# Phraseological Use and Development During a Stay Abroad: Exploring Sensitivity to Frequency and Cue Contingency

Amanda Edmonds, Aarnes Gudmestad

► To cite this version:

Amanda Edmonds, Aarnes Gudmestad. Phraseological Use and Development During a Stay Abroad: Exploring Sensitivity to Frequency and Cue Contingency. Language Learning, 2023, 73 (2), pp.475-507. 10.1111/lang.12547. hal-03864429

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EMPIRICAL STUDY

# Phraseological Use and Development
During a Stay Abroad: Exploring Sensitivity
to Frequency and Cue Contingency

<figure><img src="image_2.png" /></figure>

Amanda Edmonds IDª and Aarnes Gudmestad IDᵇ

ªUniversité Côte d'Azur, CNRS, BCL ᵇVirginia Polytechnic Institute and State University

**Abstract:** Usage-based approaches to additional-language acquisition have identified numerous determinants of language learning, two of which were the focus of our study: frequency and cue contingency. Specifically, we examined how an immersion experience may impact sensitivity to these two determinants as reflected in the production of 4,808 pairs of nouns (N) and adjectives (ADJ) by 50 anglophone learners of Spanish and French. We analyzed the use of N/ADJ combinations using mixed linear regressions for frequency and two measures of delta P, a unidirectional measure of lexical association strength reflecting cue contingency. In all three models, we explored the impact of time and four additional variables: task, initial proficiency, target language, and phraseological unit. Our analysis revealed stasis over time. Additionally, our analysis revealed phraseological unit, task, and target language each to be significant in at least one model; initial proficiency did not contribute to significantly predicting phraseological use.

**Keywords** phraseology; stay abroad; French; Spanish; usage-based approaches

A one-page Accessible Summary of this article in non-technical language is freely available in the Supporting Information online and at https://oasis-database.org

Correspondence for this article should be directed to Amanda Edmonds, Université Côte d'Azur, Études Anglophones, boulevard Edouard Herriot, Nice 06108, France. Email: amanda.edmonds@univ-cotedazur.fr

The handling editor for this article was Kris Kyle.

This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.
**Introduction**

Within usage-based approaches, additional-language¹ learning has been held to be determined by characteristics specific to the learner (e.g., attention) and to the input (e.g., frequency, cue contingency). All else being equal, higher frequency and greater reliability of form–meaning mapping (i.e., cue contingency) in the input are expected to facilitate learning. The importance of input characteristics has led many researchers working within usage-based approaches to anticipate that a stay abroad in a target-language community and the concomitant change in input should facilitate acquisition. Specifically regarding phraseological competence (the focus of our study), researchers such as Foster et al. (2014) and Ellis et al. (2015) have argued that the stay- abroad context should be beneficial. This is because encountering language “beyond the classroom in a multitude of contexts, allow[s] for at least the possibility that learners will be able to build more authentic networks of L2 [second-language] word associations” (Foster, 2009, p. 93). However, existing research on phraseological development during a stay abroad has yielded inconclusive results. Against this backdrop, we conducted a study focused on two key determinants of learning in usage-based approaches: frequency and contingency (Ellis et al., 2016). In particular, we explored whether and how a 9-month stay in a target-language environment might impact the frequency (using log frequency) and/or the cue contingency (measured using delta P) of a set of collocations—word pairs involving a noun (N) and an adjective (ADJ)—used by additional-language learners of Spanish and French. Given that previous research has reported contradictory results, our investigation importantly included several underexplored explanatory variables that might in part be responsible for the inconsistent findings of previous research. These included task, initial proficiency, target language, and phraseological unit.

**Background Literature**

**Phraseology and Usage-Based Approaches to Additional-Language
Learning**

Phraseology research has focused on identifying and analyzing recurrent or
conventional word combinations. Such combinations may have either referen-
tial or pragmatic functions and range from n-grams (i.e., contiguous sequences
of lexical items) to collocations (e.g., N/ADJ or verb [V]/N pairs) to idiomatic
expressions. Within linguistics, certain theoretical and analytic approaches
have attributed a central role to phraseology as they have recognized that
"natural language makes considerable use of recurrent patterns of words and
constructions” (Ellis, 2008, p. 4) and that these patterns constitute “the base
level of language representation where form and meaning meet with greatest
reliability” (Ellis, 2008, p. 6). Usage-based approaches (the framework adopted
for our study) have been among those that have underscored the importance of
phraseology, particularly with respect to acquisition. Although investigations
couched in usage-based approaches have taken many forms, they have shared
the foundational conviction that “grammar is the cognitive organization of
one’s experience with language” and that “certain facets of linguistic expe-
rience, such as the frequency of use of particular instances of constructions,
have an impact on representation that we can see evidenced in various ways”
(Bybee, 2006, p. 711). Ellis et al. (2016, p. 79) identified the following facets
as being significant determinants of language learning: frequency, chunking,
semantic prototypicality, contingency, form (salience, regularity, etc.), and
learner attention.

From this list, frequency and contingency have arguably been the two
determinants that have received the most attention in the field of second
language (L2) acquisition. There is now a large body of literature demon-
strating the importance of input frequency in understanding the pace and
pattern of acquisition for all linguistic subsystems and at all levels of anal-
ysis (e.g., Collins & Ellis, 2009; Ellis, 2002; Piske & Young-Scholten,
2009), including phraseological units (Durrant & Schmitt, 2009). As for
contingency, this notion refers to the reliability of two events co-occurring.
An event can be understood in various ways, including as the mapping of
a form onto a meaning/function (e.g., Wulff et al., 2009) or—as is often
the case in phraseology—as the co-occurrence of two lexical items. The
strength of co-occurrence (or association) for two lexical items can be as-
sessed in a variety of manners, including the mutual information (MI) score,
t-score, log Dice score, and delta P score, all of which are corpus-based
calculations that quantify the probability of co-occurrence of two lexical
items.

Usage-based approaches to additional-language learning have been in-
strumental in advancing knowledge about the development of phraseological
units. In particular, there has been sustained interest in the impact of input
characteristics on the acquisition of different phraseological units, with many
investigations having looked at both input frequency and at least one mea-
sure of contingency. For example, Lorenz (1999) and Durrant and Schmitt
(2009) explored N/ADJ collocation use in essays written by either German
and Turkish learners of English. In both cases, the analyses revealed that
these learners tended to use N/ADJ pairs that were highly frequent in native
reference corpora. This high usage of frequent collocations was accompanied
by a low use of strongly associated collocations (i.e., combinations with high
cue contingency, measured using MI scores). Lorenz (1999) and Durrant and
Schmitt (2009) suggested that their findings indicated a strong sensitivity on
the part of nonnative speakers to absolute frequency in the input. In a study of
verb-argument constructions in first- and additional-language English, Ellis
et al. (2016, p. 126) reported on several experiments, including one for which
their participants were asked to fill in the first verb that came to mind when
they were presented with frames such as “it ________ over the.” Results
showed that responses for native and nonnative speakers were significantly
influenced by frequency, contingency (measured using delta P), and seman-
tic prototypicality as calculated via a native-speaker reference corpus. The
researchers concluded that “L2 English language learners are affected by sta-
tistical information in their language environment. L2 knowledge of language
comes from usage” (p. 151). Given that the research that we have reviewed
has provided evidence that learners’ use of different phraseological units is
sensitive to input characteristics, it seemed reasonable to expect that changes
in learning context and the associated changes in input might impact learning
(cf. Ellis et al., 2015). However, previous research on phraseology that has fo-
cused on learners in a target-language environment has reported contradictory
conclusions.

