Explanatory item response models (EIRMs) have been applied to investigate the effects of person covariates, item covariates, and their interactions in the fields of reading education and psycholinguistics. In practice, it is often assumed that the relationships between the covariates and the logit transformation of item response probability are…

This systematic review presents the first synthesis of the scientific literature on estimating school and teacher/class effects on student academic performance using random-effects (RE) models with three or more levels. The review delves into the theoretical framework underpinning the estimation of educational effects, the associated statistical…

The "Building Your Research Data Management Toolkit" was developed to provide introductory research data management skills training to liaisons in academic libraries. This paper assesses the participants' perceived change in knowledge, behaviors and attitudes as a result of participation in the RoadShow program. Long term changes in…

The application of big data in education sparks debates on its effects. Researchers explore its impact on learning outcomes, with divergent views on neural networks' potential and negative consequences. This study assesses big data's influence on basic literacy skills in music education for 5th graders. Using clustering and k-density analyses,…

With reference to the framework in The International Data Science in Schools Project, this paper aims to discuss the course design, teaching and learning, and assessment of a foundation course offered in an undergraduate statistics and data science programme. SAS® University Edition (a free software package) is adopted in this foundation course.…

In this research project we investigate the role of responses to anomalous data during modelling processes. Modelling is seen as a comprehensive practice that encompasses various aspects of scientific thinking; hence, it is an important style of scientific thinking, especially if analysed from a process-based perspective. Therefore, it provides…

Sustainable quality education is a big challenge even for the developed countries. In response to this, education 4.0 is gradually expanding as a new era of education. This work intends to unfold some hidden parameters that are affecting the quality education ecosystem (QEE). Academic loafing, unawareness, non-participation, dissatisfaction, and…

While an increased number of industries with business operations have been shaping their use of data analytics, the use of such tools and methods within the higher education research domain, specifically research administration, is still in its infancy. This mixed-methods study collected data to identify best practices in how universities and…

While most research on restraint and seclusion use in K-12 schools focuses on the procedures with students with disabilities, the authors investigate its application to English learners and offer proactive steps for teachers.

Developmental scientists are often interested in subgroups of people who share commonalities in aspects of development; these subgroups often cannot be captured directly but instead must be inferred from other information. Mixture models can be used in these situations. Two specific types of mixture models, latent profile transition analyses and…

Data modeling practices are often invisible to students in introductory biology courses. However, developing a well-rounded understanding of these practices is critical for scientific literacy. Furthermore, introductory undergraduate science laboratory courses are often taught by graduate students or novice instructors with little autonomy,…

Qualitative coding procedures emanating from grounded theory were limited by technologies of the 1960s: colored pens, scissors, and index cards. Today, electronic documents can be flexibly stored, retrieved, and cross-referenced using qualitative data analysis (QDA) software. We argue the oft-cited grounded theory framework poorly fits many…

The focus of this paper is learning the language of data science and statistics through the use of simple classroom activities. Many terms in statistics are known to be lexically ambiguous, having one meaning in general English conversation and another, more technical, meaning in statistical English. The main aim is to investigate whether the…

Analysis of data from single-case intervention studies commonly involves visual analysis. Previous research indicates that visual analysis may suffer from low reliability and unpromising error rates. We investigated the reliability and validity of visual analysis and explored to what extent data trends affect judgments. We administered a…

Research based on educational data mining conducted at academic institutions is often limited by the institutional policy with regard to the type of learning management system and the detail level of its activity reports. Often, researchers deal with only raw data. Such data normally contain numerous fictitious user activities that can create a…