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Chapter 7. Vocabulary acquisition and the learning curve
... Para representar este proceso se utiliza una herramienta denominada curva de aprendizaje. Las curvas de aprendizaje "permiten realizar un acercamiento a la manera como el aprendizaje ocurre" [34], además de una mejor comprensión del orden en el que los conceptos son asimilados. Esta herramienta posibilita realizar esto no solo en el campo del aprendizaje de lenguas, sino en cualquier ámbito del aprendizaje en general. ...
... En cierto momento, autores como Daller, Turlik y Weir [34] y, más recientemente, otros como Mukanova, Berg, Kit, Berg, y Medvedev [37] han realizado trabajos en los que intentaron representar el proceso del aprendizaje de lenguas en una curva de aprendizaje. Es necesario aclarar, en este punto, que no existe un método único para crear las curvas de aprendizaje y "no hay un acuerdo general sobre cómo estas curvas deben ser modeladas" [34]. ...
... En cierto momento, autores como Daller, Turlik y Weir [34] y, más recientemente, otros como Mukanova, Berg, Kit, Berg, y Medvedev [37] han realizado trabajos en los que intentaron representar el proceso del aprendizaje de lenguas en una curva de aprendizaje. Es necesario aclarar, en este punto, que no existe un método único para crear las curvas de aprendizaje y "no hay un acuerdo general sobre cómo estas curvas deben ser modeladas" [34]. ...
A medida que la tecnología se difunde en los contextos educativos, es posible mejorar los procesos de enseñanza y aprendizaje. Gracias a la Inteligencia Artificial, el Aprendizaje de Máquinas y en concreto al Procesamiento del Lenguaje Natural (PNL, o NLP en inglés), una serie de posibilidades permiten a las personas mejorar su proceso de aprendizaje de idiomas, que el Marco Común Europeo de Referencia (MCER) parametriza en favor de actividades orientadas a la acción en las que los usuarios del lenguaje realizan tareas comunicativas. Por lo tanto, en este artículo intentaremos analizar si el desarrollo de una aplicación que implemente algunas características de la PNL y específicamente el Reconocimiento de Voz puede presentar ciertas relaciones entre el Procesamiento del Lenguaje Natural y la adquisición de una lengua extranjera en el marco del Aprendizaje Basado en Tareas (TBL). . Esta posibilidad fomentaría el proceso de input y mejoraría la curva de aprendizaje de idiomas en este enfoque a través de una técnica de expresión lingüística orientada a eventos enmarcada en una actividad lingüística específica: la narración de un partido de fútbol en una lengua extranjera. Esta aplicación podría representar una base para una metodología de desarrollo de software que permita desarrollar juegos serios compatibles con el enfoque de enseñanza de idiomas TBL, que podría beneficiarse enormemente de la PNL.
... Thus, establishing the correct set of basic words that learners already know is important to be able to measure subsequent development in productive vocabulary knowledge. In order to accurately track the acquisition of new vocabulary over time, researchers have focused on quantitative measures that can be used to examine different aspects of the 'lexical richness' of learner output, including lexical diversity, which uses text internal measures such as VocD (D) and MTLD (e.g., [17,21]); lexical sophistication, which makes reference to frequencies in corpora with measures like the Advanced Guiraud (AG) (e.g., [10,28]); and lexical depth, which measures knowledge of usage (e.g., [6,11]). In this paper, we focus on lexical sophistication because (1) the calculation of AG depends on the establishment of the correct set of high-frequency words that the learners may (already) know; (2) the frequency bands of 3000-9000 words are lexical items that researchers advocate should be the focus of instruction [25]; and (3) teacher perceptions of lexical proficiency have been shown to correlate strongly with lexical sophistication [10]. ...
... The literature on vocabulary development has shown that Advanced Guiraud (AG) can be an effective method of measuring of lexical sophistication [12,19], but may not always reflect development [11]. In essence, AG is a form of Type/Token ratio (TTR) [28] with two key differences. ...
... They found that Guiraud (all types/√tokens) and AG were both effective at distinguishing the China group from the UK group, whose mean (stdev) AG scores were 0.72 (.2) and 0.94 (.29) respectively. However, when Daller et al. [11] investigated the longitudinal development of 42 Arabic-speaking ESL learners, the values of AG were low and increased minimally, ranging from an average of about 0.20 to 0.25 [11]. In neither study was the composition of the AG list of 2000 basic types specified, referred to only as 'the 2000 frequency band.' Considering, as [16] says, that the needs of the users should be accounted for when replicating a word list, knowing such information would be of great use to researchers seeking to evaluate and replicate previous results. ...