Phraseological Development Over a Stay Abroad

Our review focused on previous research that had analyzed longitudinal
language-production data to explore how sensitivity to frequency and/or con-
tingency of phraseological units might change during a stay in a target-
language environment. We identified 10 such studies. Although not all the
studies had focused on the role of learning context, they had in common that
the learners under study were living in a target-language environment either
as part of a clearly delimited study-abroad period or as students enrolled in
a degree program, such as English as a second language (ESL) students. As
Table 1 shows, the studies differed, however, in the length of the stay, target
language, proficiency level, task type, and phraseological unit studied. Com-
parisons of proficiency level across studies can be challenging. However, the
learners who participated in the 10 studies showed one of three proficiency pro-
files: complete beginners at the outset of the stay abroad, participants placed
at a higher level than beginner in an intensive language program abroad, and
participants in an integrated program (i.e., enrolled in a degree program, com-
pleting an internship, etc.). In what follows, we have focused on findings
<table><caption>**Table 1** Studies addressing frequency and/or consistency in phraseological use during a stay abroad</caption><thead><tr><th rowspan="2">Study</th><th rowspan="2">Phraseological unit</th><th rowspan="2">Languages</th><th rowspan="2">Proficiency level</th><th rowspan="2">Task(s)</th><th rowspan="2">Longitudinal coverage</th><th colspan="3">Dependent variable(s)</th></tr><tr><th>Frequency</th><th>Contingency</th></tr></thead><tbody><tr><td>Li & Schmitt (2010)</td><td>N/ADJ</td><td>L1 Chinese, L2 English</td><td>Integrated program</td><td>Multiple academic writing assignments</td><td>Academic year</td><td>—</td><td>t-score, MI score</td><td>—</td></tr><tr><td>Crossley & Salsbury (2011)</td><td>n-grams</td><td>Various L1s, L2 Beginners English</td><td></td><td>Multiple oral interviews</td><td>1 year</td><td>Frequency</td><td>—</td><td>—</td></tr><tr><td>Bestgen & Granger (2014)</td><td>n-grams</td><td>Various L1s, L2 English</td><td>Intensive language program</td><td>2 written essays</td><td>1 semester</td><td>—</td><td>t-score, MI score</td><td>—</td></tr><tr><td>Siyanova-Chanturia (2015)</td><td>N/ADJ</td><td>L1 Chinese, L2 Italian</td><td>Beginners</td><td>2 short written compositions</td><td>5 months</td><td>Frequency</td><td>MI score</td><td>—</td></tr><tr><td>Yoon (2016)</td><td>V/N</td><td>Various L1s, L2 English</td><td>Intensive language program</td><td>3 written narratives, 1 semester</td><td></td><td>—</td><td>MI score</td><td>—</td></tr><tr><td>Garner & Crossley (2018)</td><td>n-grams</td><td>Various L1s, L2 English</td><td>Intensive language & integrated programs</td><td>3 written argumentative essays</td><td>4 months</td><td>Log frequency (average per text)</td><td>MI score</td><td>—</td></tr></tbody></table>

(Continued)
<table><caption>**Table 1 (Continued)**</caption><thead><tr><th rowspan="2">Study</th><th rowspan="2">Phraseological unit</th><th rowspan="2">Languages</th><th rowspan="2">Proficiency level</th><th rowspan="2">Task(s)</th><th rowspan="2">Longitudinal coverage</th><th colspan="3">Dependent variable(s)</th></tr><tr><th>Frequency (average per text)</th><th>MI score, delta P</th><th>Contingency</th></tr></thead><tbody><tr><td>Kim et al. (2018)</td><td>n-grams</td><td>Various L1s, L2 English</td><td>Beginners</td><td>Multiple oral interviews</td><td>1 year</td><td>Frequency</td><td>MI score, delta P</td><td></td></tr><tr><td>Siyanova-Chanturia & Spina (2020)</td><td>N/ADJ</td><td>L1 Chinese, L2 Italian</td><td>Intensive language program (including beginners)</td><td>2 written essays</td><td>6 months</td><td>Frequency</td><td>MI score, delta P</td><td></td></tr><tr><td>Edmonds & Gudmestad (2021)</td><td>N/ADJ</td><td>L1 English, L2 French</td><td>Integrated program</td><td>3 written essays</td><td>Academic year</td><td>Log frequency</td><td>MI score, log Dice</td><td></td></tr><tr><td>Omidian et al. (2021)</td><td>V/N</td><td>L1 Chinese, L2 Italian</td><td>Intensive language program (including beginners)</td><td>2 written essays</td><td>6 months</td><td>Log frequency</td><td>log Dice</td><td></td></tr></tbody></table>

*Note.* Garner and Crossley, Kim et al., and Siyanova-Chanturia and Spina analyzed more contingency measures than reported in this table; only the variables most central to the current study are included here. N = noun; ADJ = adjective; L1 = first language; L2 = second language; MI = mutual information; V = verb.
concerning input frequency and contingency in phraseological development
during a stay abroad and then several understudied independent variables that
may influence the use of word combinations.

Sensitivity to Frequency and Contingency

Studies have explored if and how the frequency profiles of word combinations
used by learners change over the course of a stay abroad. To assess change,
researchers have analyzed combinations produced by learners with respect to
their absolute or log frequency in a reference corpus. If frequency in the in-
put significantly influences phraseological usage, learners might be expected
to use more highly frequent combinations after a stay abroad. Relevant re-
search has overwhelmingly reported change in word combination frequency,
though in different directions. A study by Siyanova-Chanturia and Spina
(2020) found that overall learners produced significantly fewer frequent word
combinations in their written productions over time, an effect that was par-
ticularly strong for the beginner-level learners. Siyanova-Chanturia and Spina
suggested that this result indicated greater experimentation on the part of the
participants. In contrast, in four other studies, Crossley and Salsbury (2011),
Garner and Crossley (2018), Kim et al. (2018), and Siyanova-Chanturia
(2015) reported evidence of increased use of more frequent combinations
over the course of an immersion experience. Finally, Edmonds and Gudmes-
tad (2021) and Omidian et al. (2021) reported no significant change over
time.

All but one study assessed whether learners’ sensitivity to cue contingency
changed over time. To do so, researchers used reference corpora to determine
the strength of association for word combinations used by learners and then
examined whether more strongly associated combinations were more probable
after a period abroad. These studies relied on a variety of association mea-
sures, including the t-score, MI score, log Dice score, and delta P score, all of
which quantify “how strongly two events are linked” (Schneider, 2020, p. 251).
The differences between and the relative merits of each of these measures have
continued to be debated (e.g., Gablasova et al., 2017; Gries, 2013). For the pur-
poses of our article, it is important to highlight that the t-score, the MI score,
and the log Dice score are bidirectional measures, whereas the delta P score is
a unidirectional measure. Bidirectional measures determine how strongly two
words co-occur by comparing their actual frequency to a chance co-occurrence
rate, without distinguishing whether one of the two words more strongly se-
lects for the other. And yet, “associations are not necessarily reciprocal in
strength” (Ellis & Ferreira-Junior, 2009, p. 198). Thus, in the V/N collocation
make amends, the noun much better predicts the verb than does the verb predict the noun. Given these observations, Ellis and Ferreira-Junior (2009), Gries (2013), and Ellis et al. (2016), among others, have argued that unidirectional measures such as delta P are better suited for accounting for actual language processes because they specifically assess association while taking direction into account.

