Explore the vast range of titles available.

It is now widely recognized among educators that explicit attention to language is necessary in order to optimize both language and content learning in situations, such as CLIL, where learners, teachers or both operate in a second language. However, the requirement of attention to language sits uneasily with the fact that content-subject specialist teachers frequently feel unprepared to think and operate in linguistic dimensions. In an attempt to create a conceptualisation that would speak to subject teachers in terms that are meaningful to them from within their own subjects, a Construct of Cognitive Discourse Functions (henceforth CDFs) has been proposed. This construct is theoretically founded in both educational curriculum theory and linguistic pragmatics and consists of a seven-fold categorization of verbalizations which express acts of thinking about subject matter in the classroom (CLASSIFY, DEFINE, DESCRIBE, EVALUATE, EXPLAIN, EXPLORE, REPORT). As the theoretical background of the CDF Construct has been discussed at length elsewhere (Dalton-Puffer 2013, 2016), it will be presented only briefly at the outset of this article. The main purpose of this contribution is to report on steps taken towards an empirical validation of the CDF Construct. A total of four smaller-scale studies each focusing on the classroom discourse in one subject (biology, physics, economics, history) will be surveyed in order to find answers to the questions of whether CDFs actually occur in classroom interaction and if they do, which and to what extent. Comparisons to a small complementary study on a set of EFL lessons will be made where appropriate. Results show that CDFs are indeed a staple of teaching and learning in classroom-based education but are in no way equally distributed. Also, they are almost never the object of conscious attention. As a number of further questions remain yet to be answered on the way towards empirical validation of a fully articulated CDF Construct, these will be discussed in the conclusion of the article.

The present study analyzed how a group of young Spanish-speaking English as a foreign language (EFL) learners in a content and language integrated learning (CLIL) science class responded to an instructional unit integrating attention to functional language and an inquiry-oriented approach to science. Working in cooperation with the researchers, a year 4 primary school teacher implemented a teaching sequence on levers with 48 9-10-year-olds over three weeks. The sequence, which was intended to raise the children’s awareness of the demands involved in understanding (content goals) and expressing as written reports (rhetorical goals) how levers work, scaffolded their activity from item-based writing to the production of full texts. On completing the unit, each child independently wrote a report on levers, all of which were analyzed from the perspective of cognitive discourse functions and ideational meaning. The results of these analyses are discussed in terms of their significance for CLIL writing with young learners.

The present study attempts to propose a taxonomy for the discourse functions of importance markers in English academic lectures and examine their effects on ESL learners’ comprehension of important points in lectures. To this end, a corpus of 160 lecture transcripts from the BASE corpus was analyzed to identify and classify the main functions of words and expressions that mark importance in them. It was found that importance is indicated by the following lecture-specific devices and attributes: 1) student involvements, 2) topic announcers, 3) exam-related markers, 4) discourse clarifiers, 5) hedging markers, and 6) message promoters. A total of 62 Malaysian ESL students (38 females and 24 males) participated in this study and were divided into an experimental group and a control group, both of them of the same size. Through 12 forty-minute sessions of explicit instruction, the participants in the experimental group were instructed the discourse functions of importance markers in university lectures, whereas those in the control group did not receive such instruction. The result of the posttest of comprehension of important points indicated that familiarity with how importance is marked in lectures can boost ESL students’ understanding of main topics. The findings suggest that both novice lecturers and ESL/EFL students may profit from instruction as to how importance is indicated by native speaker lecturers through several lecture-specific discourse functions.

According to systematic-functional grammar, nominalization is an important source from which grammatical metaphor derives. Starting from the concept of nominalization, this paper, based on a great number of examples, attempts to discuss the following three issues: definition of nominalization; classification of nominalization and its discourse function, and points out that the use of nominalization can add objectivity, conciseness, precision, cohesion and coherence to English discourse.

Research into discourse synthesis examines the ways in which writers make use of, and transform, multiple other texts in writing their own. It is intertextual research that has blurred boundaries of various kinds, not only the boundary between the processes of reading and writing but also boundaries across disciplines as well as regions of the world. Guided by a cognitive constructivist perspective, this research into discourse synthesis drew at its origin—and continues to draw now—from multidisciplinary theoretical and empirical work. This article, which establishes the foundations for this research and traces its development, attends to writers’ transformations of multiple source texts resulting from operations of organizing, selecting, and connecting. Studies into synthesis writing for varying academic tasks have shown that, by applying these operations to multiple textual sources, writers produce discourses that function as new texts in new contexts. Following a discussion of historical background, attention in this article goes to three major issues: the variation in synthesis associated with different academic genres; the kinds of insights into product and process that come from different research approaches; and the nature of new instructional approaches that emphasize elements of discourse synthesis. All facets of this research reveal continuity as well as change, the latter occurring, in large part, through contact and convergence of discourse synthesis research with related bodies of work. The conclusion, which centers on the notion of transformation, summarizes research conducted thus far and points to future directions.

Coh-Metrix analyzes texts on multiple measures of language and discourse that are aligned with multilevel theoretical frameworks of comprehension. Dozens of measures funnel into five major factors that systematically vary as a function of types of texts (e.g., narrative vs. informational) and grade level: narrativity, syntactic simplicity, word concreteness, referential cohesion, and deep (causal) cohesion. Texts are automatically scaled on these five factors with Coh-Metrix-TEA (Text Easability Assessor). This article reviews how these five factors account for text variations and reports analyses that augment Coh-Metrix in two ways. First, there is a composite measure calledformality, which increases with low narrativity, syntactic complexity, word abstractness, and high cohesion. Second, the words are analyzed with Linguistic Inquiry and Word Count, an automated system that measures words in texts on dozens of psychological attributes. One next step in automated text analyses is a topics analysis that scales the difficulty of conceptual topics.

