Min-counting becomes increasingly maladaptive as addition problem sizes increase¶

Claim · All claims
Evidence · 1 study · associational r2 · q3
Currency · newest study 2018 · not yet checked against its sources · not reviewed by a person

Subclaims¶

q3 i? Item slopes showed min-counting was particularly costly on larger problems; on item 29 (65 + 28) it added an average of 14.61 seconds with success probability .56. → Rhodes 2018

Evidence¶

Rhodes 2018¶

Rhodes, K. T., Lukowski, S., Branum-Martin, L., Opfer, J., Geary, D. C., & Petrill, S. A. (2018). Individual Differences in Addition Strategy Choice: A Psychometric Evaluation. Journal of Educational Psychology. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11360214/

q3 · i? · associational · r2

Individual differences analysis of item-level EIRT slope factor scores (Model 2), displayed in Figures 3C and 3D. The authors interpret the plotted slopes descriptively, reporting the item 29 example statistics of 14.61 seconds and success probability .56.

"In general, using min-counting was particularly maladaptive as problem sizes increased. For example, min-counting was a particularly poor choice for item 29 (65 + 28), one of the most difficult problems on the assessment. Use of min-counting to solve this problem increased solution times by an average of 14.61 seconds with a probability of success = .56."

Discussion¶

Related Claims¶

• The effect of min-counting on solution time and accuracy varies significantly across both items and persons — a broader claim this one bears on
• Overt counting, especially min-counting, remained common in adolescents and strategy solution times followed the expected retrieval < decomposition < counting ordering — related
• Working memory demand increases with the complexity of arithmetic and math problems, including operand size and number of solution steps — a broader claim this one bears on