Past, present, and future of smart learning: a topic-based bibliometric analysis
Innovative information and communication technologies have reformed higher education
from the traditional way to smart learning. Smart learning applies technological and social …
from the traditional way to smart learning. Smart learning applies technological and social …
Student success prediction in MOOCs
Predictive models of student success in Massive Open Online Courses (MOOCs) are a
critical component of effective content personalization and adaptive interventions. In this …
critical component of effective content personalization and adaptive interventions. In this …
Evaluating the fairness of predictive student models through slicing analysis
Predictive modeling has been a core area of learning analytics research over the past
decade, with such models currently deployed in a variety of educational contexts from …
decade, with such models currently deployed in a variety of educational contexts from …
Goal-based course recommendation
With cross-disciplinary academic interests increasing and academic advising resources over
capacity, the importance of exploring data-assisted methods to support student decision …
capacity, the importance of exploring data-assisted methods to support student decision …
Is there order in the mess? A single paper meta-analysis approach to identification of predictors of success in learning analytics
Predictors of student academic success do not always replicate well across different
learning designs, subject areas, or educational institutions. This suggests that characteristics …
learning designs, subject areas, or educational institutions. This suggests that characteristics …
A self-regulated learning analytics prediction-and-intervention design: Detecting and supporting struggling biology students.
We investigated the effects of a learning analytics-driven prediction modeling platform and a
brief digital self-regulated learning skill training program targeted to support undergraduate …
brief digital self-regulated learning skill training program targeted to support undergraduate …
The curious case of centrality measures: A large-scale empirical investigation
M Saqr, S López-Pernas - Journal of Learning Analytics, 2022 - learning-analytics.info
There has been extensive research using centrality measures in educational settings. One
of the most common lines of such research has tested network centrality measures as …
of the most common lines of such research has tested network centrality measures as …
Controlled outputs, full data: A privacyprotecting infrastructure for MOOC data
Learning analytics research presents challenges for researchers embracing the principles of
open science. Protecting student privacy is paramount, but progress in increasing scientific …
open science. Protecting student privacy is paramount, but progress in increasing scientific …
How widely can prediction models be generalized? Performance prediction in blended courses
Blended courses that mix in-person instruction with online platforms are increasingly
common in secondary education. These platforms record a rich amount of data on students' …
common in secondary education. These platforms record a rich amount of data on students' …
Deep learning for dropout prediction in MOOCs
D Sun, Y Mao, J Du, P Xu, Q Zheng… - 2019 eighth …, 2019 - ieeexplore.ieee.org
In recent years, the rapid rise of massive open online courses (MOOCs) has aroused great
attention. Dropout prediction or identifying students at risk of dropping out of a course is an …
attention. Dropout prediction or identifying students at risk of dropping out of a course is an …