The DOI matches its Crossref record; 30 of the 32 references it cites were found in a registry or an index; 3 of the 24 sources its claims cite were checked for support.
Spacing Effects in Learning: A Temporal Ridgeline of Optimal Retention
Open accessAbstract
To achieve enduring retention, people must usually study information on multiple occasions. How does the timing of study events affect retention? Prior research has examined this issue only in a spotty fashion, usually with very short time intervals. In a study aimed at characterizing spacing effects over significant durations, more than 1,350 individuals were taught a set of facts and--after a gap of up to 3.5 months--given a review. A final test was administered at a further delay of up to 1 year. At any given test delay, an increase in the interstudy gap at first increased, and then gradually reduced, final test performance. The optimal gap increased as test delay increased. However, when measured as a proportion of test delay, the optimal gap declined from about 20 to 40% of a 1-week test delay to about 5 to 10% of a 1-year test delay. The interaction of gap and test delay implies that many educational practices are highly inefficient.
Overview
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
19 Own result · 8 Own interpretation · 5 No full text of the sources · 5 Own method · 3 Sources not found · 2 Partly supported · 2 Not checked yet · 2 No basis given · 1 Supported so far · accuracy not yet measured
The sources with a verdict support this claim; the rest weren’t checked yet, have no full text we could read, or their verdicts aren’t rated yet.
In the paper
“Several studies involving modest time intervals ranging from minutes to days have found that memory at the final test is best for intermediate gap durations (e.g., Balota, Duchek, & Paullin, 1989;Glenberg, 1976;Glenberg & Lehmann, 1980;Young, 1966; see Cepeda et al., 2006, for a meta-analysis focused on this point).”
§ OPTIMIZING RETENTION USING DISTRIBUTED PRACTICE Spacing effects in learning: A temporal ridgeline of optimal retention > Spacing Effects in Learning: A Temporal Ridgeline of Optimal Retention
What the sources say
- Not matchedcites Balota, Duchek, & Paullin, 1989
Couldn’t be matched to a paper in Crossref, so it can’t be checked.
- Not checked — no full text of the sourcecites Glenberg, 1976 source
- Supportedcites Cepeda et al., 2006 source
The General Discussion (p. 11) reports that, for a given retention interval, an intermediate, non-zero inter-study interval maximized final-test accuracy: longer gaps eventually reduced it. The within-study analysis (p. 9) identifies several studies with results consistent with this pattern, including Balota et al., Glenberg, and Glenberg and Lehmann. (LLM, conf=0.93)
plaincorrelational- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
- Not matched
The cited sources support only part of this claim — read each source’s verdict below.
In the paper
“Other distributed practice theories, such as encoding variability (Glenberg, 1979) and study-phase retrieval (Murray, 1983) are potentially consistent with the basic results seen in Figure 3.”
§ OPTIMIZING RETENTION USING DISTRIBUTED PRACTICE Spacing effects in learning: A temporal ridgeline of optimal retention > Theoretical Implications
What the sources say
- Supportedcites Glenberg, 1979 source
Glenberg’s introduction (p. 1) describes his account of spacing effects in terms of variable encoding, and the General Discussion (p. 15) says an encoding-variability theory could account for several spacing phenomena. The citation identifies the theory; whether it fits the citing paper’s Figure 3 is the citing authors’ own qualified assessment. (LLM, conf=0.90)
- Not matchedcites Murray, 1983
Couldn’t be matched to a paper in Crossref, so it can’t be checked.
hedged- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: unclear — It is unclear whether the paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
- Supported
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“For a fixed amount of study time, the optimal gap provided a 64% increase, d = 1.1, in final recall, and a 26% increase, d = 1.5, in final recognition, as compared to a zero-day gap”
§ OPTIMIZING RETENTION USING DISTRIBUTED PRACTICE Spacing effects in learning: A temporal ridgeline of optimal retention > Results Figure 3 shows the effect of gap on recall and recognition for each of the four different retention intervals, for the subjects who completed all the phases of the study.For each retention interval, final performance always rose initially with increasing gap and then fell as gap was further increased.The effects of gap were very large in magnitude: For a fixed amount of study time, the optimal gap provided a 64% increase, d = 1.1, in final recall, and a 26% increase, d = 1.5, in final recognition, as compared to a zero-day gap (in the present article, d values refer to the comparison of zeroday versus optimal gap).For the RIs of 7, 35, 70, and 350 days, the optimal gaps (of those included in the study) were 1, 11, 21, and 21 days, respectively, for recall data, and 1, 7, 7, and 21 days, respectively, for recognition data.All of these findings are in good agreement with the lab benchmark dataset, which, with its RI of 6 months, lay about where it would be expected to between the RI = 70 and RI = 350 conditionsdespite the fact that the laboratory study fixed session 2 exposure duration and the current study did not.(Both studies provided a fixed number of relearning trials.)For 7, 35, 70, and 350 day RIs, percentage improvements in recall for optimal versus zeroday gaps were 10, 59, 111, and 77%-t(124) = 6.5, p rep = .99,d = 1.3; t(111) = 8.9, p rep = .99,d = 0.6; t(102) = 8.6, p rep = .99,d = 1.7; t(68) = 3.9, p rep = .99,d = 0.9, respectively.For recognition data, percentage improvements for optimal versus zero-day gaps were 1, 10, 31, and 60%-t(124) = 2.3, p rep = .99,d = 0.7; t(136) = 7.5, p rep = .99,d = In Press, Psychological Science Spacing Effects in Learning 5 1.5; t(112) = 8.7, p rep = .99,d = 1.7; t(68) = 7.9, p rep = .99,d = 2.1 for 7, 35, 70, and 350 day RIs, respectively.Estimated optimal gap values rise as retention interval is increased, and these depart noticeably from the fixed ratio of retention interval suggested by some earlier researchers based on much shorter-term studies (Crowder, 1976;Murray, 1983).
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“For 7, 35, 70, and 350 day RIs, percentage improvements in recall for optimal versus zeroday gaps were 10, 59, 111, and 77%-t(124) = 6.5, p rep = .99,d = 1.3; t(111) = 8.9, p rep = .99,d = 0.6; t(102) = 8.6, p rep = .99,d = 1.7; t(68) = 3.9, p rep = .99,d = 0.9, respectively.”
§ OPTIMIZING RETENTION USING DISTRIBUTED PRACTICE Spacing effects in learning: A temporal ridgeline of optimal retention > Results Figure 3 shows the effect of gap on recall and recognition for each of the four different retention intervals, for the subjects who completed all the phases of the study.For each retention interval, final performance always rose initially with increasing gap and then fell as gap was further increased.The effects of gap were very large in magnitude: For a fixed amount of study time, the optimal gap provided a 64% increase, d = 1.1, in final recall, and a 26% increase, d = 1.5, in final recognition, as compared to a zero-day gap (in the present article, d values refer to the comparison of zeroday versus optimal gap).For the RIs of 7, 35, 70, and 350 days, the optimal gaps (of those included in the study) were 1, 11, 21, and 21 days, respectively, for recall data, and 1, 7, 7, and 21 days, respectively, for recognition data.All of these findings are in good agreement with the lab benchmark dataset, which, with its RI of 6 months, lay about where it would be expected to between the RI = 70 and RI = 350 conditionsdespite the fact that the laboratory study fixed session 2 exposure duration and the current study did not.(Both studies provided a fixed number of relearning trials.)For 7, 35, 70, and 350 day RIs, percentage improvements in recall for optimal versus zeroday gaps were 10, 59, 111, and 77%-t(124) = 6.5, p rep = .99,d = 1.3; t(111) = 8.9, p rep = .99,d = 0.6; t(102) = 8.6, p rep = .99,d = 1.7; t(68) = 3.9, p rep = .99,d = 0.9, respectively.For recognition data, percentage improvements for optimal versus zero-day gaps were 1, 10, 31, and 60%-t(124) = 2.3, p rep = .99,d = 0.7; t(136) = 7.5, p rep = .99,d = In Press, Psychological Science Spacing Effects in Learning 5 1.5; t(112) = 8.7, p rep = .99,d = 1.7; t(68) = 7.9, p rep = .99,d = 2.1 for 7, 35, 70, and 350 day RIs, respectively.Estimated optimal gap values rise as retention interval is increased, and these depart noticeably from the fixed ratio of retention interval suggested by some earlier researchers based on much shorter-term studies (Crowder, 1976;Murray, 1983).