One commonly used measure of lexical sophistication is the Advanced Guiraud (AG; [9]), whose formula requires frequency band counts (e.g., COCA; [13]). However, the accuracy of this measure is affected by the particular 2000-word frequency list selected as the basis for its calculations [27]. For example, possible issues arise when frequency lists that are based solely on native speaker corpora are used as a target for second language (L2) learners (e.g., [8]) because the exposure frequencies for L2 learners may vary from that of native speakers. Such L2 variation from comparable native speakers may be due to first language (L1) culture, home country teaching materials, or the text types which L2 learners commonly encounter. This paper addresses the aforementioned problem through an English as a Second Language (ESL) frequency list validation. Our validation is established on two sources: (1) the New General Service List (NGSL; [4]) which is based on the Cambridge English Corpus (CEC) and (2) written data from the 4.2 million-word Pitt English Language Institute Corpus (PELIC). Using open-source data science tools and natural language processing technologies, the paper demonstrates that more distinct measurable lexical sophistication differences across levels are discernible when learner-oriented frequency lists (as compared to general corpora frequency lists) are used as part of a lexical measure such as AG. The results from this research will be useful in teaching contexts where lexical proficiency is measured or assessed, and for materials and test developers who rely on such lists as being representative of known vocabulary at different levels of proficiency. This research applies data-driven exploration of learner corpora to vocabulary acquisition and pedagogy, thus closing a loop between educational data mining and classroom applications.
... Another less complex measure that has been used is a simple Guiraud Index, which is the number of types divided by the square root of the total number of tokens. This procedure is also said to control for text length (Daller, Turlik & Weir, 2013. In contrast to lexical diversity, lexical sophistication compares the range of words in learners' texts with word frequency lists (Bulté & Housen, 2014;Daller, Turlik & Weir, 2013). ...
... This procedure is also said to control for text length (Daller, Turlik & Weir, 2013. In contrast to lexical diversity, lexical sophistication compares the range of words in learners' texts with word frequency lists (Bulté & Housen, 2014;Daller, Turlik & Weir, 2013). These lists consist of bands of words grouped into frequencies of 1000. ...
... for analyzing corpora provides a combined list of BNC-COCA 1-25K bands. Daller, Turlik & Weir (2013) and Bulté and Housen (2014) both use lexical sophistication in their studies in addition to vocD. The measure of lexical sophistication that they used was the 'Advanced Guiraud' (AG), which is the number of types above the 2000 frequency band divided by the square root of total tokens. ...
This book is unique in bringing together studies on instructed second language acquisition that focus on a common question: “What renders this research particularly relevant to classroom applications, and what are the advantages, challenges, and potential pitfalls of the methodology adopted?” The empirical studies feature experimental, quasi-experimental and observational research in settings ranging from the classroom to the laboratory and CALL contexts. All contributors were asked to discuss issues of cost, ethics, participant availability, experimental control, teacher collaboration, and student motivation, as well as the generalizability of findings to different kinds of educational contexts, languages, and structures.
This volume should be of interest to graduate students in second language research, practicing teachers who want some guidance to navigate the sometimes overwhelming array of publications, and to researchers who are planning studies on instructed second language learning or teaching and are looking to make principled decisions on which of the existing methodologies to adopt.
... Findings of past feature-writing quality work have gone on to inform two often connected areas of research: the development of writing proficiency scales/ rubrics by referring to differences in linguistic feature use across bandscales (e.g., Hawkins & Filipovic, 2012), and/or the training of large-scale feedback and grading systems (e.g., Chen et al., 2017). Researchers have most persistently studied features of grammar (e.g., clauses (see Bulté & Housen, 2014)) and vocabulary (e.g., percentage of words appearing in the Academic Word List (Daller et al., 2013)), with features of cohesion occupying an inconsistent position of interest for researchers (e.g., see the review in ). Features of phraseology, for example lexical bundles (e.g., see Appel & Wood, 2016), occupy an increasingly prominent position, especially in second language literature (e.g., see reference made to this emerging importance in and Paquot (2018Paquot ( , 2019). ...
... The ratio was calculated by dividing the number of types by the square root of the number of tokens. We choose the RTTR due to its consistent use in the literature, for example see its continued use over time in vocabulary studies (e.g., Bulté & Housen, 2014;Daller et al., 2013;Hou et al., 2016;Kim, 2014;Llanes et al., 2018;Lorenzo & Rodríguez, 2014;Treffers-Daller et al., 2018;Verspoor et al., 2017) as well as the aforementioned phraseological studies. The measure itself is also simple to calculate and easily interpreted: the higher the value, the more diverse the text is taken to be. ...
