Introduction
Collocations refer to frequently recurring word combinations consisting of two content words (e.g., verb + noun, adjective + noun; Ackermann & Chen, Reference Ackermann and Chen2013; Shin, Reference Shin2006). Collocations can be adjacent (e.g., meet demand, make decisions) or nonadjacent (e.g., meet the demand , make important decisions ; Boers et al., Reference Boers, Lindstromberg and Eyckmans2014; Wood, Reference Wood and Webb2020), and are often characterized by restricted co-occurrence (e.g., make a decision but not do a decision; Paquot & Granger, Reference Paquot and Granger2012). Research suggests that collocational competence plays a pivotal role in second language (L2) learning, helping learners attain a sufficient level of accuracy and fluency (González-Fernández & Schmitt, Reference González-Fernández and Schmitt2015; Siyanova & Schmitt, Reference Siyanova and Schmitt2008). Despite the importance of collocational knowledge, research also suggests that development of collocational knowledge often lags behind that of single words (Boers et al., Reference Boers, Lindstromberg and Eyckmans2014; Laufer & Waldman, Reference Laufer and Waldman2011; Szudarski, Reference Szudarski2017). Considering the importance of collocational knowledge for L2 learning, research examining how collocation learning can be facilitated is valuable from both theoretical and pedagogical perspectives. Research has suggested that L2 collocation learning may be affected by various factors, such as frequency of exposure (e.g., Pellicer-Sánchez, Reference Pellicer-Sánchez2017; Szudarski & Carter, Reference Szudarski and Carter2016; Webb et al., Reference Webb, Newton and Chang2013), type of input (e.g., Peters, Reference Peters2016; Toomer & Elgort, Reference Toomer and Elgort2019; Webb & Chang, Reference Webb and Chang2022; Webb & Kagimoto, Reference Webb and Kagimoto2009), and type of exercise and instruction (e.g., Boers, Demecheleer et al., Reference Boers, Demecheleer, Coxhead and Webb2014; Boers et al., Reference Boers, Dang and Strong2017; Eyckmans et al., Reference Eyckmans, Boers and Lindstromberg2016).
Another factor that can potentially affect L2 collocation learning is temporal spacing. Research indicates that distributing practice over a long period often facilitates the learning of single words (e.g., Bahrick & Phelps, Reference Bahrick and Phelps1987; Kim & Webb, Reference Kim and Webb2022; Nakata & Webb, Reference Nakata and Webb2016). The memory advantage of spacing over no spacing (pure massing) is referred to as the spacing effect, whereas the advantage of longer temporal spacing over shorter spacing is referred to as the lag effect (Cepeda et al., Reference Cepeda, Pashler, Vul, Wixted and Rohrer2006). Despite the potential benefits of spacing for vocabulary learning, research examining its effects on collocation learning is still limited. The present study aims to fill a gap in existing research by investigating the effects of spacing on the learning of L2 collocations.
Literature review
Research suggests that distributing practice opportunities over longer periods facilitates L2 vocabulary learning. For instance, in Nakata and Webb (Reference Nakata and Webb2016, Experiment 2), 78 Japanese learners studied 20 English–Japanese word pairs under short- or long-spaced conditions. In the short-spaced condition, a target word was repeated after approximately 30 seconds, whereas in the long-spaced condition, a target word was repeated after approximately 3 minutes. Learning was measured by productive and receptive posttests conducted immediately and 1 week after the treatment. Posttest results suggested that long spacing was more than twice as effective as short spacing. Similarly, in Bahrick and Phelps (Reference Bahrick and Phelps1987), 35 participants studied 50 English-Spanish word pairs using one of three spacing intervals: same day, 1 day, and 30 days. Retention was measured approximately 8 years after the last treatment. Posttest results suggested that spacing of 30 days was more than twice as effective as same-day spacing. Although the findings of these studies are useful, most studies have examined the effects of spacing on the learning of single words; thus, little is known about whether the benefits of spacing also extend to collocation learning. Two recent studies (Macis et al., Reference Macis, Sonbul and Alharbi2021; Snoder, Reference Snoder2017), however, have examined the effects of spacing on L2 collocation learning and constitute exceptions.
Macis et al. (Reference Macis, Sonbul and Alharbi2021) compared the effects of massing and spacing on learning 25 adjective-noun collocations in incidental (Experiment 1) and deliberate learning conditions (Experiment 2). Across two experiments, Arabic EFL learners were assigned to one of five groups: incidental massed, incidental spaced, deliberate massed, deliberate spaced, and control. Those in the two incidental groups read short stories containing target collocations and answered comprehension questions (Experiment 1). Participants in the two deliberate groups studied the same target collocations through concordance lines and then completed matching and multiple-choice exercises (Experiment 2). In both massed and spaced groups, a given target collocation was encountered five times over 5 weeks. In the massed groups, a given target collocation was encountered five times on the same day. In the spaced groups, a given target collocation was encountered only once a week, and five occurrences were distributed over 5 weeks. Learning was measured by a fill-in-the-blank posttest, where participants were asked to supply an appropriate adjective that collocated with the noun (e.g., the adjective dead for the noun silence). The results showed that the deliberate-spaced group had the largest gains, followed by the deliberate-massed, incidental-massed, and incidental-spaced groups. The findings suggest that spacing facilitates learning of not only single words but also collocations, albeit only in intentional learning.
Snoder (Reference Snoder2017) conducted another study that examined the effects of spacing on L2 collocation learning. In it, 59 Swedish learners of English studied 28 verb-noun collocations under an expanding or intensive condition. In the expanding group, the treatment was given on days 1, 7, and 16, whereas in the intensive group, the treatment took place on days 1, 2, and 4. Learning was measured by a posttest that required participants to provide a verb that collocated with the noun. Posttests results showed no statistically significant difference between the two groups. One possible explanation for inconsistent findings between Macis et al. (Reference Macis, Sonbul and Alharbi2021) and Snoder (Reference Snoder2017) may be that whereas the former compared massing (where practice opportunities for target materials are concentrated into a single day) and spacing (where practice opportunities for target materials are distributed over multiple days) and examined the spacing effect, the latter compared effects of two spacing schedulers (i.e., relatively short vs. relatively long intervals) and examined the lag effect.
Although the findings of these studies are informative, one potential limitation is that they examined the learning of only one collocate per node word. For instance, Snoder (Reference Snoder2017) investigated the learning of 28 verb-noun collocations, but there was only one collocation for each node verb (e.g., carry a risk, entertain hope, score success). This is unfortunate because collocational development is perhaps facilitated by exposure to multiple collocations containing the same node. For instance, if Japanese learners of English first encountered the word break in the collocation break a window, they may associate break with its first language (L1) translation waru (i.e., to destroy a physical object; lexical association stage in Jiang, Reference Jiang2004), and may hypothesize that it can collocate only with concrete nouns. Exposure to collocations such as break a promise or break the record may allow learners to reconceptualize their knowledge of the meaning potential of the word (semantic restructuring; Jiang, Reference Jiang2004), helping them to comprehend or produce novel collocations such as break a rule, break one’s heart, or break the news. Considering that exposure to multiple collocations with the same node perhaps facilitates collocational development, it would be useful to examine how spacing of multiple collocations with the same node affects collocational knowledge.
