Towards intelligent E-learning systems
M Liu, D Yu - Education and Information Technologies, 2023 - Springer
The prevalence of e-learning systems has made educational resources more accessible,
interactive and effective to learners without the geographic and temporal boundaries …
interactive and effective to learners without the geographic and temporal boundaries …
MOOC dropout prediction using machine learning techniques: Review and research challenges
MOOC represents an ultimate way to deliver educational content in higher education
settings by providing high-quality educational material to the students throughout the world …
settings by providing high-quality educational material to the students throughout the world …
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 …
Prediction in MOOCs: A review and future research directions
This paper surveys the state of the art on prediction in MOOCs through a systematic
literature review (SLR). The main objectives are: first, to identify the characteristics of the …
literature review (SLR). The main objectives are: first, to identify the characteristics of the …
[HTML][HTML] Rethinking (Dis) engagement in human-computer interaction
User engagement has become a much-cited construct in human-computer interaction (HCI)
design and evaluation research and practice. Constructed as a positive and desirable …
design and evaluation research and practice. Constructed as a positive and desirable …
Analyzing large collections of open-ended feedback from MOOC learners using LDA topic modeling and qualitative analysis
There is a large variation in background and purpose of massive open online course
(MOOC) learners. To improve the overall MOOC learning experience, it is important to …
(MOOC) learners. To improve the overall MOOC learning experience, it is important to …
Beyond prediction: First steps toward automatic intervention in MOOC student stopout
High attrition rates in massive open online courses (MOOCs) have motivated growing
interest in the automatic detection of student" stopout". Stopout classifiers can be used to …
interest in the automatic detection of student" stopout". Stopout classifiers can be used to …
Delving deeper into MOOC student dropout prediction
In order to obtain reliable accuracy estimates for automatic MOOC dropout predictors, it is
important to train and test them in a manner consistent with how they will be used in practice …
important to train and test them in a manner consistent with how they will be used in practice …
Early detection prediction of learning outcomes in online short-courses via learning behaviors
W Chen, CG Brinton, D Cao… - IEEE Transactions …, 2018 - ieeexplore.ieee.org
We study learning outcome prediction for online courses. Whereas prior work has focused
on semester-long courses with frequent student assessments, we focus on short-courses …
on semester-long courses with frequent student assessments, we focus on short-courses …
MOOC dropout prediction: How to measure accuracy?
In order to obtain reliable accuracy estimates for automatic MOOC dropout predictors, it is
important to train and test them in a manner consistent with how they will be used in practice …
important to train and test them in a manner consistent with how they will be used in practice …