This Element explores relationships between collocations, writing quality, and learner and contextual variables in a first-year composition (FYC) programme. Comprising three studies, the Element is anchored in understanding phraseological complexity and its sub-constructs of sophistication and diversity. First, the authors look at sophistication through association measures. They tap into how these measures may tell us different types of information about collocation via a cluster analysis. Selected measures from this clustering are used in a cumulative links model to establish relationships between these measures, measures of diversity and measures of task, the language background of the writer and individual writer variation, and writing quality scores. A third qualitative study of the statistically significant predictors helps understand how writers use collocations and why they might be favoured or downgraded by raters. This Element concludes by considering the implications of this modelling for assessment.
... Results from these studies suggest that word learning does not follow a linear process of acquisition (Daller et al., 2013;Milton, 2006Milton, , 2009 and that students' vocabulary learning rates decline gradually as word frequency decreases. In other words, lexical learning follows a "power law of learning" pattern in which vocabulary knowledge increases rapidly during the first stages of language instruction and is followed by a learning plateau once these highfrequency words have been learned and further language competence develops (Dóczi & Kormos, 2016). ...
... It is worth noting, however, that university language courses experience a substantial learning decrease in high-frequency vocabulary during the initial stages of their learning process. Indeed, T A B L E 8 Effects of high school instruction in high-frequency vocabulary knowledge among courses F I G U R E 3 Interaction between semesters of high school and words known among courses 14 vocabulary growth flattens halfway through the 2000-frequency band, which is not consistent with the results from other studies that observed lexical development flattening in latter frequency bands (Daller et al., 2013;Dóczi & Kormos, 2016;Milton, 2009;Orosz, 2009). Such differences might be due to the fact that in these studies, students were enrolled in language courses where there was a systematic approach to vocabulary teaching, whereas university language courses seem to follow a less defined criterion when it comes to vocabulary teaching. ...
The Challenge
U.S. university students enroll in 2 years of language courses before advancing to linguistics, literature, and culture courses. However, do students have the basic vocabulary needed to transition to advanced courses? This article answers this question by examining 943 L2 Spanish students' knowledge of high‐frequency words at different proficiency levels.
... There might be a reason to believe that this trade-off between depth and breadth can be optimized based on the fundamental properties of human learning (see Son & Sethi, 2006. In the domain of human memory research, it is commonly found that the relationship between practice and performance takes on the form of a power curve at the aggregate level. 1 That is, initial trials provide the greatest benefit to memory, whereas successive trials are subject to diminishing marginal returns (Daller, Turlik, & Weir, 2013). The properties of this negatively accelerated power curve mean that, on average, earlier trials in the learning sequence will be the most efficient. ...
... 1 At least this is the case with simple stimuli, such as word pairs (Daller, Turlik, & Weir, 2013). It is hypothesized that more complex (naturalistic) materials may take on the form of a logistic learning curve (Son & Sethi, 2006). ...
Learners are often constrained by their available study time, typically having to make a trade-off between depth and breadth of learning. Classic experimental paradigms in memory research treat all items as equally important, but this is unlikely the case in reality. Rather, information varies in importance , and people vary in their ability to distinguish what is more or less important. We test the impact of this trade-off in the study of Graduate Record Examination (GRE)-synonym word pairs. In our empirical Study 1, we split our stimuli set, with some items (focal) being afforded more rounds of retrieval practice than other items (non-focal). All conditions had the same total number of trials (i.e., constant study time), but differed in the number of focal words (breadth) and repetitions (depth). The conditions differed significantly in both mean performance and variance on the day-delayed test. Using this empirical data as a base, we then conducted a simulation (Study 2) modeling depth-breadth trade-offs under various conditions of learner forecasting accuracy and test coverage. In Study 2, we found that a medium-depth medium-breadth strategy was appropriate for most of the learning situations covered by our simulation, but that learners with a well-calibrated understanding of importance may benefit from a more targeted high-depth, low-breadth approach. Our results highlight the complexity of navigating the depth-breadth trade-off. Models of learning strategy optimization will need to account for learner forecasting sensitivity, which itself is likely an interaction between relatively stable individual differences and shifting contextual factors.
... Controlled production tasks tap into productive knowledge, and online perception tasks tap into receptive knowledge. However, previous research has pointed out that the development of learners' receptive knowledge and that of their productive knowledge are often unbalanced (Laufer, 1998;Daller et al., 2013). Therefore, to gain a more comprehensive view of how L2 learners' formulaic knowledge develops, both types of knowledge need to be investigated. ...