Multiple collocations for a given node may be introduced in one of the three schedules: massed from the perspective of the same node (hereafter, node massed), massed from the perspective of individual collocations (hereafter, collocation massed), and spaced from the perspective of individual collocations (hereafter, collocation spaced). In the node-massed schedule, practice opportunities for multiple collocations for the node word (e.g., draw a line, draw tears, draw a conclusion) are concentrated into a single session, and they are never repeated in subsequent sessions. In the collocation-massed schedule, multiple collocations for the same node are introduced across multiple sessions. For instance, learners may encounter draw a line in Day 1, draw tears in Day 2, and draw a conclusion in Day 3. However, practice opportunities for individual collocations are concentrated into a single session (e.g., draw a line is studied only in Day 1). As such, the schedule is massed from the perspective of individual collocations. In the collocation-spaced schedule, learners encounter multiple collocations for the same node word within a single session, just as in the node-massed schedule. At the same time, multiple collocations for the same node are repeated across multiple sessions. For instance, learners may study draw a line, draw tears, and draw a conclusion in all Days 1, 2, and 3. Although it may be useful to examine how these three schedules affect collocation learning, the existing spacing studies on collocation learning (Macis et al., Reference Macis, Sonbul and Alharbi2021; Snoder, Reference Snoder2017) have failed to provide evidence regarding the relative effectiveness of them.
When examining the effects of spacing on learning of multiple collocations with the same node, it would also be useful to examine not only the extent to which learners acquired collocations that they were exposed to but also the extent to which learners can transfer knowledge of studied collocations to novel, unstudied collocations that contain the same node but were not previously encountered (hereafter, unstudied collocations refer to novel collocations that contain the same node as the collocations that learners were exposed to). This is because exposure to multiple collocations with the same node may help learners to comprehend or produce novel collocations with the same node. For instance, exposure to multiple collocations with break (e.g., break a window, break a promise, or break the record) may allow learners to transfer knowledge of these collocations to novel, unstudied collocations with the same node (e.g., break a rule, break one’s heart, or break the news).
Considering that exposure to multiple collocations with the same node is instrumental for collocational development, it would be useful to examine how the distributions of multiple collocations with the same node affect collocational knowledge. Furthermore, because learners do not acquire all collocations as individual units but instead make generalizations about which words can co-occur through repeated encounters with multiple collocations, examining the effects of spacing on knowledge of both studied and unstudied collocations would be useful. However, existing studies examining the effects of spacing on L2 collocation learning (Macis et al., Reference Macis, Sonbul and Alharbi2021; Snoder, Reference Snoder2017), as well as the majority of previous studies on L2 collocation learning in general (e.g., Boers et al., Reference Boers, Dang and Strong2017; Eyckmans et al., Reference Eyckmans, Boers and Lindstromberg2016; Pellicer-Sánchez, Reference Pellicer-Sánchez2017; Peters, Reference Peters2016; Szudarski & Carter, Reference Szudarski and Carter2016; Toomer & Elgort, Reference Toomer and Elgort2019; Webb & Chang, Reference Webb and Chang2022), have failed to investigate the extent to which learners can transfer knowledge of studied collocations to unstudied collocations.
Investigating effects of spacing on unstudied collocations is also useful because it allows researchers to examine whether benefits of temporal spacing apply not only to recall of previously presented materials but also to induction. Specifically, transferring knowledge of studied collocations to unstudied collocations typically involves induction because it requires learners to extract the core, underlying meaning of the node, based on multiple collocations of the same node (unless learners are explicitly taught the core meaning of the node). Most studies examining effects of spacing on single words (e.g., Bahrick & Phelps, Reference Bahrick and Phelps1987; Nakata & Webb, Reference Nakata and Webb2016), in contrast, have investigated recall of previously presented materials (i.e., learners are presented with L2 words together with their meanings, and asked to learn them), rather than induction. It should be noted that some cognitive psychologists argue that although spacing may be effective for recall, it may not necessarily facilitate inductive learning. As Kornell and Bjork (Reference Kornell and Bjork2008) state, it is possible that “spacing is the friend of recall, but the enemy of induction” (p. 585). This is because presenting multiple instances of a particular category or concept simultaneously (i.e., massing) may help learners identify underlying conceptual features. In contrast, when multiple instances of a particular concept are presented after long intervals (spacing) learners may have difficulty noticing underlying commonalities, thus making induction more difficult. Given that spacing may have differential effects on recall and induction, it is possible that the learning of collocations, especially those of unstudied collocations, may benefit from spacing to a lesser degree than the learning of single words.
The present study
The present study aims to fill this research gap by investigating effects of node-massed, collocation-massed, and collocation-spaced schedules on knowledge of studied and unstudied collocations. The treatment was conducted over 3 weeks. In the node-massed schedule, multiple collocations for the same node verb (draw a conclusion, draw a line, draw tears) were concentrated into a single day and were not repeated in subsequent days. In the collocation-massed schedule, multiple collocations for the same node verb were introduced across the 3 weeks. For instance, participants studied draw a line in Week 1, draw tears in Week 2, and draw a conclusion in Week 3. However, practice opportunities for individual collocations were concentrated into a single session (e.g., draw a line was studied only in Week 1). In the collocation-spaced group, participants studied multiple collocations for the same node verb within a single day, just like the node-massed schedule. At the same time, multiple collocations for the same node verb were repeated each week. For instance, participants studied three collocations for the node verb draw (draw a conclusion, draw a line, draw tears) in Weeks 1, 2, and 3 (see “Method” section for more details).
This study will answer the following research question: To what extent do node-massed, collocation-massed, and collocation-spaced schedules facilitate knowledge of studied and unstudied L2 collocations?
The following hypotheses were formulated for the mentioned research question:
Hypothesis 1: For the retention of studied collocations, the collocation-spaced schedule will be more effective than the node-massed and collocation-massed schedules.
Hypothesis 2: For the knowledge of unstudied collocations, the collocation-spaced schedule will be the most effective, the collocation-massed schedule will be the least, and the node-massed schedule will be between the two.