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“At any given retention interval, an increase in the inter-study gap at first increased, and then gradually reduced, test performance.”
- Also stated in: § Results Figure 3 shows the effect of gap on recall and recognition for each of the four different retention intervals, for the subjects who completed all the phases of the study.For each retention interval, final performance always rose initially with increasing gap and then fell as gap was further increased.The effects of gap were very large in magnitude: For a fixed amount of study time, the optimal gap provided a 64% increase, d = 1.1, in final recall, and a 26% increase, d = 1.5, in final recognition, as compared to a zero-day gap (in the present article, d values refer to the comparison of zeroday versus optimal gap).For the RIs of 7, 35, 70, and 350 days, the optimal gaps (of those included in the study) were 1, 11, 21, and 21 days, respectively, for recall data, and 1, 7, 7, and 21 days, respectively, for recognition data.All of these findings are in good agreement with the lab benchmark dataset, which, with its RI of 6 months, lay about where it would be expected to between the RI = 70 and RI = 350 conditionsdespite the fact that the laboratory study fixed session 2 exposure duration and the current study did not.(Both studies provided a fixed number of relearning trials.)For 7, 35, 70, and 350 day RIs, percentage improvements in recall for optimal versus zeroday gaps were 10, 59, 111, and 77%-t(124) = 6.5, p rep = .99,d = 1.3; t(111) = 8.9, p rep = .99,d = 0.6; t(102) = 8.6, p rep = .99,d = 1.7; t(68) = 3.9, p rep = .99,d = 0.9, respectively.For recognition data, percentage improvements for optimal versus zero-day gaps were 1, 10, 31, and 60%-t(124) = 2.3, p rep = .99,d = 0.7; t(136) = 7.5, p rep = .99,d = In Press, Psychological Science Spacing Effects in Learning 5 1.5; t(112) = 8.7, p rep = .99,d = 1.7; t(68) = 7.9, p rep = .99,d = 2.1 for 7, 35, 70, and 350 day RIs, respectively.Estimated optimal gap values rise as retention interval is increased, and these depart noticeably from the fixed ratio of retention interval suggested by some earlier researchers based on much shorter-term studies (Crowder, 1976;Murray, 1983). · boosted
“For each retention interval, final performance always rose initially with increasing gap and then fell as gap was further increased.”
§ OPTIMIZING RETENTION USING DISTRIBUTED PRACTICE Spacing effects in learning: A temporal ridgeline of optimal retention > Abstract
boosteddirectn = 1,350- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
- Also stated in: § Results Figure 3 shows the effect of gap on recall and recognition for each of the four different retention intervals, for the subjects who completed all the phases of the study.For each retention interval, final performance always rose initially with increasing gap and then fell as gap was further increased.The effects of gap were very large in magnitude: For a fixed amount of study time, the optimal gap provided a 64% increase, d = 1.1, in final recall, and a 26% increase, d = 1.5, in final recognition, as compared to a zero-day gap (in the present article, d values refer to the comparison of zeroday versus optimal gap).For the RIs of 7, 35, 70, and 350 days, the optimal gaps (of those included in the study) were 1, 11, 21, and 21 days, respectively, for recall data, and 1, 7, 7, and 21 days, respectively, for recognition data.All of these findings are in good agreement with the lab benchmark dataset, which, with its RI of 6 months, lay about where it would be expected to between the RI = 70 and RI = 350 conditionsdespite the fact that the laboratory study fixed session 2 exposure duration and the current study did not.(Both studies provided a fixed number of relearning trials.)For 7, 35, 70, and 350 day RIs, percentage improvements in recall for optimal versus zeroday gaps were 10, 59, 111, and 77%-t(124) = 6.5, p rep = .99,d = 1.3; t(111) = 8.9, p rep = .99,d = 0.6; t(102) = 8.6, p rep = .99,d = 1.7; t(68) = 3.9, p rep = .99,d = 0.9, respectively.For recognition data, percentage improvements for optimal versus zero-day gaps were 1, 10, 31, and 60%-t(124) = 2.3, p rep = .99,d = 0.7; t(136) = 7.5, p rep = .99,d = In Press, Psychological Science Spacing Effects in Learning 5 1.5; t(112) = 8.7, p rep = .99,d = 1.7; t(68) = 7.9, p rep = .99,d = 2.1 for 7, 35, 70, and 350 day RIs, respectively.Estimated optimal gap values rise as retention interval is increased, and these depart noticeably from the fixed ratio of retention interval suggested by some earlier researchers based on much shorter-term studies (Crowder, 1976;Murray, 1983). · boosted
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“For recognition data, percentage improvements for optimal versus zero-day gaps were 1, 10, 31, and 60%-t(124) = 2.3, p rep = .99,d = 0.7; t(136) = 7.5, p rep = .99,d = In Press, Psychological Science Spacing Effects in Learning 5 1.5; t(112) = 8.7, p rep = .99,d = 1.7; t(68) = 7.9, p rep = .99,d = 2.1 for 7, 35, 70, and 350 day RIs, respectively.”
§ OPTIMIZING RETENTION USING DISTRIBUTED PRACTICE Spacing effects in learning: A temporal ridgeline of optimal retention > Results Figure 3 shows the effect of gap on recall and recognition for each of the four different retention intervals, for the subjects who completed all the phases of the study.For each retention interval, final performance always rose initially with increasing gap and then fell as gap was further increased.The effects of gap were very large in magnitude: For a fixed amount of study time, the optimal gap provided a 64% increase, d = 1.1, in final recall, and a 26% increase, d = 1.5, in final recognition, as compared to a zero-day gap (in the present article, d values refer to the comparison of zeroday versus optimal gap).For the RIs of 7, 35, 70, and 350 days, the optimal gaps (of those included in the study) were 1, 11, 21, and 21 days, respectively, for recall data, and 1, 7, 7, and 21 days, respectively, for recognition data.All of these findings are in good agreement with the lab benchmark dataset, which, with its RI of 6 months, lay about where it would be expected to between the RI = 70 and RI = 350 conditionsdespite the fact that the laboratory study fixed session 2 exposure duration and the current study did not.(Both studies provided a fixed number of relearning trials.)For 7, 35, 70, and 350 day RIs, percentage improvements in recall for optimal versus zeroday gaps were 10, 59, 111, and 77%-t(124) = 6.5, p rep = .99,d = 1.3; t(111) = 8.9, p rep = .99,d = 0.6; t(102) = 8.6, p rep = .99,d = 1.7; t(68) = 3.9, p rep = .99,d = 0.9, respectively.For recognition data, percentage improvements for optimal versus zero-day gaps were 1, 10, 31, and 60%-t(124) = 2.3, p rep = .99,d = 0.7; t(136) = 7.5, p rep = .99,d = In Press, Psychological Science Spacing Effects in Learning 5 1.5; t(112) = 8.7, p rep = .99,d = 1.7; t(68) = 7.9, p rep = .99,d = 2.1 for 7, 35, 70, and 350 day RIs, respectively.Estimated optimal gap values rise as retention interval is increased, and these depart noticeably from the fixed ratio of retention interval suggested by some earlier researchers based on much shorter-term studies (Crowder, 1976;Murray, 1983).