For the studies that we have reviewed, cue contingency was most often assessed via MI scores. Whereas the five studies carried out by Bestgen and Granger (2014), Garner and Crossley (2018), Kim et al. (2018), Siyanova-Chanturia and Spina (2020), and Yoon (2016) reported no evolution over time in MI scores associated with combinations used by learners, Edmonds and Gudmestad (2021), Siyanova-Chanturia (2015), and Li and Schmitt (2010) discovered changes in MI scores over time. The three studies reporting change all found that learners used more strongly associated combinations at the end of a stay abroad. Two studies with contradictory results used a second bidirectional measure, the t-score: Whereas Bestgen and Granger (2014) observed that n-grams produced at the end rather than at the beginning of a semester by learners in an intensive English program had significantly lower t-scores, Li and Schmitt (2010) reported the opposite finding for the N/ADJ combinations produced by their four learners enrolled in a Master's program in English language teaching. Log Dice is the final bidirectional measure. In two studies that employed this measure, Edmonds and Gudmestad (2021) and Omidian et al. (2021) found no significant change over time.

Finally, two investigations used the unidirectional measure delta P. Siyanova-Chanturia and Spina (2020) reported that their learners used less strongly associated N/ADJ combinations in their writing at the end of a 6-month stay in Italy, an effect that was significantly stronger for their beginner (i.e., A1 level in the Common European Framework of Reference for Languages) learners compared to those at A2 and B1 levels. Kim et al. (2018) analyzed n-grams produced in oral interviews by six beginner-level ESL learners over one year according to numerous lexical variables that they then grouped into components via a principal components analysis. One component tapped into directional associations as measured via delta P. When Kim et al. (2018) analyzed the oral data for this component, they found no evidence of significant change over time among the ESL participants. Overall, the studies that we have reviewed have yielded inconclusive results. It remains unclear whether frequency and cue contingency of word combinations that are manifested in input and encountered during a stay
abroad might result in changes in phraseological use. In the following section,
we introduce four potentially important independent variables that have not
consistently been taken into account. We explored each of the four in our
study.

## Variables Potentially Influencing Phraseological Development

### Task

The development of language skills may show task-specific trajectories related to task features including genre, topic, mode, formality, and complexity, among others. Concerning phraseological development specifically, several results have underscored the importance of task. Yoon (2016) explored the impact of task genre on phraseological development by analyzing narrative and argumentative writing assignments produced by learners during their stay abroad. A comparison of the V/N combinations that learners produced led Yoon to suggest that the learners had “attained different levels of phraseological competence across different genres” (p. 53), insofar as their collocational uses were similar to those of native speakers only in the narrative genre. Siyanova-Chanturia and Spina (2020) and Omidian et al. (2021) also provided evidence of task effects; topic was a significant predictor in their analyses, indicating that the characteristics of word combinations, as used by L2 learners, varied significantly as a function of the prompt. Finally, some researchers have reported that “oral language [i]s much denser in formulaic language” than certain written genres (Ellis et al., 2015, p. 374). This difference may be explained by the role phraseological units are thought to play in oral discourse. Indeed, it has been suggested that “[a] larger repertoire of formulaic language is… one way to reduce the load on the attentional resources that can be used in parallel processing at different stages of speech production” (Tavakoli & Uchihara, 2020, p. 510). Taken together, this means that learners are potentially in contact with more oral phraseological units during a stay abroad and that the processing benefits associated with these units are particularly relevant in the oral mode. In our study, we addressed the potential importance of task variation by exploring phraseological development using two tasks: an argumentative essay and a semiguided oral interview.

### Initial Proficiency

Researchers such as DeKeyser (2007) have argued that proficiency at the beginning of the stay-abroad experience may impact language development during the sojourn abroad. According to DeKeyser, the opportunities for use and
practice that are offered by the stay-abroad experience may be particularly useful to learners who have already built up a store of declarative and procedural knowledge, allowing them to work toward their automatizing that knowledge store. Learners who are at the beginning stages of additional-language learning may be less capable of making use of the practice opportunities afforded by the stay-abroad environment. Regarding phraseological development, four studies have recognized the potential importance of proficiency and explored whether it influenced phraseological development (Edmonds & Gudmestad, 2021; Garner & Crossley, 2018; Omidian et al., 2021; Siyanova-Chanturia & Spina, 2020). For example, with respect to frequency, Garner and Crossley (2018) and Omidian et al. (2021) found evidence that general proficiency influenced the type of word combinations used, with higher proficiency learners producing word combinations of higher frequency. Although Omidian et al. (2021) found no change in frequency over time, Garner and Crossley (2018) found an overall increase in frequency that interacted with proficiency, with high beginners, the lowest proficiency participants in their study, showing the greatest gains in the frequency of two-word combinations over time. In contrast, Siyanova-Chanturia and Spina (2020) reported that frequency of lexical combinations significantly decreased over time for all the proficiency groups, but this decrease was strongest for the beginning-level learners. Finally, Edmonds and Gudmestad's (2021) analysis did not identify initial proficiency as a significant predictor of word combination use. The role of initial proficiency on phraseological development remains an open question and was addressed in our study.

*Target Language*

The third variable that might influence phraseological development concerns the target language. Among the studies that we reviewed (see Table 1), only three target languages have been examined, with English dominating. Diversifying the languages that are represented in studies is important, as it would increase the representativeness of the results reported. Siyanova-Chanturia (2015) and Siyanova-Chanturia and Spina (2020) have made a similar argument: "A wider range of L2s represented in longitudinal studies – and learner corpus research, in general – is bound to enrich and further advance the field" (Siyanova-Chanturia & Spina, 2020, p. 451). Currently, the extent to which the existing body of results may be specific to the languages included in the studies is unclear. By including two target languages in a single investigation, our design constituted a first attempt at empirically determining whether target language plays a role.
## Phraseological Unit

The studies that we reviewed in the preceding section differed in their phrase-
ological focus. Some examined one specific collocation type: either N/ADJ
(Edmonds & Gudmestad, 2021; Li & Schmitt, 2010; Siyanova-Chanturia,
2015; Siyanova-Chanturia & Spina, 2020) or V/N (Omidian et al., 2021;
Yoon, 2016). Others have cast a wider net, focusing on all contiguous
two-word (bigram) and/or three-word (trigram) combinations produced by
learners (Bestgen & Granger, 2014; Crossley & Salsbury, 2011; Garner &
Crossley, 2018; Kim et al., 2018). While the focus on a variety of lexical
combinations has arguably contributed to a more complete picture of phrase-
ological development, researchers currently do not know whether different
types of phraseological units show development in lockstep (with relevant
cross-sectional research suggesting that they do not; Granger & Bestgen,
2014). Although we limited our study to combinations involving N/ADJ pairs
(the most commonly studied collocation type to date), we were able to offer
data that potentially speak to the influence of unit type on phraseological
development. This was because in French and Spanish, N/ADJ combinations
include prenominal and postnominal adjectives. In the vast majority of cases,
a given adjective occurs consistently in prenominal or postnominal posi-
tion, with postnominal position being canonical in both French (Hawkins &
Towell, 2015, p. 85) and Spanish (Zagona, 2002, pp. 89–90). However, certain
adjectives can occur in both positions as Examples 1a to 1d from our corpus
illustrate.

