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Kai Li – International Association for Development of the Information Society, 2023
Assessing students' performance in online learning could be executed not only by the traditional forms of summative assessments such as using essays, assignments, and a final exam, etc. but also by more formative assessment approaches such as interaction activities, forum posts, etc. However, it is difficult for teachers to monitor and assess…
Descriptors: Student Evaluation, Online Courses, Electronic Learning, Computer Literacy
Whitelock-Wainwright, Alexander; Gaševic, Dragan; Tejeiro, Ricardo; Tsai, Yi-Shan; Bennett, Kate – Journal of Computer Assisted Learning, 2019
Student engagement within the development of learning analytics services in Higher Education is an important challenge to address. Despite calls for greater inclusion of stakeholders, there still remains only a small number of investigations into students' beliefs and expectations towards learning analytics services. Therefore, this paper presents…
Descriptors: Expectation, Learning Analytics, Questionnaires, College Students
Lazrig, Ibrahim; Humpherys, Sean L. – Information Systems Education Journal, 2022
Can sentiment analysis be used in an educational context to help teachers and researchers evaluate students' learning experiences? Are sentiment analyzing algorithms accurate enough to replace multiple human raters in educational research? A dataset of 333 students evaluating a learning experience was acquired with positive, negative, and neutral…
Descriptors: College Students, Learning Analytics, Educational Research, Learning Experience
Abdelhafez, Hoda Ahmed; Elmannai, Hela – International Journal of Information and Communication Technology Education, 2022
Learning data analytics improves the learning field in higher education using educational data for extracting useful patterns and making better decisions. Identifying potential at-risk students may help instructors and academic guidance to improve the students' performance and the achievement of learning outcomes. The aim of this research study is…
Descriptors: Learning Analytics, Mathematics, Prediction, Academic Achievement
Munguia, Pablo; Brennan, Amelia – Journal of Learning Analytics, 2020
No course exists in isolation, so examining student progression through courses within a broader program context is an important step in integrating course-level and program-level analytics. Integration in this manner allows us to see the impact of course-level changes to the program, as well as identify points in the program structure where…
Descriptors: Learning Analytics, Courses, College Programs, Foreign Countries
Kokoç, Mehmet; Akçapinar, Gökhan; Hasnine, Mohammad Nehal – Educational Technology & Society, 2021
This study analyzed students' online assignment submission behaviors from the perspectives of temporal learning analytics. This study aimed to model the time-dependent changes in the assignment submission behavior of university students by employing various machine learning methods. Precisely, clustering, Markov Chains, and association rule mining…
Descriptors: Electronic Learning, Assignments, Behavior Patterns, Learning Analytics
Salas-Rueda, Ricardo-Adan; Salas-Rueda, Erika-Patricia; Salas-Rueda, Rodrigo-David – Turkish Online Journal of Distance Education, 2021
This mixed research aims to design and implement the Web Application on Bayes' Theorem (WABT) in the Statistical Instrumentation for Business subject. WABT presents the procedure to calculate the probability of Bayes' Theorem through the simulation of data about the supply of products. Technology Acceptance Model (TAM), machine learning and data…
Descriptors: Bayesian Statistics, Probability, College Students, Business Administration Education
Mouri, Kousuke; Uosaki, Noriko; Hasnine, Mohammad; Shimada, Atsushi; Yin, Chengjiu; Kaneko, Keiichi; Ogata, Hiroaki – Interactive Learning Environments, 2021
This paper describes an automatic quiz generation system designed to support language learning that utilizes digital textbook logs. Learners often memorize words in digital textbooks while preparing for an examination, and they often use the highlight function for the words. Previous studies regarding annotations and highlights have shown that…
Descriptors: Computer Assisted Testing, Learning Analytics, Electronic Publishing, Textbooks
Yoshida, Masami – Education and Information Technologies, 2021
We conducted an investigational study of the formulation of the heterarchical online knowledge-based community among university students, which also involved users outside a course. As an exercise in a course, students were assigned to post their opinions regarding global issues on Twitter to connect with social actors. The emerging all…
Descriptors: College Students, Student Behavior, Social Media, Computer Mediated Communication
Krivova, Anna Leonidovna; Kalliopin, Alexander Konstantinovich; Korotaeva, Irina Eduardovna; Shafazhinskaya, Natalia Evgenievna; Ermilova, Daria Yuryevna – Journal of Educational Psychology - Propositos y Representaciones, 2021
In the era of the digital educational environment, where each participant of the educational process is actively involved in its development, the Internet and its services have become a popular tool. Open education network tools are defined as ICT tools that ensure the formation and maintenance of network electronic information resources of an…
Descriptors: Social Networks, Social Media, Educational Technology, Technology Integration
Mangaroska, Katerina; Sharma, Kshitij; Gaševic, Dragan; Giannakos, Michail – Journal of Computer Assisted Learning, 2022
Background: Problem-solving is a multidimensional and dynamic process that requires and interlinks cognitive, metacognitive, and affective dimensions of learning. However, current approaches practiced in computing education research (CER) are not sufficient to capture information beyond the basic programming process data (i.e., IDE-log data).…
Descriptors: Cognitive Processes, Psychological Patterns, Problem Solving, Programming
Cook, Jessica; Chen, Cuixian; Reid-Griffin, Angelia – Journal of Effective Teaching in Higher Education, 2019
In a society where first hand work experience is greatly valued many universities or institutions of higher education have designed their Quality enhancement plan (QEP) to address student applied learning. This paper is the results of a university's QEP plan, called Experiencing Transformative Education Through Applied Learning or ETEAL. This…
Descriptors: Experiential Learning, Learning Analytics, College Students, Statistical Analysis
Rets, Irina; Herodotou, Christothea; Bayer, Vaclav; Hlosta, Martin; Rienties, Bart – International Journal of Educational Technology in Higher Education, 2021
Learning analytics dashboards (LADs) can provide learners with insights about their study progress through visualisations of the learner and learning data. Despite their potential usefulness to support learning, very few studies on LADs have considered learners' needs and have engaged learners in the process of design and evaluation. Aligning with…
Descriptors: Learning Analytics, Educational Technology, Usability, College Students
Beile, Penny; Choudhury, Kanak; Mulvihill, Rachel; Wang, Morgan – College & Research Libraries, 2020
This large-scale study was conducted for the purposes of determining how representative library users are compared to the whole student population, to explore how library services contribute to student success, and to position the library to be included in the institution's learning analytics landscape. To that end, data were collected as students…
Descriptors: Academic Libraries, Library Services, Users (Information), College Students
Yu, Renzhe; Li, Qiujie; Fischer, Christian; Doroudi, Shayan; Xu, Di – International Educational Data Mining Society, 2020
In higher education, predictive analytics can provide actionable insights to diverse stakeholders such as administrators, instructors, and students. Separate feature sets are typically used for different prediction tasks, e.g., student activity logs for predicting in-course performance and registrar data for predicting long-term college success.…
Descriptors: Prediction, Accuracy, College Students, Success

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