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“For the RIs of 7, 35, 70, and 350 days, the optimal gaps (of those included in the study) were 1, 11, 21, and 21 days, respectively, for recall data, and 1, 7, 7, and 21 days, respectively, for recognition data.”
§ OPTIMIZING RETENTION USING DISTRIBUTED PRACTICE Spacing effects in learning: A temporal ridgeline of optimal retention > Results Figure 3 shows the effect of gap on recall and recognition for each of the four different retention intervals, for the subjects who completed all the phases of the study.For each retention interval, final performance always rose initially with increasing gap and then fell as gap was further increased.The effects of gap were very large in magnitude: For a fixed amount of study time, the optimal gap provided a 64% increase, d = 1.1, in final recall, and a 26% increase, d = 1.5, in final recognition, as compared to a zero-day gap (in the present article, d values refer to the comparison of zeroday versus optimal gap).For the RIs of 7, 35, 70, and 350 days, the optimal gaps (of those included in the study) were 1, 11, 21, and 21 days, respectively, for recall data, and 1, 7, 7, and 21 days, respectively, for recognition data.All of these findings are in good agreement with the lab benchmark dataset, which, with its RI of 6 months, lay about where it would be expected to between the RI = 70 and RI = 350 conditionsdespite the fact that the laboratory study fixed session 2 exposure duration and the current study did not.(Both studies provided a fixed number of relearning trials.)For 7, 35, 70, and 350 day RIs, percentage improvements in recall for optimal versus zeroday gaps were 10, 59, 111, and 77%-t(124) = 6.5, p rep = .99,d = 1.3; t(111) = 8.9, p rep = .99,d = 0.6; t(102) = 8.6, p rep = .99,d = 1.7; t(68) = 3.9, p rep = .99,d = 0.9, respectively.For recognition data, percentage improvements for optimal versus zero-day gaps were 1, 10, 31, and 60%-t(124) = 2.3, p rep = .99,d = 0.7; t(136) = 7.5, p rep = .99,d = In Press, Psychological Science Spacing Effects in Learning 5 1.5; t(112) = 8.7, p rep = .99,d = 1.7; t(68) = 7.9, p rep = .99,d = 2.1 for 7, 35, 70, and 350 day RIs, respectively.Estimated optimal gap values rise as retention interval is increased, and these depart noticeably from the fixed ratio of retention interval suggested by some earlier researchers based on much shorter-term studies (Crowder, 1976;Murray, 1983).
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“For the RIs of 7, 35, 70, and 350 days, the optimal gaps (of those included in the study) were 1, 11, 21, and 21 days, respectively, for recall data, and 1, 7, 7, and 21 days, respectively, for recognition data.”
§ OPTIMIZING RETENTION USING DISTRIBUTED PRACTICE Spacing effects in learning: A temporal ridgeline of optimal retention > Results Figure 3 shows the effect of gap on recall and recognition for each of the four different retention intervals, for the subjects who completed all the phases of the study.For each retention interval, final performance always rose initially with increasing gap and then fell as gap was further increased.The effects of gap were very large in magnitude: For a fixed amount of study time, the optimal gap provided a 64% increase, d = 1.1, in final recall, and a 26% increase, d = 1.5, in final recognition, as compared to a zero-day gap (in the present article, d values refer to the comparison of zeroday versus optimal gap).For the RIs of 7, 35, 70, and 350 days, the optimal gaps (of those included in the study) were 1, 11, 21, and 21 days, respectively, for recall data, and 1, 7, 7, and 21 days, respectively, for recognition data.All of these findings are in good agreement with the lab benchmark dataset, which, with its RI of 6 months, lay about where it would be expected to between the RI = 70 and RI = 350 conditionsdespite the fact that the laboratory study fixed session 2 exposure duration and the current study did not.(Both studies provided a fixed number of relearning trials.)For 7, 35, 70, and 350 day RIs, percentage improvements in recall for optimal versus zeroday gaps were 10, 59, 111, and 77%-t(124) = 6.5, p rep = .99,d = 1.3; t(111) = 8.9, p rep = .99,d = 0.6; t(102) = 8.6, p rep = .99,d = 1.7; t(68) = 3.9, p rep = .99,d = 0.9, respectively.For recognition data, percentage improvements for optimal versus zero-day gaps were 1, 10, 31, and 60%-t(124) = 2.3, p rep = .99,d = 0.7; t(136) = 7.5, p rep = .99,d = In Press, Psychological Science Spacing Effects in Learning 5 1.5; t(112) = 8.7, p rep = .99,d = 1.7; t(68) = 7.9, p rep = .99,d = 2.1 for 7, 35, 70, and 350 day RIs, respectively.Estimated optimal gap values rise as retention interval is increased, and these depart noticeably from the fixed ratio of retention interval suggested by some earlier researchers based on much shorter-term studies (Crowder, 1976;Murray, 1983).
plaincorrelational- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“For a fixed amount of study time, the optimal gap provided a 64% increase, d = 1.1, in final recall, and a 26% increase, d = 1.5, in final recognition, as compared to a zero-day gap”
§ OPTIMIZING RETENTION USING DISTRIBUTED PRACTICE Spacing effects in learning: A temporal ridgeline of optimal retention > Results Figure 3 shows the effect of gap on recall and recognition for each of the four different retention intervals, for the subjects who completed all the phases of the study.For each retention interval, final performance always rose initially with increasing gap and then fell as gap was further increased.The effects of gap were very large in magnitude: For a fixed amount of study time, the optimal gap provided a 64% increase, d = 1.1, in final recall, and a 26% increase, d = 1.5, in final recognition, as compared to a zero-day gap (in the present article, d values refer to the comparison of zeroday versus optimal gap).For the RIs of 7, 35, 70, and 350 days, the optimal gaps (of those included in the study) were 1, 11, 21, and 21 days, respectively, for recall data, and 1, 7, 7, and 21 days, respectively, for recognition data.All of these findings are in good agreement with the lab benchmark dataset, which, with its RI of 6 months, lay about where it would be expected to between the RI = 70 and RI = 350 conditionsdespite the fact that the laboratory study fixed session 2 exposure duration and the current study did not.(Both studies provided a fixed number of relearning trials.)For 7, 35, 70, and 350 day RIs, percentage improvements in recall for optimal versus zeroday gaps were 10, 59, 111, and 77%-t(124) = 6.5, p rep = .99,d = 1.3; t(111) = 8.9, p rep = .99,d = 0.6; t(102) = 8.6, p rep = .99,d = 1.7; t(68) = 3.9, p rep = .99,d = 0.9, respectively.For recognition data, percentage improvements for optimal versus zero-day gaps were 1, 10, 31, and 60%-t(124) = 2.3, p rep = .99,d = 0.7; t(136) = 7.5, p rep = .99,d = In Press, Psychological Science Spacing Effects in Learning 5 1.5; t(112) = 8.7, p rep = .99,d = 1.7; t(68) = 7.9, p rep = .99,d = 2.1 for 7, 35, 70, and 350 day RIs, respectively.Estimated optimal gap values rise as retention interval is increased, and these depart noticeably from the fixed ratio of retention interval suggested by some earlier researchers based on much shorter-term studies (Crowder, 1976;Murray, 1983).
