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Are My Learners Advanced?: Using Measures of Complexity and Accuracy to Analyze L2 Spanish Writing

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Title: Are My Learners Advanced?: Using Measures of Complexity and Accuracy to Analyze L2 Spanish Writing
Language: English
Authors: Marie Mangold
Source: Foreign Language Annals. 2025 58(2):326-345.
Availability: Wiley. Available from: John Wiley & Sons, Inc. 111 River Street, Hoboken, NJ 07030. Tel: 800-835-6770; e-mail: cs-journals@wiley.com; Web site: https://www.wiley.com/en-us
Peer Reviewed: Y
Page Count: 20
Publication Date: 2025
Document Type: Journal Articles
Reports - Research
Descriptors: Spanish, Second Language Instruction, Second Language Learning, Language Proficiency, Self Evaluation (Individuals), Accuracy, Teaching Methods, Writing Processes, Rating Scales, Guidelines, Correlation, Syntax, Criticism, Writing Skills, Phrase Structure, Error Patterns, Advanced Students
DOI: 10.1111/flan.12788
ISSN: 0015-718X
1944-9720
Abstract: One of the critiques of proficiency as defined by scales, such as that of ACTFL, is its lack of grounding in linguistic realities. Measures of complexity, accuracy, and fluency provide a route in which proficiency can be quantitatively measured by identifying linguistic correlates (see Brown et al., 2017; Long et al., 2012). This project aimed to identify the linguistic correlates that distinguish L2 Spanish writing at intermediate-high and advanced-low proficiency levels as defined by the Language Ability Self-Evaluation Resource. Forty writing samples comprised the data. Measures of lexical complexity (density and diversity), syntactic complexity (mean length of T-unit, number of clauses per T-unit, average length of error-free T-unit), and accuracy (ratio of error-free T-unit, number of errors per 100 words) were used to analyze the samples. Findings suggest that accuracy is the linguistic feature that best distinguishes intermediate from advanced proficiency in L2 Spanish writing. The implications of these findings for research and pedagogy are examined.
Abstractor: As Provided
Entry Date: 2025
Accession Number: EJ1477333
Database: ERIC
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  Value: <anid>AN0186745410;fla01jul.25;2025Jul22.02:37;v2.2.500</anid> <title id="AN0186745410-1">Are my learners advanced?: Using measures of complexity and accuracy to analyze L2 Spanish writing </title> <p>One of the critiques of proficiency as defined by scales, such as that of ACTFL, is its lack of grounding in linguistic realities. Measures of complexity, accuracy, and fluency provide a route in which proficiency can be quantitatively measured by identifying linguistic correlates (see Brown et al., 2017; Long et al., 2012). This project aimed to identify the linguistic correlates that distinguish L2 Spanish writing at intermediate‐high and advanced‐low proficiency levels as defined by the Language Ability Self‐Evaluation Resource. Forty writing samples comprised the data. Measures of lexical complexity (density and diversity), syntactic complexity (mean length of T‐unit, number of clauses per T‐unit, average length of error‐free T‐unit), and accuracy (ratio of error‐free T‐unit, number of errors per 100 words) were used to analyze the samples. Findings suggest that accuracy is the linguistic feature that best distinguishes intermediate from advanced proficiency in L2 Spanish writing. The implications of these findings for research and pedagogy are examined.</p> <p>Keywords: postsecondary/higher education; quantitative research; second language acquisition; Spanish; writing proficiency</p> <p> <img src="https://imageserver.ebscohost.com/img/embimages/rdk/FLA/01jul25/flan12788-gra-0001.jpg?ephost1=dGJyMNHX8kSepq84v%2bvlOLCmsE6epq5Srqa4SK6WxWXS" alt="flan12788-gra-0001.jpg" title="." /> </p> <p></p> <hd id="AN0186745410-3">INTRODUCTION</hd> <p>Language proficiency scales such as the Common European Framework of Reference for Languages (CEFR), Interagency Language Roundtable (ILR), and ACTFL Proficiency Guidelines have been widely adopted as a means of conceptualizing proficiency, particularly for the advanced[<reflink idref="bib1" id="ref1">1</reflink>] second language (L2) learner. The ACTFL ([<reflink idref="bib2" id="ref2">2</reflink>]) provides detailed descriptions of proficiency levels, ranging from Novice‐Low to Distinguished, and represents a comprehensive system that assesses language users' abilities across speaking, writing, listening, and reading, focusing on their performance in spontaneous, real situations. However, some scholars take issue with the conceptualization of proficiency given the descriptions often fall short in aligning with observable linguistic phenomena (see Bachman [<reflink idref="bib4" id="ref3">4</reflink>]; Lantolf & Frawley, [<reflink idref="bib32" id="ref4">32</reflink>]; Menke & Malovrh, [<reflink idref="bib41" id="ref5">41</reflink>]). This gap is particularly evident in their empirical validity concerning vocabulary range and control (Wisniewski, [<reflink idref="bib61" id="ref6">61</reflink>]). In response to these limitations, researchers have sought to identify the language features that determine advanced proficiency. One relevant approach is the analysis of complexity, accuracy, and fluency, or CAF analysis (Crookes, [<reflink idref="bib16" id="ref7">16</reflink>]; Skehan, [<reflink idref="bib56" id="ref8">56</reflink>]), which offers an objective, quantitative method for evaluating L2 learner development, quality, and proficiency (Barrot & Agdeppa, [<reflink idref="bib7" id="ref9">7</reflink>]; Ortega, [<reflink idref="bib45" id="ref10">45</reflink>]). An array of CAF measures is utilized in quantitative analyses, and several studies have demonstrated that CAF analysis can serve as a means of establishing linguistic correlates of proficiency, the linguistic features specific to distinct proficiency levels (e.g., Brown et al., [<reflink idref="bib9" id="ref11">9</reflink>]; Long et al., [<reflink idref="bib36" id="ref12">36</reflink>]).</p> <p>The present study explores features of L2 Spanish writing at the intermediate‐high and advanced‐low[<reflink idref="bib2" id="ref13">2</reflink>] levels as interpreted by the Language Ability Self‐Evaluation Resource (LASER). This assessment is informed by the ACTFL ([<reflink idref="bib1" id="ref14">1</reflink>]) and provides proficiency estimates, though it is essential to acknowledge that the proficiency ratings generated by the LASER do not constitute official ACTFL scores, and it is not an official ACTFL test. The differences between the Intermediate and Advanced levels are significant as many world and foreign language curricula along with ACTFL/CAEP accredited teacher licensure programs (e.g., Huhn et al., [<reflink idref="bib25" id="ref15">25</reflink>]) aim for learners to attain Advanced proficiency as a key outcome. More specifically, it is the minimum level at which working, or professional, proficiency is established (see ACTFL, [<reflink idref="bib2" id="ref16">2</reflink>]). The present study investigates measures of complexity and accuracy across written texts produced by L2 learners of Spanish at proficiency levels estimated to be at ACTFL Intermediate‐High and Advanced‐Low as interpreted by the LASER to delineate the linguistic features of advanced writing, therefore contributing to the understanding of the advanced learner. Fluency, often evaluated in conjunction with complexity and accuracy, is not examined in this study due to logistical constraints that prevent controlling tasks for temporal variables.</p> <hd id="AN0186745410-4">LITERATURE REVIEW</hd> <p>Analyzing L2 learners' written production is a key element in determining linguistic competence (Gregori‐Signes & Clavel‐Arroitia, [<reflink idref="bib23" id="ref17">23</reflink>]). An array of literature explores the features of L2 writing (e.g., Bardel et al., [<reflink idref="bib5" id="ref18">5</reflink>]; Bulté & Housen, [<reflink idref="bib10" id="ref19">10</reflink>]; Consolini & Kyle, [<reflink idref="bib15" id="ref20">15</reflink>]; Crossley et al., [<reflink idref="bib18" id="ref21">18</reflink>]; Gregori‐Signes & Clavel‐Arroitia, [<reflink idref="bib23" id="ref22">23</reflink>]; Kim et al., [<reflink idref="bib28" id="ref23">28</reflink>]; Kuiken & Vedder, [<reflink idref="bib29" id="ref24">29</reflink>]; Kyle et al., [<reflink idref="bib30" id="ref25">30</reflink>]; Ortega, [<reflink idref="bib45" id="ref26">45</reflink>]; Schnur & Rubio, [<reflink idref="bib54" id="ref27">54</reflink>]; Yu, [<reflink idref="bib63" id="ref28">63</reflink>]), though this research frequently explores L2 writing in the context of English as a Foreign Language (EFL) or English as a Second Language (ESL). Within this line of research, researchers have addressed the linguistic features unique to distinct proficiency levels (e.g., Barrot & Agdeppa, [<reflink idref="bib7" id="ref29">7</reflink>]; Ortega, [<reflink idref="bib45" id="ref30">45</reflink>]; Restrepo‐Ramos, [<reflink idref="bib51" id="ref31">51</reflink>]; Wisniewski, [<reflink idref="bib61" id="ref32">61</reflink>]). This study is motivated by the same purpose of identifying the linguistic features of L2 Spanish writing that are associated with specific proficiency levels, and CAF analysis has the potential to establish linguistic correlates through objective, quantitative measures.