Exploratory structural equation (ESEM) has received increased attention in the methodological literature as a promising tool for evaluating latent variable measurement models. It overcomes many of the limitations attached to exploratory factor analysis (EFA) and confirmatory factor analysis (CFA), while capitalizing on the benefits of each. Given…

Debugging is essential for identifying and rectifying errors in programming, yet time constraints and students' trivialization of errors often hinder progress. This study examines differences in debugging challenges and strategies among students with varying computational thinking (CT) competencies using weekly coding journals from an online…

Qualitative comparative analysis (QCA) is a hybrid method designed to bridge the gap between qualitative and quantitative research in a case-sensitive approach that considers each case holistically as a complex configuration of conditions and outcomes. QCA allows for multiple conjunctural causation, implying that it is often a combination of…

In higher education, many universities in Taiwan let college students learn excel in a self-directed way. The current axle of the Excel curriculum mainly relies on self-directed learning. In the study, we designed the digital game "Legendary Wizard Excel" and took a certified Excel textbook as the research tool. The game we designed…

In the last few years, Qualitative Comparative Analysis (QCA) has become one of the most important data analysis methods in comparative research. According to the guidelines of this method, there are certain steps that a researcher needs to follow, before causally analyzing the data for necessary and sufficient conditions. One of these steps is…

This study aims to compare normality tests in different sample sizes in data with normal distribution under different kurtosis and skewness coefficients obtained simulatively. To this end, firstly, simulative data were produced using the MATLAB program for different skewness/kurtosis coefficients and different sample sizes. The normality analysis…

Systematic reviews are vital for guiding practice, research and policy, although they are often slow and labour-intensive. Large language models (LLMs) could speed up and automate systematic reviews, but their performance in such tasks has yet to be comprehensively evaluated against humans, and no study has tested Generative Pre-Trained…

This study explores the writing quality of two AI chatbots, OpenAI ChatGPT and Google Gemini. The research assesses the quality of the generated texts based on five essay models using the T.E.R.A. software, focusing on ease of understanding, readability, and reading levels using the Flesch-Kincaid formula. Thirty essays were generated, 15 from…

The capabilities of large language models (LLMs) in language comprehension, conversational interaction, and content generation have led to their widespread adoption across various educational stages and contexts. Given the fundamental role of education, concerns are rising about whether LLMs can serve as competent teachers. To address the…

Nowadays, SPOCs (Small Private Online Courses) have been used as complementary methods to support classroom teaching. SPOCs are courses that apply the usage of MOOCs (Massive Open Online Courses), combining classroom with online education, making them an exciting alternative for contexts such as emergency remote teaching. Although SPOCs have been…

Learning analytics dashboards are becoming increasingly common tools for providing feedback to learners. However, there is limited empirical evidence regarding the effects of learning analytics dashboard design features on learners' cognitive load, particularly in digital learning environments. To address this gap, we developed goal-based,…

Automatic essay scoring (AES) is an essential educational application in natural language processing. This automated process will alleviate the burden by increasing the reliability and consistency of the assessment. With the advances in text embedding libraries and neural network models, AES systems achieved good results in terms of accuracy.…

The Fuzzy Analytic Hierarchy Process (FAHP) was employed to evaluate and rank language-learning applications based on criteria such as engagement, interactivity, feedback, content quality and usability. A pairwise comparison matrix was constructed, fuzzy logic was applied to convert qualitative judgements into numerical values, and these values…

ChatGPT and Bard, two chatbots powered by Large Language Models (LLMs), are propelling the educational sector towards a new era of instructional innovation. Within this educational paradigm, the present investigation conducts a comparative analysis of these groundbreaking chatbots, scrutinizing their distinct operational characteristics and…

Web recommendation systems are ubiquitous in the world used to overcome the product overload on e-commerce websites. Among various filtering algorithms, Collaborative Filtering and Content Based Filtering are the best recommendation approaches. Being popular, these filtering approaches still suffer from various limitations such as Cold Start…