Hypothesis 1 predicts that the collocation-spaced schedule will be most effective for the retention of studied collocations. This is because whereas practice opportunities for individual collocations are distributed over 3 weeks in the collocation-spaced schedule, they are concentrated into a single session in the two massed schedules. Existing studies have produced inconsistent results regarding effects of spacing on collocation learning. Specifically, whereas Macis et al. (Reference Macis, Sonbul and Alharbi2021) found benefits of distributed practice for intentional learning, Snoder (Reference Snoder2017) failed to do so. Hypothesis 1 predicts that the results of this study will be consistent with those of Macis et al. (Reference Macis, Sonbul and Alharbi2021). This is because, just like the study conducted by Macis and colleagues, the present study involves the comparison of spacing and massing and examines the spacing effect, whereas Snoder’s study involved the comparison of two spacing schedulers (i.e., relatively short vs. relatively long intervals) and examined the lag effect.
Hypothesis 2 predicts that for knowledge of unstudied collocations, the collocation-spaced schedule will be the most effective, followed by the node-massed schedule. In the node-massed and collocation-spaced schedules, learners are exposed to multiple collocations for the same node (e.g., draw a line, draw tears, draw a conclusion) within a single session, which may allow learners to extract the core, underlying meaning of the node. This in turn may improve the ability to transfer knowledge of studied collocations to novel, unstudied collocations that contain the same node. In the collocation-massed schedule, in contrast, multiple collocations with the same node are introduced in different weeks (e.g., Week 1: draw a line, Week 2: draw tears, Week 3: draw a conclusion). This may make it difficult for learners to notice underlying commonalities motivating the use of the node word, resulting in limited ability to transfer knowledge of studied collocations to unstudied collocations.
Hypothesis 2 also predicts the advantage of the collocation-spaced schedule over the node-massed schedule for knowledge of unstudied collocations. Existing studies comparing blocking (i.e., a schedule where only one concept or skill is practiced at a time) and interleaving (i.e., a schedule where multiple concepts or skills are practiced at once) suggest that blocking may be beneficial for finding commonalities among different exemplars of a particular concept or category (Carpenter & Mueller, Reference Carpenter and Mueller2013; Kang, Reference Kang, Horvath, Lodge and Hattie2016), which might predict the advantage of the node-massed schedule over the collocation-spaced schedule for unstudied collocations. This is because whereas the node-massed schedule (where exemplars from only one node are presented each day) is akin to blocking, the collocation-spaced schedule (where exemplars from multiple nodes are presented each day) is akin to interleaving. However, although encounters with a given node are concentrated into a single session in the node-massed schedule, they are distributed over 3 weeks in the collocation-spaced schedule. Because encounters with a given node distributed over a longer period in the collocation-spaced schedule may help consolidate learners’ understanding of the meaning potential of the node, Hypothesis 2 predicts the advantage of the collocation-spaced schedule over the node-massed schedule for knowledge of unstudied collocations.
Method
Participants
The original pool of participants consisted of 96 first-year Japanese EFL high school students (15–16 years old). Six students who missed one or more of the pretest, treatment, or posttest sessions were excluded from analysis, resulting in 90 participants. All participants had learned English in a formal setting for at least 4 years. Prior to the experiment, they took the 1,000 to 5,000 frequency levels on the Updated Vocabulary Level Test (UVLT), Version B (Webb et al., Reference Webb, Sasao and Ballance2017). The average scores are provided in Table 1. The participants came from three intact classes, each of which was randomly assigned to one of three groups: node massed (n = 27), collocation massed (n = 31), and collocation spaced (n = 32). Because a statistically significant difference was found among the three groups in their total scores on UVLT, F (2, 87) = 8.37, p < .001, η2 = .16 (collocation spaced > node massed [p < .001]; collocation spaced > collocation massed [p = .039]; collocation massed = node massed [p = .084]), the UVLT score was used as a covariate in the analysis (see the following text). An a priori power analysis for a mixed within-between 3 × 2 ANOVA (three groups at two measurement points) showed that when the effect size was set to be medium (f = .25), a minimum of 64 participants would be necessary. As a result, the number of participants in the present study (n = 90) was deemed sufficient.
Table 1. Proportion of correct responses on the UVLT
Materials
Fifty-four verb-noun collocations (e.g., carry weight, draw a line, take advice) were chosen as target items. All collocations were incongruent between the L1 (Japanese) and L2 (English), that is, the translation of the node verb in each collocation was different from its most common, prototypical translation equivalent (Conklin & Carrol, Reference Conklin, Carrol, Siyanova-Chanturia and Pellicer-Sánchez2018; Gyllstad & Wolter, Reference Gyllstad and Wolter2016; Szudarski, Reference Szudarski2012). Initially, 144 collocations were identified as candidates for target items. Based on results of a norming test administered to 191 Japanese high school students who did not participate in the actual experiment, the 144 items were narrowed down to 74 (see Appendix S1 in the Online Supplementary Materials). To identify collocations that were unfamiliar, a pretest was carried out 3 weeks before the treatment with actual participants of the experiment.
Two types of tests were given as the pretest: collocation filling and verb filling. In the collocation-filling test, participants were presented with a short sentence where a target collocation was deleted and asked to supply the missing verb and noun. To clarify the meaning of the target collocation, a Japanese translation of the sentence was provided. To prevent participants from providing alternate, acceptable answers (e.g., run a fever instead of have a fever), the number of letters was provided as a hint. In addition, based on a similar procedure utilized in Nakata and Webb (Reference Nakata and Webb2016), a letter from the word was sometimes provided as a hint when deemed necessary to help avoid alternative, acceptable answers. Participants were informed that they could provide multiple answers if they could think of more than one. An example of a collocation-filling item is as follows:
もし熱が出れば、できるだけ早く私に言ってくださいね。
If you ( _ _ _ ) a/an ( _ _ _ _ _ ), please tell me as soon as possible.
(Answer. run, fever)
Cloze sentences were created so that all words used in each sentence would be among the most frequent 4,000 word families of the COCA. As the results of the UVLT suggest (see “Participants” section), it is possible that some participants were not familiar with some words used in these sentences. However, because Japanese translations for all sentences were provided, potential use of unfamiliar words perhaps did not have major effects on the results of this study. Vocabulary load analysis also showed that the most frequent 1,000 word families alone cover 95.4% of running words used in the cloze sentences.
In the verb-filling test, the noun of the candidate collocation was given, and participants were required to fill in the missing verb. After completing the collocation-filling test, participants were asked not to return to any items on the collocation-filling test. Both pretests required the production, rather than comprehension, of target collocations. Because research suggests that production of collocations poses more of a challenge for L2 learners than comprehension (Gyllstad & Wolter, Reference Gyllstad and Wolter2016; Henriksen, Reference Henriksen, Bardel, Lindqvist and Laufer2013; Laufer & Waldman, Reference Laufer and Waldman2011), this study is also concerned with the development of productive knowledge of collocations. As a result, productive collocational knowledge was measured in both pretests and posttests. The pretest is provided in Appendix S2 in the Online Supplementary Materials. Based on the results of a pilot study involving 80 Japanese learners recruited from a different high school than the school where the main study was conducted, participants were given up to 40 minutes to complete the pretest. They were also instructed to put a circle around the number of the last question they solved if they were unable to complete the test within the time limit. None of the participants indicated that they were unable to complete the pretest. Because it was not possible to identify a sufficient number of target collocations based on the results of the pretest, an additional pretest with 12 novel collocations was administered 2 weeks before the treatment (see Appendix S3 in the Online Supplementary Materials). Based on results of the pretest and additional pretest, 54 target collocations, which consisted of nine node verbs and their six collocate nouns, were chosen (see Appendix S4 in the Online Supplementary Materials). Out of the 54 target collocations, 53 were chosen from the first pretest, and only one item (cut a loss) was chosen from the additional pretest.