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Estimated optimal gap values rise as retention interval is increased”
§ OPTIMIZING RETENTION USING DISTRIBUTED PRACTICE Spacing effects in learning: A temporal ridgeline of optimal retention > Results Figure 3 shows the effect of gap on recall and recognition for each of the four different retention intervals, for the subjects who completed all the phases of the study.For each retention interval, final performance always rose initially with increasing gap and then fell as gap was further increased.The effects of gap were very large in magnitude: For a fixed amount of study time, the optimal gap provided a 64% increase, d = 1.1, in final recall, and a 26% increase, d = 1.5, in final recognition, as compared to a zero-day gap (in the present article, d values refer to the comparison of zeroday versus optimal gap).For the RIs of 7, 35, 70, and 350 days, the optimal gaps (of those included in the study) were 1, 11, 21, and 21 days, respectively, for recall data, and 1, 7, 7, and 21 days, respectively, for recognition data.All of these findings are in good agreement with the lab benchmark dataset, which, with its RI of 6 months, lay about where it would be expected to between the RI = 70 and RI = 350 conditionsdespite the fact that the laboratory study fixed session 2 exposure duration and the current study did not.(Both studies provided a fixed number of relearning trials.)For 7, 35, 70, and 350 day RIs, percentage improvements in recall for optimal versus zeroday gaps were 10, 59, 111, and 77%-t(124) = 6.5, p rep = .99,d = 1.3; t(111) = 8.9, p rep = .99,d = 0.6; t(102) = 8.6, p rep = .99,d = 1.7; t(68) = 3.9, p rep = .99,d = 0.9, respectively.For recognition data, percentage improvements for optimal versus zero-day gaps were 1, 10, 31, and 60%-t(124) = 2.3, p rep = .99,d = 0.7; t(136) = 7.5, p rep = .99,d = In Press, Psychological Science Spacing Effects in Learning 5 1.5; t(112) = 8.7, p rep = .99,d = 1.7; t(68) = 7.9, p rep = .99,d = 2.1 for 7, 35, 70, and 350 day RIs, respectively.Estimated optimal gap values rise as retention interval is increased, and these depart noticeably from the fixed ratio of retention interval suggested by some earlier researchers based on much shorter-term studies (Crowder, 1976;Murray, 1983).
hedgeddirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
- It may state two separate claims as one. 9
- Probably not a substantial claim. 6
- The quote only partly states this claim. 1
The cited sources support only part of this claim — read each source’s verdict below.
In the paper
“A recent review of distributed practice studies involving verbal recall (Cepeda et al., 2006) examined more than 400 papers.However, only about a dozen of these looked at retention intervals as long as one day, with just a handful examining retention intervals longer than one week.”
§ OPTIMIZING RETENTION USING DISTRIBUTED PRACTICE Spacing effects in learning: A temporal ridgeline of optimal retention > Spacing Effects in Learning 2
What the sources say
- Partly supportedcites Cepeda et al., 2006 sourceExperimental — accuracy not yet measured
Split into 2 atoms — 1 confirmed, 1 partially supported, 0 disputed, 0 misattributed, 0 unverifiable. Expand the claim to see per-atom verdicts.
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
- Partly supported
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“The optimum gap value was about 20% of the test delay for delays of a few weeks, falling to about 5% when delay was one year.”
§ OPTIMIZING RETENTION USING DISTRIBUTED PRACTICE Spacing effects in learning: A temporal ridgeline of optimal retention > Abstract
plaincorrelationaln = 1,350- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“In Figure 4, for example, the optimal gap for RI = 350 equals 23 days, which is just 7% of the RI.”
§ OPTIMIZING RETENTION USING DISTRIBUTED PRACTICE Spacing effects in learning: A temporal ridgeline of optimal retention > Discussion
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: unclear — It is unclear whether the paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
The paper states this without a source or data behind it here, so there is nothing to check it against. The quote shows it is in the paper.
In the paper
“First, for any gap duration, recall performance must decline as a function of RI (i.e., test delay) in a negatively accelerated fashion in order to produce the familiar forgetting curve consistent with more than 100 years of memory findings.”
§ OPTIMIZING RETENTION USING DISTRIBUTED PRACTICE Spacing effects in learning: A temporal ridgeline of optimal retention > Discussion
boosteddirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: fails — The paper may give no reason why it holds.
Probably not a substantial claim. The paper may give no reason why it holds.
- Rests on an assumption: The forgetting curve is negatively accelerated (information loss per unit time gradually shrinks).
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“The results presented here document the existence of enormous and non-monotonic spacing effects that unfold over very long periods of time, with study time equated across conditions.”
§ OPTIMIZING RETENTION USING DISTRIBUTED PRACTICE Spacing effects in learning: A temporal ridgeline of optimal retention > Discussion
boostedcorrelational- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Exploration of the data indicated that a number of other functions can also provide quite decent fits to the data, with various tradeoffs between interpretability of parameters and simplicity of the function, and we do not contend that this function offers a uniquely accurate characterization of the surface-merely a reasonable one.”
§ OPTIMIZING RETENTION USING DISTRIBUTED PRACTICE Spacing effects in learning: A temporal ridgeline of optimal retention > Discussion
hedged- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it. It may state two separate claims as one.
What the paper did — it cites no source for this, so there is none to check. The quote shows it is in the paper.
In the paper
“There were 26 gap-by-retention interval combinations, and each subject was randomly assigned to one of these.”
§ OPTIMIZING RETENTION USING DISTRIBUTED PRACTICE Spacing effects in learning: A temporal ridgeline of optimal retention > Stimuli and materials.
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim.
What the paper did — it cites no source for this, so there is none to check. The quote shows it is in the paper.
In the paper
“There were also no detectable differences between the groups in age, gender, number of obscure facts known before beginning the study, or a wide array of background and demographic characteristics.”
§ OPTIMIZING RETENTION USING DISTRIBUTED PRACTICE Spacing effects in learning: A temporal ridgeline of optimal retention > Subjects.
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: unclear — It is unclear whether the paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
What the paper did — it cites no source for this, so there is none to check. The quote shows it is in the paper.
In the paper
“We held constant the number of restudy trials in the second study session, thus allowing us to look at the effect of gap apart from the amount of time provided for restudy.”
§ OPTIMIZING RETENTION USING DISTRIBUTED PRACTICE Spacing effects in learning: A temporal ridgeline of optimal retention > Spacing Effects in Learning 2
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim.
In the paper
“The results showed that increasing the inter-study spacing out to 56 days improved performance (Figure 2).”
§ OPTIMIZING RETENTION USING DISTRIBUTED PRACTICE Spacing effects in learning: A temporal ridgeline of optimal retention > Spacing Effects in Learning 2
What the sources say
- Not checked — no full text of the sourcecites Bahrick et al., 1993 source
plaindirectn = 4- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
The quote only partly states this claim.
In the paper
“The non-monotonic pattern noted in short-term studies was indeed found: Recall success (for both facts and names) was best for a 1-month gap, with much worse recall for shorter gaps and slightly poorer recall for longer ones.”
§ OPTIMIZING RETENTION USING DISTRIBUTED PRACTICE Spacing effects in learning: A temporal ridgeline of optimal retention > Preliminary Data
What the sources say
- Not matchedcites Cepeda et al., 2007
Couldn’t be matched to a paper in Crossref, so it can’t be checked.
plaincorrelationaln = 150- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
- Not matched
In the paper
“However, 56 days is actually a relatively short proportion of the extremely long retention intervals used in Bahrick et al.'s study, and it is this ratio that is probably most critical, as will emerge below.”
