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…

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…

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…

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.…

Collaborative staff development in education is the vehicle to student success, and research shows that the closer professional learning is to daily practice, the more meaningful and impactful it will be. Written with deep respect for the work educators do in their classrooms each day, this practical resource illustrates the importance of…

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…

We consider the ability to complete an investigative cycle as an indicator of the robustness of students' statistical knowledge. From this standpoint, we analyzed the written reports of primary education student teachers when they developed an investigative cycle in a Chilean and a Spanish university. In their development of the stages of the…

This paper addresses the topical issue of searching for optimum technology for fostering professional competencies in a target audience of business informatics students. The authors discuss the relevance of using the competency-based approach in the context of pedagogical goalsetting. The work describes the key stages in a study that involved…

Higher education institutions are developing the capacity for learning analytics. However, the technical development of learning analytics has far exceeded the consideration of ethical issues around learning analytics. We examined higher education academics' knowledge, attitudes, and concerns about the use of learning analytics though four focus…

We have designed, developed, and implemented a student-facing learning analytics dashboard in order to support students as they learn in online environments. There are two separate dashboards in our system: a content recommender dashboard and a skills recommender dashboard. The content recommender helps students identify gaps in their content…

The current study explored preservice and inservice teachers' perspectives on data literacy for teaching. Semi-structured interviews were employed with 12 teacher candidates in elementary and special education. The findings revealed participants' misconceptions regarding formative and summative data; their understanding of the value of formative…