The puzzle of study time allocation for the most challenging items

Monika Undorf, Rakefet Ackerman

Research output: Contribution to journalArticlepeer-review

Abstract

Learners often allocate more study time to challenging items than to easier ones. Nevertheless, both predicted and actual memory performance are typically worse for difficult than for easier items. The resulting inverse relations between people’s predictions of their memory performance (judgments of learning; JOLs) and self-paced study time (ST) are often explained by bottom-up, data-driven ST allocation that is based on fluency. However, we demonstrate robust inverted U-shaped relations between JOLs and ST that cannot be explained by data-driven ST allocation alone. Consequently, we explored how two models of top-down, strategic ST allocation account for curvilinear JOL-ST relations. First, according to the Region of Proximal Learning model, people stop quickly on items for which they experience too little progress in learning. Second, according to the Diminishing Criterion Model, people set a time limit and stop studying when this time limit is reached. In three experiments, we manipulated motivation with different methods and examined which model best described JOL-ST relations. Consistent with the Diminishing Criterion Model but not with the Region of Proximal Learning model, results revealed that curvilinearity was due to people setting a time limit.

Original languageEnglish
Pages (from-to)2003-2011
Number of pages9
JournalPsychonomic Bulletin and Review
Volume24
Issue number6
DOIs
StatePublished - 1 Dec 2017

Keywords

  • Judgments of learning
  • Metamemory
  • Monitoring and control
  • Self-regulation
  • Strategic behavior

ASJC Scopus subject areas

  • Experimental and Cognitive Psychology
  • Developmental and Educational Psychology
  • Arts and Humanities (miscellaneous)

Fingerprint

Dive into the research topics of 'The puzzle of study time allocation for the most challenging items'. Together they form a unique fingerprint.

Cite this