... A major reason for this is that the number of achievers is very small, especially for learners of a non-English language such as Chinese. Another reason may have to do with the general assumption of the lexical plateau (see Daller et al., 2013 for an overview). Motivated by general learning curve models, L2 researchers have found that the development of lexical knowledge follows the general learning curve with slow growth at the beginning, followed by an accelerating phase and then flattening out to a plateau. ...
The study examined the development of Chinese as a second language learners’ formulaic knowledge through comparing the processing of Chinese idioms versus non-idiomatic formulaic sequences (FSs) by advanced-level learners (ALs), super-advanced learners (SLs), and native speakers (NSs). Using two phrase acceptability judgment tasks with and without think-aloud protocols, we collected data on participants’ processing accuracy, processing speed, and processing strategies of reading the two types of FSs. Four processing patterns emerged from the analyses of the datasets. First, learners’ processing accuracy and speed increased along with their proficiency. Second, learners’ idiom processing ability was generally lower than that of non-idiom processing ability, but they demonstrated an improving trend as their proficiency level increased. Third, learners’ use of processing strategies did not change much as proficiency rose and demonstrated a categorical difference from NSs. Fourth, all three groups exhibited poorer productive idiom knowledge than productive non-idiom knowledge. The overall findings denote that second language learners’ formulaic knowledge can evolve beyond the lexical plateau as learners move from the advanced to a higher proficiency level, but the productive idiom knowledge can be a long-term problem. The findings provide implications for measuring and teaching Chinese formulaic knowledge at the higher-than-advanced stage.
... Overwhelmingly, the evidence in this area confirms the intuitive claim that more advanced texts employ a more diverse vocabulary in both first (e.g. Berman & Nir, 2010;Crossley et al., 2011;Malvern et al., 2004;Olinghouse & Wilson, 2013;Uccelli et al., 2013) and second language writing (Crossley et al., 2010;Daller et al., 2013;Guo et al., 2013;Hou et al., 2016;Treffers-Daller et al., 2018). ...
... Some have reported significant increases in the use of low-frequency words over time (Daller et al., 2013;Knoch et al., 2015;Knoch et al., 2014;Storch, 2009) or with increasing proficiency (Vidakovic & Barker, 2010). Others have reported no increase with time and/or no relationship between use of low-frequency words and text quality (Bulté & Housen, 2014;J.-Y. ...
Recently-developed tools which quickly and reliably quantify vocabulary use on a range of measures open up new possibilities for understanding the construct of vocabulary sophistication. To take this work forward, we need to understand how these different measures relate to each other and to human readers’ perceptions of texts. This study applied 356 quantitative measures of vocabulary use generated by an automated vocabulary analysis tool ( Kyle & Crossley, 2015 ) to a large corpus of assignments written for First-Year Composition courses at a university in the United States. Results suggest that the majority of measures can be reduced to a much smaller set without substantial loss of information. However, distinctions need to be retained between measures based on content vs. function words and on different measures of collocational strength. Overall, correlations with grades are reliable but weak.
... Overwhelmingly, the evidence in this area confirms the intuitive claim that more advanced texts employ a more diverse vocabulary in both first (e.g. Berman & Nir, 2010;Crossley et al., 2011;Malvern et al., 2004;Olinghouse & Wilson, 2013;Uccelli et al., 2013) and second language writing (Crossley et al., 2010;Daller et al., 2013;Guo et al., 2013;Hou et al., 2016;Treffers-Daller et al., 2018). Work on sophistication remains more open. ...
... L2 studies have been similarly inconsistent. Some have reported significant increases in the use of low-frequency words over time (Daller et al., 2013;Knoch et al., 2015;Knoch et al., 2014;Storch, 2009) or with increasing proficiency (Vidakovic & Barker, 2010). Others have reported no increase with time and/or no relationship between use of low-frequency words and text quality (Bulté & Housen, 2014;J.-Y. ...
... As Murre (2014) shows, the emphasis on power or exponential learning curves may be an artifact of cognitive psychology's focus on simple word-pair learning experiments. Rather, complex tasks, such as learning to juggle (Qiao, 2021) or learning a foreign language (Daller et al., 2013), are most likely to show an S-shaped learning curve (Son & Sethi, 2010). Even the learning of nonsense syllables can exhibit an S-shaped curve when the list length is sufficiently large, as shown by Hull et al.'s (1940) data from the learning of 205 nonsense syllables over multiple presentations (see Figs. 26 and 27 of Hull et al., 1940). ...
