Abstract
Despite the voluminous literatures on testing effects and lag effects, surprisingly few studies have examined whether testing and lag effects interact, and no prior research has directly investigated why this might be the case. To this end, in the present research we evaluated the elaborative retrieval hypothesis (ERH) as a possible explanation for why testing effects depend on lag. Elaborative retrieval involves the activation of cue-related information during the long-term memory search for the target. If the target is successfully retrieved, this additional information is encoded with the cue–target pair to yield a more elaborated memory trace that enhances target access on a later memory test. The ERH states that the degree of elaborative retrieval during practice is greater when testing takes place after a long rather than a short lag (whereas elaborative retrieval during restudy is minimal at either lag). Across two experiments, final-test performance was greater following practice testing than following restudy only, and this memorial advantage was greater with long-lag than with short-lag practice. The final test also included novel cue conditions used to diagnose the degree of elaborative retrieval during practice. The overall pattern of performance in these conditions provided consistent evidence for the ERH, with more extensive elaborative retrieval during long- than during short-lag practice testing.
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Notes
Adopting terminology used in recent reviews (Cepeda et al., 2006; Delaney, Verkoeijen, & Spirgel, 2010), we distinguish between spacing effects and lag effects, which are often conflated. Practice trials for a given item can be presented consecutively (i.e., massed) or separated by intervening time or material (i.e., spaced); the spacing effect refers to enhanced performance for spaced over massed trials. When practice is spaced, the interval between trials for a given item (i.e., the lag) can also be varied. Lag effects refer to differences in performance for longer versus shorter lags, which is the effect of interest here.
Cull’s (2000) Experiments 3 and 4 involved longer retention intervals and compared lags of minutes versus days. Unfortunately, these outcomes are not readily interpretable, due to several methodological limitations (in brief, retention interval and lag were confounded, such that the retention intervals were 6 days longer for short- than for long-lag conditions; participants completed the practice trials without supervision outside the lab; and performance was consistently at or near ceiling in one or more of the conditions).
McEldoon, Durkin, and Rittle-Johnson (2013) noted that effect sizes and observed power “should be considered when interpreting the practical significance of results, and relying too heavily on p-values may lead to misguided interpretations . . . limited power can be a rival explanation of statistically non-significant findings, and one must be careful not to falsely reject the alternative hypothesis” (p. 622). Also following recent recommendations (Simmons et al., 2011), we elected to terminate data collection with the intended sample size indicated by a priori power analyses and then to conduct a replication study (Exp. 2), rather than adding data to Experiment 1 in an attempt to reach statistical significance. When adopting this approach, Simmons et al. recommended that readers “should be more tolerant of imperfections in results. . . . Underpowered studies with perfect results are the ones that should invite extra scrutiny.”
In principle, on the basis of the theoretical assumptions of the ERH outlined here, one would expect lower performance for mediator cues in the short-lag restudy condition than in the other seven conditions. However, given that neither Carpenter (2011) nor the present Experiment 2 demonstrated a reversal, we assume that this outcome reflects noise.
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Author note
The research reported here was supported by a James S. McDonnell Foundation 21st Century Science Initiative in Bridging Brain, Mind and Behavior Collaborative Award.
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Appendices
Appendix A: Items used in Experiments 1 and 2
Original Cues | Target Words | Mediator Cues | Related Cues | Associative Strength | ||
C-M | C-T | R-T | ||||
mother | child | father | birth | .597 | .010 | .015 |
prescription | doctor | drug | hospital | .477 | .034 | .027 |
soil | earth | dirt | continent | .717 | .040 | .041 |
dusk | evening | dawn | morning | .609 | .042 | .047 |
donor | heart | blood | liver | .524 | .042 | .041 |
weapon | knife | gun | axe | .592 | .075 | .046 |
sonnet | music | poem | dancer | .471 | .059 | .052 |
employment | office | job | government | .605 | .020 | .024 |
trash | paper | garbage | ink | .526 | .013 | .013 |
vocabulary | school | words | text | .507 | .013 | .013 |
jacket | shirt | coat | hanger | .564 | .013 | .014 |
pedestrian | street | walk | neighborhood | .597 | .032 | .034 |
breeze | summer | wind | mosquito | .606 | .012 | .014 |
coffee | table | tea | banquet | .442 | .020 | .020 |
frame | window | picture | shingle | .811 | .014 | .014 |
agony | ecstasy | pain | pleasure | .649 | .019 | .014 |
alive | breathe | dead | vapor | .554 | .020 | .040 |
anatomy | biology | body | lab | .607 | .028 | .022 |
bait | hook | fish | pirate | .629 | .053 | .047 |
clock | hands | time | pray | .652 | .036 | .033 |
pepper | sneeze | salt | dust | .695 | .041 | .054 |
umbrella | dry | rain | rinse | .701 | .042 | .035 |
wallet | leather | money | boots | .630 | .041 | .042 |
vine | ivy | grape | league | .605 | .020 | .014 |
flipper | scuba | dolphin | tank | .797 | .020 | .016 |
glacier | mountain | ice | volcano | .723 | .020 | .022 |
hammer | pound | nail | knock | .800 | .028 | .027 |
rake | hoe | leaves | shovel | .622 | .047 | .042 |
king | crown | queen | jewel | .772 | .016 | .020 |
peel | potato | orange | tomato | .571 | .065 | .062 |
pork | beef | pig | cattle | .594 | .042 | .041 |
lamp | post | light | mailbox | .769 | .026 | .013 |
lather | shave | soap | whiskers | .673 | .048 | .073 |
mouse | trap | cat | cage | .543 | .029 | .028 |
tusk | tooth | elephant | pick | .660 | .028 | .034 |
antler | moose | deer | noose | .615 | .027 | .021 |
The first 16 items are the same as in Carpenter (2011, Exp. 2). C-T = cue-to-target strength. C-M = cue-to-mediator strength. R-T = related-to-target strength. The mediator-to-target strength was 0 for all pairs. The associative strength between mediator cues and all other target words was 0, and the associative strength between related cues and all other target words was also 0.