</p> <hd id="AN0186745410-5">Complexity in L2 writing</hd> <p>Complexity is defined as the amount of elaboration, variety of linguistic features used, connections established between units, and sophistication of the forms employed (Ellis & Barkhuizen, [<reflink idref="bib20" id="ref33">20</reflink>]). Measures of complexity are used as indicators of proficiency (Barrot & Agdeppa, [<reflink idref="bib7" id="ref34">7</reflink>]), as the way information is connected, condensed, and elaborated varies across different levels of development (Menke & Strawbridge, [<reflink idref="bib42" id="ref35">42</reflink>]). Furthermore, the measures employed reflect the way in which a researcher conceives complexity (e.g., subordination used to evaluate syntactic complexity and lexical diversity to assess lexical complexity).</p> <hd id="AN0186745410-6">Lexical complexity in L2 writing</hd> <p>Like many CAF measures, lexical complexity has been used as a method of analyzing L2 performance for development (Bulté & Housen, [<reflink idref="bib10" id="ref36">10</reflink>]; Colombi, [<reflink idref="bib13" id="ref37">13</reflink>]; Gregori‐Signes & Clavel‐Arroitia, [<reflink idref="bib23" id="ref38">23</reflink>]), and distinguishing L2 learners across distinct proficiency levels (Restrepo‐Ramos, [<reflink idref="bib51" id="ref39">51</reflink>]; Schnur & Rubio, [<reflink idref="bib54" id="ref40">54</reflink>]). According to Schnur and Rubio ([<reflink idref="bib54" id="ref41">54</reflink>]), the patterns that emerge in "learners' lexical repertoires as their proficiency advances not only provide benchmarks for measuring advancement but also illuminate key elements that distinguish one proficiency level from the next," informing our understanding of language development and assessment design (p. 53). This understanding aids in designing assessments that are "theory‐driven, empirically tested, and practical" (Zareva et al., [<reflink idref="bib64" id="ref42">64</reflink>], p. 568). Lexical complexity involves measures of density, diversity, and sophistication, among others.</p> <p>Lexical density entails the percentage of lexical (i.e., content) words in a text (Eggins, [<reflink idref="bib19" id="ref43">19</reflink>]; Laufer & Nation, [<reflink idref="bib35" id="ref44">35</reflink>]), indicating nouns, verbs, adjectives, and adverbs (Johansson, [<reflink idref="bib27" id="ref45">27</reflink>]; Laufer & Nation, [<reflink idref="bib35" id="ref46">35</reflink>]). In the context of Spanish, research has demonstrated that this feature evolves over time (Colombi, [<reflink idref="bib13" id="ref47">13</reflink>]), and may be indicative of L2 proficiency level (Schnur & Rubio, [<reflink idref="bib54" id="ref48">54</reflink>]). Greater lexical density typically characterizes more advanced stages of language use and register, as seen in academic writing, compared to everyday language (e.g., Colombi, [<reflink idref="bib13" id="ref49">13</reflink>]), though it varies with task type and genre (Schnur & Rubio, [<reflink idref="bib54" id="ref50">54</reflink>]). Colombi ([<reflink idref="bib13" id="ref51">13</reflink>]) found that advanced writers in a Spanish for Native Speakers program used more embedded clauses, contributing to greater lexical density, while Schnur and Rubio ([<reflink idref="bib54" id="ref52">54</reflink>]) attributed increases in lexical density to overall L2 proficiency gain, though changes were minimal between Intermediate‐High and Advanced levels according to ACTFL Assessment of Performance toward Proficiency in Languages (AAPPL) test scores. Schnur and Rubio observed a small variance in lexical density and attributed early gains at lower proficiency levels to noun usage, but concluded that lexical density was less indicative of proficiency than lexical diversity and lexical sophistication, and was better suited for analyzing different registers and genres. In contrast, research on L2 English has not necessarily linked lexical density to more proficient writing (Crossley & McNamara, [<reflink idref="bib17" id="ref53">17</reflink>]). Contrary to Colombi ([<reflink idref="bib13" id="ref54">13</reflink>]) and Schnur and Rubio ([<reflink idref="bib54" id="ref55">54</reflink>]), Gregori‐Signes and Clavel‐Arroitia found a decrease in lexical density with increased proficiency in L2 learners of English, suggesting that advanced learners used more function words in their writing. Thus, lexical density may not consistently reflect proficiency levels across languages.</p> <p>The assumption in language proficiency assessment is that "more diverse vocabularies are indicative of more proficiency and larger lexicons" (Crossley et al., [<reflink idref="bib18" id="ref56">18</reflink>], p. 564). Lexical diversity, or variation, measures the variety of word types in a text and is commonly assessed using type‐token ratio (TTR), which divides the number of unique word types by the total number of words (Laufer & Nation, [<reflink idref="bib35" id="ref57">35</reflink>]), <emph>VOCD</emph> (or <emph>D</emph>), which accounts for text length (Malvern et al., [<reflink idref="bib37" id="ref58">37</reflink>]), and measure of textual lexical diversity (MTLD), which considers the length of sequential word strings (McCarthy & Jarvis, [<reflink idref="bib38" id="ref59">38</reflink>]). Research supports lexical diversity as a reliable indicator of lexical proficiency, linking it to vocabulary breadth and knowledge of lexical features (Crossley et al., [<reflink idref="bib18" id="ref60">18</reflink>]; Schnur & Rubio, [<reflink idref="bib54" id="ref61">54</reflink>]). Studies on L2 Spanish have demonstrated a positive relationship between lexical diversity and writing proficiency (Consolini & Kyle, [<reflink idref="bib15" id="ref62">15</reflink>]; Schnur & Rubio, [<reflink idref="bib54" id="ref63">54</reflink>]), particularly between Intermediate‐Mid and Advanced levels, underscoring "that both breadth and depth of lexical knowledge are a distinguishing factor" at higher proficiency levels (Schnur & Rubio, [<reflink idref="bib54" id="ref64">54</reflink>], p. 69). However, Restrepo‐Ramos ([<reflink idref="bib51" id="ref65">51</reflink>]) observed no significant differences in lexical diversity between two proficiency groups of L2 learners of Spanish, suggesting that more time may be needed to observe lexical development. In EFL and ESL contexts, lexical diversity has been found to correlate with proficiency (Crossley et al., [<reflink idref="bib18" id="ref66">18</reflink>]; Gregori‐Signes & Clavel‐Arroitia, [<reflink idref="bib23" id="ref67">23</reflink>]; Yu, [<reflink idref="bib63" id="ref68">63</reflink>]). Using <emph>D</emph> and MTLD, Crossley et al. ([<reflink idref="bib18" id="ref69">18</reflink>]) determined lexical diversity as a key measure of proficiency, reflecting a greater variety of word types used by learners. Conversely, Bulté and Housen ([<reflink idref="bib10" id="ref70">10</reflink>]) did not determine lexical diversity significant in measuring lexical complexity growth in L2 English, proposing that other linguistic features or the measure's validity were possible factors. Additionally, lexical diversity, like lexical density, may vary with prompt formality (Yu, [<reflink idref="bib63" id="ref71">63</reflink>]).</p> <p>Despite the contradictions in research findings, Kim et al. ([<reflink idref="bib28" id="ref72">28</reflink>]) encouraged future studies to utilize test scores to explore the relationship between proficiency level and lexical complexity. In response to this call, the present study employs estimated proficiency scores based on an assessment modeled from the ACTFL ([<reflink idref="bib1" id="ref73">1</reflink>]) to examine lexical density and lexical diversity and provide a comprehensive view of lexical features and overall complexity in L2 Spanish writing. This analysis complements the syntactic measures detailed in the following section.