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Effects of problem difficulty and reinforcer quality on time allocated to concurrent arithmetic problems

F C Mace1, N A Neef, D Shade

  • 1University of Pennsylvania, Philadelphia 19104, USA.

Journal of Applied Behavior Analysis
|January 1, 1996
PubMed
Summary

Problem difficulty and reinforcer quality impact student time allocation in arithmetic tasks. Richer rewards did not overcome harder problems, but lower quality rewards reduced time on easier problems.

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Area of Science:

  • Behavioral Psychology
  • Educational Psychology
  • Applied Behavior Analysis

Background:

  • Students with learning difficulties often face challenges with academic tasks.
  • Understanding factors influencing their engagement and time allocation is crucial for effective interventions.
  • Reinforcement schedules and the quality of reinforcers are known to affect behavior.

Purpose of the Study:

  • To investigate how problem difficulty and reinforcer quality affect time allocation in students with learning difficulties.
  • To analyze these effects under concurrent variable-interval reinforcement schedules.
  • To explore implications for the matching law in asymmetrical reinforcement scenarios.

Main Methods:

  • Two studies were conducted with students with learning difficulties performing arithmetic problems.

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  • Study 1 used a single-subject design with high/low difficulty problems and rich/lean nickel schedules.
  • Study 2 examined problem difficulty and reinforcer quality (nickels vs. program money) under concurrent schedules.

    • Main Results:

    • In Study 1, high-difficulty problems paired with richer schedules did not increase time allocation.
    • In Study 2, lower quality reinforcers (program money) with richer schedules decreased time allocation.
    • This effect was most pronounced when lower quality reinforcers were paired with low-difficulty problems.

    Conclusions:

    • Reinforcer quality can significantly influence time allocation, sometimes overriding problem difficulty.
    • Findings have implications for understanding and applying the matching law to educational settings.
    • Interventions should consider both the difficulty of tasks and the perceived value of reinforcers.