§ OPTIMIZING RETENTION USING DISTRIBUTED PRACTICE Spacing effects in learning: A temporal ridgeline of optimal retention > Spacing Effects in Learning 2
What the sources say
- Not checked — no full text of the sourcecites Bahrick et al., 1993 source
hedgedcorrelationaln = 4- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
What the paper did — it cites no source for this, so there is none to check. The quote shows it is in the paper.
In the paper
“Non-completion rates increased at the longer delays, as one would expect in any multi-year study (Table 1)”
§ OPTIMIZING RETENTION USING DISTRIBUTED PRACTICE Spacing effects in learning: A temporal ridgeline of optimal retention > Subjects.
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it.
None of the sources cited for this claim have been checked yet.
In the paper
“As described in the Appendix, the reliability and validity of internet data collection has become increasingly clear in recent years.”
§ OPTIMIZING RETENTION USING DISTRIBUTED PRACTICE Spacing effects in learning: A temporal ridgeline of optimal retention > Spacing Effects in Learning 2
What the sources say
- Not matchedcites Reips, 2002
Couldn’t be matched to a paper in Crossref, so it can’t be checked.
- Not checked — no full text of the sourcecites Gosling et al., 2004 source
boosted- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim.
- Not matched
None of the sources cited for this claim have been checked yet.
In the paper
“The validity of internet testing has been well supported in recent reviews (Gosling et al., 2004), with excellent correspondence between results obtained with internet samples are results obtained in the laboratory (e.g., Birnbaum, 1999;Krantz & Dalal, 2000;McGraw, Tew, & Williams, 2000;Reips, 2002).”
§ OPTIMIZING RETENTION USING DISTRIBUTED PRACTICE Spacing effects in learning: A temporal ridgeline of optimal retention > Appendix: Comments and Validity of Internet Memory Testing Data
What the sources say
boostedcorrelational- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
The paper relies on this without support.
The 32 obscure trivia facts and object names used in the study are representative of the kinds of information people need to learn and retain in educational settings.
“Stimuli consisted of 32 obscure but true trivia facts (e.g.,”
The paper relies on this without support.
The forgetting curve is negatively accelerated (information loss per unit time gradually shrinks).
“The amount of information lost per unit of time gradually shrinks, producing the well-known increasingly gradual forgetting curve.”
The paper relies on this without support.
Working memory operates on a time scale of seconds or minutes.
“Working memory operates on a time scale of seconds or minutes, whereas gap effects are seen on a scale of day and weeks (optimal gap is several weeks, for longer retention intervals).”
The paper relies on this without support.
The 26 gap-by-retention interval combinations adequately sample the retention surface.
“To properly characterize the interaction of gap and retention interval, the current study combines various gap and RI values, for a total of 26 different conditions.”
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
The cited source doesn’t support the claim as written.
In the citing paper
“The optimal ratio of spacing and retention interval should be 10-30%.”
From MASSED TASK REPETITION IS A DOUBLE-EDGED SWORD FOR FLUENCY DEVELOPMENT: AN EFL CLASSROOM STUDY (2022) · cites this paper as Cepeda et al., 2008
Checked by a reasoning model — may be wrong.
Experimental — accuracy not yet measuredThe source backs part of the claim, not all of it — or backs it for a different population, condition or comparison.
In the citing paper
“However, such research also emphasizes that the effect of retention intervals on the distributed practice advantage does not continuously increase as the retention interval increases (Cepeda et al., 2008).”
From The Distributed Practice Effect on Classroom Learning: A Meta-Analytic Review of Applied Research (2025) · cites this paper as Cepeda et al., 2008
Experimental — accuracy not yet measuredThe source backs part of the claim, not all of it — or backs it for a different population, condition or comparison.
In the citing paper
“There are two issues: (1) learning is not spaced-out despite evidence that enduring retention is achieved through substantial gaps in practice (gaps of months to achieve knowledge lasting years) (Cepeda et al., 2008);”
From Using version control to document genuine effort in written assignments: a protocol with examples for universities (2023) · cites this paper as Cepeda et al., 2008
Experimental — accuracy not yet measuredThe cited source says what the claim attributes to it.
In the citing paper
“According to cognitive psychologists (Cepeda et al., 2008;Rohrer & Pashler, 2007), the optimal spacing depends on the retention interval (i.e., the timing of delayed posttest).”
From MASSED TASK REPETITION IS A DOUBLE-EDGED SWORD FOR FLUENCY DEVELOPMENT: AN EFL CLASSROOM STUDY (2022) · cites this paper as Cepeda et al., 2008
Citations
Cites
From dissertation abstracts international
(1974) · ACM SIGGRAPH Computer Graphics · doi:10.1145/988616.988619 · Cited by 12,208
Editorial Office (1997) · Obesity Surgery · doi:10.1381/096089297765555359 · Cited by 3,941
Gosling, S. D., Vazire, S., Srivastava, S., & John, O. P. (2004) · American Psychologist · doi:10.1037/0003-066x.59.2.93 · Cited by 2,932
Distributed practice in verbal recall tasks: A review and quantitative synthesis.
Cepeda, N. J., Pashler, H., Vul, E., Wixted, J. T., & Rohrer, D. (2006) · Psychological Bulletin · doi:10.1037/0033-2909.132.3.354 · Cited by 1,888
Self-citationSchmidt, R. A., & Bjork, R. A. (1992) · Psychological Science · doi:10.1111/j.1467-9280.1992.tb00029.x · Cited by 1,582
Principles of Learning and Memory
Murdock, B. B., & Crowder, R. G. (1977) · The American Journal of Psychology · doi:10.2307/1422060 · Cited by 1,306
Standards for Internet-Based Experimenting
Reips, U. (2002) · Experimental Psychology (formerly Zeitschrift für Experimentelle Psychologie) · doi:10.1026/1618-3169.49.4.243 · Cited by 878
Analysis of rehearsal processes in free recall.