</p> <hd id="AN0186745410-7">Syntactic complexity in L2 writing</hd> <p>Under the umbrella of complexity falls syntactic complexity, which entails "the range of forms that surface in language production and the degree of sophistication of such forms" (Ortega, [<reflink idref="bib45" id="ref74">45</reflink>], p. 493); in other words, the "variety, diversity, or elaborateness of grammatical resources" that appear in that production (Ortega, [<reflink idref="bib46" id="ref75">46</reflink>], p. 86). Methods of evaluating syntactic complexity include measuring the length of syntactic units, coordination, variety of forms, sophistication of forms, and acquisition timing of grammatical forms (Norris & Ortega, [<reflink idref="bib43" id="ref76">43</reflink>]). Many measures of written complexity are grounded in the T‐unit (Hunt, [<reflink idref="bib26" id="ref77">26</reflink>]), defined as a main clause and its subordinate clauses that are connected or embedded within that main clause. A collection of syntactic complexity measures has been established as reliable in evaluating L2 development (e.g., mean length of sentence [MLTU], simple sentence ratio, compound sentence ratio) (Bulté & Housen, [<reflink idref="bib10" id="ref78">10</reflink>]), but the relationship between syntactic complexity measures and proficiency levels is less known (Ortega, [<reflink idref="bib46" id="ref79">46</reflink>]). Most of this research focuses on L2 English or explores correlations with other proficiency scales.</p> <p>In the context of L2 Spanish writing, coordination presented significant differences across proficiency levels in a study by Restrepo‐Ramos ([<reflink idref="bib51" id="ref80">51</reflink>], and Menke and Strawbridge ([<reflink idref="bib42" id="ref81">42</reflink>]) suggested a correlation between an increase in MLTU and continued study of the target language across semesters (Menke & Strawbridge, [<reflink idref="bib42" id="ref82">42</reflink>]). Most relevant to the present study, Kuiken and Vedder ([<reflink idref="bib29" id="ref83">29</reflink>]) found C/TU as insignificant in writing produced by L2 Spanish writers. However, in L2 English and Italian, measures of subordination (Barrot & Agdeppa, [<reflink idref="bib7" id="ref84">7</reflink>]) and C/TU (Kuiken & Vedder, [<reflink idref="bib29" id="ref85">29</reflink>]) have been determined as effective and reliable in distinguishing learners across proficiency levels for each language, respectively. Additional research outside of L2 Spanish suggests a positive relationship between MLTU and proficiency (Wolfe‐Quintero et al., [<reflink idref="bib62" id="ref86">62</reflink>]), particularly when producing writing that is designed for public discourse (Byrnes et al., [<reflink idref="bib12" id="ref87">12</reflink>]). Unlike MLTU and C/TU, the length of error‐free T‐unit (LEFTU) blends concepts of accuracy and syntactic complexity. In this study, it was categorized as a measure of complexity due to its focus on the length of a certain type of T‐unit (i.e., error‐free). LEFTU has been identified as a reliable predictor of proficiency level in L2 learners of English (Larsen‐Freeman, [<reflink idref="bib33" id="ref88">33</reflink>]). Thus, the mixed findings and predominant emphasis on L2 English motivate the need for the present study.</p> <hd id="AN0186745410-8">Accuracy in L2 writing</hd> <p>Accuracy is frequently measured using error analysis (Ellis & Barkhuizen, [<reflink idref="bib20" id="ref89">20</reflink>]), stemming from Foster and Skehan's ([<reflink idref="bib21" id="ref90">21</reflink>]) definition of accuracy in which discourse is free from errors. Measures of accuracy include frequency and severity of errors, error type (e.g., lexical, morphological, syntactic), and ratio of error‐free T‐units. Polio and Shea ([<reflink idref="bib49" id="ref91">49</reflink>]) reported that few studies have investigated how accuracy in L2 writing varies according to proficiency level, and those that do occur in a variety of contexts, often focusing on L2 English and other languages beyond Spanish. For example, Long et al. ([<reflink idref="bib36" id="ref92">36</reflink>]) identified accuracy in morphological, syntactic, and lexical features as a significant factor in determining the oral proficiency of L2 learners of Russian. In the same line, Barrot and Agdeppa ([<reflink idref="bib7" id="ref93">7</reflink>]) identified the weighted clause ratio, a measure that takes into consideration the severity of error (see Foster & Wigglesworth, [<reflink idref="bib22" id="ref94">22</reflink>]), as effective in distinguishing the severity of errors in writing across various CEFR levels for L2 English. Hence, a connection between measures of accuracy in the line of L2 Spanish writing and learner proficiency levels remains underexplored.</p> <p>EFTU has been widely adopted in assessing L2 accuracy (Polio & Shea, [<reflink idref="bib49" id="ref95">49</reflink>]) and established as a significant measure in the production of L2 learners of English and languages other than Spanish, particularly in evaluating L2 production across different tasks (Way et al., [<reflink idref="bib58" id="ref96">58</reflink>]; Wigglesworth & Storch, [<reflink idref="bib59" id="ref97">59</reflink>]), as well as in assessing L2 language development (Larsen‐Freeman & Strom, [<reflink idref="bib34" id="ref98">34</reflink>]; Sánchez Abchi & De Mier, [<reflink idref="bib53" id="ref99">53</reflink>]). With respect to proficiency level, Larsen‐Freeman and Strom ([<reflink idref="bib34" id="ref100">34</reflink>]) and Larsen‐Freeman ([<reflink idref="bib33" id="ref101">33</reflink>]) found that EFTU was a reliable predictor of proficiency level in L2 English; the number of error‐free T‐units produced by learners increased as proficiency level advanced. Like EFTU, errors per 100 words is considered to be a general measure of accuracy and widely adopted (Ellis & Barkhuizen, [<reflink idref="bib20" id="ref102">20</reflink>]), specifically in L2 English and German speech (e.g., Mehnert, [<reflink idref="bib39" id="ref103">39</reflink>]; Polat & Kim, [<reflink idref="bib48" id="ref104">48</reflink>]; Suzuki & Kormos, [<reflink idref="bib57" id="ref105">57</reflink>]). Errors per 100 words is a global measure that has been shown to be affected by factors such as planning time and intermediate proficiency (Mehnert, [<reflink idref="bib39" id="ref106">39</reflink>]), correlates with perceived fluency and comprehensibility (Suzuki & Kormos, [<reflink idref="bib57" id="ref107">57</reflink>]), or simply assist in identifying how many errors an individual makes (Polat & Kim, [<reflink idref="bib48" id="ref108">48</reflink>]). However, these findings are unique to the L2 speech context and lacking from literature is the adoption of this measure in L2 writing. Like EFTU, it remains unclear how the measure of errors per 100 words relates to proficiency level in L2 writing, specifically in the case of L2 Spanish.</p> <hd id="AN0186745410-9">METHODS</hd> <p>The objective of this study (IRB #: 00010443) was to compare complexity and accuracy at proficiency levels estimated to be at ACTFL Intermediate‐High and Advanced‐Low as interpreted by an assessment informed by the ACTFL ([<reflink idref="bib1" id="ref109">1</reflink>]) in written narratives by L2 learners of Spanish. The following questions motivated the study:</p> <p></p> <ulist> <item> 1. Does lexical complexity vary in written texts of L2 Spanish at the threshold between intermediate and advanced proficiency? If so, how?</item> <p></p> <item> 2. Does syntactic complexity vary in written texts of L2 Spanish at the threshold between intermediate and advanced proficiency? If so, how?</item> <p></p> <item> 3. Does accuracy vary in written texts of L2 Spanish at the threshold between intermediate and advanced proficiency? If so, how?</item> </ulist> <hd id="AN0186745410-10">Participants</hd> <p>Forty adult L2 learners of Spanish enrolled at a major university in the western United States participated in this study. Participants were part of a larger project and were selected via a random stratified sample from a larger pool. Most participants were recruited via enrollment in a course in which the instructor required completion of the task materials, in this case, the LASER assessment, as a diagnostic tool; other participants completed the LASER to determine in which course they should enroll. Of the 40 participants in this study, 20 of the participants were estimated to write at a proficiency level consistent with ACTFL Intermediate‐High, and the other 20 participants were estimated to write at a proficiency level congruent with ACTFL Advanced‐Low. Henceforth, the participants' proficiency ratings will be categorized as <emph>intermediate‐high</emph> and <emph>advanced‐low</emph>, reflecting the fact that these ratings were not official ACTFL Writing Proficiency Test (WPT) scores but were derived from the self‐assessment component of the LASER, which utilizes Can‐Do statements designed according to the ACTFL ([<reflink idref="bib1" id="ref110">1</reflink>]). A summary of participants is provided in Table 1, and the specifics of each participant are found in Appendix A.</p> <p>1 Table Summary of participant data.