Formulaic sequences play a crucial role in building academic discourse. From among the variety of formulaic expressions, lexical bundles have been shown to serve particular facilitative functions in academic discourse. Defined as strings of word forms that commonly co-occur in natural discourse, lexical bundles are characterized statistically by their frequency of occurrence and they contribute significantly to fluency in speech and writing. While previous research had focused on the use of these expressions in academic research articles across disciplines or on the difference between spoken and written registers, little research has been carried out to find out the language use of academic lectures from different disciplines in terms of the use of these bundles, orally. Taking into account this consideration, the present study aimed to investigate how lexical bundles are used by academic lecturers from different disciplinary communities. With the aim of comparing their language selection, the most frequent four-word lexical bundles in academic lectures of two disciplines, namely politics and chemistry were identified and categorized. The procedure adopts Biber et al.’s (2004) functional categorization of lexical bundles to investigate the communicative purposes that lexical bundles convey in the lectures of the two groups and to see whether there were any disciplinary differences with regard to the bundles used. Based on the findings, there were some marked variations found across the two disciplines in terms of discourse functions of the lexical bundles. It seemed that academic lectures rely heavily on the use of specific word combinations to fulfill those functions related to their discipline.

This study investigates the integration of Cognitive Discourse Functions (CDFs) in English-Medium Instruction (EMI) classrooms across various disciplines in Turkish higher education, with a particular focus on teacher education programs. CDFs provide a systematic framework for analysing how language facilitates cognitive processes such as describing, explaining, evaluating, and categorising in disciplinary contexts. The data comprise 472 minutes of lesson recordings from five courses across three fields: Computer Education and Educational Technology, English Language Teaching, and Mathematics and Science Education. Lessons were analysed using CDF coding to examine field-specific variations in language use and their implications for disciplinary literacies. The study provides an initial exploration of the interconnectedness of CDFs with disciplinary literacies by delineating their role in building foundational knowledge, facilitating reasoning, and fostering critical thinking. These findings indicate that explicit integration of CDFs into EMI pedagogy has potential for addressing language and content challenges faced by students in EMI settings. The article contributes to the growing body of research on EMI by providing insights into the interplay between language and disciplinary knowledge construction. Niniejsze badanie dotyczy integracji poznawczych funkcji dyskursu (CDFs) w dydaktyce prowadzonej w języku angielskim (English-Medium Instruction, EMI) na różnych kierunkach studiów w Turcji, ze szczególnym uwzględnieniem programów kształcenia nauczycieli. CDFs posłużyły jako rama analityczna do zbadania, w jaki sposób język wspiera procesy poznawcze, takie jak opisywanie, wyjaśnianie, ocenianie i kategoryzowanie w kontekstach akademickich. Materiał badawczy obejmuje 472 minuty nagrań zajęć z pięciu kursów w trzech dziedzinach: edukacji informatycznej i technologii edukacyjnej, nauczania języka angielskiego oraz edukacji matematyczno-przyrodniczej. Analiza z zastosowaniem kodowania CDF umożliwiła identyfikację specyfiki poszczególnych dziedzin w zakresie użycia języka oraz sformułowanie implikacji dla rozwijania kompetencji dyskursywnych w ujęciu międzydziedzinowym. Wyniki ukazują związki między CDFs a rozwojem podstaw wiedzy oraz wspieraniem umiejętności wnioskowania i myślenia krytycznego. Sugerują także, że świadoma integracja CDFs w nauczaniu EMI może stanowić odpowiedź na wyzwania językowe i treściowe, z którymi mierzą się studenci. Artykuł wpisuje się w dynamicznie rozwijający się nurt badań nad EMI, dostarczając wglądu w relacje między językiem a konstruowaniem wiedzy w różnych dziedzinach akademickich.

When generating text from probabilistic models, the chosen decoding strategy has a profound effect on the resulting text. Yet the properties elicited by various decoding strategies do not always transfer across natural language generation tasks. For example, while mode-seeking methods like beam search perform remarkably well for machine translation, they have been observed to lead to incoherent and repetitive text in story generation. Despite such observations, the effectiveness of decoding strategies is often assessed on only a single task. This work—in contrast—provides a comprehensive analysis of the interaction between language generation tasks and decoding strategies. Specifically, we measure changes in attributes of generated text as a function of both decoding strategy and task using human and automatic evaluation. Our results reveal both previously observed and novel findings. For example, the nature of the diversity–quality trade-off in language generation is very task-specific; the length bias often attributed to beam search is not constant across tasks.

Matching for causal inference is a well-studied problem, but standard methods fail when the units to match are text documents: the high-dimensional and rich nature of the data renders exact matching infeasible, causes propensity scores to produce incomparable matches, and makes assessing match quality difficult. In this paper, we characterize a framework for matching text documents that decomposes existing methods into (1) the choice of text representation and (2) the choice of distance metric. We investigate how different choices within this framework affect both the quantity and quality of matches identified through a systematic multifactor evaluation experiment using human subjects. Altogether, we evaluate over 100 unique text-matching methods along with 5 comparison methods taken from the literature. Our experimental results identify methods that generate matches with higher subjective match quality than current state-of-the-art techniques. We enhance the precision of these results by developing a predictive model to estimate the match quality of pairs of text documents as a function of our various distance scores. This model, which we find successfully mimics human judgment, also allows for approximate and unsupervised evaluation of new procedures in our context. We then employ the identified best method to illustrate the utility of text matching in two applications. First, we engage with a substantive debate in the study of media bias by using text matching to control for topic selection when comparing news articles from thirteen news sources. We then show how conditioning on text data leads to more precise causal inferences in an observational study examining the effects of a medical intervention.