Randomized experiments involving education interventions are typically implemented as cluster randomized trials, with schools serving as clusters. To design such a study, it is critical to understand the degree to which learning outcomes vary between versus within clusters (schools), specifically the intraclass correlation coefficient. It is also…

This article offers a diffractive methodological intervention into workplace studies of academic life. In its engagement of a playful, performative research and writing practice, the article speaks back to technocratic organisational and sociological workplace 'time and motion' studies which centre on the human and rational, and presume a linear…

Low-cost devices have widened the use of multimodal data in experiments providing a more complete picture of behavioural effects. However, the accurate collection and combination of multimodal and behavioural data in a manner that enables reproducibility is challenging and often requires researchers to refine their approaches. This paper presents…

To identify the ways teachers and educational systems can improve learning, researchers need to make causal inferences. Analyses of existing datasets play an important role in detecting causal patterns, but conducting experiments also plays an indispensable role in this research. In this article, we advocate for experiments to be embedded in real…

The benefits of undergraduate research are well documented, and many colleges and universities include a senior research requirement for graduation. In addition, most science curricula attempt to include discoverystyle, laboratory components to prepare students for their research experiences and to expose them to research methods in different…

In this paper, we study how to support a human tutor who regulates learners' activities, in a situation of mediated tutoring. Our goal is to provide the tutor with information about the effect of his/her interventions. To achieve this, we adopt an indicator-based approach and define the notion of meta-indicator. The distinguishing feature of…

The most important dimension of learning is the content, and a Learning Management System (LMS) suffices this to a certain extent. The present day LMS are designed to primarily address issues like ease of use, search, content and performance. Many surveys had been conducted to identify the essential features required for the improvement of LMS,…

This report describes in detail how researchers, policymakers, and program administrators can recognize opportunities for experiments and carry them out. Specifically, the report focuses on opportunistic experiments, defined as randomized controlled trials (RCTs) that study the effects of initiatives, program changes, or policy actions that…

Predicting the success or failure of a student in a course or program is a problem that has recently been addressed using data mining techniques. In this paper we evaluate some of the most popular classification and regression algorithms on this problem. We address two problems: prediction of approval/failure and prediction of grade. The former is…

This article describes a predictive model that assesses whether a student will have greater perceived learning in group assignments or in individual work. The model produces correct classifications 87.5% of the time. The research is notable in that it is the first in the education literature to adopt a predictive modeling methodology using data…

To investigate student difficulties in solving word problems in algebra, we carried out a teaching experiment involving 51 Indonesian students (12/13 year-old) who used a digital mathematics environment. The findings were backed up by an interview study, in which eighteen students (13/14 year-old) were involved. The perspective of mathematization,…

An opportunistic experiment is a type of randomized controlled trial that studies the effects of a planned intervention or policy change with minimal added disruption and cost. This guide defines opportunistic experiments and provides examples, discusses issues to consider when identifying potential opportunistic experiments, and outlines the…

This article presents a new approach to online graduate education. With hopes of recruiting a larger cohort in order to preserve a graduate program struggling with low enrollment, we began offering a limited number of seats to students who would attend class in real time but from remote locations, using a videoconferencing platform. Unlike…

In this paper, we describe an in-class experiment that is easy to implement with large groups of students. The experiment takes approximately 15-20 minutes to run and involves each student completing one of four types of Sudoku puzzles and recording the time it takes to completion. The resulting data set can be used as a teaching tool at an…

New high-frequency, automated data collection and analysis algorithms could offer new insights into complex learning processes, especially for tasks in which students have opportunities to generate unique open-ended artifacts such as computer programs. These approaches should be particularly useful because the need for scalable project-based and…