</p> <p> <ephtml> <table><thead valign="bottom"><tr valign="bottom"><th /><th align="left">Female</th><th align="left">Male</th><th align="left">Mean age</th><th align="left">SD</th></tr></thead><tbody valign="top"><tr><td>intermediate‐high</td><td>20</td><td>20</td><td>22.5</td><td>1.69</td></tr><tr><td>advanced‐low</td><td>20</td><td>20</td><td>22.7</td><td>0.83</td></tr></tbody></table> </ephtml> </p> <hd id="AN0186745410-11">Procedures</hd> <p>The LASER assessment completed by the participants "estimates speaking and writing proficiency as described in the ACTFL proficiency guidelines based on test‐taker responses" and "when administered properly, [the scores from the LASER] are indicators of speaking and writing proficiency" (Wilcox et al., forthcoming). The LASER first elicits information about the language learner's background (e.g., language learning background, language‐learning grit, willingness to communicate, and productive skills self‐assessment) and asks learners to self‐assess their proficiency using Can‐Do statements aligned with the ACTFL ([<reflink idref="bib1" id="ref111">1</reflink>]). This information is not diagnostic but rather assists instructors in evaluating an individual's proficiency on the LASER writing and speaking tests. Speaking and writing prompts targeted at participants' self‐assessed proficiency level comprise the second part of the LASER. The writing portion of the assessment utilizes prompts dependent on the results of the self‐assessment component, beginning with a simpler task and advancing to one that is more complex. For example, the prompt aligned to the ACTFL Intermediate level asked learners <emph>What is a typical day like for you? What do you generally do from the time you wake up until you go to bed?</emph>, whereas the prompt reflective of the ACTFL Advanced level inquired <emph>What is the biggest surprise you had coming home from abroad? Describe in detail the person, place, thing, or circumstance that surprised you. What led to the surprise? How do you envision seeing this incident 5 years from now?</emph> In addition to one warm‐up question, all participants in this sample received the same two aforementioned prompts during the writing portion of the LASER. The instructions were in English.</p> <p>The materials comprising this study included typed essays from participants' responses to the LASER prompt consistent with the ACTFL Advanced level and their estimated proficiency rating derived from the self‐assessment component of the test. The current project analyzed participants' responses to the prompt aligned to the ACTFL Advanced level to determine if there was a difference between learners estimated to be at the ACTFL Intermediate‐High and Advanced‐Low levels. Although there was no time limit, the median time to complete all writing and speaking prompts was 50 min (Wilcox et al., [<reflink idref="bib60" id="ref112">60</reflink>]). The LASER was distributed using Qualtrics, which includes a basic spell check function, and was not proctored, indicating that participants completed the task at a time and location of their choosing.</p> <hd id="AN0186745410-12">ANALYSIS</hd> <p>The 40 writing samples were coded for seven measures of complexity and accuracy by the author, a near‐native L2 speaker of Spanish. A second evaluator, who was an L1 Spanish speaker from Colombia, assisted in the coding for syntactic complexity and accuracy. Both evaluators are trained in linguistic analyses. The coding entailed identifying content and lexical words, word types, T‐units, and errors, and is described in greater detail in the following sections.</p> <hd id="AN0186745410-13">Lexical complexity</hd> <p>The measures of lexical complexity employed in this study were lexical density and lexical diversity. Lexical density is the number of lexical, or content, words divided by the total number of words in a text (Laufer & Nation, [<reflink idref="bib35" id="ref113">35</reflink>]). The corpus analysis software AntConc (Anthony, [<reflink idref="bib3" id="ref114">3</reflink>]), which possesses a function to identify the frequency of each word within a text, was utilized to generate word lists for each writing sample. The classification of content and function words was then completed manually by the author. Content words contribute semantically to a text (Bell et al., [<reflink idref="bib8" id="ref115">8</reflink>]) and include nouns, verbs, adjectives, and adverbs (Johansson, [<reflink idref="bib27" id="ref116">27</reflink>]; Laufer & Nation, [<reflink idref="bib35" id="ref117">35</reflink>]). Beyond nouns, verbs, adjectives, and adverbs, this study included personal and subject pronouns as content words due to the fact that Spanish third‐person singular forms may be ambiguous,[<reflink idref="bib3" id="ref118">3</reflink>] and pronouns provide specification. Function words, in contrast, contribute grammatically to a text (Bell et al., [<reflink idref="bib8" id="ref119">8</reflink>]), and include prepositions, articles, conjunctions, auxiliary verbs (e.g., <emph>ser</emph> and <emph>estar</emph>), and deictic markers. Lexical density was then calculated for each writing sample.</p> <p>Lexical diversity, also referred to as lexical variation (see Laufer & Nation, [<reflink idref="bib35" id="ref120">35</reflink>]), is the percentage of different word types in a text. Using the same word lists generated by AntConc for lexical density, the words were then manually grouped into the same word type (e.g., <emph>habla</emph> [she/he speaks], <emph>hablamos</emph> [we speak], <emph>hablé</emph> [I spoke], etc.). Masculine and feminine, as well as plural and singular, versions of the same word were also grouped into the same word type, such as <emph>mismo</emph> and <emph>misma</emph> [same]. Variations of definite articles (e.g., <emph>el, los, la, las</emph> [the]), indefinite articles (e.g., <emph>un</emph> [an], <emph>una</emph> [an], <emph>unos</emph> [some/a few], <emph>unas</emph> [some/a few]), possessive adjectives, deictic markers, and diminutives and superlatives, were also grouped as the same word type. The TTR was then calculated by dividing the variety of word types in the text by the total number of words (Laufer & Nation, [<reflink idref="bib35" id="ref121">35</reflink>]). This produced the lexical diversity for each writing sample.</p> <hd id="AN0186745410-14">Syntactic complexity</hd> <p>Three features of syntactic complexity were employed to analyze the writing samples: mean length of T‐unit (MLTU), number of clauses per T‐unit (C/TU), and average LEFTU. The T‐units were first identified for each writing sample to calculate MLTU, C/TU, and LEFTU. MLTU consisted of calculating the average number of words per T‐unit (see Bulté & Housen, [<reflink idref="bib10" id="ref122">10</reflink>]). C/TU involved determining the average number of clauses per T‐unit (see Byrnes et al., [<reflink idref="bib12" id="ref123">12</reflink>]). In addition, C/TU entailed counting coordinated verb phrases as separate clauses, meaning verbs without overt subjects were counted as individual clauses, as done by Bardovi‐Harlig and Bofman ([<reflink idref="bib6" id="ref124">6</reflink>]) and Ortega ([<reflink idref="bib44" id="ref125">44</reflink>]). For example, the phrase <emph>y continué aprendiendo y practicando mi español desde entonces</emph> [and I continued learning and practicing my Spanish since then] was counted as two clauses; the first clause included <emph>y continué aprendiendo</emph> [and I continued learning], and the second consisted of the remainder of the phrase.</p> <p>The process of calculating LEFTU was more intricate. In this study, LEFTU was categorized as a measure of complexity due to the focus on the length of a certain type of T‐unit (e.g., Larsen‐Freeman, [<reflink idref="bib33" id="ref126">33</reflink>]). LEFTU first required identifying the errors[<reflink idref="bib4" id="ref127">4</reflink>] in each text. Researchers have different interpretations of the concept of error‐free: Larsen‐Freeman and Strom ([<reflink idref="bib34" id="ref128">34</reflink>]) defined error‐free as without morphological, syntactic, orthographic, or punctuation errors, whereas Scott and Tucker ([<reflink idref="bib55" id="ref129">55</reflink>]) considered error‐free to mean free of morphological and syntactic errors. Following Bardovi‐Harlig and Bofman ([<reflink idref="bib6" id="ref130">6</reflink>]), the present study defined error‐free as without morphological (e.g., unnecessary or missing prepositions, articles, or reflexive pronouns, unconjugated or misconjugated verb, inappropriate tense, agreement), syntactic (i.e., words in appropriate order), or lexical (e.g., inappropriate preposition, article, or word) errors, and did not take into account orthographic (e.g., missing accent marks) or punctuation errors. Therefore, morphological, syntactic, and lexical errors were identified in the writing samples by the author and the second evaluator. The two evaluators are trained in linguistic analyses and instructors of Spanish and, therefore, were cognizant of the linguistic variation that may occur across participants' language use. The two individuals separately identified the errors so as not to influence one another. Following this, the error analyses were compared, and any inconsistencies were discussed. Following discussion, the researcher and second evaluator reached greater than 98% agreement on errors.