Appendix B: Preliminary study that informed the methodology used in Experiments 1 and 2
Method
Undergraduates (n = 128) were randomly assigned to one of four groups defined by lag (short vs. long) and type of practice (test vs. restudy). Final-test cue (original, mediator, or related) was manipulated within participants. The targeted sample size of 128 was based on the same power analysis reported for Experiment 1. The materials and procedure were the same as in Experiment 1, except that (1) items were presented for three blocks of learning trials (either SSS in the restudy group or STT in the test group), and (2) the final test was administered 20 min after the final block.
Results and discussion
During practice, mean cued recall was significantly greater with a short lag (85.2 %, SE = 2.8) than with a long lag (70.2 %, SE = 3.5), t(63) = 3.32, p = .001, d = 0.82. Concerning final-test performance in the original-cue condition (Table 4), we did not find significant effects of either testing (F < 1) or lag, F(1, 124) = 2.80, MSE = 600.08, p = .097, η p 2 = .02 (interaction F < 1). In hindsight, these outcomes are consistent with prior research showing weaker or reversed lag effects with shorter retention intervals and/or low levels of practice (e.g., Cepeda et al., 2006; Pavlik & Anderson, 2005; Rawson, 2012) and weaker or reversed testing effects at short retention intervals (e.g., Congleton & Rajaram, 2012; Coppens et al., 2011; Roediger & Karpicke, 2006; Toppino & Cohen, 2009).
With that said, a testing effect may still have been expected, given that the present experiment was a close replication of Carpenter (2011). One difference between these two studies involved set size (16 items in Carpenter, 2011, vs. 36 items here, to include enough items in each cell of the expanded design to accommodate the additional manipulation of lag). Consistent with list length effects (e.g., Cary & Reder, 2003; Ward & Tan, 2004), practice recall was lower in Experiment 1 than in Carpenter’s (2011) study (78 % overall in Exp. 1 vs. 91 % in Carpenter, 2011), and testing effects depend in part on the level of retrieval success during practice (e.g., Halamish & Bjork, 2011; Kornell et al., 2011). These outcomes motivated methodological changes in Experiments 1–2 to increase successful retrieval during practice (by increasing the amount of practice) and to use more sensitive conditions for detecting testing and lag effects (by using a longer retention interval).
Final-test performance in the mediator- and related-cue conditions (Table 4) replicated the key outcomes reported by Carpenter (2011): The advantage of mediator cues over related cues was greater in the testing group (28.1 vs. 16.4 %, d = 0.50) than in the restudy group (13.8 vs. 10.1 %, d = 0.22). A 2 (Practice Group: test or restudy) × 2 (Cue: mediator or related) ANOVA revealed main effects of practice group and cue [F(1, 126) = 11.28, MSE = 606.34, p = .001, η p 2 = .08; F(1, 126) = 26.42, MSE = 143.07, p < .001, η p 2 = .17, respectively] and a significant interaction [F(1, 126) = 7.09, MSE = 143.07, p = .009, η p 2 = .05]. Given the absence of lag effects in the original-cue condition, not surprisingly, no effect or interaction involving lag was significant in the new-cue conditions, Fs < 1.
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Rawson, K.A., Vaughn, K.E. & Carpenter, S.K. Does the benefit of testing depend on lag, and if so, why? Evaluating the elaborative retrieval hypothesis. Mem Cogn 43, 619–633 (2015). https://doi.org/10.3758/s13421-014-0477-z
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DOI: https://doi.org/10.3758/s13421-014-0477-z