Rundus, D. (1971) · Journal of Experimental Psychology · doi:10.1037/h0031185 · Cited by 797
On interpreting the effects of repetition: Solving a problem versus remembering a solution
Jacoby, L. L. (1978) · Journal of Verbal Learning and Verbal Behavior · doi:10.1016/s0022-5371(78)90393-6 · Cited by 667
Standards for Internet-Based Experimenting
Reips, U.-D. (2002) · Experimental Psychology · doi:10.1026//1618-3169.49.4.243 · Cited by 469
Research works printed but not linked: 2
- Murray J.T., 1983, Dissertation Abstracts International, 43, 3058
- Young J.L., 1966, Dissertation Abstracts International, 27, 3699
Cited by
Sorted by citations
Items 201–300 of 625
Cuevas, J. A., Childers, G. M., & Dawson, B. L. (2023) · Trends in Neuroscience and Education · doi:10.1016/j.tine.2023.100209 · Cited by 28
Stocco, A., Rice, P. G., Thomson, R., Smith, B. M., Morrison, D., & Lebiere, C. J. (2023) · Computational Brain & Behavior · doi:10.1007/s42113-023-00189-y · Cited by 22
Pauses and spacing in learning to program
Leppänen, L., Leinonen, J., & Hellas, A. (2016) · Koli Calling International Conference on Computing Education Research · doi:10.1145/2999541.2999549 · Cited by 22
Lack of spacing effects during piano learning
Wiseheart, M., LaPlume, A. A., & Chae, J. (2017) · PLoS ONE · doi:10.1371/journal.pone.0182986 · Cited by 19
The half-life of MOOC knowledge
Davis, D., Kizilcec, R. F., Hauff, C., & Houben, G. (2018) · International Conference on Learning Analytics and Knowledge (LAK) · doi:10.1145/3170358.3170383 · Cited by 19
Examining the potential of digital flashcards to facilitate independent grammar learning
Serfaty, J., & Serrano, R. (2020) · System · doi:10.1016/j.system.2020.102342 · Cited by 28
Doolittle, P. E., & Byrnes, M. K. (2023) · Wiley eBooks · doi:10.1002/9781119852865.ch3 · Cited by 20
What the Science of Learning Teaches Us About Arithmetic Fluency
McNeil, N. M., Jordan, N. C., Viegut, A. A., & Ansari, D. (2025) · Psychological Science in the Public Interest · doi:10.1177/15291006241287726 · Cited by 36
Prabhu, R., Simpson, T. W., Miller, S. R., & Meisel, N. A. (2021) · Journal of Engineering Design · doi:10.1080/09544828.2021.1876843 · Cited by 18
A Stochastic Shortest Path Algorithm for Optimizing Spaced Repetition Scheduling
Ye, J., Su, J., & Cao, Y. (2022) · ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD) · doi:10.1145/3534678.3539081 · Cited by 18
Spitzer, M., Moeller, K., & Musslick, S. (2023) · PLoS ONE · doi:10.1371/journal.pone.0284868 · Cited by 18
When I say … test‐enhanced learning
Larsen, D. P. (2013) · Medical Education · doi:10.1111/medu.12238 · Cited by 18
Nazari, K. B., & Ebersbach, M. (2019) · Trends in Neuroscience and Education · doi:10.1016/j.tine.2019.100122 · Cited by 19
The Evolutionary Rationality of Social Learning
McElreath, R. L., Wallin, A., & Fasolo, B. (2012) · Oxford University Press eBooks · doi:10.1093/acprof:oso/9780195388435.003.0014 · Cited by 23
Who remembers the Beatles? The collective memory for popular music
Spivack, S., Philibotte, S. J., Spilka, N. H., Passman, I., & Wallisch, P. (2019) · PLoS ONE · doi:10.1371/journal.pone.0210066 · Cited by 18
Advancing a temporal science of behavior
Abney, D. H., Fausey, C. M., Suárez-Rivera, C., & Tamis‐LeMonda, C. S. (2025) · Trends in Cognitive Sciences · doi:10.1016/j.tics.2025.05.010 · Cited by 18
Yan, V. X., & Sana, F. (2021) · Journal of Educational Psychology · doi:10.1037/edu0000470 · Cited by 17
Optimizing Spaced Repetition Schedule by Capturing the Dynamics of Memory
Su, J., Ye, J., Nie, L., Cao, Y., & Chen, Y. (2023) · IEEE Transactions on Knowledge and Data Engineering · doi:10.1109/tkde.2023.3251721 · Cited by 25
Trust-Your-Doctor: A Simple Heuristic in Need of a Proper Social Environment
Wegwarth, O., & Gigerenzer, G. (2012) · Oxford University Press eBooks · doi:10.1093/acprof:oso/9780195388435.003.0003 · Cited by 20
Judging credibility: Can spaced lessons help students think more critically online?
Foot‐Seymour, V., Foot, J., & Wiseheart, M. (2019) · Applied Cognitive Psychology · doi:10.1002/acp.3539 · Cited by 18
Sequential Mastery of Multiple Visual Tasks: Networks Naturally Learn to Learn and Forget to Forget
Davidson, G., & Mozer, M. C. (2020) · IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings · doi:10.1109/cvpr42600.2020.00930 · Cited by 22
Translating the learning sciences into practice: A primer for clinical and translational educators
Norman, M. K., & Lotrecchiano, G. R. (2021) · Journal of Clinical and Translational Science · doi:10.1017/cts.2021.840 · Cited by 24
Simple Heuristics: The Foundations of Adaptive Social Behavior
Hertwig, R., & Hoffrage, U. (2012) · Oxford University Press eBooks · doi:10.1093/acprof:oso/9780195388435.003.0001 · Cited by 20
Laws of Human MemoryPreprint
Kahana, M. J., Diamond, N. B., & Aka, A. (2022) · doi:10.31234/osf.io/aczu9 · Cited by 17
Testing the reminding account of the lag effect in L2 vocabulary learning
Koval, N. G. (2021) · Applied Psycholinguistics · doi:10.1017/s0142716421000370 · Cited by 20
Pelánek, R. (2021) · International Journal of Artificial Intelligence in Education · doi:10.1007/s40593-021-00251-5 · Cited by 17
Fiechter, J. L., & Benjamin, A. S. (2019) · Psychonomic Bulletin & Review · doi:10.3758/s13423-019-01617-6 · Cited by 17
Yan, V. X., Sana, F., & Carvalho, P. F. (2023) · Policy Insights from the Behavioral and Brain Sciences · doi:10.1177/23727322231218906 · Cited by 26
The effects of distributed practice on second language fluency development
Kakitani, J., & Kormos, J. (2024) · Studies in Second Language Acquisition · doi:10.1017/s0272263124000251 · Cited by 23
Video Self-Modeling Interventions for Students With Autism Spectrum Disorder
Schaeffer, K. M., Hamilton, K. A., & Johnson, W. L. B. (2016) · Intervention in School and Clinic · doi:10.1177/1053451216630281 · Cited by 15
Impact of Structural Plasticity on Memory Formation and Decline
Knoblauch, A. (2017) · Elsevier eBooks · doi:10.1016/b978-0-12-803784-3.00017-2 · Cited by 17
Distributed Learning in the Classroom: Effects of Rereading Schedules Depend on Time of Test
Greving, C. E., & Richter, T. (2019) · Frontiers in Psychology · doi:10.3389/fpsyg.2018.02517 · Cited by 15
Effects of distributed practice and criterion level on word retrieval in aphasia
Schuchard, J., Rawson, K. A., & Middleton, E. L. (2020) · Cognition · doi:10.1016/j.cognition.2020.104216 · Cited by 15
Anatomy integration: Effective change or change of affect?