The target collocations were divided into two sets of 27 items (nine node verbs and their three collocate nouns each). One set of items was assigned to studied items, whereas the other to unstudied items. Both studied and unstudied items were tested on the pretest and posttest. However, although studied items were presented and practiced during the treatment, unstudied items did not appear throughout the treatment. Unstudied items were included to examine effects of the treatment on the ability to transfer knowledge of studied collocations to unstudied, novel collocations that contain the same node. The two sets were created so that they were matched for variables such as the average pretest score, t-score (Hunston, Reference Hunston2002; Webb et al., Reference Webb, Newton and Chang2013), frequency in the Corpus of Contemporary American English (COCA), and familiarity ratings of the nouns by Japanese learners (see Appendix S4 in the Online Supplementary Materials). Care was also taken to ensure that collocations with similar meanings (e.g., cut class and cut school) would not be included in the same set. Only collocations that were semantically motivated by the core meaning of the node verb were used as target collocations. This is because otherwise we would not be able to expect learners to transfer the knowledge of studied collocations to unstudied collocations. The relationship between the core meaning of the node verb and the meaning of each target collocation is provided in Appendix S4 in the Online Supplementary Materials.
Procedure
Treatment
Three weeks after the pretest and 2 weeks after the additional pretest, the treatment was conducted over 3 weeks. Three treatment sessions were given each week (on Monday, Wednesday, and Friday), resulting in nine sessions in total. Each session took approximately 5 to 10 minutes and was conducted during regular class hours. Different target collocations were introduced in each class, depending on the participants’ group (i.e., node massed, collocation massed, or collocation spaced). Figure 1 presents target collocations introduced in each session in the three groups. In the node-massed group, participants learned three collocations containing the same node verb each day (e.g., draw a conclusion, draw a line, draw tears). In the collocation-massed group, multiple collocations for the same node verb were studied in different weeks. For instance, participants studied draw a line in Week 1, draw tears in Week 2, and draw a conclusion in Week 3. In the collocation-spaced group, participants studied multiple collocations for the same node verb (e.g., draw a conclusion, draw a line, draw tears) within a single day. At the same time, multiple collocations for the same node were encountered every week throughout the treatment. For instance, participants studied three collocations for the node verb draw (draw a conclusion, draw a line, draw tears) in each week of the treatment.
Figure 1. Target items introduced in each treatment.
For each treatment session, materials were presented on a screen in front of the classroom using presentation software. The treatment session consisted of the following seven stages: (1) presentation of target collocations, (2) presentation of target collocations in context, (3) retrieval of target verbs, (4) translation of target collocations, (5) retrieval of target verbs in context, (6) retrieval of target collocations in context, and (7) a quiz. See Appendix S5 in the Online Supplementary Materials for further details of the stages. Three out of the seven stages (Stages 2, 5, and 6) involved a context sentence containing a target collocation. For a given collocation, the same context sentence was used for all three stages. This is because a study conducted by Durrant and Schmitt (Reference Durrant and Schmitt2010) suggests that repeating the same context sentence three times may facilitate L2 collocational development more than using three different sentences.
For Stages (1)–(7), the target collocations were presented in a block of three (for the node-massed and collocation-massed groups) or nine items (for the collocation-spaced group) and repeated, instead of one collocation going through all seven stages one by one. For instance, as shown in Figure 1, in the node-massed group, for the first treatment session (Wednesday in Week 1), the following three collocations were introduced: run a fever, run a story, run a finger. At the beginning of the treatment, all three collocations were presented for Stage (1). After this, the three collocations were practiced in Stage (2). This was followed by the three collocations practiced in Stage (3), and so forth. To minimize order effect, the items appeared in a different order for each stage.
As shown in Figure 1, whereas three collocations were practiced each day in the two massed groups, in the collocation-spaced group, nine collocations were practiced each day. Please note, however, that when collapsed across all treatment sessions, the number of encounters was held constant for all three groups. For instance, in the two massed groups, participants completed all seven stages for the target collocation run a story in the first treatment session in Week 1 (see Appendix S5 in the Online Supplementary Materials). In contrast, for the target collocation run a story, participants in the collocation-spaced group completed Stages (1), (2), and (7) in Week 1, Stages (3) and (4) in Week 2, and Stages (5) and (6) in Week 3. Because each target collocation was practiced seven times throughout the treatment in all three conditions, the number of encounters was held constant for all three groups. Because the treatment was paced by the presentation software, time-on-task was also held constant, and the only difference was how the practice opportunities were distributed.
Posttests
Immediately after the last treatment session (Monday in Week 3; Figure 1), participants took the immediate posttest. It was different from the pretest in four respects. First, although the number of letters, and sometimes one letter from the word, was provided as a hint in the pretest (e.g., _ _ _ _ for take), no hint was provided on the posttest. Second, in the pretest, 98 items (74 in the pretest and 24 in the additional pretest) were tested in both the collocation-filling and verb-filling tests. In the posttest, only 27 studied collocations were tested in the collocation-filling test, and 54 target collocations (27 studied and 27 unstudied) were tested in the verb-filling test. Unstudied items were not tested in the collocation-filling test (which required learners to provide both the node verb and collocate noun) because we cannot expect any of the treatments to contribute to the learners’ ability to successfully provide the correct collocate noun, which was not encountered during the treatment. Third, a randomized item order different from the pretest was used for the immediate posttest to minimize order effect. Fourth, because the posttest involved less items than the pretest, the time limit for the posttest (20 minutes) was shorter than that for the pretest (40 minutes). The time limit for the posttest was determined based on a pilot study with 80 Japanese learners recruited from a different high school than the school where the main study was conducted. Other than these, the immediate posttest was the same as the pretest (see the immediate posttest in Appendix S6 in the Online Supplementary Materials). Two weeks after the immediate posttest, a delayed posttest was administered without prior announcement. This was identical to the immediate posttest except for item order. Two types of posttests (collocation filling and verb filling) were used in the present study. This is because administering two posttests with different levels of sensitivity may provide a more comprehensive picture regarding the incremental nature of collocation learning (Peters, Reference Peters2016; Szudarski & Carter, Reference Szudarski and Carter2016).
