Text-based recall and extra-textual generations resulting from simplified and authentic texts

This study uses a moving windows self-paced reading task to assess text comprehension of beginning and intermediate-level simplified texts and authentic texts by L2 learners engaged in a text-retelling task. Linear mixed effects (LME) models revealed statistically significant main effects for reading proficiency and text level on the number of text-based propositions recalled: More proficient readers recalled more propositions. However, text level was a stronger predictor of propositional recall than reading proficiency. LME models also revealed main effects for language proficiency and text level on the number of extra-textual propositions produced. Text level, however, emerged as a stronger predictor than language proficiency. Post-hoc analyses indicated that there were more irrelevant elaborations for authentic texts and intermediate and authentic texts led to a greater number of relevant elaborations compared to beginning texts

Measuring Longitudinal Writing Development Using Indices of Syntactic Complexity and Sophistication

Measures of syntactic complexity such as mean length of T-unit have been common measures of language proficiency in studies of second language acquisition. Despite the ubiquity and usefulness of such structure-based measures, they could be complemented with measures based on usage-based theories, which focus on the development of not just syntactic forms but also form-meaning pairs, called constructions (Ellis, 2002). Recent cross-sectional research (Kyle &amp; Crossley, 2017) has indicated that indices related to usage-based characteristics of verb argument construction (VAC) use may be better indicators of writing proficiency than structure-based indices of syntactic complexity. However, because cross-sectional studies can only show general trends across proficiency benchmarks, it is important to test these findings in individuals over time (Lowie &amp; Verspoor, 2019). Thus, this study investigates the developmental trajectories of second language learners of English across two academic years with regard to syntactic complexity and VAC sophistication. </p

Measuring Longitudinal Writing Development Using Indices of Syntactic Complexity and Sophistication

Measures of syntactic complexity such as mean length of T-unit have been common measures of language proficiency in studies of second language acquisition. Despite the ubiquity and usefulness of such structure-based measures, they could be complemented with measures based on usage-based theories, which focus on the development of not just syntactic forms but also form-meaning pairs, called constructions (Ellis, 2002). Recent cross-sectional research (Kyle & Crossley, 2017) has indicated that indices related to usage-based characteristics of verb argument construction (VAC) use may be better indicators of writing proficiency than structure-based indices of syntactic complexity. However, because cross-sectional studies can only show general trends across proficiency benchmarks, it is important to test these findings in individuals over time (Lowie & Verspoor, 2019). Thus, this study investigates the developmental trajectories of second language learners of English across two academic years with regard to syntactic complexity and VAC sophistication

What's so simple about simplified texts? A computational and psycholinguistic investigation of text comprehension and text processing

This study uses a moving windows self-paced reading task to assess both text comprehension and processing time of authentic texts and these same texts simplified to beginning and intermediate levels. Forty-eight second language learners each read 9 texts (3 different authentic, beginning, and intermediate level texts). Repeated measures ANOVAs reported linear effects of text type on reading time (normalized for text length) and true/false comprehension scores indicating that beginning level texts were processed faster and were more comprehensible than intermediate level and authentic texts. The linear effect of text type on comprehension remained significant within an ANCOVA controlling for language proficiency (i.e., TOEFL scores), reading proficiency (i.e., Gates-MacGinitie scores), and background knowledge, but not for reading time. Implications of these findings for materials design, reading pedagogy, and text processing and comprehension are discussed

Text readability and intuitive simplification: A comparison of readability formulas

Texts are routinely simplified for language learners with authors relying on a variety of approaches and materials to assist them in making the texts more comprehensible. Readability measures are one such tool that authors can use when evaluating text comprehensibility. This study compares the Coh-Metrix Second Language (L2) Reading Index, a readability formula based on psycholinguistic and cognitive models of reading, to traditional readability formulas on a large corpus of texts intuitively simplified for language learners. The goal of this study is to determine which formula best classifies text level (advanced, intermediate, beginner) with the prediction that text classification relates to the formulas’ capacity to measure text comprehensibility. The results demonstrate that the Coh-Metrix L2 Reading Index performs significantly better than traditional readability formulas, suggesting that the variables used in this index are more closely aligned to the intuitive text processing employed by authors when simplifying texts

Predicting Math Success in an Online Tutoring System Using Language Data and Click-Stream Variables: A Longitudinal Analysis

Previous studies have demonstrated strong links between students\u27 linguistic knowledge, their affective language patterns and their success in math. Other studies have shown that demographic and click-stream variables in online learning environments are important predictors of math success. This study builds on this research in two ways. First, it combines linguistics and click-stream variables along with demographic information to increase prediction rates for math success. Second, it examines how random variance, as found in repeated participant data, can explain math success beyond linguistic, demographic, and click-stream variables. The findings indicate that linguistic, demographic, and click-stream factors explained about 14% of the variance in math scores. These variables mixed with random factors explained about 44% of the variance

Critical perspectives on writing analytics

Writing Analytics focuses on the measurement and analysis of written texts for the purpose of understanding writing processes and products, in their educational contexts, and improving the teaching and learning of writing. This workshop adopts a critical, holistic perspective in which the definition of "the system" and "success" is not restricted to IR metrics such as precision and recall, but recognizes the many wider issues that aid or obstruct analytics adoption in educational settings, such as theoretical and pedagogical grounding, usability, user experience, stakeholder design engagement, practitioner development, organizational infrastructure, policy and ethics