Mining big data in education: Affordances and challenges
The emergence of big data in educational contexts has led to new data-driven approaches
to support informed decision making and efforts to improve educational effectiveness. Digital …
to support informed decision making and efforts to improve educational effectiveness. Digital …
Student performance analysis and prediction in classroom learning: A review of educational data mining studies
Student performance modelling is one of the challenging and popular research topics in
educational data mining (EDM). Multiple factors influence the performance in non-linear …
educational data mining (EDM). Multiple factors influence the performance in non-linear …
Examining Students' Online Course Perceptions and Comparing Student Performance Outcomes in Online and Face-to-Face Classrooms.
D Spencer, T Temple - Online Learning, 2021 - ERIC
Through the use of existing grade and student survey data, this study investigated online
courses offered at a public four-year university. Specifically, the study explored differences in …
courses offered at a public four-year university. Specifically, the study explored differences in …
Predicting achievement and providing support before STEM majors begin to fail
ML Bernacki, MM Chavez, PM Uesbeck - Computers & Education, 2020 - Elsevier
Prediction models that underlie “early warning systems” need improvement. Some predict
outcomes using entrenched, unchangeable characteristics (eg, socioeconomic status) and …
outcomes using entrenched, unchangeable characteristics (eg, socioeconomic status) and …
Predicting student outcomes using digital logs of learning behaviors: Review, current standards, and suggestions for future work
CJ Arizmendi, ML Bernacki, M Raković… - Behavior research …, 2023 - Springer
Using traces of behaviors to predict outcomes is useful in varied contexts ranging from buyer
behaviors to behaviors collected from smart-home devices. Increasingly, higher education …
behaviors to behaviors collected from smart-home devices. Increasingly, higher education …
Practical early prediction of students' performance using machine learning and eXplainable AI
Predicting students' performance in advance could help assist the learning process; if “at-
risk” students can be identified early on, educators can provide them with the necessary …
risk” students can be identified early on, educators can provide them with the necessary …
Early prediction of learners at risk in self-paced education: A neural network approach
To address the demands of modern education and increase flexibility, many higher
education institutions are considering self-paced education programs. However, student …
education institutions are considering self-paced education programs. However, student …
Designing, developing, and validating a measure of undergraduate students' conceptions of artificial intelligence in education
The purpose of this research study is to design, develop, and validate an instrument for
measuring undergraduate students' conceptions of artificial intelligence in education …
measuring undergraduate students' conceptions of artificial intelligence in education …
Predicting student performance in interactive online question pools using mouse interaction features
Modeling student learning and further predicting the performance is a well-established task
in online learning and is crucial to personalized education by recommending different …
in online learning and is crucial to personalized education by recommending different …
Analytic study for predictor development on student participation in generic competence development activities based on academic performance
Generic competence (GC) development is an integral part of higher education to provide
holistic education and enhance student career development. It also plays a critical role in …
holistic education and enhance student career development. It also plays a critical role in …