In classroom assessments, examinees can often answer test items multiple times, resulting in sequential multiple-attempt data. Sequential diagnostic classification models (DCMs) have been developed for such data. As student learning processes may be aligned with a hierarchy of measured traits, this study aimed to develop a sequential hierarchical…

In the contemporary world of digitalisation, comprehensive digital competence (DC) is and should be an integral part of students' repertoire to guarantee not only academic but also professional success. However, the level and requirements for DC may vary within specific educational contexts, especially in culturally oriented institutions. This…

In recent years, knowledge tracing (KT) within intelligent tutoring systems (ITSs) has seen rapid development. KT aims to assess a student's knowledge state based on past performance and predict the correctness of the next question. Traditional KT often treats questions with different difficulty levels of the same concept as identical…

In classroom assessments, examinees can often answer test items multiple times, resulting in sequential multiple-attempt data. Sequential diagnostic classification models (DCMs) have been developed for such data. As student learning processes may be aligned with a hierarchy of measured traits, this study aimed to develop a sequential hierarchical…

Example-generation tasks have been suggested as an effective way to both promote students' learning of mathematics and assess students' understanding of concepts. E-assessment offers the potential to use example-generation tasks with large groups of students, but there has been little research on this approach so far. Across two studies, we…

Designing and constructing pedagogical tests that contain items (i.e. questions) which measure various types of skills for different levels of students equitably is a challenging task. Teachers and item writers alike need to ensure that the quality of assessment materials is consistent, if student evaluations are to be objective and effective.…

Science education reforms advocate modeling as a core practice in which "analogy" is a significant form and "analogical modeling" is a creative process for scientific explanation and discovery. This study adopts the self-generated analogical modeling approach involving electricity, which considers all the modeling subprocesses…

The pervasive issue of cheating in educational tests has emerged as a paramount concern within the realm of education, prompting scholars to explore diverse methodologies for identifying potential transgressors. While machine learning models have been extensively investigated for this purpose, the untapped potential of TabNet, an intricate deep…

Teachers need to judge students accurately to ensure social justice within classrooms. Currently, many reviews have estimated how accurately teachers overall judge students, but only a few provided clues about how teachers' accuracy could be improved. To provide insight regarding the sources of teachers' (in)accuracy, we review and synthesise lens…

Written comments in student evaluations of teaching offer a rich source of data for understanding instructors' teaching and students' learning experiences. However, most previous studies on student evaluations of teaching have focused on numeric ratings of close-ended questions, while few studies have tried to analyze the content of students'…

In this study, we introduced a cross-classified multidimensional nominal response model (CC-MNRM) to account for various response styles (RS) in the presence of cross-classified data. The proposed model allows slopes to vary across items and can explore impacts of observed covariates on latent constructs. We applied a recently developed variant of…

Short-Answer Grading (SAG) is a time-consuming task for teachers that automated SAG models have long promised to make easier. However, there are three challenges for their broad-scale adoption: A technical challenge regarding the need for high-quality models, which is exacerbated for languages with fewer resources than English; a usability…

Program-level assessment is a holistic approach for arranging assessments throughout a degree program that supports sequential development of discipline knowledge, transferable skills and career readiness. Currently, the modular arrangement of courses means that student learning is partial, limited to passing the assessment and compartmentalized…

Background: Increasingly, students are using ChatGPT to assist them in learning and even completing their assessments, raising concerns of academic integrity and loss of critical thinking skills. Many articles suggested educators redesign assessments that are more 'Generative-AI-resistant' and to focus on assessing students on higher order…

Teaching equitable clinical practice is of critical importance, yet how best to do so remains unknown. Educators utilize implementation science frameworks to disseminate clinical evidence-based practices (EBP). The Health Equity Implementation Framework (HEIF) is one of these frameworks, and it delineates how health equity may be concomitantly…