While research has shown that students' epistemic beliefs can be a strong predictor of their academic performance, cognitive abilities, or self-efficacy, studies of this topic in computer education are rare. The purpose of this study was twofold. First, it aimed to validate a newly developed questionnaire for measuring students' epistemic beliefs…

The electricity-related topics in the secondary school science curriculum are near-universal standards across countries. We prepared a three-stage robotic STEM program incorporating coding, robotic integrated science (in the topic of electricity), STEM engineering processes, and their educational structures. We investigated the impact of the…

At present, the traditional education quality evaluation system has some problems, such as insufficient data processing ability and poor real-time performance, which is difficult to meet the needs of teaching quality improvement in rapidly developing higher vocational colleges. In order to solve such problems, this paper designs an intelligent…

The American College Personnel Association recognized the increased prominence of digital technologies in student affairs work, developing a technology competency area that includes foundational, intermediate, and advanced objectives for data use. However, as the role of technology use in student affairs practice rapidly changes, it is…

This study aimed to visualize self-regulated learning (SRL) behaviors performed by users from an online teacher professional development platform called the EdHub Library using the pm4py algorithm in Python to parse event data during the first 30 days of the school year and the first 90 days of the COVID-19 pandemic in March 2020. Process mining…

Rough set theory (RST) was proposed by Zdzistaw Pawlak (Pawlak,1982) as a methodology for data analysis using the notion of discernibility of objects based on their attribute values. The main advantage of using RST approach is that it does not need additional assumptions--like data distribution in statistical analysis. Besides, it provides…

The purpose of this research was to determine classification accuracy of the factors affecting the success of students' reading skills based on PISA 2018 data by using Artificial Neural Networks, Decision Trees, K-Nearest Neighbor, and Naive Bayes data mining classification methods and to examine the general characteristics of success groups. In…

This dissertation presents two essays on econometric methods for program evaluation and policy choice. In Chapter 1, I develop a statistically optimal way of using data to make policy decisions when the performance of counterfactual policies is only partially identified. Specifically, I consider a class of statistical decision problems in which…

Clustering, a prevalent class of machine learning (ML) algorithms used in data mining and pattern-finding--has increasingly helped engineering education researchers and educators see and understand assessment patterns at scale. However, a challenge remains to make ML-enabled educational inferences that are useful and reliable for research or…

Various studies have been conducted on applying intelligent recognition technology, especially speech recognition technology to improve English learning ability, mostly listening and speaking. However, few studies have touched on how image-to-text recognition technology can be used for writing. The present research was conducted to fill this gap…

Academic scholars face a difficult challenge when attempting to grasp the intricate world of mathematics. The complexity of mathematical concepts often lies hidden beneath layers of formulas and procedures, obscuring their true essence. Traditional educational resources often fall short in conveying the profound meaning behind these concepts,…

The first books in Polish about the Pascal programming language appeared in the late 1970s, and were soon followed by a Polish translation of Niklaus Wirth's book "Algorithms + Data Structures = Programs." At that time, many efforts were made to prepare teachers to teach informatics in schools, and Pascal was one of the topics taught,…

A majority of research in Computational Thinking (CT) mainly focuses on teaching coding to school students. However, CT involves more than just coding and includes other skills like algorithmic thinking. The current study developed an Online Inquiry-based Learning Platform for Computational Thinking (CT-ONLINQ) that follows Inquiry-Based Learning…

In this paper, to handle the problem of the quick evolution of cyber-security attacks, we developed the iMonsters board game and proposed the attack and defense knowledge self-evolving algorithm. Three versions of the iMonsters were launched in 2013, 2017, and 2019, respectively. Accordingly, the cyber-security ontology can be refined by the…

In-class group work activities are found to promote the interpersonal skills of learners. To support the teachers in facilitating such activities, we designed a learning analytics-enhanced technology framework, Group Learning Orchestration Based on Evidence (GLOBE) using data-driven approaches. In this study, we implemented the algorithmic group…