Background and Context: Feedback on one's progress is essential to new programming language learners, particularly in out-of-classroom settings. Though many study materials offer assessment mechanisms, most do not examine the accuracy of the feedback they deliver, nor give evidence on its validity. Objective: We investigate the potential use of a…

Educational games have gained widespread interest among teachers and researchers across various fields due to their capacity to engage students, foster active participation, and improve learning outcomes. In the context of computer programming, which demands significant cognitive effort, the use of educational games has grown substantially. While…

The reliability of assessment tools is critical for accurately monitoring student performance in various educational contexts. When multiple assessments are combined to form an overall evaluation, each assessment serves as a data point contributing to the student's performance within a broader educational framework. Determining composite…

Background and Context: Students' programming projects are often assessed on the basis of their tests as well as their implementations, most commonly using test adequacy criteria like branch coverage, or, in some cases, mutation analysis. As a result, students are implicitly encouraged to use these tools during their development process (i.e., so…

This paper proposes to evaluate learning efficiency by implementing the flipped classroom and automatic source code evaluation based on the Kirkpatrick evaluation model in students of CS1 programming course. The experimentation was conducted with 82 students from two CS1 courses; an experimental group (EG = 56) and a control group (CG = 26). Each…

At an unrivaled and enduring pace, computing has transformed the world, resulting in demand for a universal fourth foundation beyond reading, writing, and arithmetic: computational thinking (CT). Despite increasingly widespread acceptance of CT as a crucial competency for all, transforming education systems accordingly has proven complex. The…

The multiple imputation two-stage (MI2S) approach holds promise for evaluating the model fit of structural equation models for ordinal variables with multiply imputed data. However, previous studies only examined the performance of MI2S-based residual-based test statistics. This study extends previous research by examining the performance of two…

A frequent criticism of exploratory factor analysis (EFA) is that it does not allow correlated residuals to be modelled, while they can be routinely specified in the confirmatory (CFA) model. In this article, we propose an EFA approach in which both the common factor solution and the residual matrix are unrestricted (i.e., the correlated residuals…

In psychology, researchers are often interested in testing hypotheses about mediation, such as testing the presence of a mediation effect of a treatment (e.g., intervention assignment) on an outcome via a mediator. An increasingly popular approach to testing hypotheses is the Bayesian testing approach with Bayes factors (BFs). Despite the growing…

Evidence-based programs and grassroots programs are often adapted during implementation. Adaptations are often hidden, ignored, or punished. Although some adaptations stem from lack of organizational capacity, evaluators report other adaptations happen in good faith or are efforts to better fit the local context. Program implementers, facilitators…

Knowledge components (KCs) have many applications. In computing education, knowing the demonstration of specific KCs has been challenging. This paper introduces an entirely data-driven approach for: (1) discovering KCs; and (2) demonstrating KCs, using students' actual code submissions. Our system is based on two expected properties of KCs: (1)…

An overview of reviews aims to collect, assess, and synthesize evidence from multiple systematic reviews (SRs) on a specific topic using rigorous and reproducible methods. An important methodological challenge in conducting an overview of reviews is the management of overlapping data due to the inclusion of the same primary studies in SRs. We…

Knowledge tracing (KT) models are a popular approach for predicting students' future performance at practice problems using their prior attempts. Though many innovations have been made in KT, most models including the state-of-the-art Deep KT (DKT) mainly leverage each student's response either as correct or incorrect, ignoring its content. In…

For the last decades, programming courses are being taught in nearly every educational sector. Students are now more likely to use an e-learning platform compared to traditional system because of lower internet costs, remote access, and faster communication facilities. For a programming course studied in both manual and e-learning platforms,…

Systematic reviews (SRs) have an important role in the healthcare decision-making practice. Assessing the overall confidence in the results of SRs using quality assessment tools, such as "A MeaSurement Tool to Assess Systematic Reviews 2" (AMSTAR 2), is crucial since not all SRs are conducted using the most rigorous methods. In this…