### Example 1

a. *hay que hacer nuevas amigos* (Participant 171, interview, prestay)
“you have to have new friends”

b. *no tengo muchos amigos nuevos* (Participant 165, interview, poststay)
“I don’t have many friends new”

c. *mais d'un autre côté il existe les gens avec les fortes opinions* (Participant 102, essay, poststay)
“but on the other hand there exist people with strong opinions”

d. *pour avoir un opinion plus forte* (Participant 127, essay, poststay)
“to have an opinion more strong”

Although we identified two longitudinal studies that focused on N/ADJ com-
binations in Italian, a language that also allows both prenominal and post-
nominal adjectives, both investigations appear to have restricted their analysis
to postnominal adjectives (Siyanova-Chanturia, 2015; Siyanova-Chanturia &
Spina, 2020). It is thus currently unclear whether this difference in word order impacted development, and, for this reason, we included both N + ADJ and ADJ + N occurrences in our analysis (see also Edmonds & Gudmestad, 2021).

## The Current Study

A stay in a target-language environment offers the possibility of greater and more varied contact with the target language compared to classroom learning in a learner's home country. Researchers working within usage-based approaches have thus suggested that a stay abroad may be particularly beneficial for phraseological development (Ellis et al., 2015; Foster et al., 2014). However, previous findings on phraseological development during an immersion experience have largely been inconclusive, which might have been due to researchers' not consistently accounting for certain potentially important variables, for example, task, initial proficiency, target language, phraseological unit. We sought to contribute novel insights to this body of research through an analysis of longitudinal production data collected from anglophone learners of either French or Spanish. The research question that guided this study was: To what extent is additional-language learners' use of N/ADJ pairs impacted by the variables of time, task, initial proficiency, target language, and phraseological unit?

## Method

### Corpus

We analyzed data from the Languages and Social Networks Abroad Project (LANGSNAP) corpus (Mitchell et al., 2017).² The LANGSNAP team followed two cohorts of undergraduate students based in the United Kingdom—one majoring in Spanish (n = 27), the other in French (n = 29)—over a period of 21 months, during which time each student spent an academic year in a target-language environment (9 in Mexico, 18 in Spain, 29 in France). All the participants were enrolled at the same British university at the beginning of the project, which coincided with the end of the second year of their degree program. For our analysis, we considered data from all participants who reported English to be their only native language, which corresponded to 25 Spanish and 25 French majors.³ These participants included nine men and 41 women whose mean age was 20.19 years (SD = 0.98, range: 19–25 years) at the beginning of the project. They reported having studied the language of their major for an average of 8.24 years (SD = 3.68, range: 2–16 years).⁴ Additionally,
44 participants reported knowledge of at least one other additional language. The participants chose one of three placement types for their academic-year abroad: Six participants completed internships, 30 were teaching assistants, and 14 were exchange students.

The LANGSNAP team assessed overall proficiency in French or Spanish at the outset of the project using an elicited imitation (EI) task, a type of task that has been used widely in L2 acquisition research to assess proficiency (see Kostromitina & Plonsky, 2021, for a meta-analysis). The participants heard 30 sentences in the target language and were required to repeat them aloud (see Tracy-Ventura et al., 2014; Ortega, 2000). Up to four points for each sentence were awarded on the basis of completeness and accuracy. The French students obtained a mean of 62.9 points (SD = 18.21, range: 36–97 points), whereas the Spanish learners’ mean was 85.15 points (SD = 11.73, range: 59–108 points). Although the French and Spanish versions of the tasks were developed following similar principles, the fact that they were normed separately means that the same numerical score on the French and Spanish tasks cannot be interpreted to reflect the same level of competence in the respective language. To include this variable in our analysis, we converted the participants’ proficiency scores into z scores for each group. The resultant z scores offered a standardized indication of relative proficiency within each group, as the participants were situated according to how far their score differed from the group mean. Thus, this variable operationalized proficiency not as specific levels (i.e., intermediate, advanced, etc.), but in relative terms.

LANGSNAP researchers met with the participants six times. For our project, we focused on production data collected prior to the immersion experience (prestay: May 2011) and 1 year later, at the end of the 9-month stay abroad (end-stay: May 2012). At each data collection session, the participants wrote an approximately 200-word argumentative essay, participated in a semiguided interview, and completed a story retelling task. Because the story retelling data contained few instances of N/ADJ combinations, our analysis relied on data from the other two tasks. For the argumentative essay, the same topic, which asked the participants whether they thought that same-sex couples had the right to get married and adopt children, was used at prestay and end-stay. The semiguided oral interviews focused on general questions concerning the stay abroad (expectations, desires, experiences, difficulties). Table 2 provides details concerning the size of the corpus analyzed.
<table><caption>**Table 2** Size of corpus in number of words</caption><thead><tr><th rowspan="2">Task</th><th colspan="2">Prestay</th><th colspan="2">End-stay</th></tr><tr><th>French</th><th>Spanish</th><th>French</th><th>Spanish</th></tr></thead><tbody><tr><td>Essay</td><td>5,389</td><td>4,799</td><td>5,094</td><td>5,460</td></tr><tr><td>Interview</td><td>31,144</td><td>29,065</td><td>29,418</td><td>40,755</td></tr><tr><td>Total</td><td>36,533</td><td>33,864</td><td>34,512</td><td>46,215</td></tr></tbody></table>

## Data Coding

We manually identified all instances where the participants had produced a noun modified by an adjective within the same noun phrase. We embraced a broad understanding of the category adjective that included comparative and superlative forms (Example 2a) and what Durrant and Schmitt (2009, p. 166) called semideterminers (Example 2b).

### Example 2

a. French: *la chose plus importante* “the more important thing”

Spanish: *la cosa más importante* “the most important thing”

b. French: *toutes les choses* “all things”; *deux choses* “two things”; *la même chose* “the same thing”

Spanish: *muchisimas cosas* “many things”; *tantas cosas* “so many things”; *la primera cosa* “the first thing”; *ciertas cosas* “certain things”

Before coding the dataset, we removed all instances from the written data where the learners had used the N/ADJ combination “same-sex couple” (*couple/homosexuel* in French; *pareja/gay* in Spanish) that had appeared in the prompt to which they had responded. The final dataset contained 4,808 N/ADJ pairs (2,240 in French, 2,568 in Spanish).

Using a reference corpus, we coded each N/ADJ pair for three dependent variables that enabled us to investigate important usage-based determinants of language learning, one tapping input frequency and the two others, delta $P_{noun→adj}$ and delta $P_{adj→noun}$, reflecting cue contingency. As we noted in the literature review, there exist numerous measures that reflect cue contingency. We opted for delta P because of the importance of taking directionality of association into account (see Ellis & Ferreira-Junior, 2009; Ellis et al., 2016; Gries, 2013). To analyze the French and Spanish data in a single analysis, it was important to choose reference corpora that were comparable in size and construction. The corpora created through the Web-As-Corpus Kool
Yinitiative (2009) provided such resources. In particular, we chose the Ten-Ten family of corpora (Jakubíček et al., 2013), which offer multibillion-word web-crawled corpora developed according to the same criteria for numerous languages. We used similar sized corpora compiled during the period of the LANGSNAP data collection for Spanish (esTenTen11 European Spanish + American Spanish: 9,497,213,009 words) and French (frTenTen12: 9,889,689,889 words).

