Knowledge tracing aims to model and predict students' knowledge states during learning activities. Traditional methods like Bayesian Knowledge Tracing (BKT) and logistic regression have limitations in granularity and performance, while deep knowledge tracing (DKT) models often suffer from lacking transparency. This paper proposes a…

The prediction of student performance and the analysis of students' learning behaviour play an important role in enhancing online courses. By analysing a massive amount of clickstream data that captures student behaviour, educators can gain valuable insights into the factors that influence students' academic outcomes and identify areas of…

The present study used quantitative and qualitative measures to examine Iranian applied linguists' (mis-) conceptions of ethical issues in research. For this purpose, one hundred and twelve applied linguists completed a research ethics questionnaire constructed and validated by the researchers. In the follow-up qualitative phase, 15 applied…

To date, research on mixed-reality simulation (MRS) has focused on various skills including applied behavior analysis, but studies have not evaluated the role of preservice teachers' perceived knowledge, confidence, usefulness, or actual practice related to data collection. To address this gap, we conducted two separate MRS studies, one for…

This study focuses on describing data based school management processes in Türkiye, Spain and Romania. The study group consists of 49 participants. Maximal variation and stratified sampling were applied. For internal trustworthiness, respondent validation, data triangulation and cross check were utilized. For transferability, 'expert opinions' and…

Previous research has extensively analysed teachers' and students' Facebook use for instructional engagement, writing, research dissemination and e-learning. However, Facebook as a data collection mechanism for research has scarcely been the subject of previous studies. The current study addressed these gaps by analysing students' awareness,…

In the contemporary society a massive amount of data is generated continuously by various means, and they are called Big-Data sets. Big Data has potential and limits which need to be understood by statisticians and statistics consumers, therefore it is a challenge to develop Big-Data Literacy to support the needs of constructive, concerned, and…

This research presents an integrative review about the methodological procedures adopted in the research of the Chemistry PCK, with the aim of identifying the data collection instruments used to explain the PCK in this field, seeking to observe its frequency of use and also contribute to the advancement of knowledge established by previous…

Project Extension for Community Healthcare Outcomes (ECHO) Nevada applied the ECHO virtual hub-and-spoke telementoring model over nine 6-week cohorts (between November 2019 and November 2021) supporting community health workers (CHWs) who advise clients with diabetes or pre-diabetes. This study describes the program implementation, including…

Despite a growing focus on access to and use of emergent literacy assessment in early childhood, little is known about early childhood teachers' data practices and their associations with children's emergent literacy skills. A questionnaire was used to confirm and elaborate findings from prior qualitative work (Schachter & Piasta, 2022)…

Collecting data on learners' performance in different chemistry contents and analysing them to identify their knowledge and understanding in related content areas is a major task of Chemistry Education Research. The data collection process on the learners' content knowledge and understanding of content knowledge requires a standard measuring tool.…

This article reports on how a pedagogical entrepreneurship approach combined with fundamental elements of mathematical modelling may be used to strengthen students' development of mathematical literacy in upper primary school. This is done first through a review of the relationship between pedagogical entrepreneurship in mathematics, mathematical…

Promoting understanding of the epistemologies of science has long been the primary objective in science education, and can be viewed as a form of science learning outcome. Many studies have attempted to understand learners' conceptions of epistemology in science from various perspectives and methods; however, no recent reviews have focused on the…

This paper describes the evolution of "recognition of need for data" and "strategical thinking", two types of thinking identified by Wild and Pfannkuch in their Framework for Statistical Thinking in Empirical Enquiry, as well as its relevance for math teacher professional development. The research was carried out with ten…

We introduce a model which combines principles from psychometric and connectionist paradigms to allow direct Q-matrix refinement via backpropagation. We call this model dAFM, based on augmentation of the original Additive Factors Model (AFM), whose calculations and constraints we show can be exactly replicated within the framework of neural…