</p> <hd id="AN0186745410-15">Accuracy</hd> <p>Two measures of accuracy were utilized in the analysis: ratio of error‐free T‐units (EFTU) and number of errors per 100 words (E/100). EFTU was calculated by dividing the number of error‐free T‐units by the total number of T‐units and was recorded as a percentage. E/100 was determined by taking the first 100 words from each participant's sample and recording the number of errors. This measure was influenced by Polat and Kim ([<reflink idref="bib48" id="ref131">48</reflink>]), who identified errors in each sample for every set of 100 words, and by Suzuki and Kormos ([<reflink idref="bib57" id="ref132">57</reflink>]), who calculated the average number of lexical, morphological, or syntactic errors per 100 words.</p> <p>The seven measures adopted in the analysis were calculated for each writing sample, and the averages for each proficiency level group were identified. All measures were manually calculated. Lexical density and error coding guides used for the present study can be freely downloaded on the IRIS Database; iris-database.org.</p> <hd id="AN0186745410-16">RESULTS</hd> <p>To determine the significance of each CAF measure, a Shapiro‐Wilk test for normality was run in SPSS, a statistical software package, to check if the data met the common assumption of normality. Not all CAF measures met the normality assumption, and therefore, a Kruskal–Wallis test was run with a lowered <emph>p</emph>‐value. Given that there were seven measures in the analysis, adjusted family‐wise correction was applied using Bonferroni Correction to control for error rate. Hence, the significance value was lowered to <emph>p</emph> < .007. The following sections individually address each CAF measure, presenting first the descriptive statistics followed by the inferential statistics.</p> <hd id="AN0186745410-17">Research question 1: Lexical complexity</hd> <p>2 Table Group averages for lexical measures.</p> <p> <ephtml> <table><thead valign="bottom"><tr valign="bottom"><th>Measure</th><th>intermediate‐high</th><th>advanced‐low</th><th>Cohen's <italic>d</italic></th><th>Significance (<italic>p</italic> value)</th></tr></thead><tbody valign="top"><tr><td>Lexical density</td><td>62.63%</td><td>62.01%</td><td align="char" char=".">0.00</td><td align="char" char=".">.626</td></tr><tr><td>SD</td><td>3.6</td><td>4.4</td><td /><td /></tr><tr><td>Lexical diversity</td><td>45.90%</td><td>45.19%</td><td align="char" char=".">0.00</td><td align="char" char=".">.465</td></tr><tr><td>SD</td><td>4.8</td><td>9.2</td><td /><td /></tr></tbody></table> </ephtml> </p> <p>Descriptive statistics for lexical complexity are reported in Table 2 and revealed similar values between the proficiency groups for both lexical density and lexical diversity. Differences in measures were minimal between both proficiency levels; nonetheless, in both cases, the participants rated at the intermediate‐high level produced texts with slightly greater lexical complexity values, suggesting participants at this level used a greater ratio of content words, as well as a greater variety of word types. The small differences between groups did not reach statistical significance for either lexical density, <emph>t</emph>(<reflink idref="bib20" id="ref133">20</reflink>) = 0.237, <emph>p</emph> = .626, or lexical diversity, <emph>t</emph>(<reflink idref="bib20" id="ref134">20</reflink>) = 0.53, <emph>p</emph> = .465.</p> <hd id="AN0186745410-18">Research question 2: Syntactic complexity</hd> <p>3 Table Group averages for syntactic measures.</p> <p> <ephtml> <table><thead valign="bottom"><tr valign="bottom"><th>Measure</th><th align="left">intermediate‐high</th><th align="left">advanced‐low</th><th>Cohen's <italic>d</italic></th><th>Significance (<italic>p</italic> value)</th></tr></thead><tbody valign="top"><tr><td>MLTU</td><td>11.94</td><td>11.98</td><td align="char" char=".">−0.01</td><td align="char" char=".">.808</td></tr><tr><td>SD</td><td>2.2</td><td>3.1</td><td /><td /></tr><tr><td>C/TU</td><td>1.73</td><td>1.77</td><td align="char" char=".">−0.11</td><td align="char" char=".">.892</td></tr><tr><td>SD</td><td>0.3</td><td>0.4</td><td /><td /></tr><tr><td>LEFTU</td><td>9.27</td><td>9.61</td><td align="char" char=".">−0.12</td><td align="char" char=".">.705</td></tr><tr><td>SD</td><td>2.8</td><td>2.8</td><td /><td /></tr></tbody></table> </ephtml> </p> <p>Like measures of lexical complexity, texts produced by participants at both proficiency levels had similar levels of syntactic complexity as measured by MLTU, C/TU, and EFTU. Calculations for the three measures of syntactic complexity are displayed in Table 3. Unlike the slightly higher rates of lexical measures for participants whose proficiency was rated at the intermediate‐high level, participants at the advanced‐low level produced texts with greater syntactic complexity values. Texts evaluated at the advanced‐low level had, on average, longer T‐units, a greater number of clauses per T‐unit, and longer T‐units free of errors, as reported in Table 3. Despite these observed differences, the inferential statistics revealed that there were no statistically significant differences for any of the syntactic complexity measures according to proficiency level: MLTU, <emph>t</emph>(<reflink idref="bib20" id="ref135">20</reflink>) = 0.059, <emph>p</emph> = .808; C/TU, <emph>t</emph>(<reflink idref="bib20" id="ref136">20</reflink>) = 0.018, <emph>p</emph> = .705; LEFTU, <emph>t</emph>(<reflink idref="bib20" id="ref137">20</reflink>) = 0.144, <emph>p</emph> = .705.</p> <hd id="AN0186745410-19">Research question 3: Accuracy</hd> <p>4 Table Group averages for accuracy measures. a</p> <p> <ephtml> <table><thead valign="bottom"><tr valign="bottom"><th>Measure</th><th align="left">intermediate‐high</th><th align="left">advanced‐low</th><th>Cohen's <italic>d</italic></th><th>Significance (<italic>p</italic> value)</th></tr></thead><tbody valign="top"><tr><td>E/100</td><td>9.45</td><td>5.44</td><td align="char" char=".">1.11</td><td align="char" char=".">.002*</td></tr><tr><td>SD</td><td>4.0</td><td>3.2</td><td /><td /></tr><tr><td>EFTU</td><td>37%</td><td>53%</td><td align="char" char=".">−0.01</td><td align="char" char=".">.017</td></tr><tr><td>SD</td><td>19.2</td><td>16.9</td><td /><td /></tr></tbody></table> </ephtml> </p> <p>1 a There were two fewer writing samples for the measure E/100 as two advanced‐low writing samples did not meet the length of 100 words. These two writing samples were omitted from the calculation of this measure. The (*) symbol represents a statistically significant value.</p> <p>The two participant groups showed greater differences with respect to accuracy; averages for E/100 and EFTU are displayed in Table 4 according to proficiency level. Participants whose proficiency was categorized as intermediate‐high averaged more than nine errors in the first 100 words, and learners whose writing was determined to be at the advanced‐low level averaged fewer than six errors. The difference in EFTU was also notable in that those at the advanced‐low level wrote a greater rate of T‐units that were error‐free compared to those at the intermediate‐high proficiency level, 53% and 37%. Observed differences reached statistical significance only for E/100, <emph>t</emph>(<reflink idref="bib38" id="ref138">38</reflink>) = 9.86, <emph>p</emph> = .002. EFTU was found to be insignificant according to proficiency level: <emph>t</emph>(<reflink idref="bib20" id="ref139">20</reflink>) = 5.58, <emph>p</emph> = .017.</p> <hd id="AN0186745410-20">DISCUSSION</hd> <p>The goal of this project was to determine whether measures of complexity and accuracy differ between written texts of L2 Spanish at proficiency levels estimated to be at ACTFL Intermediate‐High and Advanced‐Low as interpreted by the LASER. Based on previous findings, it was anticipated that complexity and accuracy would be indicative of proficiency level and that L2 learners of Spanish at advanced‐low proficiency would demonstrate more accurate and more complex writing compared to their intermediate‐high peers. Results indicated that measures of lexical and syntactic complexity did not distinguish between writing at the two proficiency levels. In other words, L2 learners who were more advanced did not write more intricately or utilize more sophisticated or elaborate language compared to those at the intermediate level. Accuracy measures, however, suggest a different trend. Specifically, fewer errors per the first 100 words indicated writing reflective of advanced‐low proficiency, whereas a greater ratio of error‐free T‐unit (EFTU) trended toward significance and may be associated with writing reflective of the advanced level. Table 5 summarizes the significance of the relationship between each CAF measure and proficiency group. In summary, differences in accuracy appear to differentiate writing at these two levels of proficiency.