The three dependent variables required three queries per N/ADJ combination: lemmatized frequency of the N, the ADJ, and the N/ADJ combination.⁵ For each search, we specified part-of-speech. In our N/ADJ combination searches, we respected the order N + ADJ or ADJ + N in which the learner produced the combination. Moreover, we allowed for up to one word to separate the N and ADJ, given that other elements can separate an adjective from the noun that the adjective modifies. We specified, however, that the potential intervening element could not be a verb in the case of combinations with a postnominal adjective or a preposition for combinations involving a prenominal adjective (see Appendix S1 in the Supporting Information online for query examples). The results of these searches provided the dependent variable of frequency, which corresponded to the lemmatized frequency of the combination, as well as the values needed to calculate the two delta P dependent variables. We used equations 1 and 2 to calculate delta P (Gries, 2013, p. 144; see also Appendix S2 in the Supporting Information online for an example):

$$ \text{delta P}_A \rightarrow B = \begin{aligned}[t] & \text{(frequency of the collocation AB/frequency of A)} \\ & - \text{(frequency of B without A/number of total tokens that are not A)} \end{aligned} \quad (1) $$

$$ \text{delta P}_B \rightarrow A = \begin{aligned}[t] & \text{(frequency of the collocation AB/frequency of B)} \\ & - \text{(frequency of A without B/number of total tokens that are not B)} \end{aligned} \quad (2) $$

For a single word combination, the two equations provide different information: delta $P_{A→B}$ calculates how strongly the first word selects for the second word, whereas delta $P_{B→A}$ provides a measure of how strongly the second word selects for the first word. In our study, we were not interested in lexical association as a function of basic word order ($A \rightarrow B$ and $B \rightarrow A$). Instead, we wanted to know how strongly (a) the N selected for the ADJ ($\text{delta } P_{\text{noun→adj}}$) and (b) how strongly the ADJ selected for the N ($\text{delta } P_{\text{adj→noun}}$) in N/ADJ pairs. Thus, we calculated the dependent variable delta $P_{\text{noun→adj}}$ using delta $P_{A→B}$ for cases where the ADJ was in postnominal position, whereas we used delta $P_{B→A}$ in the case of prenominal adjectives. For the dependent variable
<table><caption>**Table 3** Fixed-effects variables</caption><thead><tr><td>Independent variables</td><td>Values</td></tr></thead><tbody><tr><td>Time</td><td>Prestay, end-stay</td></tr><tr><td>Task</td><td>Interview, essay</td></tr><tr><td>Elicited imitation score (z score)</td><td>-2.23 - 1.95</td></tr><tr><td>Target language</td><td>French, Spanish</td></tr><tr><td>Phraseological unit</td><td>N + ADJ, ADJ + N</td></tr></tbody></table>

delta $P_{adj→noun}$, we used delta $P_{A→B}$ for occurrences with prenominal adjectives and delta $P_{B→A}$ for instances involving postnominal modification.

We explored five independent, fixed-effects variables (see Table 3). The first variable of time allowed us to verify whether the frequency or cue contingency associated with N/ADJ pairs changed between prestay and end-stay, thus allowing us to determine whether development occurred over time. The four remaining variables corresponded to variables that might influence phraseological use and development: task, initial proficiency (EI score), target language, and phraseological unit (N + ADJ vs. ADJ + N).

## Data Analysis

The analysis consisted of mixed-effects models for frequency, delta $P_{noun→adj}$, and delta $P_{adj→noun}$. We first noted that the three dependent variables showed positive skew. Following recommendations presented by Larson-Hall (2015, p. 125), we applied a log transformation to the frequency variable and a reciprocal transformation to the two delta P variables.⁶ We then identified outliers, that is, any data point above the third quartile (Q3) plus 1.5 times the interquartile range (IQR) or below the first quartile (Q1) minus 1.5 times the IQR (Winter, 2020, pp. 59–60). We replaced all such data points with the value to which they were closest—either Q3 + (1.5 × IQR) or Q1 – (1.5 × IQR).

Of the five fixed effects, one was continuous (i.e., EI score) and four were categorical. For the categorical variables, we designated one category as the reference category, meaning that the model assessed differences with respect to that reference point. The reference categories were prestay for time, interview for task, French for target language, and N + ADJ for phraseological unit. The random-effects structure of the models included participant as a random intercept; we explored random slopes but ultimately removed them because they did not significantly improve the models. We fit each model using the package lme4 in RStudio (RStudio Team, 2020). We then used the function dredge()
<table><caption>**Table 4** Descriptive statistics for tokens and types of noun/adjective pairs per participant (N = 50) at prestay and end-stay</caption><thead><tr><th rowspan="2">Time</th><th colspan="2">Tokens</th><th colspan="2">Types</th></tr><tr><th><i>M</i> (<i>SD</i>)</th><th>Range</th><th><i>M</i> (<i>SD</i>)</th><th>Range</th></tr></thead><tbody><tr><td>Prestay</td><td>44.02 (14.29)</td><td>25–82</td><td>38.56 (12.12)</td><td>21–76</td></tr><tr><td>End-stay</td><td>52.14 (18.65)</td><td>21–107</td><td>44 (14.10)</td><td>18–77</td></tr></tbody></table>

from the MuMln package to select the best model, based on the Bayesian information criterion (BIC), a goodness-of-fit metric (Kass & Raftery, 1995).⁷ The BIC balances between good fit and simplicity by placing a penalty on more complex models, thus guarding against overfitting (Stoica & Selen, 2004).

Given that our project focused on potential longitudinal development, for every significant independent variable, we examined whether it significantly interacted with the independent variable of time. A significant interaction would have indicated a change in the effect of the variable between prestay and post-stay, thus offering evidence of language development. We based the decision about whether to include a significant interaction on the BIC values for the model with and without the interaction term. With this metric, scholars have considered that a difference of between at least 6 and 10 points is strong evidence in favor of the model with the lower value (Kass & Raftery, 1995; Lorah & Womack, 2019). In our analyses, when the difference between the BICs for a model with and without an interaction was at least 6 points, we opted for the model with the smaller BIC. When the BICs of two models were less than 6 points, we opted for the simpler model in the spirit of statistical parsimony. Once we had identified the final models, we used the relaimpo package to calculate the relative importance metric LMG (Grömping, 2006). The R code that we used for this analysis and its output are available via IRIS (Edmonds & Gudmestad, 2022). We assessed the fit of each model by considering its marginal and conditional $R^2$ values. The marginal and conditional $R^2$ values reflect, respectively, how much of the overall variance is explained only by the fixed effects and how much is accounted for by the whole model, that is, both fixed and random effects.

## Results

Table 4 provides the number of N/ADJ tokens and types per participant identified at prestay and end-stay and reveals that both the total tokens and the number of N/ADJ types produced by participants increased between the two
<figure><img src="image_3.png" /><figcaption>**Figure 1** Boxplots illustrating significant fixed effects in the log frequency analysis. The symbol × indicates the location of the group means.</figcaption></figure>

data-collection points. Table 5 presents descriptive statistics for the three dependent variables. In absolute terms, we noted a small increase in the average values for the three dependent variables.

## Log Frequency

In the mixed-effects analysis for log frequency, two fixed effects significantly explained the log frequency of the N/ADJ pairs used: phraseological unit and task. Time, EI score, and target language were not important, and we removed the only significant interaction (Time × Task) because the BIC (14,378.40) for the model with the interaction term was higher (i.e., worse) than the model without the interaction (14,368.80). As Table 6 shows, the likelihood of producing more frequent combinations was lower in the essay than in the interview (see the negative coefficient estimate). For phraseological unit, we found that ADJ + N (compared to N + ADJ) combinations were associated with higher frequency (see the positive coefficient estimate). The results from the relative importance analysis (i.e., the LMG values) identified phraseological unit as the most important regressor, followed by task. Our verification of the model fit showed that, overall, this model accounted for 24.89% of the variance present in the dataset. Figure 1 provides boxplots of the two significant main effects.

