Relationship between students' online learning behavior and course performance: What contextual information matters?
This study examines whether including more contextual information in data analysis could
improve our ability to identify the relation between students' online learning behavior and …
improve our ability to identify the relation between students' online learning behavior and …
A time‐driven FCA‐based approach for identifying students' dropout in MOOCs
In online learning, the dropout phenomenon is a relevant issue to address with practical
solutions. Several data sets stimulate original, and resolutive data analysis approaches …
solutions. Several data sets stimulate original, and resolutive data analysis approaches …
Early prediction of course grades: models and feature selection
In this paper, we compare predictive models for students' final performance in a blended
course using a set of generic features collected from the first six weeks of class. These …
course using a set of generic features collected from the first six weeks of class. These …
Re-Designing the Structure of Online Courses to Empower Educational Data Mining.
The amount of information contained in any educational data set is fundamentally
constrained by the instructional conditions under which the data are collected. In this study …
constrained by the instructional conditions under which the data are collected. In this study …
结合学生行为模式分析的成绩早期预警研究.
张明焱， 杜旭， 李浩 - Journal of Computer Engineering & …, 2022 - search.ebscohost.com
早期预警是在线学习中的重要主题, 通过早期预警识别有不及格风险的学生可帮助教师及时开展
个性化教学干预. 使用深度学习模型对学生微观行为模式进行分析以提高早期预警的效果 …
个性化教学干预. 使用深度学习模型对学生微观行为模式进行分析以提高早期预警的效果 …
Revealing at-risk learning patterns and corresponding self-regulated strategies via LSTM encoder and time-series clustering
Purpose This study aims to propose a learning pattern analysis method which can improve a
predictive model's performance, as well as discover hidden insights into micro-level learning …
predictive model's performance, as well as discover hidden insights into micro-level learning …
Representing and predicting student navigational pathways in online college courses
Representation and prediction of student navigational pathways, typically based on neural
network (NN) methods, have seen their potential of improving instruction and learning under …
network (NN) methods, have seen their potential of improving instruction and learning under …
A CNN model with data imbalance handling for course-level student prediction based on forum texts
PHG Nguyen, CTN Vo - … 10th International Conference, ICCCI 2018, Bristol …, 2018 - Springer
Nowadays teaching and learning activities in a course are greatly supported by information
technologies. Forums are among information technologies utilized in a course to encourage …
technologies. Forums are among information technologies utilized in a course to encourage …
Heterogeneous educational data classification at the course level
NHG Phuc, VTN Chau - Vietnam Journal of Computer Science, 2021 - World Scientific
Nowadays, teaching and learning activities in a course are greatly supported by information
technologies. Forums are among information technologies utilized in a course to encourage …
technologies. Forums are among information technologies utilized in a course to encourage …
[PDF][PDF] Predicting Challenge Outcomes for Students in a Digital Game for Learning Genetics.
In recent years, digital games for learning have shown significant potential for creating
engaging and effective student learning experiences. A common gameplay design used by …
engaging and effective student learning experiences. A common gameplay design used by …