</p> <p>5 Table Summary of results.</p> <p> <ephtml> <table><thead valign="bottom"><tr valign="bottom"><th /><th>LexDens</th><th>LexDiv</th><th>MLTU</th><th>C/TU</th><th>LEFTU</th><th>E/100</th><th>EFTU</th></tr></thead><tbody valign="top"><tr><td>Proficiency level</td><td>n.s.</td><td>n.s.</td><td>n.s.</td><td>n.s.</td><td>n.s.</td><td>+*</td><td>+app</td></tr></tbody></table> </ephtml> </p> <p>2 <emph>Note</emph>: +: positive relationship; *: statistically significant, n.s.: no significant relationship, app: approaching significance.</p> <p>An important finding from this project is that the two accuracy measures were either significant or trended toward significance, whereas measures of complexity were conclusively insignificant. This takeaway supports the concept of trade‐offs (Skehan, [<reflink idref="bib56" id="ref140">56</reflink>]) and corroborates findings from studies that have established linguistic correlates of accuracy according to L2 proficiency (see Long et al., [<reflink idref="bib36" id="ref141">36</reflink>]). The data also suggest that learners may be reaching a plateau in their L2 Spanish writing acquisition with respect to complexity (see Restrepo‐Ramos, [<reflink idref="bib51" id="ref142">51</reflink>]; Schnur & Rubio, [<reflink idref="bib54" id="ref143">54</reflink>]). The present discussion thus considers these explanations for the relationship between complexity and accuracy measures and proficiency in the current study.</p> <p>EFTU has been identified as a reliable measure in previous studies examining the production of L2 learners (Polio & Shea, [<reflink idref="bib49" id="ref144">49</reflink>]), including across different tasks (Way et al., [<reflink idref="bib58" id="ref145">58</reflink>]; Wigglesworth & Storch, [<reflink idref="bib59" id="ref146">59</reflink>]) and measuring L2 language development (Larsen‐Freeman & Strom, [<reflink idref="bib34" id="ref147">34</reflink>]; Sánchez Abchi & De Mier, [<reflink idref="bib53" id="ref148">53</reflink>]), and additional literature has established the number of errors as more sensitive to differences among learners (Mehnert, 1988). The contrast between existing literature and the results in the present study, specifically around EFTU and other measures of accuracy, may differ among studies due to the definitions of "error‐free" employed by the researcher. The present study identified and included morphological, syntactic, and lexical errors, not taking into account orthographic and punctuation errors. In comparison, Larsen‐Freeman and Strom ([<reflink idref="bib34" id="ref149">34</reflink>]) included morphological, syntactic, orthographic, and punctuation errors in their analysis. If the present study had adopted Larsen‐Freeman and Strom's concept of errors, a greater number of errors would have been observed with the inclusion of orthographic and punctuation errors, affecting the ratio of EFTU. Hence, the type of errors the researcher includes to classify a T‐unit as error‐free will inevitably affect the results of the study. In the case of complexity, the T‐unit is a standardized measure, whereas errors leave greater room for ambiguity.</p> <p>Results signal a stronger relationship between proficiency level and error‐based measures of accuracy than measures of lexical and syntactic complexity. The question then arises as to why L2 differences in writing proficiency are more strongly associated with accuracy than complexity. Skehan ([<reflink idref="bib56" id="ref150">56</reflink>]) and Wolfe‐Quintero et al. ([<reflink idref="bib62" id="ref151">62</reflink>]), among others, highlight the trade‐offs that occur between accuracy and complexity. In this relationship, the trade‐offs between the two prevent a co‐linear relationship, entailing that development is unlikely to occur at the same rate. In other words, participants may be at a stage in their proficiency development in which they are using their cognitive resources to produce more accurate discourse than discourse that is complex, elaborate, or sophisticated. Moreover, this may also occur for measures of complexity, as observed by Bulté and Housen ([<reflink idref="bib10" id="ref152">10</reflink>]), who found that lexical complexity and syntactic complexity do not develop in parallel; changes in syntactic complexity were detected in L2 English writing,[<reflink idref="bib5" id="ref153">5</reflink>] whereas lexical complexity remained unchanging. Therefore, in the context of the present study, it is possible that changes in error rate are occurring as learners advance to the subsequent proficiency level, whereas features of complexity are unchanging, or developing at an undetectable rate. Although data may point to trade‐offs as an explanation for the relationship between accuracy and proficiency at the writing proficiency levels of the learners, causation cannot be determined based on the design and analysis of this project. Therefore, while it is possible that learners are focused more on accuracy than complexity at these levels, it is also feasible that learners are more cognizant of committing errors if they are producing writing for the purpose of course placement, as seen with the LASER, or that learners are arriving at a plateau with respect to employing certain complexity measures in their L2 writing.</p> <p>Before plateauing at a higher proficiency level, the lack of significant differences in complexity measures between the intermediate‐high and advanced‐low levels may be due to a faster rate of growth at lower proficiency levels. This was observed by Schnur and Rubio ([<reflink idref="bib54" id="ref154">54</reflink>]) in that greater growth in lexical density occurred at lower levels, specifically from the Novice to Intermediate level. As proficiency level increases, L2 learners may be capable of arriving to the next proficiency level in some aspects but cannot maintain production at the subsequent level, indicating that L2 learners may demonstrate characteristics of both their assigned proficiency level and the one that ensues. Long et al. ([<reflink idref="bib36" id="ref155">36</reflink>]) observed gradual differences across proficiency levels, determining that it is not the linguistic structures that are unique to each level but the relative frequency of their use. For example, Restrepo‐Ramos ([<reflink idref="bib51" id="ref156">51</reflink>]) stated that learners at beginner levels of proficiency seemed to produce different rates of production for syntactic measures compared to their intermediate peers. These findings, paired with the data from the present study, support the notion that differences in lexical and syntactic complexity across contiguous proficiency levels may be more likely observed in lower levels of L2 Spanish writing. Therefore, if higher proficiency is associated with greater accuracy, it would be expected that L2 learners of Spanish who have reached an advanced level in their writing commit less errors on average, suggesting a greater focus on accuracy over complexity in moving learners toward advancedness and indicating that complexity may level off as proficiency level increases (see Byrnes et al., [<reflink idref="bib12" id="ref157">12</reflink>]; Norris & Ortega, [<reflink idref="bib43" id="ref158">43</reflink>]).</p> <hd id="AN0186745410-21">Pedagogical implications</hd> <p>The findings from this study offer pedagogical implications for the L2 classroom, particularly with respect to accuracy. Thus, if advancing L2 writing from the intermediate to advanced level is one of the proficiency objectives of the learner, educator, or program, a greater focus on accuracy versus complexity would be expected based on the significance of E/100. Recommendations from existing literature on accuracy in L2 writing include carefully evaluating rubrics used to analyze learners' written discourse (see Barrot & Agdeppa, [<reflink idref="bib7" id="ref159">7</reflink>]). For example, asking questions such as <emph>How is the student being assessed? How does the student know that they are being assessed?</emph> and <emph>What do they understand about how the instructor is going to assess them?</emph> may inform the creation of such rubrics. In this context, while developing rubrics and grading criteria, it is important to consider that errors might be more salient to language instructors and evaluators in L2 writing than aspects of complexity (Polio & Shea, [<reflink idref="bib49" id="ref160">49</reflink>]). Hence, viewing changes in linguistic features, in this case, error type, as progress reflects an asset‐based perspective. In other words, if a learner initially exhibits consistent morphological errors in their writing but eventually shifts to producing a notable number of syntactic errors with minimal morphological errors later in the semester or in a subsequent course, this shift should not be interpreted as a lack of development. Instead, persistent errors may shift in <emph>type</emph>, suggesting that the learner could be improving in one area, such as verb conjugation (accuracy), while attempting to write more elaborately (complexity). To complement this outlook, it is fundamental to recognize that accuracy alone is not a comprehensive representation of a language learner's abilities, and instructors must look beyond the frequency and error type when considering L2 proficiency development.