## Delta P<sub>noun→adj</sub>

Three fixed effects significantly predicted the delta P<sub>noun→adj</sub> of N/ADJ combinations (see Table 7 and Figure 2): phraseological unit, target language, and task. Time and EI score were not significant. Although the interactions between time and the three significant fixed effects were significant, all were ultimately removed because the BIC values did not support retaining them (model without interaction: -22,369.80; model with Task × Time interaction:
<table><caption>**Table 5** Descriptive statistics for the measures of the three dependent variables in the study (N = 50): Frequency and two cue contingency scores</caption><thead><tr><th rowspan="2">Time</th><th colspan="2">Log frequency</th><th colspan="2">Delta P<sub>noun→adj</sub></th><th colspan="2">Delta P<sub>adj→noun</sub></th></tr><tr><th>M (SD)</th><th>Range</th><th>M (SD)</th><th>Range</th><th>M (SD)</th><th>Range</th></tr></thead><tbody><tr><td>Prestay</td><td>3.920 (1.211)</td><td>0.551–6.231</td><td>1.381 (0.023)</td><td>1.360–1.433</td><td>1.092 (0.027)</td><td>1.068–1.156</td></tr><tr><td>End-stay</td><td>4.013 (1.256)</td><td>0.551–6.231</td><td>1.385 (0.026)</td><td>1.360–1.434</td><td>1.094 (0.028)</td><td>1.068–1.156</td></tr></tbody></table>
<table><caption>**Table 6** Mixed-effects regression results for the log frequency model</caption><thead><tr><th>Fixed effects</th><th><i>b</i></th><th><i>SE</i></th><th>95% CI</th><th><i>t</i></th><th>LMG</th></tr></thead><tbody><tr><td>Intercept</td><td>3.30</td><td>0.03</td><td>[3.24, 3.36]</td><td>110.46</td><td></td></tr><tr><td>Phraseological unit ADJ + N</td><td>1.21</td><td>0.03</td><td>[1.15, 1.27]</td><td>38.07</td><td>0.24</td></tr><tr><td>Taskessay</td><td>-0.13</td><td>0.04</td><td>[-0.20, -0.06]</td><td>-3.51</td><td>0.01</td></tr></tbody></table><table><thead><tr><th>Random effect</th><th>Variance</th><th><i>SD</i></th></tr></thead><tbody><tr><td>Intercept</td><td>0.01</td><td>0.10</td></tr></tbody></table>

Note. $R^2_{\text{marginal}} = .24$; $R^2_{\text{conditional}} = .25$. LMG = relative importance estimate.

<table><caption>**Table 7** Mixed-effects regression results for the delta $P_{\text{noun→adj}}$ model</caption><thead><tr><th>Variable</th><th><i>b</i></th><th><i>SE</i></th><th>95% CI</th><th><i>t</i></th><th>LMG</th></tr></thead><tbody><tr><td>Intercept</td><td>1.373</td><td>0.0010</td><td>[1.372, 1.375]</td><td>1,790.626</td><td></td></tr><tr><td>Phraseological unit ADJ + N</td><td>0.013</td><td>0.0007</td><td>[0.0115, 0.0142]</td><td>18.433</td><td>0.0692</td></tr><tr><td>Target language Spanish</td><td>0.006</td><td>0.0008</td><td>[0.0042, 0.0076]</td><td>6.963</td><td>0.0139</td></tr><tr><td>Taskessay</td><td>-0.005</td><td>0.0008</td><td>[-0.0065, -0.0033]</td><td>-6.030</td><td>0.0108</td></tr></tbody></table><table><thead><tr><th>Random effect</th><th>Variance</th><th><i>SD</i></th></tr></thead><tbody><tr><td>Intercept</td><td>0.0000031</td><td>0.001761</td></tr></tbody></table>

Note. $R^2_{\text{marginal}} = .09$; $R^2_{\text{conditional}} = .10$. LMG = relative importance estimate.

-2,362.20; model with Language × Time interaction: -22,362.80; model with Phraseological Unit × Time interaction: -22,370.40). First, we found that ADJ + N combinations resulted in higher delta $P_{\text{noun→adj}}$ scores than did N + ADJ combinations. Additionally, the productions in Spanish versus those in French showed higher delta $P_{\text{noun→adj}}$ scores. Finally, the participants used significantly less strongly associated combinations in the essays than they did in the interviews. The relative importance analysis (i.e., LMG) revealed phraseological unit to be the most important predictor, followed by language and task. Overall, this model accounted for 9.92% of the variance.

## Delta $P_{\text{adj→noun}}$

In the analysis of delta $P_{\text{adj→noun}}$, two independent variables were significant (see Table 8 and Figure 3): phraseological unit and task. Time, EI score, and target language were not significant, and no interactions with time reached significance. Stronger delta $P_{\text{adj→noun}}$ scores were found for ADJ + N (vs. N +
<figure><img src="image_4.png" /><figcaption>**Figure 2** Boxplots illustrating significant fixed effects in the delta $P_{noun→adj}$ analysis. The symbol × indicates the location of the group means.</figcaption></figure>

<table><caption>**Table 8** Mixed-effects regression results for the delta $P_{adj→noun}$ model</caption><thead><tr><th>Variable</th><th>b</th><th>SE</th><th>95% CI</th><th>t</th><th>LMG</th></tr></thead><tbody><tr><td>Intercept</td><td>1.087</td><td>0.0008</td><td>[1.086, 1.089]</td><td>1,390.894</td><td></td></tr><tr><td>Phraseological unit ADJ + N</td><td>0.009</td><td>0.0008</td><td>[0.0071, 0.0102]</td><td>10.755</td><td>0.0228</td></tr><tr><td>Task essay</td><td>0.003</td><td>0.0009</td><td>[0.0011, 0.0048]</td><td>3.169</td><td>0.0013</td></tr></tbody></table><table><thead><tr><th>Random effect</th><th>Variance</th><th>SD</th></tr></thead><tbody><tr><td>Intercept</td><td>0.000008119</td><td>0.002849</td></tr></tbody></table>

Note. $R^2_{marginal}$ = .02; $R^2_{conditional}$ = .03. LMG = relative importance estimate.

ADJ pairs, as well as in essays (compared to the interviews). Phraseological unit was the most important variable, followed by task. The final model was able to account for a small amount of total variance (3.49%).

## Discussion

Usage-based approaches to additional-language acquisition have identified many features of the input that act as determinants of learning, two of which were the focus of our study: frequency and cue contingency. Following Ellis
<figure><img src="image_5.png" /><figcaption>**Figure 3** Boxplots illustrating significant fixed effects in the delta $P_{adj→noun}$ analysis. The symbol × indicates the location of the group means.</figcaption></figure>

et al.’s (2015) and Foster et al.’s (2014) studies, we started from the assumption that a stay in a target-language environment—with its associated change in input—might have a demonstrable impact on phraseological development. More specifically, sensitivity to input frequency and cue contingency might be visible in the types of word combinations used by learners. To explore this possibility, we assessed whether the frequency and cue contingency of N/ADJ pairs used by a group of 50 learners significantly evolved during an academic year spent in a target-language environment. This was accomplished by exploring both whether the variable of time significantly predicted the log frequency and delta P scores of all N/ADJ combinations produced by the participants and whether the variable of time significantly interacted with other significant variables.

## Change Over Time

With respect to the main effect of time, although descriptive statistics (see Table 5) showed a slight increase for all three dependent variables between prestay and end-stay, none of the mixed-effects regression analyses selected time as a significant predictor. Our final models also contained no interactions with the variable of time. This indicated that the impact of other significant predictors was not modulated by the change in learning context. Taken together, this indicated that the frequency and cue contingency characteristics of the N/ADJ pairs that the participants used before and after an extended period abroad did not show significant change.

