In recent years, an array of studies has focused on 'translationese' (i.e., unique features that manifest in translated texts, causing second language (L2) writings to be similar to translated texts but different from native language (L1) writings). This intriguing linguistic pattern has motivated scholars to investigate potential markers for…

The education system has relied on conventional single-score assessments, which provide limited insights into students' cognitive abilities. Cognitive diagnostic assessment (CDA) offers a promising alternative by providing detailed information on students' cognitive processes. The review aims to explore the recent trends of cognitive diagnostic…

Linguistic phenomena (e.g., words and syntactic structure) co-occur with a wide variety of meanings. These systematic correlations can help readers to interpret a text and create predictions about upcoming material. However, to what extent these correlations influence discourse processing is still unknown. We address this question by examining…

This guide offers a comprehensive handbook to scientific research methodology and experimental design, specifically for novice MA and PhD researchers in Education and Language Learning (TESOL/TEFL). It establishes scientific research as a systematic, objective inquiry focused on identifying cause-and-effect relationships through empirical data.…

Learners' self-initiated language learning with mobile technology occurring outside the classroom is often contextualized, heterogeneous, and idiosyncratic. In this study, we propose a time-series clustering methodology for researching informal mobile language learners' learning and development of another language, with a view to unravelling the…

Background and Context: Data science and statistics are used across a broad spectrum of professions, experience levels and programming languages. The popular scientific computing languages, such as Matlab, Python and R, were organized without using empirical methods to show evidence for or against their design choices, resulting in them feeling…

Discourse markers can have various functions depending on the context in which they are used. Taking this into consideration, in this corpus-based research, we analyzed and unveiled quantitatively and qualitatively the functions of four discourse markers in academic spoken English. To this purpose, four discourse markers, i.e., "I mean,"…

National standards that centre on the underpinning epistemic practices of the discipline has emphasised the need for teachers to focus much more on knowledge generation approaches to learning. Adopting a complexity perspective, we attempt to understand how teachers shift over time by examining their epistemic orientation to knowledge generation…

The use of unidimensional scales that contain both positively and negatively worded items is common in both the educational and psychological fields. However, dimensionality investigations of these instruments often lead to a rejection of the theorized unidimensional model in favor of multidimensional structures, leaving researchers at odds for…

How can we measure the resource mobilization (RM) efforts of social movements on Twitter? In this article, we create the first ever measure of social movements' RM efforts on a social media platform. To this aim, we create a four-conditional lexicon that can parse through tweets and identify those concerned with RM. We also create a simple RM…

Education research has recently seen the emergence of two distinct frameworks guiding the application of quantitative methods through a more critical and equity-oriented lens. These two frameworks are critical quantitative (CritQuant) studies and quantitative critical race theory (QuantCrit). Although different in their intellectual traditions,…

Moderated multiple regression (MMR) has become a fundamental tool for applied researchers, since many effects are expected to vary based on other variables. However, the inherent complexity of MMR creates formidable challenges for adequately performing power analysis on interaction effects to ensure reliable and replicable research results. Prior…

Purpose: Many studies using machine learning (ML) in speech, language, and hearing sciences rely upon cross-validations with single data splitting. This study's first purpose is to provide quantitative evidence that would incentivize researchers to instead use the more robust data splitting method of nested k-fold cross-validation. The second…

This paper delves into statistical disparities between human-written and ChatGPT-generated texts, utilizing an analysis of Shannon's equitability values, and token frequency. Our findings indicate that Shannon's equitability can potentially be a differentiating factor between texts produced by humans and those generated by ChatGPT. Additionally,…

The aim of the study was to examine the effects of rubric co-creation on peer feedback. From a social constructivist perspective, rubric co-creation might have the ability to promote the quality of feedback messages, interactivities within feedback processes, and uptake of feedback information in a peer-based collaborative setting of higher…