Related papers: Predicting community college astronomy performance…

This research was a qualitative transcendental phenomenological exploration of astronomy identity formation among astronomy majors and physics majors engaged in astronomy research. Participants (N=10), all of whom identified with…

We use four years of introductory astronomy scores to analyze the ability of the current population to perform college level work and measure the amount of grade inflation across various majors. Using an objective grading scale, one that is…

With the development of MOOCs massive open online courses, increasingly more subjects can be studied online. Researchers currently show growing interest in the field of MOOCs, including dropout prediction, cheating detection and achievement…

One of the important measures of quality of education is the performance of students in the academic settings. Nowadays, abundant data is stored in educational institutions about students which can help to discover insight on how students…

Machine learning methods tend to outperform traditional statistical models at prediction. In the prediction of academic achievement, ML models have not shown substantial improvement over logistic regression. So far, these results have…

Having observed low success rates among first-year university students in both Belgium and France, we develop prediction models in this paper in order to identify, at the earliest possible stage, those students who are at risk of failing at…

We summarize the first exploratory investigation into whether Machine Learning techniques can augment science strategic planning. We find that an approach based on Latent Dirichlet Allocation using abstracts drawn from high impact astronomy…

Online tools provide unique access to research students' study habits and problem-solving behavior. In MOOCs, this online data can be used to inform instructors and to provide automatic guidance to students. However, these techniques may…

Professional astronomy is historically not an environment of diverse identities. In recognizing that public outreach efforts affect career outcomes for young people, it is important to assess the demographics of those being reached and…

Creating equitable performance outcomes among students is a focus of many instructors and researchers. One focus of this effort is examining disparities in physics student performance across genders, which is a well-established problem.…

This textbook provides a systematic treatment of statistical machine learning for astronomical research through the lens of Bayesian inference, developing a unified framework that reveals connections between modern data analysis techniques…

An educational institution needs to have an approximate prior knowledge of enrolled students to predict their performance in future academics. This helps them to identify promising students and also provides them an opportunity to pay…

Predicting performance outcomes has the potential to transform training approaches, inform coaching strategies, and deepen our understanding of the factors that contribute to athletic success. Traditional non-automated data analysis in…

Improving undergraduate success in STEM requires identifying actionable factors that impact student outcomes, allowing institutions to prioritize key leverage points for change. We examined academic, demographic, and institutional factors…

Modeling and predicting the performance of students in collaborative learning paradigms is an important task. Most of the research presented in literature regarding collaborative learning focuses on the discussion forums and social learning…

The credit scoring risk management is a fast growing field due to consumer's credit requests. Credit requests, of new and existing customers, are often evaluated by classical discrimination rules based on customers information. However,…

This research investigates the use of machine learning methods to forecast students' academic performance in a school setting. Students' data with behavioral, academic, and demographic details were used in implementations with standard…

Instructors have limited time and resources to help struggling students, and these resources should be directed to the students who most need them. To address this, researchers have constructed models that can predict students' final course…

Now-a-days the amount of data stored in educational database increasing rapidly. These databases contain hidden information for improvement of students' performance. Educational data mining is used to study the data available in the…

We are totally immersed in the Big Data era and reliable algorithms and methods for data classification are instrumental for astronomical research. Random Forest and Support Vector Machines algorithms have become popular over the last few…