Although general discussions of the importance of input as well as more specific considerations concerning usage-based determinants of learning suggest that an immersion experience may lead to learners using word pairs that are more frequent in the input and that are characterized by stronger cue contingency, previous empirical research exploring this issue has reported
contradictory results. With respect to frequency, four longitudinal studies involving learners in a target-language environment found significant change in the direction of greater use of frequent word combinations (Crossley & Salsbury, 2011; Garner & Crossley, 2018; Kim et al., 2018; Siyanova-Chanturia, 2015). However, Siyanova-Chanturia and Spina (2020) reported the use of phraseological units that were significantly less frequent after a six-month stay abroad, whereas Edmonds and Gudmestad (2021) and Omidian et al. (2021) reported no significant change. Research focusing on cue contingency has used various measures, with most studies reporting no change over time for at least one measure (Bestgen & Granger, 2014; Edmonds & Gudmestad, 2021; Garner & Crossley, 2018; Kim et al., 2018; Omidian et al., 2021; Siyanova-Chanturia & Spina, 2020; Yoon, 2016). Edmonds and Gudmestad (2021), Li and Schmitt (2010), and Siyanova-Chanturia (2015) reported a significant change in the direction of more strongly associated word combinations, whereas Bestgen and Granger (2014) and Siyanova-Chanturia and Spina (2020) found that learners produced less strongly associated combinations after a stay abroad. Against this backdrop, our results offer additional evidence of stability across time—despite the immersion experience—for both the frequency and cue contingency of word combinations produced by learners.

## Role of Phraseological Unit

To understand this mixed set of results, we suggest that examining other potentially influential variables may be necessary. In particular, considering the type of phraseological unit under study may offer some insight. Indeed, it is currently unclear whether phraseological development may proceed differently as a function of type of word combination. Researchers may expect differences when they consider the multiplicity of definitions, identification criteria, and ultimately word combinations that have been argued to belong under the general term of phraseology, including, among others, idiomatic expressions, collocations, and n-grams (Myles & Cordier, 2017; Wray, 2000). Among past phraseological research involving learners in a stay-abroad context, it is striking that studies focusing on n-grams have consistently shown development in frequency measures (Crossley & Salsbury, 2011; Garner & Crossley, 2018; Kim et al., 2018), with very little evidence of change in lexical association (only Bestgen & Granger, 2014, reported such change).

These findings are consistent with two interesting interpretations. First, for n-grams, learners may show increases in frequency before any such increase in lexical association, regardless of learning context. Such a conclusion would
further support findings that have documented learners’ tendency to use (and even overuse) highly frequent phraseological units, without a concomitant use of highly associated lexical combinations (e.g., Durrant & Schmitt, 2009). Second, learners may be particularly sensitive to n-gram frequency in the input. If this is the case, a change in learning context from at-home to target-language environment—and the resultant change in input—may be expected to lead to the use of more highly frequent n-grams. Studies that include longitudinal data collected several times prior to a stay abroad would allow future research to explore these two possibilities.

Compared to research on n-grams, the results from studies on linguistically defined word combinations are much less consistent, with past research having reported both change in frequency and lexical association and the lack thereof. It may be the case that this lack of consistency reflects the diversity of word combinations included in this category. Namely, different linguistically defined combinations may show different developmental trajectories. Among previous studies involving learners in a stay-abroad context, two are particularly instructive on the potential influence of word combination as they focused on different combinations using the same corpus. Siyanova-Chanturia and Spina (2020) and Omidian et al. (2021) conducted studies based on a corpus collected from Chinese learners of Italian (Common European Framework of Reference for Languages levels A1, A2, B1) before and after a six-month intensive Italian course in Italy. Siyanova-Chanturia and Spina (2020) focused on N/ADJ combinations, whereas Omidian et al. (2021) studied V/N pairs. Despite having worked on the same corpus, the results reported in the two studies diverged, suggesting differences in development as a function of combination type.

Concerning frequency, although the learners used N/ADJ combinations that were less frequent after their stay abroad, no change was found for V/N collocations. For cue contingency, comparisons are more difficult because the two studies used different measures. However, the two bidirectional measures used (log Dice scores for V/N pairs and MI scores for N/ADJ combinations) showed no significant change over time. Siyanova-Chanturia and Spina’s (2020) study on N/ADJ combinations included the unidirectional measure delta P, and their analyses found that delta P scores for N/ADJ pairs were significantly lower at the end of the stay abroad. Given that Omidian et al. (2021) did not report delta P scores, the question remains open as to whether they might have documented similar change in the V/N combinations. The interpretations in the two studies also highlighted differences. In interpreting the lack of change in their overall results, Omidian et al. (2021) underscored the presence of substantial random
variation (i.e., a large difference between marginal and conditional R² values) in both the frequency and the log Dice analyses. Omidian et al. suggested that the lack of significant trends reflected the considerable individual differences in the production of V/N combinations. In comparison, Siyanova-Chanturia and Spina (2020) attributed the decrease in N/ADJ frequency and cue contingency to the learners' growing (lexical) experimentation:

> It seems that, following extended exposure to the L2, as learners become more able language users and as they acquire more extensive (single word) vocabularies, they also tend to experiment more with word combinatorial mechanisms and, as a result, produce less idiomatic, less nativelike word sequences. (p. 451)

Strikingly, these comparable studies of the same dataset have provided strong evidence of differences in learning trajectories as a function of lexical combination type. This observation suggests that care must be taken when comparisons are made across studies, as phraseological development appears to be sensitive to type of phraseological unit.

The results from our study provide further evidence in favor of the influence of phraseological unit on usage patterns. Because French and Spanish show two possible orders for N/ADJ combinations within a noun phrase, we included phraseological unit, that is, N + ADJ versus ADJ + N, as an independent variable in this study. Some researchers may argue that our dataset presents a set of collocations that happen to have two linear orders. This is particularly the case for approaches that define phraseological units as co-occurring word combinations independent of word order (e.g., Paquot, 2019). However, the fact that linear word order was both significant and the most important predictor in all three analyses signals that ADJ + N and N + ADJ combinations had different usage properties in this corpus, raising the question as to whether they should be considered to be different collocations entirely. We suggest that learner attention—also a determinant of learning identified by usage-based approaches (Ellis et al., 2016, p. 79)—may aid in understanding the importance of word order in this analysis. This is because learners’ attention is molded by experience with other languages, and especially with their native language (e.g., Ellis & Sagarra, 2011). Regarding N/ADJ combinations, the fact that prenominal adjectives dominate in English may plausibly result in greater attention and perhaps sensitivity to input properties for collocations showing prenominal word order. In our analysis, it is precisely ADJ + N that
resulted in higher frequency and delta P scores for these anglophone learners
of Spanish and French.

Effect of Task

In addition to phraseological unit, the variable of task was also significant in all three analyses: The N/ADJ pairs that the participants used in the essays tended to be less frequent and to have lower delta P<sub>noun→adj</sub> scores but higher delta P<sub>adj→noun</sub> scores than did N/ADJ pairs in interviews. These results underscore the important influence of task on word combination use. Whereas Yoon (2016) reported a significant difference in phraseological development as a function of task genre (argumentative vs. narrative), our study built on and extended these results by demonstrating the importance of task variation among stay-abroad learners using a written argumentative essay and an oral semiguided interview. Although the two tasks from the LANGSNAP corpus differed in several ways (genre, mode, potentially formality), our interpretation focuses on the difference in mode. Based on past research, we might have expected phraseological development in oral versus written tasks to vary because of the higher reported density of phraseology in oral production (e.g., Ellis et al., 2015) and the important processing role that phraseology may play in oral tasks (e.g., Tavakoli & Uchihara, 2020). Given the particular importance of phraseology in oral tasks, it would be unsurprising for N/ADJ pairs in the oral interviews to have both higher frequency and higher cue contingency than in the argumentative essays.

