Random Equating (RE) and Heuristic Approach (HA) are two linking procedures that may be used to compare the scores of individuals in two tests that measure the same latent trait, in conditions where there are no common items or individuals. In this study, RE--that may only be used when the individuals taking the two tests come from the same…

Information and communication technology (ICT) has become an essential part of the daily lives of tertiary students. However, research into assessing digital competency and its effects on academic performance is still limited. This paper explores students' needs for digital competence, the impact of digital access on academic performance, and the…

In this study, technology-enhanced statistical problem-solving tasks designed by pre-service teachers (PTs) were examined. The PTs designed 28 tasks. The designed tasks were analyzed within the context of the Considerations for Design and Implementation of Statistics Tasks (C-DIST) components. It was revealed that the tasks were mostly designed…

Intelligent tutoring systems (ITS) have been shown to be highly effective at promoting learning as compared to other computer-based instructional approaches. However, many ITS rely heavily on expert design and hand-crafted rules. This makes them difficult to build and transfer across domains and limits their potential efficacy. In this paper, we…

Feedback on how students progress through completing subgoals can improve students' learning and motivation in programming. Detecting subgoal completion is a challenging task, and most learning environments do so either with "expert-authored" models or with "data-driven" models. Both models have advantages that are…

The growing interest of educational researchers in computational thinking (CT) has led to an expanding literature on assessments of CT skills and attitudes. However, few studies have examined whether CT attitudes influence CT skills. The present study examines the relationship between CT attitudes and CT skills for preservice teachers (PSTs). The…

This study focuses on how the quality of students' arguments and their conceptions of data and evidence change as a result of experiencing two types of laboratory courses, one employing a scripted inquiry approach and the other employing argument-driven inquiry. The analysis explores the connections between students' conceptions of data and…

The present study examines the difficulties novice data modelers face when asked to provide a data model addressing a given problem. In order to map these difficulties and their causes, two short data modeling problems were given to 82 students who had completed an introductory course in database modeling. Both problems involve three entity sets…

The African Data Initiative started as a crowd-sourced campaign to improve the teaching of statistics in African universities. The analysis of climate data provides one suitable context to illustrate ideas that lead to a radical new form of teaching. The problem within the context comes first, the technicalities are largely reduced -- mathematics…

We have been incrementally adding data-driven methods into the Deep Thought logic tutor for the purpose of creating a fully data-driven intelligent tutoring system. Our previous research has shown that the addition of data-driven hints, worked examples, and problem assignment can improve student performance and retention in the tutor. In this…

In partnership with both formal and informal learning institutions, researchers have been building a suite of online games, called choicelets, to serve as interactive assessments of learning skills, e.g. critical thinking or seeking feedback. Unlike more traditional assessments, which take a retrospective, knowledge-based view of learning,…

Learner modeling, a challenging and complex endeavor, is an important and oft-studied research theme in computer-supported education. From this perspective, Educational Data Mining (EDM) research has focused on modeling and comprehending various dimensions of learning in computer-based learning environments (CBLE). Researchers and designers are…

The use of data to track and manage progress is critical to a collective impact initiative achieving results or understanding impact. Yet, little research has been done to determine how collective impact practitioners can effectively use data. This article--including a literature review, semistructured interviews with experts on performance…

This study discusses aspects of the association between Mathematical Modeling (MM) and Big Data in the scope of mathematical education. We present an example of an activity to discuss two ontological factors that involve MM. The first is linked to the modeling stages. The second involves the idea of pedagogical objectives. The main findings…

With the latest re-authorization of the Individuals with Disabilities Education Improvement Act (IDEA, 2004), states are allowed to use a Response to Intervention (RtI) framework to determine whether students qualify for special education services. Although RtI has promise and has been implemented well with documented results, further research is…