</p> <p>Despite the lack of significant findings with respect to complexity, there are implications to advancing L2 writing in this context. Writing for different genres (Schnur & Rubio, [<reflink idref="bib54" id="ref161">54</reflink>]), audiences, and registers (Yu, [<reflink idref="bib63" id="ref162">63</reflink>]), specifically by employing embedded clauses in academic texts (Colombi, [<reflink idref="bib13" id="ref163">13</reflink>]), are means of developing lexical complexity in L2 writing. On the other hand, writing more public discourse versus personal texts, which may involve discipline‐specific topics and audiences (Menke & Strawbridge, [<reflink idref="bib42" id="ref164">42</reflink>]), are strategies shown to advance syntactic complexity in L2 written discourse, whereas developing length of production may be indicative of a higher proficiency level (Barrot & Agdeppa, [<reflink idref="bib7" id="ref165">7</reflink>]). One example that unites lexical and syntactic mechanisms is that of grammatical metaphor, which has been established as a linguistic feature of advanced L2 writing (e.g., Ryshina‐Pankova, [<reflink idref="bib52" id="ref166">52</reflink>]). This phenomenon, which has been described in detail using systemic functional linguistics (e.g., Halliday & Matthiessen, [<reflink idref="bib24" id="ref167">24</reflink>]; Ravelli, [<reflink idref="bib50" id="ref168">50</reflink>]), entails utilizing an adjective or a verb as a noun (e.g., <emph>immigrate</emph> becomes <emph>immigration</emph>). Based on the findings of the present study, such strategies may be more advantageous at other levels of proficiency (see Byrnes, [<reflink idref="bib11" id="ref169">11</reflink>]; Ryshina‐Pankova, [<reflink idref="bib52" id="ref170">52</reflink>]).</p> <hd id="AN0186745410-22">Limitations and future directions</hd> <p>Although E/100 emerged as the sole significant variable in this study, it is insufficient in determining advancedness in the greater context of assessing L2 writing. Despite the lack of significant findings, the absence of change in a measure does not equate invalidity (Pallotti, [<reflink idref="bib47" id="ref171">47</reflink>]). Concurrently, the presence of empirical evidence alone does not guarantee the overall validity of an assessment (Wisniewski, [<reflink idref="bib61" id="ref172">61</reflink>]). Instead, a broader body of research is required to evaluate the reliability of CAF measures across a span of proficiency levels and a variety of languages. Additionally, it is plausible that the effectiveness of the indices used to distinguish proficiency levels may vary depending on the levels being evaluated, as noted by Menke and Strawbridge ([<reflink idref="bib42" id="ref173">42</reflink>]), and whether the focus is on performance or development. Lastly, provided that the LASER derives estimated writing proficiency ratings from responses to two prompts, it is essential to acknowledge the potential discrepancies with proficiency ratings generated from official ACTFL tests, which are based on more extensive language samples.</p> <p>Future studies should consider additional accuracy measures (e.g., error‐free clauses, type, and frequency of error type) to better characterize the trade‐offs that occur between complexity and accuracy at the intermediate and advanced proficiency levels. Controlling for time would additionally permit the exploration of fluency measures, such as words per minute. With respect to the participants, it is worth mentioning that the majority were individuals returning from missions overseas, which lasted between 18 and 24 months. This project did not explore individual differences across participants; hence, it would be worthwhile to collect data on participants' language use and exposure while serving their missions in Spanish‐speaking countries to determine whether this plays a role in the measures of complexity and accuracy employed in the study. Furthermore, the analysis of genre, formality, and register would be valuable, as these factors have been shown to play a significant role in the use and development of measures of complexity (e.g., Colombi, [<reflink idref="bib13" id="ref174">13</reflink>]; Restrepo‐Ramos, [<reflink idref="bib51" id="ref175">51</reflink>]; Schnur & Rubio, [<reflink idref="bib54" id="ref176">54</reflink>]; Yu, [<reflink idref="bib63" id="ref177">63</reflink>]). The use of fine‐grained measures, such as phrasal complexity, would contribute to a more comprehensive analysis as well, especially provided that fine‐grained indices are found to be reliable predictors of writing quality scores (Kyle & Crossley, [<reflink idref="bib31" id="ref178">31</reflink>]).</p> <hd id="AN0186745410-23">CONCLUSION</hd> <p>The purpose of conducting CAF analysis in L2 production is to contribute quantitative and objective measures that may serve as linguistic correlates in distinguishing learners of different proficiency levels, therefore increasing the validity of large‐scale assessments and assisting in defining the advanced L2 learner. Findings from this study revealed that measures of lexical and syntactic complexity did not differ across written texts by L2 learners of Spanish at proficiency levels estimated to be at ACTFL Intermediate‐High and Advanced‐Low as interpreted by the LASER. This also applied for EFTU, a measure of accuracy. However, E/100 was found to be significant according to the proficiency level of the writer, suggesting that it may serve as a quantitative and objective measure in distinguishing the writing of L2 learners of Spanish at intermediate and advanced proficiency levels. Employing CAF analysis serves as a step in the direction of developing objective methods of evaluation, as well as reveals that learners with intermediate writing proficiency may be unable to sustain advanced functions; in this case, sufficient accuracy.</p> <p>In conclusion, further extensive research utilizing CAF analysis is necessary to establish linguistic correlates that can serve as identifiers across proficiency levels, which will have significant implications for objectively defining the advanced L2 learner. The underlying motivation for studies that employ CAF analysis is to provide empirical evidence that can effectively distinguish learners of various proficiency levels. As stated by Wisniewski ([<reflink idref="bib61" id="ref179">61</reflink>]), a more comprehensive validation approach that is based on empirical validity versus relying on human evaluations is required in the evaluation of L2 proficiency. This is not exclusive to the Advanced‐Low level, working or professional Spanish, or L2 writing, but is necessary across various proficiency scales for all languages in both written and spoken discourse (2018).</p> <hd id="AN0186745410-24">ACKNOWLEDGMENTS</hd> <p>The author would like to thank the Center for Language Studies at Brigham Young University, as well as Dr. Troy L. Cox and Dr. Matthew P. Wilcox for the sharing of second language Spanish data from the Language Ability Self‐Evaluation Resource (LASER). The author would also like to thank Dr. Vivian H. Franco Díaz for playing a key role in coding, as well as Dr. Mandy R. Menke and the three anonymous reviewers for their generous input on this manuscript.</p> <hd id="AN0186745410-25">A APPENDIX</hd> <p>See Table A1</p> <p>A1 Table Participant specifics.</p> <p> <ephtml> <table><thead valign="bottom"><tr valign="bottom"><th>Participant</th><th>Gender</th><th align="left">Age</th><th>Estimated ACTFL WPT score</th></tr></thead><tbody valign="top"><tr><td>P1</td><td>M</td><td>22</td><td>IH</td></tr><tr><td>P2</td><td>F</td><td>22</td><td>IH</td></tr><tr><td>P3</td><td>M</td><td>23</td><td>IH</td></tr><tr><td>P4</td><td>F</td><td>23</td><td>IH</td></tr><tr><td>P5</td><td>M</td><td>24</td><td>IH</td></tr><tr><td>P6</td><td>M</td><td>21</td><td>IH</td></tr><tr><td>P7</td><td>F</td><td>20</td><td>IH</td></tr><tr><td>P8</td><td>F</td><td>22</td><td>IH</td></tr><tr><td>P9</td><td>F</td><td>22</td><td>IH</td></tr><tr><td>P10</td><td>M</td><td>23</td><td>IH</td></tr><tr><td>P11</td><td>F</td><td>24</td><td>IH</td></tr><tr><td>P12</td><td>F</td><td>22</td><td>IH</td></tr><tr><td>P13</td><td>M</td><td>23</td><td>IH</td></tr><tr><td>P14</td><td>M</td><td>28</td><td>IH</td></tr><tr><td>P15</td><td>F</td><td>21</td><td>IH</td></tr><tr><td>P16</td><td>M</td><td>22</td><td>IH</td></tr><tr><td>P17</td><td>M</td><td>23</td><td>IH</td></tr><tr><td>P18</td><td>F</td><td>25</td><td>IH</td></tr><tr><td>P19</td><td>F</td><td>22</td><td>IH</td></tr><tr><td>P20</td><td>M</td><td>22</td><td>IH</td></tr><tr><td>P21</td><td>F</td><td>22</td><td>AL</td></tr><tr><td>P22</td><td>M</td><td>22</td><td>AL</td></tr><tr><td>P23</td><td>M</td><td>23</td><td>AL</td></tr><tr><td>P24</td><td>M</td><td>23</td><td>AL</td></tr><tr><td>P25</td><td>M</td><td>22</td><td>AL</td></tr><tr><td>P26</td><td>M</td><td>22</td><td>AL</td></tr><tr><td>P27</td><td>F</td><td>23</td><td>AL</td></tr><tr><td>P28</td><td>M</td><td>22</td><td>AL</td></tr><tr><td>P29</td><td>M</td><td>23</td><td>AL</td></tr><tr><td>P30</td><td>M</td><td>23</td><td>AL</td></tr><tr><td>P31</td><td>M</td><td>21</td><td>AL</td></tr><tr><td>P32</td><td>M</td><td>22</td><td>AL</td></tr><tr><td>P33</td><td>F</td><td>22</td><td>AL</td></tr><tr><td>P34</td><td>F</td><td>25</td><td>AL</td></tr><tr><td>P35</td><td>F</td><td>23</td><td>AL</td></tr><tr><td>P36</td><td>F</td><td>22</td><td>AL</td></tr><tr><td>P37</td><td>F</td><td>22</td><td>AL</td></tr><tr><td>P38</td><td>F</td><td>22</td><td>AL</td></tr><tr><td>P39</td><td>F</td><td>23</td><td>AL</td></tr><tr><td>P40</td><td>F</td><td>23</td><td>AL</td></tr></tbody></table> </ephtml> </p> <p>GRAPH: SUPPLEMENTARY INFORMATION.