Hartley, R. S., Smith, G. A., & Rosenberg, M. J. (2018) · Anatomical Sciences Education · doi:10.1002/ase.1773 · Cited by 15
Immekus, J. C. (2019) · Journal of Statistics Education · doi:10.1080/10691898.2019.1629852 · Cited by 20
Predicting memory formation over multiple study episodesPreprint
Sievers, C., Bird, C. M., & Renoult, L. (2019) · Learning & Memory · doi:10.1101/lm.049791.119 · Cited by 17
Using Spacing to Promote Lasting Learning in Educational Contexts: Promises and Challenges
Ebersbach, M., Lachner, A., Scheiter, K., & Richter, T. (2022) · Zeitschrift für Entwicklungspsychologie und Pädagogische Psychologie · doi:10.1026/0049-8637/a000259 · Cited by 14
Everyday Parameters for Episode‐to‐Episode Dynamics in the Daily Music of Infancy
Mendoza, J. K., & Fausey, C. M. (2022) · Cognitive Science · doi:10.1111/cogs.13178 · Cited by 19
Comparing models of learning and relearning in large-scale cognitive training data sets
Kumar, A., Benjamin, A. S., Heathcote, A., & Steyvers, M. (2022) · npj Science of Learning · doi:10.1038/s41539-022-00142-x · Cited by 14
The effects of binge-watching and spacing on learning L2 multi-word units from captioned TV series
Pattemore, A., & Muñoz, C. (2023) · Language Learning Journal · doi:10.1080/09571736.2023.2211614 · Cited by 21
McConnell, M., Azzam, K., Xenodemetropoulos, T., & Panju, A. A. (2015) · Journal of Continuing Education in the Health Professions · doi:10.1002/chp.21293 · Cited by 15
A three‐step model for the gamification of training and automaticity acquisition
Jamshidifarsani, H., Tamayo‐Serrano, P., Garbaya, S., & Lim, T. (2021) · Journal of Computer Assisted Learning · doi:10.1111/jcal.12539 · Cited by 14
Clegg, B. A., McKernan, B., Martey, R. M., Taylor, S. M., Stromer‐Galley, J., Kenski, K. M., Saulnier, E. T., Rhodes, M. G., Folkestad, J., McLaren, E., et al. (2015) · Procedia Manufacturing · doi:10.1016/j.promfg.2015.07.438 · Cited by 14
Kassim, A. A., Rehman, R., & Price, J. M. (2018) · Acta Psychologica · doi:10.1016/j.actpsy.2018.01.012 · Cited by 15
Çekiç, A., & Bakla, A. (2019) · Instructional Science · doi:10.1007/s11251-019-09483-4 · Cited by 15
Samudra, P. G., Wong, K. M., & Neuman, S. B. (2019) · Journal of Cognitive Education and Psychology · doi:10.1891/1945-8959.18.2.160 · Cited by 14
Reinstein, I., Hill, J., Cook, D. A., Lineberry, M. C., & Pusic, M. V. (2021) · Advances in Health Sciences Education · doi:10.1007/s10459-021-10027-0 · Cited by 14
Dabiri, S., Mohammadi, A., & Mojtahedzadeh, R. (2019) · PubMed Central · doi:10.30476/jamp.2019.74696 · Cited by 13
Recurrent knowledge tracing machine based on the knowledge state of students
Lai, Z., Wang, L., & Ling, Q. (2021) · Expert Systems · doi:10.1111/exsy.12782 · Cited by 14
Farrell, R. M., Gilbert, G. E., Betance, L., Huck, J., Hunt, J., Dundas, J. M., & Pope, E. R. (2022) · Veterinary Surgery · doi:10.1111/vsu.13791 · Cited by 16
The Effect of a Final Exam on Long-Term Retention
Glass, A. L., Ingate, M. R., & Sinha, N. (2013) · The Journal of General Psychology · doi:10.1080/00221309.2013.797379 · Cited by 13
Nadeau, S. E., Davis, S. E., Wu, S. S., Dai, Y. E., & Richards, L. G. (2014) · Neurorehabilitation and neural repair · doi:10.1177/1545968314532032 · Cited by 13
Grain size of recall practice for lengthy text material: Fragile and mysterious effects on memory.
Wissman, K. T., & Rawson, K. A. (2014) · Journal of Experimental Psychology Learning Memory and Cognition · doi:10.1037/xlm0000047 · Cited by 13
The Effects of Distributed Learning on Enhanced Cognitive Interview Training
Heidt, C. T., Arbuthnott, K. D., & Price, H. L. (2015) · Psychiatry Psychology and Law · doi:10.1080/13218719.2015.1032950 · Cited by 18
Kornell, N., & Vaughn, K. E. (2018) · Archives of Scientific Psychology · doi:10.1037/arc0000042 · Cited by 20
Individualization of practice distribution in second language grammar learning
Suzuki, Y. (2019) · Journal of Second Language Studies · doi:10.1075/jsls.18023.suz · Cited by 13
A Review of the Interleaving Effect: Theories and Lessons for Future ResearchPreprint
Yan, V. X., Schuetze, B. A., & Eglington, L. G. (2020) · doi:10.31234/osf.io/ur6g7 · Cited by 15
Effects of distributed practice on the acquisition of second language English syntax—ERRATUM
Bird, S. (2011) · Applied Psycholinguistics · doi:10.1017/s0142716410000470 · Cited by 19
The Distributed Practice Effect on Classroom Learning: A Meta-Analytic Review of Applied Research
Mawson, R. D., & Kang, S. H. K. (2025) · Behavioral Sciences · doi:10.3390/bs15060771 · Cited by 14
de Lima, M. F. R., Júnior, S. V. P., da Costa, J. F. D., & Buratto, L. G. (2020) · The Spanish Journal of Psychology · doi:10.1017/sjp.2020.33 · Cited by 13
Edmonds, A., Gerbier, É., Palasis, K., & Whyte, S. (2021) · Lexis · doi:10.4000/lexis.5652 · Cited by 10
Speaking to remember: Model-based adaptive vocabulary learning using automatic speech recognition
Wilschut, T., Sense, F., & van Rijn, H. (2023) · Computer Speech & Language · doi:10.1016/j.csl.2023.101578 · Cited by 13
Horn, S., & Hernick, M. (2015) · Chemistry Education Research and Practice · doi:10.1039/c5rp00133a · Cited by 12
Effective teaching of economics: A constrained optimization problem?
Hultberg, P. T., & Calonge, D. S. (2017) · The Journal of Economic Education · doi:10.1080/00220485.2017.1353458 · Cited by 12
Exploration and Skill Acquisition in a Major Online Game
Stafford, T., Devlin, S., Sifa, R., & Drachen, A. (2017) · University of Southern Denmark Research Portal (University of Southern Denmark) · Cited by 11
Fahy, B. G., Vasilopoulos, T., Bensalem‐Owen, M., & Chau, D. F. (2018) · Journal of Clinical Neurophysiology · doi:10.1097/wnp.0000000000000554 · Cited by 12
Pachur, T., Schooler, L. J., & Stevens, J. R. (2012) · Oxford University Press eBooks · doi:10.1093/acprof:oso/9780195388435.003.0007 · Cited by 12
Designing Effective Speech-Language Interventions for Children in the Public Schools
Justice, L. M., Logan, J. A. R., Schmitt, M. B., & Jiang, H. (2016) · Policy Insights from the Behavioral and Brain Sciences · doi:10.1177/2372732215624705 · Cited by 12
Expanded taxonomies of human memory
Finley, J. R. (2025) · Frontiers in Cognition · doi:10.3389/fcogn.2024.1505549 · Cited by 17
Greving, C. E., & Richter, T. (2021) · Frontiers in Psychology · doi:10.3389/fpsyg.2021.685245 · Cited by 12
Nwokenna, E. N., Sewagegn, A. A., & Falade, T. A. (2022) · Medicine · doi:10.1097/md.0000000000032112 · Cited by 19
Yan, T., & Zhou, D. (2023) · System · doi:10.1016/j.system.2023.103049 · Cited by 14
Zhang, Y., Paquette, L., & Hu, X. (2024) · Computers & Education · doi:10.1016/j.compedu.2024.105029 · Cited by 13
Spacing learning units affects both learning and forgetting
Kornmeier, J., Sosic-Vasic, Z., & Joos, E. (2022) · Trends in Neuroscience and Education · doi:10.1016/j.tine.2022.100173 · Cited by 11
