Performance loss after breaks in practice grows with delay: a 100-day delay yields a 20% reduction and a 400-day delay a 50% reduction in first-gameplay performance¶

Claim · All claims
Evidence · 1 study · associational r2 · q2
Currency · newest study 2022 · not yet checked against its sources · not reviewed by a person

Subclaims¶

q2 i? For the first gameplay within a session, longer retention intervals produce proportionally larger performance losses in naturalistic practice data. → Aakriti Kumar 2022

Evidence¶

Aakriti Kumar 2022¶

Aakriti Kumar, Aaron S. Benjamin, Andrew Heathcote and Mark Steyvers. (2022). Comparing models of learning and relearning in large-scale cognitive training data sets. npj Science of Learning 7:24. https://doi.org/10.1038/s41539-022-00142-x

q2 · i? · associational · r2

Analysis of Lumosity retention data plotting first- and second-gameplay performance as a function of retention interval, from a few days to over 2 years, showing "a delay of 100 days leads to a 20% reduction in performance". No standardized effect size is printed.

"For the first game within the session, delay has a substantial effect on the proportional change in performance: a delay of 100 days leads to a 20% reduction in performance and a delay of 400 days leads to a 50% reduction."

Discussion¶

Related Claims¶

• Losses after long breaks in naturalistic practice are rapidly offset by very little practice: a single gameplay can restore prior performance levels even after delays of hundreds of days — related
• The interactive two-timescale model (M4) provides the most general account of naturalistic learning, though the additive-forgetting model (M3) fits better at six of eight interval subsets — related