Bayesian Knowledge Tracing, a model used for cognitive mastery estimation, has been a hallmark of adaptive learning research and an integral component of deployed intelligent tutoring systems (ITS). In this paper, we provide a brief history of knowledge tracing model research and introduce pyBKT, an accessible and computationally efficient library…

Learning to code is far from an easy task, it is a promising approach that underscores the use of the video game culture of students to motivate them to invest their time in the practice of programming. The students in this discipline are often discouraged by the amount of information to remember and the complex and constraining syntaxes.…

Educational process mining is now a promising method to provide decision-support information for the teaching-learning process via finding useful educational guidance from the event logs recorded in the learning management system. Existing studies mainly focus on mining students' problem-solving skills or behavior patterns and intervening in…

Creating practice questions for programming learning is not an easy job. It requires the instructor to diligently organize heterogeneous learning resources. Although educational technologies have been adopted across levels of programming learning, programming question generation (PQG) is still predominantly performed by instructors without…

The ability to efficiently optimize or re-optimize an algorithm for high performance on a particular processor architecture is crucial in a wide spectrum of engineering and scientific applications. To help bridge the gap between fully automated optimization, which does not reliably produce optimal code, and fully manual optimization, which is…

Novice programmers, who have yet to form effective mental models of the domain, often experience high cognitive load, low confidence, and high anxiety, negatively affecting learning and retention rates. These cognitive and affective limitations pose an instructional challenge. This study aimed to investigate the effectiveness of a whole-task…

Since the late twentieth century, with the development of the Internet of Things (IoT), the IoT covers the application of comprehensive knowledge and technology in the fields of circuitry, physics, mechanics, and information, making it a suitable topic for hands-on science, technology, engineering, and mathematics (STEM) activities. The IoT covers…

Wheel-spinning refers to the failure to master a skill in a timely manner or after a considerable number of practice opportunities. Several past studies have developed wheel-spinning models in the areas of Mathematics and Physics. However, no models have been made for the context of novice programming. The purpose of this study was to develop…

Self-efficacy is seen as a barrier for youth, females in particular, to enter computer science (CS). In this study, I presented a near-peer mentoring model that focused on changing the mentee's self-efficacy in CS. The present study had three objectives: (a) to design a near-peer mentoring model (i.e., a conceptual model) around the sources of…

This paper presents an authoring tool in the cMOOC context called MOOCAT (MOOC Authoring Tool). It is a visual authoring tool that helps teachers to design cMOOC-oriented pedagogical scenarios. MOOCAT has two main innovative features. The first is that it offers a tool for conceiving pedagogical scenarios in a simple way through graphical…

We developed a near-peer mentoring model for high school youth to mentor middle school youth on how to program using MIT App Inventor. The purpose of this study was to investigate: (a) the effectiveness of the near-peer mentoring model for the mentees; and (b) how the mentees' vicarious experience with the near-peer mentors led to changes in their…

This study explored teachers' conceptualizations of integrated computational modeling in secondary physics by exposing twelve experienced physics teachers to programming and then analyzing interview responses. Responses revealed that teachers fell along a spectrum of disciplinary boundary-stretching mentalities. This paper presents a preliminary…

The purpose of this research was to compare the performances of the Fixed Effect Model (FEM) and the Random Effects Model (REM) in the meta-analysis studies conducted through 5, 10, 20 and 40 studies with an outlier and 4, 9, 19 and 39 studies without an outlier in terms of estimated common effect size, confidence interval coverage rate and…

Predictive learning analytics has been widely explored in educational research to improve student retention and academic success in an introductory programming course in computer science (CS1). General-purpose and interpretable dropout predictions still pose a challenge. Our study aims to reproduce and extend the data analysis of a privacy-first…

Learning standards for K-12 science education emphasize the importance of engaging students in practices that scientists perform in their profession. K-12 teachers are expected to engage students in scientific modeling, which entails constructing, testing, evaluating, and revising their own models of science phenomena while pursuing an epistemic…