Generating personalized learning pathways for e-learners is a critical issue in the field of e-learning as it plays a pivotal role in guiding learners towards the successful achievement of their learning objectives. The existing literature has proposed various methods from different perspectives to address this issue, including learner-based,…

The flipped classroom (FC) is a pedagogical model with an active learning concept and a hybrid course design that reverses the typical lecture process. Given the widespread use of online delivery methods, there is a need to explore the FC in delivering statistics courses. This study employs a prospective quasi-experimental study design to evaluate…

As we examine the pandemic's impact on higher education, we can see that many previously traditional teaching and learning frameworks have been invalidated, and the need for new teaching and learning approaches has increased. This indicates that the traditional frameworks for higher education may no longer be effective. Consequently, there is a…

Teachers form expectations that can influence their students' performance, and there are a variety of ways these expectations can be communicated. In the current study, we tested a novel method for communicating expectations via examples of student work--examples that contain basic, entry-level work and communicate low, but manageable expectations…

Students with and without disabilities may be educated across various service delivery models (SDMs): general education, cotaught, pull-out, and self-contained. Still, evidence for their relative effectiveness at scale remains limited. Using longitudinal administrative data from Indiana, we measured the effect of different SDMs on test scores,…

Understanding professional development is a key component in ensuring school improvement. This study examines the professional development experiences of 16 school leaders and staff members in the Northeast Region of the United States. This qualitative grounded theory study investigates the type of professional development experiences that result…

The purpose of this article is to share how one teacher education program at a Midwestern university prepares teacher candidates to analyze student achievement data, which is believed essential as one of the roles a teacher candidate needs in order to develop teacher leadership in the classroom. The authors provide the teacher candidates' relevant…

This editorial introduces a special section of the "Journal of Learning Analytics," for which Neil Selwyn's keynote address to LAK '18 has been written up as an article, "What's the problem with learning analytics?" His claims and arguments are engaged in commentaries from Alfred Essa, Rebecca Ferguson, Paul Prinsloo, and…

Even under ideal conditions, teaching is tough work. Facing unrelenting pressure from administrators and parents and caught in a race against time to improve student outcomes, educators can easily become discouraged (or worse, burn out completely) without a robust coaching system in place to support them. For more than 20 years, perfecting such a…

In Applied AI, or 'machine learning', methods such as neural networks are used to train computers to perform tasks without human intervention. In this article, we question the applicability of these methods to education. In particular, we consider a case of recent attempts from data scientists to add AI elements to a handful of online learning…

There has been extensive research using centrality measures in educational settings. One of the most common lines of such research has tested network centrality measures as indicators of success. The increasing interest in centrality measures has been kindled by the proliferation of learning analytics. Previous works have been dominated by…

Prediction of student performance is one of the most important subjects of educational data mining. Artificial neural networks are seen to be an effective tool in predicting student performance in e-learning environments. In the studies carried out with artificial neural networks, performance predictions based on student scores are generally made,…

Data walls are a data use practice increasingly being adopted in western, Anglophone countries to display student academic achievement data. The purpose of data walls is to improve teaching and learning by helping teachers and/or students to identify patterns of growth and achievement, set goals, and plan instructional interventions or…

The Responses to Educational Disruption Survey (REDS), conducted by the International Association for the Evaluation of Educational Achievement (IEA), studied how teaching and learning were affected by the disruptions caused by COVID-19 and aimed to paint a picture of national responses to the global pandemic. REDS was based on the premise that…

Drawing upon recent theorising of numbers and data, and applications to schooling, this paper reveals how tensions between more accountability-oriented logics, and more contextually-situated conceptions of engagement with data, played out in one school in a regional community in northern Queensland, Australia. The research reveals that at the same…