</p> <ref id="AN0186745410-26"> <title> Footnotes </title> <blist> <bibl id="bib1" idref="ref1" type="bt">1</bibl> <bibtext> When <emph>advanced</emph> is used with a lowercase "a," it refers to general contexts, whereas <emph>Advanced</emph> with a capital "A" is in reference to the ACTFL proficiency level.</bibtext> </blist> <blist> <bibl id="bib2" idref="ref2" type="bt">2</bibl> <bibtext> The use of lowercase letters to describe proficiency levels (e.g., intermediate‐high and advanced‐low) is to distinguish the LASER scores from official ACTFL ratings (e.g., Intermediate‐High and Advanced‐Low).</bibtext> </blist> <blist> <bibl id="bib3" idref="ref114" type="bt">3</bibl> <bibtext> For example, the conjugation of the verb <emph>tener</emph> in the fragment <emph>el tiempo que tenía</emph> may reference a variety of individuals (e.g., first person, second person formal, third person) without specific context.</bibtext> </blist> <blist> <bibl id="bib4" idref="ref3" type="bt">4</bibl> <bibtext> The term "error" is recognized as polemic due to (1) the debate around what constitutes an error, as illustrated in the variation across definitions from Larsen‐Freeman and Strom ([34]), Scott and Tucker ([55]), and Bardovi‐Harlig and Bofman ([6]), and (2) the social and linguistic implications of the construct (see Mendez Seijas & Spino, [40]).</bibtext> </blist> <blist> <bibl id="bib5" idref="ref18" type="bt">5</bibl> <bibtext> The participants in Bulté and Housen's ([10]) study included L2 English learners randomly selected from a corpus (Connor‐Linton & Polio, [14]) consisting of four different classes, not to be synonymous with proficiency level.</bibtext> </blist> </ref> <ref id="AN0186745410-27"> <title> REFERENCES </title> <blist> <bibtext> ACTFL. 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  Label: Title
  Group: Ti
  Data: Are My Learners Advanced?: Using Measures of Complexity and Accuracy to Analyze L2 Spanish Writing
– Name: Language
  Label: Language
  Group: Lang
  Data: English
– Name: Author
  Label: Authors
  Group: Au
  Data: <searchLink fieldCode="AR" term="%22Marie+Mangold%22">Marie Mangold</searchLink>
– Name: TitleSource
  Label: Source
  Group: Src
  Data: <searchLink fieldCode="SO" term="%22Foreign+Language+Annals%22"><i>Foreign Language Annals</i></searchLink>. 2025 58(2):326-345.
– Name: Avail
  Label: Availability
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  Data: Wiley. Available from: John Wiley & Sons, Inc. 111 River Street, Hoboken, NJ 07030. Tel: 800-835-6770; e-mail: cs-journals@wiley.com; Web site: https://www.wiley.com/en-us
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  Label: Peer Reviewed
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  Data: Y
– Name: Pages
  Label: Page Count
  Group: Src
  Data: 20
– Name: DatePubCY
  Label: Publication Date
  Group: Date
  Data: 2025
– Name: TypeDocument
  Label: Document Type
  Group: TypDoc
  Data: Journal Articles<br />Reports - Research
– Name: Subject
  Label: Descriptors
  Group: Su
  Data: <searchLink fieldCode="DE" term="%22Spanish%22">Spanish</searchLink><br /><searchLink fieldCode="DE" term="%22Second+Language+Instruction%22">Second Language Instruction</searchLink><br /><searchLink fieldCode="DE" term="%22Second+Language+Learning%22">Second Language Learning</searchLink><br /><searchLink fieldCode="DE" term="%22Language+Proficiency%22">Language Proficiency</searchLink><br /><searchLink fieldCode="DE" term="%22Self+Evaluation+%28Individuals%29%22">Self Evaluation (Individuals)</searchLink><br /><searchLink fieldCode="DE" term="%22Accuracy%22">Accuracy</searchLink><br /><searchLink fieldCode="DE" term="%22Teaching+Methods%22">Teaching Methods</searchLink><br /><searchLink fieldCode="DE" term="%22Writing+Processes%22">Writing Processes</searchLink><br /><searchLink fieldCode="DE" term="%22Rating+Scales%22">Rating Scales</searchLink><br /><searchLink fieldCode="DE" term="%22Guidelines%22">Guidelines</searchLink><br /><searchLink fieldCode="DE" term="%22Correlation%22">Correlation</searchLink><br /><searchLink fieldCode="DE" term="%22Syntax%22">Syntax</searchLink><br /><searchLink fieldCode="DE" term="%22Criticism%22">Criticism</searchLink><br /><searchLink fieldCode="DE" term="%22Writing+Skills%22">Writing Skills</searchLink><br /><searchLink fieldCode="DE" term="%22Phrase+Structure%22">Phrase Structure</searchLink><br /><searchLink fieldCode="DE" term="%22Error+Patterns%22">Error Patterns</searchLink><br /><searchLink fieldCode="DE" term="%22Advanced+Students%22">Advanced Students</searchLink>
– Name: DOI
  Label: DOI
  Group: ID
  Data: 10.1111/flan.12788
– Name: ISSN
  Label: ISSN
  Group: ISSN
  Data: 0015-718X<br />1944-9720
– Name: Abstract
  Label: Abstract
  Group: Ab
  Data: One of the critiques of proficiency as defined by scales, such as that of ACTFL, is its lack of grounding in linguistic realities. Measures of complexity, accuracy, and fluency provide a route in which proficiency can be quantitatively measured by identifying linguistic correlates (see Brown et al., 2017; Long et al., 2012). This project aimed to identify the linguistic correlates that distinguish L2 Spanish writing at intermediate-high and advanced-low proficiency levels as defined by the Language Ability Self-Evaluation Resource. Forty writing samples comprised the data. Measures of lexical complexity (density and diversity), syntactic complexity (mean length of T-unit, number of clauses per T-unit, average length of error-free T-unit), and accuracy (ratio of error-free T-unit, number of errors per 100 words) were used to analyze the samples. Findings suggest that accuracy is the linguistic feature that best distinguishes intermediate from advanced proficiency in L2 Spanish writing. The implications of these findings for research and pedagogy are examined.
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  Data: 2025
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  Data: EJ1477333
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      – Type: doi
        Value: 10.1111/flan.12788
    Languages:
      – Text: English
    PhysicalDescription:
      Pagination:
        PageCount: 20
        StartPage: 326
    Subjects:
      – SubjectFull: Spanish
        Type: general
      – SubjectFull: Second Language Instruction
        Type: general
      – SubjectFull: Second Language Learning
        Type: general
      – SubjectFull: Language Proficiency
        Type: general
      – SubjectFull: Self Evaluation (Individuals)
        Type: general
      – SubjectFull: Accuracy
        Type: general
      – SubjectFull: Teaching Methods
        Type: general
      – SubjectFull: Writing Processes
        Type: general
      – SubjectFull: Rating Scales
        Type: general
      – SubjectFull: Guidelines
        Type: general
      – SubjectFull: Correlation
        Type: general
      – SubjectFull: Syntax
        Type: general
      – SubjectFull: Criticism
        Type: general
      – SubjectFull: Writing Skills
        Type: general
      – SubjectFull: Phrase Structure
        Type: general
      – SubjectFull: Error Patterns
        Type: general
      – SubjectFull: Advanced Students
        Type: general
    Titles:
      – TitleFull: Are My Learners Advanced?: Using Measures of Complexity and Accuracy to Analyze L2 Spanish Writing
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            NameFull: Marie Mangold
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              M: 07
              Type: published
              Y: 2025
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              Value: 1944-9720
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              Value: 58
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            – TitleFull: Foreign Language Annals
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