Scoring and data analysis
Collocation-filling test
The knowledge of intact, studied collocations was measured by the collocation-filling test. If participants provided both the verb and noun successfully, it was scored as correct. Misspelled responses were scored as correct as long as they were recognizable (e.g., Snoder, Reference Snoder2017; Sonbul & Schmitt, Reference Sonbul and Schmitt2013; Toomer & Elgort, Reference Toomer and Elgort2019). To control for effects of prior knowledge, for each participant, items answered successfully on the pretest were treated as missing values and excluded from analysis (e.g., Nakata & Suzuki, Reference Nakata and Suzuki2019). This resulted in the exclusion of 1.3% of items on average per participant (node massed: 1.1%, collocation massed: 1.2%; collocation spaced: 1.5%). All analyses had α levels set at .05.
Responses were analyzed using a mixed-effect logistic regression model with the lme4 package (version 1.1-27.1; Bates et al., Reference Bates, Maechler, Bolker and Walker2015) in R (version 4.1.2; R Core Team, 2021). The response variables were discrete binary data (correct = 1, incorrect = 0). Treatment (node massed, collocation massed vs. collocation spaced) and Test_timing (immediate vs. delayed posttest) were included as fixed effects. To control for English proficiency effects, UVLT scores were included as a covariate in the model. Furthermore, to control for recency effect, lag to test (the number of days between the last occurrence of the item during the treatment and immediate posttest) was also included as a covariate. For instance, the last occurrence for the target item run a fever during the treatment was in the first treatment session (Wednesday in Week 1) in the node-massed group, whereas it was in the seventh treatment session (Wednesday in Week 3) in the collocation-spaced group (Figure 1). Therefore, lag to test was 19 days for the node-massed group, and 5 days for the collocation-spaced group. Because the difference between 17 and 19 days, for instance, may be larger than the difference between 0 and 2 days, lag to test was squared before it was entered into the model. To avoid multicollinearity and convergence issues, both UVLT scores and squares of lag to test were centered and standardized before they were entered into the model as s.UVLT_score and s.Lag_to_test, respectively.
The random effects were fitted using the maximum likelihood method, assuming random intercepts for participants and target collocations, and random slopes for target collocations toward the UVLT scores and lag to test. An interaction between Treatment and Test_timing was also entered into the model, assuming that the treatment’s effect was different for the immediate and delayed posttests.
Verb-filling test
Knowledge of verbs in studied and unstudied collocations was measured by the verb-filling test. The verb-filling test was scored in the same way as the collocation-filling test. As in the collocation-filling test, items answered correctly on the pretest were treated as missing values for each participant. This resulted in the exclusion of 2.1% of items on average per participant (node massed: 2.8%, collocation massed: 1.8%; collocation spaced: 1.7%).
The model used for the verb-filling test was the same as the one used for the collocation-filling test, except that collocation type (Studied = 1 and Unstudied = 0) was included as new fixed and random effects after it was centered and standardized (s.Collocation_type). Two interactions (Test_timing × Treatment × s.Collocation_type; Test_timing × s.Collocation_type) were also included. To make the model converge, we added an additional optimizer, and pipelines to random effects, which allow the exclusion of correlated parameters between random variables. Because the unstudied items did not appear in any of the treatment sessions, dummy coding was used for s.Lag_to_test of these items.
Results
Pretest
Table 2 shows results of the pretest scores. More detailed information about the pretest performance is provided in Appendix S7 in the Online Supplementary Materials. The differences in the pretest scores of the three groups were not statistically significant, producing negligible effects; collocation-filling pretest: H(2) = 1.88, p = .391, r = .09, verb-filling pretest: H(2) = 0.14, p = .933, r = .01.
Table 2. Proportion of correct responses on the pretest
Learning-phase performance
The proportion of correct responses on the quiz given at the end of each treatment session (Stage 7; see Appendix S5 in the Online Supplementary Materials) was 96.4% (95% CI = [93.6%, 99.2%]; SD = 7.6%) for the node-massed group, 94.4% (95% CI = [92.0%, 96.9%]; SD = 6.5%) for the collocation-massed group, and 75.8% (95% CI = [70.2%, 81.5%]; SD = 15.7%) for the collocation-spaced group. The difference was statistically significant, H (2) = 46.34, p < .001, and a large effect size (r = .68) was detected, according to Plonsky and Oswald (Reference Plonsky and Oswald2014) benchmark. Post-hoc analysis with Bonferroni adjustment revealed a statistically significant difference between the collocation-spaced and node-massed groups (z = –5.87, p < .001, r = .76 [large effect]), as well as between the collocation-spaced and collocation-massed groups (z = –5.48, p < .001, r = .70 [large effect]). No statistically significant difference, however, was found between the two massed groups (z = –1.91, p = .170, r = .25 [medium effect]). The findings suggest that the two massed groups led to higher scores than the collocation-spaced group during the learning phase.
Collocation-filling test
The reliability of the collocation-filling test indexed by Cronbach alpha was .917 for the immediate posttest and .904 for the delayed posttest, showing sufficient reliability (Plonsky & Derrick, Reference Plonsky and Derrick2016). Results for the collocation-filling test are summarized in Tables 3 to 5, as well as in Figure 2. Table 4 shows fixed and random effects in the mixed-effect logistic regression model. The significant fixed effect of the collocation-spaced group suggests that when collapsed across the immediate and delayed posttests, the collocation-spaced group significantly outperformed the node-massed group. The odds ratio (OR) of 9.58 indicates that the odds of being able to answer correctly on the posttest in the collocation-spaced group were 9.58 times higher than the node-massed group, which is considered a large effect size, according to guidelines proposed by Chen et al. (Reference Chen, Cohen and Chen2010), where odds of 1.68/3.47/6.71 are interpreted as small, medium, and large effects, respectively. The significant fixed effect of the UVLT suggests that higher UVLT scores were associated with higher posttest scores, with a small effect (OR = 2.36). The fixed effect of lag to test, however, was not statistically significant, which suggests that the recency effect (i.e., whether the last encounter with the target collocation was close to the posttest or not) did not significantly affect learning. Although the fixed effects of Collocation-massed and Test_timing were also significant, they are not discussed in detail because an interaction containing these effects was also significant (see the following text).
Figure 2. Distributions of scores for the collocation-filling test.
