This research examines the relationship between prerequisite algebra knowledge and graduate corporate finance course performance. Standardized math questions designed for an undergraduate introductory finance course also predict quantitative performance metrics among 128 business graduate students. Results demonstrate that prerequisite math…

Community colleges often employ measures to determine student course placement. Though much research has examined the predictive validity of placement measures such as ACT or high-school GPA, little research examines the effects of students' traditional and non-traditional status. Using data from a rural state community college, we examined the…

A multitude of research shows that the secondary education (SE) outcomes relate with university academic achievement (AA). More research is needed on SE outcomes subject-specifically. We examined the relationship between the Finnish matriculation examination (ME) results and AA, study success (grades) and study progress (credits), of educational…

Neural networks are ubiquitous in applied machine learning for education. Their pervasive success in predictive performance comes alongside a severe weakness, the lack of explainability of their decisions, especially relevant in humancentric fields. We implement five state-of-the-art methodologies for explaining black-box machine learning models…

We investigate two research questions using a recent statewide transition from paper to computer-based testing: first, the extent to which test mode effects found in prior studies can be eliminated in large-scale administration; and second, the degree to which online and paper assessments offer different information about underlying student…

We investigate two research questions using a recent statewide transition from paper to computer-based testing: first, the extent to which test mode effects found in prior studies can be eliminated; and second, the degree to which online and paper assessments offer different information about underlying student ability. We first find very small…

This study aims to employ the supervised machine learning algorithms to examine factors that negatively impacted academic performance among college students on probation (underperforming students). We used the Knowledge Discovery in Databases (KDD) methodology on a sample of N = 6514 college students spanning 11 years (from 2009 to 2019) provided…

The COVID-19 pandemic has affected the way we learn, teach and support students in many different ways. In particular, the impact of the pandemic on the mathematical capabilities of students arriving at university is now starting to be seen and reported. Students arriving at UK universities in 2021, and having completed their A levels in 2021, had…

Education plays a major role in the development of the consciousness of the whole society. Education has been improved by analyzing educational data related to student academic performance. By using data mining techniques and algorithms on data from the educational environment, students' performances can be predicted. In this study, a novel Hybrid…

The COVID-19 pandemic constrained higher education institutions to switch to online teaching, which led to major changes in students' learning behavior, affecting their overall performance. Thus, students' academic performance needs to be meticulously monitored to help institutions identify students at risk of academic failure, preventing them…

Past studies have explored student self-perception within chemistry courses. Various factors have been explored including course level, student academic background, and gender. However, it appears that there are few (if any) studies that have looked at whether students are aware of how they have performed previously in the course. Through a study…

The present research evaluated whether behavioral tasks ("direct assessments") commonly used to assess young children's social cognitive development in laboratory studies could have utility for measuring and predicting U.S. children's outcomes in educational contexts. To do so, children (N = 95; 49 boys, 46 girls; 41.05% White, 16.84%…

The study investigated the joint contribution of the self-regulated learning (SRL) and individual differences approaches to the prediction of university students' grade point average (GPA) obtained at three separate time points throughout their degree (3 years). We assessed cognitive (i.e., previous academic performance, cognitive ability, and…

We address the problem of predicting the correctness of the student's response on the next exam question based on their previous interactions in the course of their learning and evaluation process. We model the student performance as a dynamic problem and compare the two major classes of dynamic neural architectures for its solution, namely the…

As universities around the world have begun to use learning management systems (LMSs), more learning data have become available to gain deeper insights into students' learning processes and make data-driven decisions to improve student learning. With the availability of rich data extracted from the LMS, researchers have turned much of their…