Assessing students' performance in online learning could be executed not only by the traditional forms of summative assessments such as using essays, assignments, and a final exam, etc. but also by more formative assessment approaches such as interaction activities, forum posts, etc. However, it is difficult for teachers to monitor and assess…

The purpose of this descriptive research study was to evaluate the web-based practice experience tracking system at a school of public health (SPH) at a large southeastern university. Applied practice experiences (APEs) are a key component of public health education, and schools and programs of public health in the United States must provide…

The challenge: This paper examines the state of knowledge and evaluation in prison higher education. Little is known about its efforts, outcomes, and impact or about the students enrolled in such efforts. Potential consequences: Incarcerated college students are a disenfranchised population with restricted autonomy. Without understanding prison…

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…

Medical schools are required to assess and evaluate their curricula and to develop exam questions with strong reliability and validity evidence, often based on data derived from statistically small samples of medical students. Achieving a large enough sample to reliably and validly evaluate courses, assessments, and exam questions would require…

In the educational landscape, educational data mining has emerged as an indispensable tool for institutions seeking to deliver exceptional and high-quality education. However, education data revealed suboptimal academic performance among a significant portion of the student population, which consequently resulted in delayed graduation. This…

As a result of increasing complexity of assessing all aspects of human behaviours, a lot of data are generated on individual learner and from teachers and the system. What qualifies as big data in assessment in Nigeria? This research identifies the sources of assessment big data in Nigeria, investigates how the big data are generated and…

The purpose of this study was to evaluate the use of behavioral skills training (BST) that included video vignettes used for modeling and rehearsal to train preservice general educators how to collect accurate antecedent-behavior-consequence (ABC) data using a structured recording format. The effectiveness of the intervention was evaluated within…

Assessing group work formatively in higher education poses a significant challenge. The complexity of evaluating individual contributions is compounded by the lack of efficient and effective methods for tracking, analysing and assessing individual engagement and contributions, which can impede timely feedback and the development of group work…

We turn a critical lens to ethical research practices in the context of 'insider' higher education research. Tensions arise due to the risks involved in navigating academic identity and teacher-researcher authenticity. We offer two case studies where ethical tensions surfaced methodological concerns for researchers and participants. Case study one…

The teaching performance expectations and assignments that preservice art teachers currently address in field experiences and in their coursework are designed to help them meet the expectations of being a quality art educator in the 21st century. These assignments may be very different from the assignments that art educators had in their…

The rapid development of online education has underscored the necessity of data-driven teaching functions for enhancing teaching quality and efficiency. This paper investigates the role of data-driven approaches in online education, with a particular focus on the practical application of data for evaluating learning outcomes. It highlights the…

Although faculty are an important part of collecting, analyzing, and using student learning data for improvement, significant barriers often prevent faculty from being involved in assessment work outside the classroom. One potential obstacle to faculty involvement in assessment is the misalignment between the work and faculty rewards structures.…

Artificial intelligence (AI) and operations research (OR) have long been intertwined because of their synergistic relationship. Given the increasing popularity of AI and machine learning in particular, we face growing demand for educational offerings in this area from our students. This paper describes two courses that introduce machine learning…

Overview and Problem of Practice: The evaluation of student learning in higher education is of interest to many stakeholders including students, faculty, higher education administrators, employers, governmental entities, and accreditors. Despite this interest, many institutions struggle to successfully facilitate the process of evaluating student…