Table 3. Proportion of correct responses on the posttest
Table 4. List of fixed and random effect fitted: Collocation-filling test fixed effects
Model Formula: glmer (Phrase_accuracy ~ Treatment*Test_timing + s.UVLT_score + s.Lag_to_test + (1 | ID) + (s.UVLT_score + s.Lag_to_test + 1 | Item), Data, family = binomial, control = glmerControl (optimizer = “bobyqa”))
Random Effects
Table 5. Results of the post-hoc analysis for treatment: Collocation-filling test
None of the interactions in the model were statistically significant except for the interaction between Collocation-massed × Test_timing (OR = 0.56). This significant interaction indicates that scores for the node-massed group decayed more than those for the collocation-massed group from the immediate posttest to the delayed posttest, widening the gap between the two groups. Post-hoc analysis with Tukey’s test was conducted using the R package lsmeans (Lenth, Reference Lenth2021). Results (Table 5) showed that on the immediate posttest, the collocation-spaced group significantly outperformed both the node-massed (OR = 7.77 [large effect]) and collocation-massed groups (OR = 4.66 [medium effect]). The collocation-massed group, in contrast, failed to significantly outperform the node-massed group, producing a negligible effect (OR = 1.67). On the delayed posttest, the collocation-spaced group significantly outperformed both the node-massed (OR = 9.58 [large effect]) and collocation-massed groups (OR = 3.22 [small effect]). Unlike on the immediate posttest, the collocation-massed group significantly outperformed the node-massed group, and a small effect was found (OR = 2.97). The findings suggest the following order on the collocation-filling test:
Immediate posttest: collocation-spaced > collocation-massed = node-massed
Delayed posttest: collocation-spaced > collocation-massed > node-massed
Verb-filling test
The reliability of the verb-filling test indexed by Cronbach alpha was .934 for the immediate posttest and .930 for the delayed posttest, showing sufficient reliability (Plonsky & Derrick, Reference Plonsky and Derrick2016). Results for the verb-filling test are summarized in Tables 3, 6, and 7, as well as Figure 3. Table 6 shows fixed and random effects in the mixed-effect logistic regression model. The significant fixed effect of the collocation-spaced group suggests that when collapsed across the immediate and delayed posttests and studied and unstudied collocations, the collocation-spaced group significantly outperformed the node-massed group, producing a medium effect (OR = 5.47). The fixed effect of the collocation-massed group, however, was not statistically significant, and only a negligible effect was observed (OR = 1.63). This suggests that when collapsed across the immediate and delayed posttests and studied and unstudied collocations, no significant difference existed between the two massed groups. The significant fixed effect of Test_timing shows that when collapsed across the three groups, the immediate posttest scores were significantly higher than the delayed posttest scores, producing a small effect (OR = 2.03). The significant main effect of collocation type suggests that when collapsed across the three groups and immediate and delayed posttests, scores for the studied collocations were significantly higher than those for the unstudied collocations, producing a small effect (OR = 2.48). The significant fixed effect of the UVLT suggests that higher UVLT scores were associated with higher posttest scores, with a small effect (OR = 2.41). The fixed effect of lag to test was not statistically significant, which suggests that the recency effect did not significantly affect learning. None of the interactions fitted into the model were statistically significant.
Figure 3. Distributions of scores for the verb-filling test.
Table 6. List of fixed and random effects fitted: Verb-filling test fixed effects
Model Formula: glmer (Verb_accuracy ~ Treatment*Test_timing*s.Collocation_type + s.UVLT_score + s.Lag_to_test + (s.Collocation_type + 1 || ID) + (s.UVLT_score + s.Lag_to_test + s.Collocation_type + 1 || Item), Data, family = binomial, control = glmerControl (optimizer = "bobyqa", optCtrl=list(maxfun=2e5))
Random Effects
To examine where significant differences lay at immediate and delayed posttests, post-hoc analysis with Tukey’s test was conducted (Table 7). The results showed that on the immediate posttest, for studied collocations, the collocation-spaced group significantly outperformed both the node-massed (OR = 8.41 [large effect]) and collocation-massed groups (OR = 4.85 [medium effect]). The collocation-massed group, however, failed to significantly outperform the node-massed group, producing a small effect (OR = 1.73). For unstudied collocations, the collocation-spaced group significantly outperformed the collocation-massed group, with a small effect size (OR = 3.13). No significant difference, however, existed between the collocation-spaced and node-massed groups (OR = 3.25), or between the collocation-massed and node-massed groups (OR = 1.04), and no more than small effects were found.
Table 7. Results of the post-hoc analysis for treatment: Verb-filling test
On the delayed posttest, the collocation-spaced group significantly outperformed other groups for both studied and unstudied collocations, producing small to large effect sizes (3.19 ≤ OR ≤ 6.96). The difference between the two massed groups, however, was not statistically significant for either studied (OR = 2.16 [small effect]) or unstudied collocations (OR = 1.23 [negligible effect]). The findings suggest the following order on the verb-filling test:
Studied collocations
Immediate and delayed posttests: collocation spaced > collocation massed = node massed
Unstudied collocations
Immediate posttest: collocation spaced ≥ node massed; collocation spaced > collocation massed; node massed = collocation massed
Delayed posttest: collocation spaced > collocation massed = node massed
Discussion
The present study was the first attempt to examine the effects of spacing on the knowledge of both studied and unstudied L2 collocations. Hypothesis 1 predicted an advantage of the collocation-spaced schedule over the two massed schedules for the retention of studied collocations. It was shown that the collocation-spaced schedule led to better retention of studied collocations than the massed schedules, regardless of type (collocation filling or verb filling) or timing of posttest (immediate or delayed), supporting Hypothesis 1. The collocation-spaced schedule led to superior retention possibly because it was the only condition that involved spaced retrieval practice of individual collocations. In other words, whereas retrieval opportunities for a given collocation were concentrated into a single session in the two massed schedules, they were distributed over 3 weeks in the collocation-spaced schedule. Retrieval opportunities distributed over a long time perhaps resulted in effortful retrieval, which facilitates retention according to the desirable difficulty framework (e.g., Bjork, Reference Bjork, Metcalfe and Shimamura1994; Suzuki et al., Reference Suzuki, Nakata and DeKeyser2019). It should also be noted that during the treatment, the same context sentence was repeated three times, instead of using three different contexts (see the “Method” section). The repetition of the same context perhaps increased the reminding potential for studied collocations. As a result, retrieval practice in the collocation-spaced schedule was not only effortful but also successful, which facilitated retention even more (reminding theory; Benjamin & Tullis, Reference Benjamin and Tullis2010; Koval, Reference Koval2022).
A limited advantage of the collocation-massed schedule over the node-massed schedule for the studied collocations was also found. On the delayed collocation-filling posttest, the collocation-massed group significantly outperformed the node-massed group, although the difference was not statistically significant on any other posttests. The limited advantage of the collocation-massed group was caused possibly by retrieval-induced facilitation (Chan et al., Reference Chan, McDermott and Roediger2006), according to which retrieval facilitates retention of not only practiced materials but also unpracticed related materials. Specifically, in the collocation-massed group, three studied collocations for the same node verb were distributed over 3 weeks (Week 1: draw a line, Week 2: draw tears, Week 3: draw a conclusion). Encountering draw a conclusion in Week 3, for instance, might have reactivated knowledge of the two studied collocations introduced in earlier weeks (Week 1: draw a line, Week 2: draw tears), resulting in retrieval-induced facilitation from later weeks to earlier weeks. In the node-massed group, in contrast, three studied collocations for the same node verb were concentrated into a single day. As a result, retrieval-induced facilitation across weeks was not possible. At the same time, the advantage of the collocation-spaced group over the collocation-massed group suggests that effects of retrieval-induced facilitation were rather limited and repeating the same collocations across multiple sessions facilitates retention more than repeating different collocations with the same node.