Selective remembering and directed forgetting are influenced by similar stimulus properties
Murphy, D. H., & Castel, A. (2022) · Memory · doi:10.1080/09658211.2022.2092152 · Cited by 10
The Importance of the Interface between Humans and Computers on the Effectiveness of eHRM
Johnson, R. D., Lukaszewski, K. M., Stone, D. L., & Tech, V. (2017) · AIS Transactions on Human-Computer Interaction · doi:10.17705/1thci.00087 · Cited by 13
Correcting Student Errors and Misconceptions
Marsh, E. J., & Eliseev, E. D. (2019) · Cambridge University Press eBooks · doi:10.1017/9781108235631.018 · Cited by 14
Amabile, A. H., Nixon‐Cave, K., Georgetti, L. J., & Sims, A. C. (2021) · BMC Medical Education · doi:10.1186/s12909-021-02925-z · Cited by 13
O’Sullivan, L., Casey, D., & Crowley, J. (2021) · Teaching Mathematics and its Applications An International Journal of the IMA · doi:10.1093/teamat/hrab016 · Cited by 11
van den Broek, G. S. E., van Gog, T., Jansen, E., Pleijsant, M., & Kester, L. (2021) · Journal of Educational Psychology · doi:10.1037/edu0000499 · Cited by 15
Benefits of Adaptive Learning Transfer From Typing-Based Learning to Speech-Based Learning
Wilschut, T., Sense, F., van der Velde, M., Fountas, Z., Maaß, S. C., & van Rijn, H. (2021) · Frontiers in Artificial Intelligence · doi:10.3389/frai.2021.780131 · Cited by 11
The Is and Ought of Sharing: The Equality Heuristic Across the Lifespan
Keller, M., Gummerum, M., Canz, T., Gigerenzer, G., & Takezawa, M. (2012) · Oxford University Press eBooks · doi:10.1093/acprof:oso/9780195388435.003.0006 · Cited by 12
Learning techniques that medical students use for long-term retention: A cross-sectional analysis
Urrizola, A., Santiago, R., & Arbea, L. (2023) · Medical Teacher · doi:10.1080/0142159x.2022.2137016 · Cited by 10
Time-dependent consolidation mechanisms of durable memory in spaced learning
Yang, Y., Huang, Z., Yang, Y., Fan, M., & Yin, D. (2025) · Communications Biology · doi:10.1038/s42003-025-07964-6 · Cited by 10
Choe, M. S., Huffman, L. C., Feldman, H. M., & Hubner, L. M. (2022) · Frontiers in Medicine · doi:10.3389/fmed.2022.835045 · Cited by 10
Tracing Undergraduate Science Learners’ Digital Cognitive Strategy Use and Relation to Performance
Mefferd, K., & Bernacki, M. L. (2023) · Journal of Science Education and Technology · doi:10.1007/s10956-022-10018-9 · Cited by 14
Fang, N., Elgort, I., & Chen, Z. (2024) · Studies in Second Language Acquisition · doi:10.1017/s0272263124000184 · Cited by 11
Memory from nonsense syllables to novels: A survey of retention
Radvansky, G. A., Parra, D., & Doolen, A. C. (2024) · Psychonomic Bulletin & Review · doi:10.3758/s13423-024-02514-3 · Cited by 12
Stuart, J., Gannon, P. R., Dotto, V. R., Regina, R., & Mumma, J. M. (2025) · American Journal of Infection Control · doi:10.1016/j.ajic.2025.01.007 · Cited by 10
Reynolds, B. L., & Ding, C. (2022) · English Teaching Practice & Critique · doi:10.1108/etpc-05-2021-0049 · Cited by 10
Between-list lag effects in recall depend on retention interval
Pyc, M. A., Balota, D. A., McDermott, K. B., Tully, T., & Roediger, H. L., III (2014) · Memory & Cognition · doi:10.3758/s13421-014-0406-1 · Cited by 11
Quizzes and conversations: exploring the role of retrieval in medical education
Larsen, D. P., & Dornan, T. (2013) · Medical Education · doi:10.1111/medu.12274 · Cited by 11
Investigating Optimal Memory Enhancement Procedures in Foreign Language Learning
Huffman, W. B., & Hahn, S. (2017) · Applied Cognitive Psychology · doi:10.1002/acp.3351 · Cited by 10
Chemical Hygiene and Safety Badge for an Upper-Level Laboratory Course
Roberts, A., O’Neil, A., Barlow, R. E., Keeler, C., Nelligan, W. S., & Westmoreland, T. D. (2020) · Journal of Chemical Education · doi:10.1021/acs.jchemed.0c00118 · Cited by 11
Modeling Growth in Electronic Learning Environments Using a Longitudinal Random Item Response Model
Kadengye, D. T., Ceulemans, E., & Noortgate, W. V. D. (2014) · The Journal of Experimental Education · doi:10.1080/00220973.2014.907226 · Cited by 10
A negative effect of repetition in episodic memory.
Peterson, D. J., & Mulligan, N. W. (2012) · Journal of Experimental Psychology Learning Memory and Cognition · doi:10.1037/a0028220 · Cited by 10
Evered, A. (2018) · Cytopathology · doi:10.1111/cyt.12578 · Cited by 9
The Mind as an Intuitive Pollster: Frugal Search in Social Spaces
Pachur, T., Hertwig, R., & Rieskamp, J. (2012) · Oxford University Press eBooks · doi:10.1093/acprof:oso/9780195388435.003.0009 · Cited by 11
Cromley, J. G., & Byrnes, J. P. (2012) · Wiley Interdisciplinary Reviews Cognitive Science · doi:10.1002/wcs.1192 · Cited by 10
Making Memories: Why Time Matters
Kelley, P., Evans, M. D. R., & Kelley, J. (2018) · Frontiers in Human Neuroscience · doi:10.3389/fnhum.2018.00400 · Cited by 10
Metadata
- Authors
- Cepeda, N. J., Vul, E., Rohrer, D., Wixted, J. T., & Pashler, H.
- Affiliations
- York University (CA)
- University of California San Diego (US)
- University of South Florida (US)
- Corresponding author
- Pashler, Harold
- Venue
- Psychological Science
- Publisher
- SAGE Publications
- Published
- 2008-11
- Volume
- 19
- Issue
- 11
- Pages
- 1095-1102
- ISSN
- 0956-7976 (ISSN-L)
- 1467-9280
- OpenAlex
- W2169419728
- Cited by
- 631
- References
- 32
- Citations by year
- 2026: 41 · 2025: 54 · 2024: 52 · 2023: 39 · 2022: 51 · 2021: 54 · 2020: 38 · 2019: 49 · 2018: 36 · 2017: 27 · 2016: 25 · 2015: 31 · 2014: 34 · 2013: 25 · 2012: 44
- FWCI
- 5.17
- Type
- journal article
- Language
- en
- Open access
- green
- escholarship.org
- Locations
- Psychological Science (publishedVersion)
- PubMed (publishedVersion)
- eScholarship (California Digital Library) (submittedVersion)
- Digital Commons - University of South Florida (University of South Florida) (submittedVersion)
- Funders
- National Science Foundation (0542013, 0720375)
- U.S. Department of Education
- Institute of Education Sciences
- Topics
- Life Sciences › Neuroscience › Cognitive Neuroscience › Memory Processes and Influences
- Social Sciences › Psychology › Experimental and Cognitive Psychology › Visual and Cognitive Learning Processes
- Life Sciences › Neuroscience › Cognitive Neuroscience › Memory and Neural Mechanisms
- Keywords
- spacing effect, retention, test delay, spaced learning, long-term memory
- MeSH terms
- Adolescent, Adult, Aged, Female, Humans, Learning, Male, Memory, Middle Aged, Retention, Psychology, Space Perception, Time Factors, Young Adult
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
A language model drew the claims from the paper on 2026-10-12, under version 3 of the claim definition (model deepseek-v4.1-flash, prompt extract-v3).
A second model labelled each claim on 2026-10-12 (model jev-1.13-20260917, definition revision gold-guideline-v0.2).
Cited sources are checked with a language model’s help (gpt-6-sol).
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
