There is a growing need to empirically evaluate the quality of online instructional interventions at scale. In response, some online learning platforms have begun to implement rapid A/B testing of instructional interventions. In these scenarios, students participate in series of randomized experiments that evaluate problem-level interventions in…

This study aimed to compare the effectiveness and efficiency of the model-lead-test (MLT) and video modeling (VM) methods in teaching individuals with ID how to access and use the services provided by the Turkish state in digital environments. Four individuals participated in the study, in which the adapted alternating treatments design, one of…

This paper explores the move towards an all-female teaching force, particularly in the developed world, where men are turning their backs on the profession. It attempts to gather the evidence as to what is affecting men's choice to reject teaching as a career. It explores the possible causes of this change, which has been increasing over the last…

Recently, abstracted quantitative structures (AQS), a construct from quantitative reasoning, has been offered as a means to conceptualize and study mathematization during mathematical modeling. Extending this theoretical work, we provide empirical evidence that an intervention targeting participants' AQS can assist in aligning modelers' models…

Assessment is not an end in itself but a vehicle for educational improvement. Assessment is vital to the educational process as it enhances teaching and learning, promotes accountability, motivates students, guides instructional decisions, and drives systemic improvements. Assessment plays a crucial role in the educational process as it serves…

Students with learning disabilities/difficulties in mathematics often apply ineffective procedures to solve word problems. Given that current mathematics curriculum standards emphasize conceptual understanding in problem solving as well as higher-order thinking and reasoning, the purpose of this study was to evaluate the impact of a model-based…

This paper explores school development processes in four schools in challenging circumstances. These schools were selected from a sample of schools in a longitudinal mixed-method study over a five-year period of around 100 schools using a typology of different models of change over time. The paper presents first selected findings from the overall…

Learning analytics primarily deals with the optimization of learning environments and the ultimate goal of learning analytics is to improve learning and teaching efficiency. Studies on learning analytics seem to have been made in the form of adaptation engine and intervention engine. Adaptation engine studies are quite widespread, but intervention…

The gold-standard for evaluating the effect of an educational intervention on student outcomes is running a randomized controlled trial (RCT). However, RCTs may often be small due to logistical considerations, and resulting treatment effect estimates may lack precision. Recent methods improve experimental precision by incorporating information…

Typically, more primary students qualify for mathematics intervention support than schools have the capacity to assist. This highlights the importance of every primary mathematics teacher having the expertise to design inclusive and responsive curricula and instruction for students who may experience difficulty. Our study addresses this issue…

The study used tailored interventions for ten schools which were deemed chronically low performing in Florida. Treatment schools included a majority of students that were minorities, economically disadvantaged and academically struggling or at-risk of failure. The ten schools received a progression of intensive professional development and…

Open-ended learning environments (OELEs) allow students to freely interact with the content and to discover important principles and concepts of the learning domain on their own. However, only some students possess the necessary skills for efficient and effective exploration. Guidance in the form of targeted interventions or feedback therefore has…

This paper addresses a key challenge in Educational Data Mining, namely to model student behavioral trajectories in order to provide a means for identifying students most at risk, with the goal of providing supportive interventions. While many forms of data including clickstream data or data from sensors have been used extensively in time series…

Personalized learning considers that the causal effects of a studied learning intervention may differ for the individual student. Making the inference about causal effects of studies interventions is a central problem. In this paper we propose the Residual Counterfactual Networks (RCN) for answering counterfactual inference questions, such as…

Recognizing the limitations of the existing frameworks and models applied to estimate the learning loss caused by COVID-19 across the world by different studies, and the urgent need for estimating such loss at the different education levels, this paper, employs the Education Value Chain Analysis ( EVCA) approach as a new paradigm, attempts to…