The computational model of school achievement represents a novel approach to theorizing school achievement, conceptualizing educational interventions as modifications to students’ learning curves. By modeling the process and products of educational achievement simultaneously, this tool addresses several unresolved questions in educational psychology through computational modeling. For example, prior research has highlighted perplexing inconsistencies in the relationship between time spent on task and academic achievement. The present simulation reveals that even under the assumption that time-on-task always positively contributes to achievement, the correlations between time-on-task and achievement can vary substantially across different contexts and, in some cases, may even be negative. Analysis of the correlation between prior knowledge and knowledge gains uncovers similar patterns. The computational model of school achievement presents a framework, bolstered through simulation, enabling researchers to formalize their assumptions, address ongoing debates, and design tailored interventions that consider both the school environment and individual student contexts.
... Other studies have presented mixed results when evaluating the usefulness of AG. Daller et al. (2013) found no significant increases in AG over time for Arabic learners whose AG increased from 0.20 to 0.25, leading to the conclusion that AG may not reflect vocabulary development. Unfortunately, the Daller et al. study did not state the frequency lists used. ...
Vocabulary lists of high-frequency lexical items are an important resource in language education and a key product of corpus research. However, no single vocabulary list will be useful for every learning context, with the appropriateness of such lists affected by the corpora on which they are based. This paper investigates the impact of corpus selection on one measure of lexical sophistication, Advanced Guiraud, focusing on two frequency lists originating from an in-house learner corpus (PELIC) and a global learner corpus (Cambridge Learner Corpus). This analysis shows that frequency lists derived from both types of learner corpus can effectively serve as the basis for measuring the development of lexical sophistication, regardless of the specific program of the learners. Therefore, publicly available learner corpus frequency lists can be a reliable resource for stakeholders interested in the lexical gains of language learners.
... This interpretation obviously relates to the broader question of language learning curves and the corresponding challenge of modeling them accurately. Daller, Turlik, and Weir (2013) have noticeably reported on a body of literature pertaining to these issues as part of their work on vocabulary acquisition. They, too, observed that the rate of improvement of their subjects is reduced as their practice continues. ...
The current study focuses on an e-learning platform called Furago designed to provide language instructors with exercises complementing activities already implemented in their classes. Its objective was to assess the impact the use of Furago could have on the listening skills of first-year Japanese university students. Statistical analyses that were used to outline the correlations between the main test variables (i.e., the grades achieved by students on two listening comprehension tests) and several predictor variables pertaining to the platform, such as the score the participants had accumulated or the consistency in which they use it, were all found to be statistically significant, albeit with correlation coefficients that were rather weaker than expected. Despite its users’ slow margin of progression, as evidenced by the linear model conducted during this study, such results confirmed the value of Furago as a means to improve students’ listening skills, especially, it would seem, at the very beginning of foreign language acquisition. Unexpectedly, these results also suggested that the users’ improvement might have more to do with the overall amount of time they put in their study (reflected here by their scores on Furago) than their consistency.
... As such, their home environment might become less relevant as they grow older, meaning that students' achievement may become more independent of their parents' migration background over time. Furthermore, language development likely takes a non-linear form (Daller, Turlik, and Weir 2014), whereby children's vocabulary grows quickly initially until it reaches a point of saturation and learning tapers off. Thus, while gaps may emerge initially, the host language gains of children without a migration background may slow down over time, allowing children with a migration background to reduce their initial disadvantage. ...
Education is key to the structural integration of immigrants and their children. While research indicates that migrant educational underachievement is a serious issue, relatively little is known about when, how and why migrant gaps develop. Hitherto, longitudinal research on skill gaps is scarce. The current paper adds to the literature by investigating how much of the migration-related disparities found during primary school can be attributed to inequalities that already existed before school life. To do so, it uses structural equation modelling and draws on a national longitudinal study of children in Ireland. Results indicate that migration-related disparities largely find their roots in the period before formal schooling, after which they remain relatively stable or even decrease. This implies that researchers and policymakers may want to focus their efforts on the period proceeding primary school.
... This seems to imply that, as learners gain more experience with the target language, they are more likely to become risk-averse with respect to using new types of collocations and prefer to rely on the ones they have already mastered. As Laufer (1998) argues, this is the point where the development and use of L2 items reach a 'plateau' beyond which there is little incentive for learners to produce high-stakes, novel, and infrequent words or word sequences (also see Daller et al., 2013). This is consistent with the findings of Siyanova-Chanturia & Spina (2019), who also found that beginner learners were more likely to experiment with unusual word combinations in their writing than more proficient learners. ...
