Research on self-assessment has overwhelmingly conceptualized it as a product and treated students as a homogeneous group, restraining our understanding of the topic. To address this gap, this study aimed to identify different student profiles based on their self-assessment and to examine how it related to their learning achievement over time.…

This study aims to discover groups of students enrolled in the emergency remote teaching online course based on the various course-related data collected throughout the first year of COVID-19 pandemic. Research was conducted among 222 students enrolled in the course "Business Informatics" at the Faculty of Organization and Informatics of…

Conventional methods for evaluating the utility of subscores rely on traditional indices of reliability and on correlations among subscores. One limitation of correlational methods is that they do not explicitly consider variation in subtest means. An exception is an index of score profile reliability designated as [G], which quantifies the ratio…

Background: Promoting and improving STEM education is being driven by economic concerns as modern economies have a rising demand for qualified researchers, technicians, and other STEM professionals. In addition, women remain under-represented in STEM-related fields, with significant economic and societal consequences. Abundant research has shown…

This research uses a three-phase method to evaluate and forecast the academic efficiency of engineering programs. In the first phase, university profiles are created through cluster analysis. In the second phase, the academic efficiency of these profiles is evaluated through Data Envelopment Analysis. Finally, a machine learning model is trained…

Developmental surveillance tools are used to closely monitor the early development of infants and young children. This study provides a novel implementation of a multidimensional item response model, using Bayesian hierarchical priors, to construct developmental profiles for a small sample of children (N = 115) with sparse data collected through…

This convergent mixed-methods study examined the distinct burnout profiles of novice school counselors and their respective professional experiences. A cluster analysis yielded a three-factor solution revealing unique burnout profiles. Qualitative analyses identified job-related challenges and resources impacting the work performance of novice…

With the U.S. adult education system providing education services to millions of immigrants annually, understanding the unique skills and assets among adult immigrant learners is important. Using data from the U.S. Program for the International Assessment of Adult Competencies, this study used data on immigrants (n = 1,873) to identify latent…

The present study illustrates the utility of applying multilevel mixture models in educational research, using data on the homework behavior of 1,812 Swiss eighth-grade students in French as a second language. A previous person-centered study identified 5 homework learning types characterized by different patterns of high or low homework time and…

In this paper, we describe a theoretically-grounded data mining approach to identify types of collaborative problem solvers based on students' interactions with an online simulation-based task about electronics concepts. In our approach, we developed an ontology to identify the theoretically-grounded features of collaborative problem solving…

The study aims at investigating students' learning/defence profiles. It also explores students' profiles during different years of study. Participants comprised of 425 undergraduates. They completed the 'Approaches to Study and Skills Inventory' and the 'Defense Style Questionnaire'. The students' academic achievement was measured through grade…

This study uses a complexity-accuracy-lexis-fluency (CALF) framework to explore performance on 2 speaking tasks: a narrative picture-based task and an interactive decision-making task. A preliminary aim is to compare performance on the 2 tasks, using a wide range of CALF measures to explore where scores are similar and where they are different.…

Survey data are usually of mixed type (quantitative, multistate categorical, and/or binary variables). Multidimensional scaling (MDS) is one of the most extended methodologies to visualize the profile structure of the data. Since the past 60s, MDS methods have been introduced in the literature, initially in publications in the psychometrics area.…

Background: Research suggests that considerable individual differences may exist among preschool children in terms of emergent writing performance. However, there is no study examining this variability. Objective: This research explored the patterns of within-group individual differences in the emergent writing skills of preschool children.…

Research Findings: Using a sample of 568 students from 61 kindergarten classrooms whose primary caregivers completed a questionnaire describing their child's early childhood education and care (ECEC) by year from birth to pre-kindergarten, we identified seven pathways characterizing children's ECEC experiences using a latent class analysis. Once…