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Oscar Blessed Deho; Lin Liu; Jiuyong Li; Jixue Liu; Chen Zhan; Srecko Joksimovic – IEEE Transactions on Learning Technologies, 2024
Learning analytics (LA), like much of machine learning, assumes the training and test datasets come from the same distribution. Therefore, LA models built on past observations are (implicitly) expected to work well for future observations. However, this assumption does not always hold in practice because the dataset may drift. Recently,…
Descriptors: Learning Analytics, Ethics, Algorithms, Models
Liu, Lingyan; Zhao, Bo; Rao, Yiqiang – International Journal of Information and Communication Technology Education, 2022
A lot of studies have shown that there is an "inverse U-curve" relationship between learners' grades and cognitive load. Learners' grades are closely related to their learning behavior characteristics on online learning. Is there any relationship between online learners' behavior characteristics and cognitive load? Based on this, the…
Descriptors: Cognitive Processes, Difficulty Level, Learning Analytics, Electronic Learning
Yuang Wei; Bo Jiang – IEEE Transactions on Learning Technologies, 2024
Understanding student cognitive states is essential for assessing human learning. The deep neural networks (DNN)-inspired cognitive state prediction method improved prediction performance significantly; however, the lack of explainability with DNNs and the unitary scoring approach fail to reveal the factors influencing human learning. Identifying…
Descriptors: Cognitive Mapping, Models, Prediction, Short Term Memory
Juan Antonio Martinez-Carrascal; Jorge Munoz-Gama; Teresa Sancho-Vinuesa – IEEE Transactions on Learning Technologies, 2024
Academic institutions dedicate a substantial effort to ensure the academic success of their students. At the course level, teachers recommend learning paths (RLPs) for students to guarantee the achievement of their learning outcomes. In terms of performance, these kinds of approaches are deemed more effective than others based uniquely on…
Descriptors: Online Courses, Mathematics Instruction, Undergraduate Students, Mathematics Achievement
Hui Han; Silvana Trimi – Education and Information Technologies, 2024
Cloud computing-based online education has played a vital role in enabling uninterrupted learning during crises such as the COVID-19 pandemic. This study explored the key variables associated with cloud computing that can effectively support the operation of online education platforms. By analyzing real data from 63 online learning platforms, the…
Descriptors: Computer Software, Learning Management Systems, Online Courses, Correlation
Giannakos, Michail; Cukurova, Mutlu – British Journal of Educational Technology, 2023
This study presents the outcomes of a semi-systematic literature review on the role of learning theory in multimodal learning analytics (MMLA) research. Based on previous systematic literature reviews in MMLA and an additional new search, 35 MMLA works were identified that use theory. The results show that MMLA studies do not always discuss their…
Descriptors: Learning Theories, Multimedia Instruction, Learning Analytics, Research Reports
Marcel R. Haas; Colin Caprani; Benji T. van Beurden – Journal of Learning Analytics, 2023
We present an innovative modelling technique that simultaneously constrains student performance, course difficulty, and the sensitivity with which a course can differentiate between students by means of grades. Grade lists are the only necessary ingredient. Networks of courses will be constructed where the edges are populations of students that…
Descriptors: Bayesian Statistics, Computer Software, Learning Analytics, Grades (Scholastic)
Using Analytics to Predict Students' Interactions with Learning Management Systems in Online Courses
Ali Alshammari – Education and Information Technologies, 2024
In online education, it is widely recognized that interaction and engagement have an impact on students' academic performance. While previous research has extensively explored interactions between students, instructors, and content, there has been limited exploration of course design elements that promote the fourth type of interaction:…
Descriptors: Learning Analytics, Learning Management Systems, Academic Achievement, Correlation
Xiaona Xia; Wanxue Qi – European Journal of Education, 2025
Massive Open Online Courses (MOOCs) effectively support online learning behaviour; while constructing a sustainable learning process, MOOCs have also formed the social network. In addition, learners' burnout state has become a serious obstacle to the development and promotion of MOOCs. This study analyzes the potential social behaviour associated…
Descriptors: MOOCs, Burnout, Social Behavior, Feedback (Response)
Tong, Yao; Zhan, Zehui – Interactive Technology and Smart Education, 2023
Purpose: The purpose of this study is to set up an evaluation model to predict massive open online courses (MOOC) learning performance by analyzing MOOC learners' online learning behaviors, and comparing three algorithms -- multiple linear regression (MLR), multilayer perceptron (MLP) and classification and regression tree (CART).…
Descriptors: MOOCs, Online Courses, Learning Analytics, Prediction
Hua Ma; Wen Zhao; Yuqi Tang; Peiji Huang; Haibin Zhu; Wensheng Tang; Keqin Li – IEEE Transactions on Learning Technologies, 2024
To prevent students from learning risks and improve teachers' teaching quality, it is of great significance to provide accurate early warning of learning performance to students by analyzing their interactions through an e-learning system. In existing research, the correlations between learning risks and students' changing cognitive abilities or…
Descriptors: College Students, Learning Analytics, Learning Management Systems, Academic Achievement
Eran Hadas; Arnon Hershkovitz – Journal of Learning Analytics, 2025
Creativity is an imperative skill for today's learners, one that has important contributions to issues of inclusion and equity in education. Therefore, assessing creativity is of major importance in educational contexts. However, scoring creativity based on traditional tools suffers from subjectivity and is heavily time- and labour-consuming. This…
Descriptors: Creativity, Evaluation Methods, Computer Assisted Testing, Artificial Intelligence
Sudeshna Pal; Patsy Moskal; Anchalee Ngampornchai – International Journal on E-Learning, 2024
This study investigated the effectiveness of blended instruction in enhancing student success in an advanced undergraduate engineering course. The research used learning analytics captured from pre-recorded lecture videos, course grade data, and student surveys. Results revealed positive correlations between lecture video viewership and course…
Descriptors: Blended Learning, Advanced Courses, Engineering Education, Undergraduate Students
Grajzel, Katalin; Dumas, Denis; Acar, Selcuk – Journal of Creative Behavior, 2022
One of the best-known and most frequently used measures of creative idea generation is the Torrance Test of Creative Thinking (TTCT). The TTCT Verbal, assessing verbal ideation, contains two forms created to be used interchangeably by researchers and practitioners. However, the parallel forms reliability of the two versions of the TTCT Verbal has…
Descriptors: Test Reliability, Creative Thinking, Creativity Tests, Verbal Ability
Karolína Dockalová Burská; Jakub Rudolf Mlynárik; Radek Ošlejšek – Education and Information Technologies, 2024
In cyber security education, hands-on training is a common type of exercise to help raise awareness and competence, and improve students' cybersecurity skills. To be able to measure the impact of the design of the particular courses, the designers need methods that can reveal hidden patterns in trainee behavior. However, the support of the…
Descriptors: Computer Science Education, Information Security, Computer Security, Training Methods