In the past three decades, a variety of formulaic units have been identified and researched and linked to fluent and natural production of both spoken and written language. Despite these efforts, relatively few studies have thus far endeavored to investigate the longitudinal development of the productive knowledge of formulaic sequences in second language (L2) learner writing. To address this gap, the present study sought to investigate the developmental trajectory of L2 phraseological knowledge by looking at the use of verb-noun collocations in a large-scale longitudinal corpus of essays written by Chinese learners of Italian. For this purpose, we examined three key dimensions of phraseological knowledge, each assessed by a specific measure: exclusivity (Log Dice), phrasal frequency (logarithmic frequency), and phrasal diversity (RTTR). Following this, we conducted three separate Linear Mixed Effects regression analyses to verify if, and to what degree, the above-mentioned measures varied as a function of time, in combination with other related factors (e.g., proficiency level, prior language exposure) that might influence the production of word combinations in a second language. The results of our analysis showed that L2 phraseological development is a multifaceted process, in which the multiplicity of interacting elements can profoundly affect learner performance over time. Importantly, our results point to the conclusion that time is but one part of this process and that language proficiency and other individual-level learner differences can influence the overall trajectory of L2 collocation development.
... One way of measuring development is to look at lexical sophistication, which is the knowledge and use of infrequent words. Daller et al. ( 2013 ) found that production of 'advanced types', lexis beyond the 2,000 frequency level, over a two-year period showed a Loess curve (locally weighted scatterplot smoothing) line in which there is no increase at the beginning of the period, but then there is an increase in the middle and then a fl attening out towards the end (p. 206). ...
This chapter focuses on how lexis changes over time and the relationships with the learning style construct memory-analysis. The study looks at lexical development beyond the 2,000 frequency level over one semester and whether any developments are related to memory and analysis. The lexical profiles from the written compositions show most development from L2 English participants with a high analytical learning style which was tested by inferring grammatical rules from an unknown language. Implications for pedagogy are discussed in that to develop academic lexical knowledge, one way may be fostered by data-driven learning in which examples from corpora are used.
... For lexis, a measure of lexical diversity was used, as this has been identified as the component that best correlates with NS ratings of the quality of non-NS output (Lu, 2012). Guiraud's index (GI) was found most suitable because it has been found to be reliable for learner data below 1,000 words (Daller, Turlik, & Weir, 2013), and because it is more reliable, and more stable than other commonly used measures (e.g., time-token ratio and its variants). We also measured the learner's use of smallwords to investigate lexical development. ...
This article reports a longitudinal case study of two German high‐school exchange students’ 5.5‐month study abroad (SA) in New Zealand, examining their social lives and oral second language (L2) development. Six informal interviews, weekly diary entries, and monthly summaries were used to elicit data about their overseas experiences and reflections associated with them. The qualitative analysis investigated the nature of the students’ social lives at school, in their homestay, in their hobbies, and during their free time. The results demonstrated that opportunities for L2 engagement varied considerably with context—some affording and others restricting interaction. Especially the presence of co‐nationals impeded L2 interaction and required the students to seek out opportunities themselves—an effort that the students were not always willing to make. For the quantitative analysis, the interview data were coded using multiple measures of complexity, accuracy, lexis, and fluency (CALF). Compared to previous studies, the results showed that all CALF dimensions improved during SA, but just for one student and not in a linear fashion. The two learners’ L2 profiles varied considerably, demonstrating that development is dynamic and unique and that interpretations of it need to take account of the learners’ social contexts and what they make of these.
... Some words will be acquired quite early, whereas after gaining a certain level of proficiency, the growth slows down (c.f. Daller, Turlik & Weir, 2013). Contradicting Nation's (2001) Historically, there is a lot more research on L1 acquisition than on L2 acquisition (Tiefenthal, 2009, p. 107). ...
... Should this be the case, the lack of significant differences at more advanced levels may simply be a characteristic of lexical development. Daller et al. (2013), for instance, suggest that lexical development can be approximated by a power curve, initially steep, but flattening out later. In their study, such a curve especially fitted the development of diversity, human judgments and, to a lesser extent, sophistication. ...
The development of lexical complexity in second language acquisition has received a considerable amount of attention in applied linguistics research. Many studies have examined the role of lexical diversity, sophistication and density as indicators of L2 proficiency. Few studies, though, have considered the development of lexical complexity from an explicitly cross-linguistic perspective. This article reports on an explorative, cross-linguistic study on the development of lexical diversity, sophistication and density in L2 French and English at four levels of linguistic proficiency. Additionally, the study proposes a number of alternative measures tapping into collocational knowledge and lexical sophistication. The analyses were carried out on a cross-sectional, multilingual corpus of L2 French and English consisting of oral narrative data. The results show a similar development of lexical diversity in L2 French and English, but considerably different developmental tendencies in terms of sophistication and density. The concluding sections discuss possible explanations for these differences and consequences for the measurement of linguistic proficiency.
