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Ning, Xiaoke – International Journal of Web-Based Learning and Teaching Technologies, 2023
With the vigorous development of intelligent campus construction, great changes have taken place in the development of information technology in colleges and universities from the previous digital to intelligent development. In the teaching process, the analysis of students' classroom learning has also changed from the previous manual observation…
Descriptors: College Students, Algorithms, Student Behavior, Artificial Intelligence
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
Aom Perkash; Qaisar Shaheen; Robina Saleem; Furqan Rustam; Monica Gracia Villar; Eduardo Silva Alvarado; Isabel de la Torre Diez; Imran Ashraf – Education and Information Technologies, 2024
Developing tools to support students, educators, intuitions, and government in the educational environment has become an important task to improve the quality of education and learning outcomes. Information and communication technology (ICT) is adopted by educational institutions; one such instance is video interaction in flipped teaching.…
Descriptors: Academic Achievement, Colleges, Artificial Intelligence, Predictor Variables
Shao-Heng Ko; Kristin Stephens-Martinez – ACM Transactions on Computing Education, 2025
Background: Academic help-seeking benefits students' achievement, but existing literature either studies important factors in students' selection of all help resources via self-reported surveys or studies their help-seeking behavior in one or two separate help resources via actual help-seeking records. Little is known about whether computing…
Descriptors: Computer Science Education, College Students, Help Seeking, Student Behavior
Chinsook, Kittipong; Khajonmote, Withamon; Klintawon, Sununta; Sakulthai, Chaiyan; Leamsakul, Wicha; Jantakoon, Thada – Higher Education Studies, 2022
Big data is an important part of innovation that has recently attracted a lot of interest from academics and practitioners alike. Given the importance of the education industry, there is a growing trend to investigate the role of big data in this field. Much research has been undertaken to date in order to better understand the use of big data in…
Descriptors: Student Behavior, Learning Analytics, Computer Software, Rating Scales
Constructing Theoretically Informed Measures of Pause Duration in Experimentally Manipulated Writing
Sophie Hall; Veerle M. Baaijen; David Galbraith – Reading and Writing: An Interdisciplinary Journal, 2024
This paper argues that traditional threshold-based approaches to the analysis of pauses in writing fail to capture the complexity of the cognitive processes involved in text production. It proposes that, to capture these processes, pause analysis should focus on the transition times between linearly produced units of text. Following a review of…
Descriptors: Writing (Composition), Cognitive Processes, Writing Processes, College Students
Varun Mandalapu – ProQuest LLC, 2021
Educational data mining focuses on exploring increasingly large-scale data from educational settings, such as Learning Management Systems (LMS), and developing computational methods to understand students' behaviors and learning settings better. There has been a multitude of research dedicated to studying the student learning process, leading to…
Descriptors: Models, Student Behavior, Learning Management Systems, Data Use
Du, Xiaoming; Ge, Shilun; Wang, Nianxin – International Journal of Information and Communication Technology Education, 2022
In the context of education big data, it uses data mining and learning analysis technology to accurately predict and effectively intervene in learning. It is helpful to realize individualized teaching and individualized teaching. This research analyzes student life behavior data and learning behavior data. A model of student behavior…
Descriptors: Prediction, Data, Student Behavior, Academic Achievement
Xu, Tonghui – Journal of Educators Online, 2023
The early detection of students' academic performance or final grades helps instructors prepare their online courses. In the Open University Learning Analytics Dataset, I found many online students clicked the course materials before the first day of class. This study aims to investigate how data mining models can use this student interaction data…
Descriptors: College Students, Online Courses, Academic Achievement, Data Analysis
HaeJin Lee; Nigel Bosch – International Journal of STEM Education, 2024
Self-regulated learning (SRL) strategies can be domain specific. However, it remains unclear whether this specificity extends to different subtopics within a single subject domain. In this study, we collected data from 210 college students engaged in a computer-based learning environment to examine the heterogeneous manifestations of learning…
Descriptors: Computer Assisted Instruction, Self Management, Intellectual Disciplines, College Students
Hayama, Tessai; Odate, Hidetaka; Ishida, Naoto – International Journal on E-Learning, 2020
The field of learning analytics has been limited by its frequent dependence on learning logs created by students while learning. Most of the research has dealt with the relationships between learning during a course and the achieved results. Although students' in-class behavior affects learning achievement, this remains a challenging aspect to…
Descriptors: Student Behavior, Data Collection, Measurement Equipment, College Students
Chih-Hsing Liu; Jeou-Shyan Horng; Sheng-Fang Chou; Tai-Yi Yu; Yung-Chuan Huang; Yen-Ling Ng; Jun-You Lin – Interactive Learning Environments, 2024
The current study provides an integrated comprehensive analysis of mediation-moderation models to understand 567 tourism and hospitality students' viewpoints by exploring multidisciplinary contributions relevant to the big data and new technology application bodies of literature. The results show that self-efficacy was the primary motivation…
Descriptors: Foreign Countries, College Students, Tourism, Hospitality Occupations
Melcher, Jennifer; Lavoie, Joel; Hays, Ryan; D'Mello, Ryan; Rauseo-Ricupero, Natali; Camacho, Erica; Rodriguez-Villa, Elena; Wisniewski, Hannah; Lagan, Sarah; Vaidyam, Aditya; Torous, John – Journal of American College Health, 2023
Objective: This study assessed the feasibility of capturing smartphone based digital phenotyping data in college students during the COVID-19 pandemic with the goal of understanding how digital biomarkers of behavior correlate with mental health. Participants: Participants were 100 students enrolled in 4-year universities. Methods: Each…
Descriptors: Telecommunications, Handheld Devices, College Students, COVID-19
King, Seth A.; Dzenga, Chaidamoyo; Burch, Taneal; Kennedy, Krystal – Journal of Behavioral Education, 2021
Virtual reality (VR) places individuals within a simulated experience using an array of visual, auditory, and tactile interfaces. Research suggests VR, which facilitates the rehearsal of actual job duties and performance assessment during training, may improve professional development across a range of disciplines. Although studies incorporating…
Descriptors: Computer Simulation, Training, Behavior Change, College Students
Bronson Nichols – ProQuest LLC, 2021
Access to the Internet has increased connectivity between people across large distances. It has also amplified the desire of college students to engage in the illegal sharing and distribution of data. The purpose of this quantitative research study was to analyze the behaviors that motivate Michigan college students to engage in digital piracy.…
Descriptors: College Students, Intellectual Property, Copyrights, Information Technology