy: F = 3.7, p < 0.05, Full WE > Isolated groups Interaction, F < 1. Test scores: Ability F = 22.4, p < 0.001; Strategy F < 1 Interaction F < 1
Transfer Ability F = 42.7, p < 0.001 Strategy: F < 1 Interaction F = 4.0, p < 0.05, Simple Effects • High Ability, F < 1.5 • Low Ability; Isolated > Targeted • Efficiency (transfer) Ability; F = 29.5, p < 0.001 High > Low Strategy: F = 3.3, p < 0.05, Combined ability: Targeted > Total worked example Interaction, F < 1
Efficiency (Test) Ability; F = 19.0, p < 0.001 High > Low Strategy: F = 4.3, p < 0.02, Combined ability: Targeted > Total worked example Interaction, F < 1
Summary • Low ability students • Single isolated > targeted on test scores (Exp. 1) • Single isolated > targeted on transfer scores (Exp. 2) • High Ability Students • No differences between groups • Overall ability effects • CL measures: full worked examples had greatest CL measures • Both efficiency measures (Targeted > full worked examples)