This paper tests three hypotheses about written vocabulary in child L2 English. Specifically, as children mature, (1) the mean frequency values of the nouns they use increase; (2) the mean frequencies of other parts-of-speech decrease; (3) the use of academic vocabulary increases only in certain types of writing. Using a corpus of writing by children in Norway, hypothesis 1 was confirmed up to the mid-teenage years. The mean frequency values of nouns then decreased. Analysis showed that the early increase is due to decreased repetition of low-frequency topic words. After age 15, frequencies drop as the main source of vocabulary moves from a region around the 150th most frequent lemma to one around the 550th. Hypotheses 2 and 3 were partially confirmed. Mean frequencies of non-nouns decreased in non-stories after Year 9. Non-stories became more academic across school years. Stories had much lower scores overall but also showed an increase at Year 10.
Learning curves are a well-known phenomenon in learning and describe the oscillation between correct and incorrect performance that precedes mastery. It demonstrates that making mistakes is part of the learning process. It is equally clear that these learning curves are highly individual and therefore pose a challenge in their description and direct comparison. With the ability to collect large amounts of data through learning games with adaptively generated content, it is now possible to take a novel look at this process. Literacy games were deployed in a school setting for the iRead EU Horizon 2020 Project. The Navigo app delivered a complex task of practising to distinguish vowel length in bi-syllabic words in German to pupils in the disguise of a game. Pupils' engagement with the game resulted in the largest longitudinal corpus that has ever been collected for this sort of task from 251 pupils in German elementary schools. The resulting data exhibits learning curves as trajectories, depicting response time and correctness across several weeks for each pupil’s playing sessions. The work presented here attempts to (a) model and parameterise these curves, (b) automate their classification into common forms across a larger population, and (c) detect mastery. In doing so, we propose a method of learning curve representation and interpretation and apply it to the data. A describable pattern of cognitive processing seems to be observable and common to all curves that may allow a prediction of mastery and ability for skill transfer to other environments for a subset of the players. As a result, we were able to describe five general types of common progressions. These findings are in part supported by additional data from pre- and post-tests in the form of paper-and-pencil activities. The work presented here should serve to demonstrate the importance of using large scale input data for training literacy skills rather than a few examples as is the norm in static schoolbooks.
La complejidad lingüística como fenómeno multidimensional cuantificable apenas se ha abordado en la adquisición de español como lengua extranjera (ELE), obviando, además, la afinidad lingüística como una variable clave con efectos empíricamente demostrables. El presente estudio tiene como objetivo determinar la influencia de la afinidad lingüística en el nivel de sofisticación léxica comparando la producción escrita de dos grupos de hablantes de ELE de contextos plurilingües: un grupo de 40 caboverdianos con LM (criollo caboverdiano) y L2 (portugués) afines al español, y un grupo de 40 indios con LM (telugu) y L2 (inglés) no afines al español. Metodológicamente, se emplea el Lexical Frequency Profile (LFP) de Laufer y Nation (1995), el Beyond 2000 de Laufer (1995) y el Advanced Giraud como operacionalizaciones a partir de dos listas de clasificación del vocabulario: la lista de lemas del Corpus de aprendientes de español (CAES) y la clasificación en niveles del Marco común europeo de referencia para las lenguas (MCER) a través de la herramienta CFER Checker. Los resultados muestran que la sofisticación léxica del grupo criollo es cuantitativamente superior a la del telugu independientemente de la lista y la operacionalización empleada. La prueba de Mann-Witney permite confirmar la hipótesis de influencia de la afinidad lingüística en el nivel de sofisticación mediante las operacionalizaciones realizadas a partir del MCER, siendo los resultados obtenidos a partir de la lista del CAES no significativos.
This paper reports on the findings of a 15-year-old German girl’s motivational and linguistic experiences during her one-semester study abroad (SA) in New Zealand. Chiara primarily interacted in social settings with either locals (e.g. homestay) or other Germans (e.g. school breaks). This paper investigates the nature of her second language (L2) learning motivation in different social settings, as elicited in interviews, reports and blog entries; and the dynamics of her oral L2 development, as captured in six interviews. The findings show that Chiara’s L2 motivation was highly situational: she only made significant efforts in L2 use when she considered the specific social setting valuable for reaching non-linguistic goals and when it validated her sense of self. The linguistic findings, measured in language complexity, accuracy, lexis and fluency (CALF) demonstrated that Chiara improved her already highly functioning oral skills during SA – especially fluency and accuracy – despite inconsistent L2 interactions.