The results of this study regarding Hypothesis 1 (i.e., collocation spaced > node massed = collocation massed) are consistent with those of Macis et al. (Reference Macis, Sonbul and Alharbi2021, Experiment 2), which showed that for intentional learning, studying collocations over multiple days facilitated learning, relative to massing them into a single day. However, this study’s results were not consistent with Snoder (Reference Snoder2017), who found that long spacing did not facilitate the retention of studied collocations. The inconsistent findings may be due to the amount of spacing used in the studies. Specifically, whereas Macis et al. (Reference Macis, Sonbul and Alharbi2021) compared spacing and massing (no spacing) and examined the spacing effect as in the present study, Snoder (Reference Snoder2017) compared effects of two spacing schedulers (i.e., relatively short vs. relatively long intervals) and examined the lag effect.
Hypothesis 2 predicted that for knowledge of unstudied collocations, the collocation-spaced schedule will be the most effective, and the collocation-massed schedule will be the least. Although results on the verb-filling test showed the advantage of the collocation-spaced schedule over the other two, no significant difference was found between the two massed schedules (collocation spaced > node massed = collocation massed). Hypothesis 2, therefore, was only partially supported. The findings suggest that the benefits of spacing apply not only to recall of previously presented materials (i.e., studied words) but also to induction. The collocation-spaced schedule was the most effective for unstudied collocations possibly because participants encountered multiple collocations for the same node word every week throughout the treatment. For instance, in the first treatment session (Wednesday in Week 1; see Figure 1), participants in the collocation-spaced group were exposed to three collocations for the node verb carry (e.g., carry a product, carry a tune, carry weight). This may have allowed participants to make generalizations about what kinds of nouns the node verb could take as an object, allowing them to transfer the knowledge of studied collocations to unstudied collocations. Furthermore, the collocation-spaced group encountered the same three collocations in the subsequent 2 weeks (Wednesday in Weeks 2 and 3). The retrieval opportunities for the multiple collocations for the same node verb distributed over the 3 weeks perhaps consolidated the learners’ understanding of the meaning potential of carry, resulting in the largest gains in the collocation-spaced group for the unstudied collocations.
In the node-massed schedule, participants were also exposed to multiple collocations for the same node word within the same day, as in the collocation-spaced schedule. This may have allowed learners to reconceptualize their knowledge of the meaning potential of the node word. However, unlike the collocation-spaced schedule, in the node-massed schedule, encounters with a given node verb were concentrated into a single session, and they were never repeated in subsequent sessions. As a result, in the node-massed schedule, learners’ knowledge of the meaning potential of the node words perhaps decayed by the time of the posttests, resulting in the lack of significant difference between the two massed schedules. These findings highlight the value of distributed retrieval practice not only for studied but also for unstudied collocations.
At the same time, this study did not use a comparison group where multiple collocations for the same node word were repeated on different days over multiple weeks (e.g., carry a product is repeated on Mondays, carry a tune is repeated on Wednesdays, and carry weight is repeated on Fridays over 3 weeks, instead of all three collocations for carry being repeated on Wednesdays). As a result, it is not clear to what extent the superiority of the collocation-spaced schedule was due to the fact that participants encountered multiple collocations for the same node word on the same day. In future research, it would be useful to include a condition where multiple collocations for the same node are repeated on different days over multiple weeks.
Results of this study suggested that the collocation-spaced schedule was more effective than the two massed schedules not only for studied but also unstudied collocations. The collocation-spaced group, at the same time, may have resulted in more over-extension errors (i.e., erroneously using a target node verb to collocations where a different verb should have been used) than the other two groups. To examine whether this was the case, an error analysis was conducted. The error analysis indicated that the collocation-spaced schedule resulted in more over-extension errors than the two massed schedules (for details, see Appendix S8 in the Online Supplementary Materials). The findings suggest that although the collocation-spaced schedule enabled learners to transfer the knowledge of studied collocations to novel, unstudied collocations, it can be a double-edged sword in the sense that it may lead to over-extension errors. In future research, it may be useful to examine how over-extension errors may be reduced.
In this study, all three groups showed improvements on the verb-filling test for unstudied items on the posttests. The findings suggest that learners were able to transfer the knowledge of studied collocations to unstudied collocations. One explanation for the findings is that exposure to multiple collocations with the same node allowed learners to make comparisons between their existing knowledge of the verb’s semantics and range of different uses of the verb in given collocations, which triggered semantic restructuring (Jiang, Reference Jiang2004). Another explanation is that learners produced novel collocations based on L1 translations of studied collocations. Some studied and unstudied collocations for a given node shared the same L1 translation. For instance, cut in both cut class (studied collocation) and cut school (unstudied collocation) is translated into the same Japanese word, saboru. Similarly, the node verbs for the following studied and unstudied collocations share the same L1 translations: draw tears and draw laughs (sasou), draw attention and draw a line (hiku), and run an article and run a story (keisaisuru). For these collocations, learners might have been able to guess the correct node word based solely on the L1 translations, without understanding the core meaning of the node.
To examine the effects of overlap of L1 translations among studied and unstudied items, a follow-up analysis was conducted. The follow-up analysis that included overlap of L1 translations as fixed and random effects suggested that unstudied items that shared L1 translations with studied items were more likely to be answered successfully than those that did not share L1 translations (p = .017, OR = 1.51 [negligible effect]; full results of the follow-up analysis are presented in Appendix S9 in the Online Supplementary Materials). At the same time, it should be noted that inferences based on L1 translations were probably not always successful because, for some target collocations, different node verbs shared the same L1 translations. For instance, in all the following collocations, the node verbs are translated into the same Japanese word, suru: cut a deal, make a mention, meet death, put emphasis, and take pains. Because all these collocations required different node verbs, it would not be possible to guess the correct node for these collocations based solely on L1 translations (suru), and at least some understanding of the meaning potential of the node might have been necessary.
