This study proposes a Bayesian method for diagnostic classification models (DCMs) for a partially known Q-matrix setting between exploratory and confirmatory DCMs. This Q-matrix setting is practical and useful because test experts have pre-knowledge of the Q-matrix but cannot readily specify it completely. The proposed method employs priors for…

Topic models are mathematical and statistical models used to analyze textual data. The objective of topic models is to gain information about the latent semantic space of a set of related textual data. The semantic space of a set of textual data contains the relationship between documents and words and how they are used. Topic models are becoming…

As the development and application of large language models (LLMs) in physics education progress, the well-known AI-based chatbot ChatGPT4 has presented numerous opportunities for educational assessment. Investigating the potential of AI tools in practical educational assessment carries profound significance. This study explored the comparative…

This study examines the efficacy of artificial intelligence (AI) in creating parallel test items compared to human-made ones. Two test forms were developed: one consisting of 20 existing human-made items and another with 20 new items generated with ChatGPT assistance. Expert reviews confirmed the content parallelism of the two test forms.…

This research explores students' homework engagement across three dimensions: (a) cognitive, (b) emotional, and (c) behavioral activities, specifically contrasting private and public secondary schools in Addis Ababa. A qualitative research methodology was utilized, with reliability and validity assessments carried out through peer review, site…

This paper comprehensively evaluates the online learning experience of secondary and senior secondary school students during COVID-19 in India. Nine hypotheses have been developed to explore the implications of students' online experiences and identify students' learning experiences using online platforms in contrast to their experience in…

This dissertation investigates the application of network models in educational assessment across diverse learning settings, encompassing both clinical and classroom environments. As educational paradigms shift and digital tools become more embedded in learning processes, traditional assessment methods often fall short in effectively capturing the…