Whereas significantly higher frequency was indeed documented in oral interviews, the cue contingency results showed a mixed picture: The delta P<sub>noun→adj</sub> analysis showed the expected result, whereas the delta P<sub>adj→noun</sub> scores were significantly lower in the oral interviews than in the argumentative essays. We suggest that this finding may reflect the demands of online planning. Schneider (2020, p. 269) observed (with respect to noun phrases contained within prepositional phrases) that “speakers might plan heads of noun phrases before any other words in the phrase.” From an acquisitional point of view, planning nouns ahead of planning adjectives in oral production may result in a tendency for learners to favor combinations with a higher lexical association in the direction N→ADJ, a tendency that would not be expected to be as strong in the written modality where writers have time to plan and revise their productions. Finally, in an effort to avoid speculative remarks, we do not offer an interpretation for the significance of task in the delta P<sub>adj→noun</sub> analysis because we have not found an explanation for this finding in previous theoretical or empirical research. Future research involving a greater number
of tasks and reflecting a larger number of task characteristics may be necessary
to shed light on this finding.

Target Language

We found one final variable to be significant in this study: target language. In
the analysis of delta P<sub>noun→adj</sub>, the participants majoring in Spanish produced
more strongly associated combinations than did the participants majoring in
French. Although past studies (Siyanova-Chanturia, 2015; Siyanova-Chanturia
& Spina, 2020) have argued that research on phraseology would benefit from
the inclusion of more and varied target languages, our study offers the first
evidence of the influence of this variable on phraseological development, high-
lighting the clear need to broaden horizons to encompass more than a sin-
gle target language in investigations of additional-language phraseology. The
availability of parallel corpora, like those created via the Web-As-Corpus Kool
Yinitiative (Baroni et al., 2009), has helped to make the simultaneous inves-
tigation of more than one target language feasible. And, as is the case in our
study, this methodological decision contributed to empirically demonstrating
the generalizability, but also the limits, of the findings. The finding that tar-
get language was significant in one analysis is also of importance for dis-
cussions concerning lexical association measures. In particular, the fact that
target language significantly impacted scores for delta P<sub>noun→adj</sub>, but not for
delta P<sub>adj→noun</sub>, provides additional empirical support for the conceptual ar-
gument in favor of unidirectional measures, namely that “associations are not
necessarily reciprocal in strength” (Ellis & Ferreira-Junior, 2009, p. 198). The
tendency in previous research (including our own) to rely on bidirectional mea-
sures, such as the MI score and log Dice, for the evaluation of cue contingency
may be at least in part responsible for the previous inconsistent findings, as
such measures may effectively mask trends that involve cue contingency in
only one direction, such as the finding for target language in our study.

Limitations and Future Directions

To end the discussion, we reflect on limitations and future directions that
have come to light as a result of this study. The first limitation concerns the
amount of total variance accounted for in each model: Whereas the final log
frequency model accounted for 24.89%, the delta P<sub>noun→adj</sub> model accounted
for only 9.92% and the delta P<sub>adj→noun</sub> analysis for only 3.49%. Although
these R<sup>2</sup> values are similar to those reported by Siyanova-Chanturia and Spina
(2020, p. 447), they suggest that other as yet unidentified variables play an
important role in phraseological patterns. These findings invite future research
that seeks to identify other sources of variance (i.e., other independent vari-
ables) that advance the understanding of phraseological use and development.
A second limitation concerns the tasks under study. The LANGSNAP corpus
offers a rich set of longitudinal data, collected using three types of tasks. For
our study, we focused on the two tasks that contained the most N/ADJ combi-
nations: oral interviews and written argumentative essays. These tasks differed
in several respects, including modality, genre, and formality. On the basis of
the LANGSNAP corpus, it was not possible to disentangle the role of specific
task features. Future research on longitudinal phraseological development is
needed in which the systematic manipulation of task features is included in the
design. Finally, although our study focused on a single lexical combination, we
argue that our own results, as well as those from previous studies, are consistent
with the idea that different phraseological units have different developmental
trajectories. Longitudinal research focusing on multiple phraseological units
in a single investigation would be ideal so that researchers could determine
whether different trajectories indeed exist and, if so, what differences may be
uncovered.

Conclusion

In our three analyses, we explored how anglophone learners of French and
Spanish used N/ADJ combinations, investigating their sensitivity to two usage-
based determinants of learning. Although our models provided several impor-
tant insights to phraseological use, we found no evidence of change between
the beginning and the end of an academic year spent in a target-language en-
vironment. In addition to exploring the impact of a stay abroad, we also in-
vestigated how the four independent variables—task, initial proficiency, target
language, and phraseological unit—impacted phraseological use. Our results
showed that phraseological use was significantly impacted by phraseological
unit (analyses of frequency: delta Pnoun→adj and delta Padj→noun), by task (anal-
yses of frequency: delta Pnoun→adj and delta Padj→noun), and by target language
(analysis of delta Pnoun→adj). However, the three models accounted for rel-
atively low proportions of the total variance—between 3.49% and 24.89%.
Overall, our analyses demonstrated stasis with respect to sensitivity to fre-
quency and cue contingency after a 9-month stay in a target-language envi-
ronment. In sum, we illustrated how usage-based investigations that consider
the role that a range of variables play in the use and development of phrase-
ological competence are well-suited for offering explanations of the complex
characteristics of phraseological units.

Final revised version accepted 10 August 2022
# Open Research Badges

<figure><img src="image_6.png" /></figure>

This article has earned an Open Materials badge for making publicly available the components of the research methods needed to reproduce the reported procedure. All materials that the authors have used and have the right to share are available at http://www.iris-database.org. All proprietary materials have been precisely identified in the manuscript.

## Notes

1. The term additional languages refers to any language learned after the first language.

2. The corpus is available at http://langsnap.soton.ac.uk and https://slabank.talkbank.org/access.

3. We excluded Participant 122 because a complete dataset was not complete.

4. Information concerning the age of Participants 150 and 175 was not available, nor was the number of years that Participant 150 spent studying Spanish.

5. For interlanguage forms, if the target form was clearly recognizable, our corpus searches were based on the target form. This was the case for examples like *provoca reacciones diferentes en distintas personas y distintas demográficas* "It provokes different reactions in different people and different demographics" where the learner used the adjective *demográficas* instead of the target-like nominal form *demografias*. Our corpus search for this item used *demografia* in combination with the adjective *distinto*.

6. Following Field et al. (2012, p. 192), we reversed the scores prior to transformation to preserve their directionality. For the transformation, we used the following equation: $1/(X_{highest} - X)$. For example, the combination *bueno* + *ejemplo* ("good" + "example") had a delta $P_{nouns→adj}$ score of 0.00036640. We began by reversing the score, so that it became negative (-0.000366). To calculate the denominator, we then subtracted this score from the highest delta $P_{noun→adj}$ score in the dataset (0.732326: $0.732326 - (-0.000366) = 0.732692$. This number was then plugged into the equation, resulting in: $1/0.732692 = 1.36483$

7. To maintain statistical parsimony, when more than one model had the same BIC, we selected the model with the fewest predictors.

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**Supporting Information**

Additional Supporting Information may be found in the online version of this article at the publisher's website:

**Accessible Summary**

**Appendix S1. Corpus-Based Frequency Searches: The Three Dependent Variables.**

**Appendix S2. Calculation of Delta P.**