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 …
[HTML][HTML] Temporally-focused analytics of self-regulated learning: A systematic review of literature
We present a systematic literature review of data-driven self-regulated learning (SRL) that
emphasises the methodological importance of temporality and sequence, as opposed to …
emphasises the methodological importance of temporality and sequence, as opposed to …
Utilizing Student Time Series Behaviour in Learning Management Systems for Early Prediction of Course Performance.
F Chen, Y Cui - Journal of Learning Analytics, 2020 - ERIC
Predictive analytics in higher education has become increasingly popular in recent years
with the growing availability of educational big data. Particularly, a wealth of student activity …
with the growing availability of educational big data. Particularly, a wealth of student activity …
[HTML][HTML] Image encoding selection based on Pearson correlation coefficient for time series anomaly detection
Recently, anomaly detection in time-series data has received great attention from
researchers due to its importance in problem-solving and predicting future system events …
researchers due to its importance in problem-solving and predicting future system events …
Unfolding students' online assignment submission behavioral patterns using temporal learning analytics
This study analyzed students' online assignment submission behaviors from the
perspectives of temporal learning analytics. This study aimed to model the time-dependent …
perspectives of temporal learning analytics. This study aimed to model the time-dependent …
Analytics of self-regulated learning scaffolding: effects on learning processes
Self-regulated learning (SRL) is the ability to regulate cognitive, metacognitive, motivational,
and emotional states while learning and is posited to be a strong predictor of academic …
and emotional states while learning and is posited to be a strong predictor of academic …
Application of educational data mining approach for student academic performance prediction using progressive temporal data
R Trakunphutthirak, VCS Lee - Journal of Educational …, 2022 - journals.sagepub.com
Educators in higher education institutes often use statistical results obtained from their
online Learning Management System (LMS) dataset, which has limitations, to evaluate …
online Learning Management System (LMS) dataset, which has limitations, to evaluate …
Data-driven unsupervised clustering of online learner behaviour
The widespread adoption of online courses opens opportunities for analysing learner
behaviour and optimising web-based learning adapted to observed usage. Here, we …
behaviour and optimising web-based learning adapted to observed usage. Here, we …
A Probabilistic Approach to Modeling Students' Interactions in a Learning Management System for Facilitating Distance Learning
Learning mostly involves communication and interaction that leads to new information being
processed, which eventually turns into knowledge. In the digital era, these actions pass …
processed, which eventually turns into knowledge. In the digital era, these actions pass …
Examining Algorithmic Fairness for First-Term College Grade Prediction Models Relying on Pre-matriculation Data
T Yanagiura, S Yano, M Kihira… - Journal of …, 2023 - jedm.educationaldatamining.org
Many colleges use AI-powered early warning systems (EWS) to provide support to students
as soon as they start their first semester. However, concerns arise regarding the fairness of …
as soon as they start their first semester. However, concerns arise regarding the fairness of …