This edited volume provides a single coherent overview of vocabulary teaching and learning in relation to each of the four skills (reading, writing, listening, speaking). Each of the four sections presents a skill area with two chapters presented by two leading experts in the field, relating recent advances in the field to the extent that each skill area relates differently to vocabulary and how this informs pedagogy and policy. The book opens with a summary of recent advances in the field of vocabulary, and closes by drawing conclusions from the skill areas covered. The chapters respond to emerging vocabulary research trends that indicate that lexical acquisition needs to be treated differently according to the skill area. The editors have chosen chapters to respond to recent research advances and to highlight practical and pedagogical application in a single coherent volume. Jon Clenton is Associate Professor at Hiroshima University, Japan. His main research interests include the assessment of vocabulary knowledge, L2 vocabulary development in terms of bilingual models, second language acquisition, word association studies, lexical processing, and L2 measurement tools. He has examined several vocabulary measurement tools, with focus on attempts to isolate the construct of productive vocabulary knowledge. Paul Booth is Senior Lecturer at Kingston University, London, and teaches both undergraduate and postgraduate courses. His research interests include second language vocabulary, especially individual differences, lexical diversity, and frequency. He has also researched situated learning and language teacher development.
Location and investment selection features lakes of hydropower plant investments are presented in a proposed expert, event, and data-driven fact-based robot and platform. The traditional magical number 4 scale is tested in simple natural language process clustering at sub-factors, factors, main factors, and metafactors. The traditional Decision Making Trial and Evaluation Laboratory methodology is tested in complex mathematical natural language process clustering at top metafactors as Political, Economic, Social and Technological with its extensions. 9 presumptive logarithmic learning curve functions as experience curves are modeled considering time-domain effects. The functions with 0,1; 0,5; and 0,9 learning rates are tested in the current models. They cover almost the whole possibility space. Weighted arithmetic mean and weighted geometric mean as group decision-making approximation methods are tested for decision aggregation on the time domain. In the end, 6 clustering configurations are compared with each other at the top metafactors level. 6 top metafactors, 12 metafactors, 27 main factors, 114 factors, and 10612 sub-factors are found and clustered in location selection features. There are 11 hierarchical levels. 2 top metafactors, 5 metafactors, 42 main factors, 136 factors, and 4276 sub-factors are found and clustered in investment selection features. There are 10 hierarchical levels.
Within higher education, it is often believed that the adoption of English-medium instruction (EMI) will provide domestic students with the language skills that will enable them to be more competitive in their future professional pursuits. However, research into language learning and EMI at the university level is very scarce. This study examined essays by 195 undergraduate students (99 1st-year and 96 3rd-year learners) at a major university in Spain in order to investigate the effect of three years of instruction through the medium of English on their level of proficiency, essay quality and lexical diversity (as measured by the Oxford Placement test, the CEFR writing scale and three measures of lexical diversity). The results showed a significant improvement in the learners’ second language (L2) proficiency and a significant but subtle increase in essay quality ratings but no significant increase in lexical diversity scores. In the same vein as the findings of some of the other studies we discuss, the present findings seem to suggest the need to rethink and re-evaluate the implementation of EMI in contexts like the one examined in this study.
An ever-increasing global demand for food, coupled with increasingly volatile commodity prices have charged producers with the task of becoming more efficient. As such, technologies aimed at producing more with less are continually being developed and marketed to producers. However, whether or not these expensive new technologies have resulted in improved profitability is still unknown, as the vast majority of studies showing their impact on profitability have been performed using hypothetical farms and simulations. These studies have shown the potential for increases in profitability from use, but their impact in the real world is still uncertain. This project uses various fixed-effect panel data models to examine the realized economic impact of using precision agriculture technologies amongst a sample of producers across Nebraska using financial data from 1995-2014. Results of the study show the existence of a strong, positive relationship between number of technologies used and net farm income, indicating that precision agriculture use is associated with higher profitability. However, whether use is driving profitability or profitability is driving use remains somewhat unclear. Pre-and-post analysis among users of the technologies suggest profitability has in fact increased from use, but the result is not statistically significant. This may be a consequence of mixed results among users, with many factors influencing the level of benefit achievable from use. Nonetheless, an obvious learning effect exists for users, with profitability increasing more as experience with the technologies increases. This would be expected due to the need to produce data regarding within-field variability on which to capitalize, along with the investment in learning the ideal use of these relatively complicated technologies. Overall, it is obvious that further research regarding the impact of these technologies is of great relevance. Advisor: Bradley D. Lubben
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