Although all three groups showed improvements on the verb-filling posttest for unstudied items, the posttest scores for the unstudied collocations were much lower than those for the studied collocations in all three groups (Table 3). The relatively low scores for the unstudied items may be in part due to three factors. First, during the treatment, learners were exposed to only three collocations per node. This may have made it difficult for learners to notice the core meaning underlying different uses of the node word. Second, in this study, target collocations were determined so that the choice of the node verb can be explained by the core meaning of the node verb (see Appendix S4 in the Online Supplementary Materials). At the same time, for some collocations (e.g., meet a need, run an article, take root), the relationship between the meaning of the collocation and the core meaning of the node verb might have been difficult to understand. This was perhaps another factor responsible for the relatively low scores for the unstudied collocations on the verb-filling test. Third, some node verbs had similar core meanings. For instance, as shown in Appendix S4, the core meanings of four node verbs (draw, run, meet, and take) involved moving something. Due to the similarity among these node verbs, learners might have had difficulty in transferring the knowledge of studied collocations to unstudied collocations, resulting in the relatively low scores for the unstudied collocations on the posttests.
Results for the quiz given at the end of each treatment session (Stage 7) have shown that the node-massed (96.4%) and collocation-massed groups (94.4%) outperformed the collocation-spaced group (75.8%) during the learning phase. The results may be partly attributed to the number of exposures before the quizzes. Specifically, whereas a quiz was given after six exposures to each collocation in the two massed groups in all 3 weeks, it was given after two (Week 1), four (Week 2), or six exposures (Week 3) in the collocation-spaced group (see Appendix S5 in the Online Supplementary Materials). On the posttests, however, the collocation-spaced group significantly outperformed the massed groups. The findings are consistent with the desirable difficulty framework (Bjork, Reference Bjork, Metcalfe and Shimamura1994; Suzuki et al., Reference Suzuki, Nakata and DeKeyser2019), according to which a condition that increases learning phase performance does not necessarily lead to better long-term retention than a condition that decreases learning phase performance.
This study also showed wide gaps between the learning phase and posttest performance for the two massed groups. Although the average score for the node-massed group was 96.4% on the quiz given at the end of the learning phase (Stage 7), it dropped to 14.9% and 6.6% for the immediate and delayed collocation-filling posttests, respectively. Similarly, the collocation-massed group showed a substantial decrease from the learning phase performance (94.4%) to the posttest performance (immediate collocation filling: 23.0%; delayed collocation filling: 15.9%). Figures 2 and 3 also indicate that some participants in the two massed groups scored 0 on the posttest. The significant decrease was caused possibly because the two massed groups encountered only three collocations per treatment session, whereas the collocation-spaced group encountered nine collocations each day (Figure 1). The larger number of collocations practiced each day perhaps increased retrieval effort required for the collocation-spaced group. In other words, although retrieval practice for the two massed groups was highly successful, it was perhaps not very effortful. This may be partly responsible for the substantial decrease from the learning phase to the posttest in these two groups.
Although direct comparisons of this study and other studies are difficult due to a number of methodological differences, posttest scores in this study were relatively high, compared with other studies involving L2 collocation learning. Boers, Demecheleer, et al. (Reference Boers, Demecheleer, Coxhead and Webb2014), for instance, report 4.5% to 11.2% gains on the verb-filling posttest and 8.9% to 13.7% gains on the collocation-filling posttest, after a single treatment session. These scores were much lower than those obtained by the collocation-spaced group in this study (62.1% on the immediate verb-filling and 57.8% on the immediate collocation-filling posttest). The results may demonstrate the value of spacing for collocation learning. As a case in point, Ferguson et al. (Reference Ferguson, Siyanova-Chanturia and Leeming2021) found that a treatment that involved the repetitions of same collocations three times after 2-day gaps led to gains that are similar to or larger than those in this study (48.0% to 62.5% on the immediate and 38.0 % to 64.7% on the delayed posttests).
Pedagogical implications
The findings of this study suggest that introducing spacing in terms of individual collocations (i.e., collocation-spaced schedule) facilitates the knowledge of both studied and unstudied collocations. Pedagogically, the findings suggest that it may be useful for learners to be exposed to multiple collocations containing the same node regularly. This study also showed that although the two massed groups significantly outperformed the collocation-spaced group during the learning phase, the collocation-spaced group resulted in higher posttest scores than the massed groups. Pedagogically, the findings suggest that learners or instructors should not be discouraged even if the treatment induces a large number of incorrect responses during learning (desirable difficulty framework).
Concluding remarks
Although many studies have examined the effects of spacing on vocabulary learning, most studies have investigated the learning of single words. Related studies that compared massing and spacing for collocation learning so far investigated the learning of only one collocate per node word (Macis et al., Reference Macis, Sonbul and Alharbi2021; Snoder, Reference Snoder2017). Thus, it was not clear how the spacing of multiple collocations with the same node affects the knowledge of studied and unstudied collocations. The findings of this study are valuable because they suggest that introducing spacing in terms of individual collocations (collocation-spaced schedule) may facilitate the knowledge of both studied and unstudied L2 collocations. At the same time, because this study was the first to examine the role of spacing for collocation learning in this way, it has several limitations.
First, this study was conducted within an authentic classroom setting. Although classroom-based research helps increase ecological validity and has its benefits (Rogers & Cheung, Reference Rogers and Cheung2021), it is also limited in that experimental manipulations are not as tightly controlled as in laboratory studies. For instance, during the treatment in this study, participants were asked to say the correct answers aloud (Stages 3–6 during the treatment; see Appendix S5 in the Online Supplementary Materials). Although overhearing other students’ responses is common in real-world classroom settings, it might have affected learning. In future research, it may be useful to replicate this study in laboratory settings. Second, in this study, the collocation-spaced group, who showed better learning outcomes than the two massed groups, had the highest UVLT scores among the three groups. Although the UVLT score was used as a covariate in the analysis to control for English proficiency effects, in future research, it may be useful to compare groups that are equivalent in their proficiency levels. Considering the value of collocational knowledge for the appropriate and fluent use of L2 vocabulary, further research examining the effects of spacing on collocation learning is warranted. Investigating the effects of spacing on the knowledge of unstudied collocations is also valuable from a theoretical viewpoint because it allows researchers to examine whether the benefits of spacing apply not only to recall of previously presented materials but also to induction.
Supplementary Materials
To view supplementary material for this article, please visit http://doi.org/10.1017/S0272263122000225.
Acknowledgments
This research was supported by JSPS KAKENHI grants (Grant Numbers: 19H00115 and 19K13306) and a Murata Science Foundation grant (Grant Number: M20 海人 08). We greatly appreciate the invaluable suggestions given by anonymous reviewers and the handling editor, Dr. Luke Plonsky. We would like to thank Dr. Akira Murakami, Mr. Akihiko Sato, and Dr. Atsushi Mizumoto for their invaluable advice regarding statistical analyses. We would also like to thank Mr. Yasuaki Morikawa, Ms. Mika Inoue, and Ms. Sakiho Itami for their help with data collection. Finally, our deepest gratitude goes to the high school students who took part in the project.
Data Availability Statement
The experiment in this article earned an Open Materials badge for transparent practices. The materials are available at https://osf.io/w2qj7/.
Open access
