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Ge Bai – International Journal of Web-Based Learning and Teaching Technologies, 2025
This study focuses on the construction of the learner-centered teaching college English teaching mode under big data technology. Traditional college English teaching has issues, such as standardized teaching ignoring individual differences and lagging feedback. However, the development of big data technology offers opportunities for teaching…
Descriptors: Student Centered Learning, English Instruction, College Instruction, College Students
Pelletier, Kathe; Hutt, Chris – Change: The Magazine of Higher Learning, 2021
Digital transformation (Dx) refers to a series of deep and coordinated culture, workforce, and technology shifts that enable new educational and operating models and transform an institution's business model, strategic directions, and value proposition. Dx initiatives on many campuses are anchored in student success goals. As a result of this…
Descriptors: Technology Uses in Education, Educational Change, Faculty Advisers, College Students
Owan, Valentine J.; Obla, Moses E.; Asuquo, Michael E.; Owan, Mercy V.; Okenjom, Godian P.; Undie, Stephen B.; Ogar, Joseph O.; Udeh, Kelechi V. – Journal of Pedagogical Research, 2023
Previous research has extensively analysed teachers' and students' Facebook use for instructional engagement, writing, research dissemination and e-learning. However, Facebook as a data collection mechanism for research has scarcely been the subject of previous studies. The current study addressed these gaps by analysing students' awareness,…
Descriptors: Student Attitudes, Social Media, Student Research, Data Collection
Nkomo, Larian M.; Nat, Muesser – TechTrends: Linking Research and Practice to Improve Learning, 2021
With various digital technologies increasingly integrated into higher education, understanding how students engage with such technologies has become vital. There are different ways to measure student engagement; however, self-reported measures such as questionnaires are predominantly used to understand student engagement. In contrast, this study…
Descriptors: Learner Engagement, Blended Learning, Educational Environment, Data Collection
Wonkyung Choi; Jun Jo; Geraldine Torrisi-Steele – International Journal of Adult Education and Technology, 2024
Despite best efforts, the student experience remains poorly understood. One under-explored approach to understanding the student experience is the use of big data analytics. The reported study is a work in progress aimed at exploring the value of big data methods for understanding the student experience. A big data analysis of an open dataset of…
Descriptors: College Students, Data Analysis, Data Collection, Learning Analytics
Williamson, Ben – British Journal of Educational Technology, 2019
Digital data are transforming higher education (HE) to be more student-focused and metrics-centred. In the UK, capturing detailed data about students has become a government priority, with an emphasis on using student data to measure, compare and assess university performance. The purpose of this paper is to examine the governmental and commercial…
Descriptors: Foreign Countries, Higher Education, Technology Uses in Education, Data Analysis
Senger, Kim; Nordmo, Ivar – Journal of Geoscience Education, 2021
The emergence of digital tools, including tablets with a multitude of built-in sensors, allows gathering many geological observations digitally and in a geo-referenced context. This is particularly important in the polar environments where (1) limited time is available at each outcrop due to harsh weather conditions, and (2) outcrops are rarely…
Descriptors: Earth Science, Science Instruction, Teaching Methods, Educational Technology
Liao, Soohyun Nam; Zingaro, Daniel; Thai, Kevin; Alvarado, Christine; Griswold, William G.; Porter, Leo – ACM Transactions on Computing Education, 2019
As enrollments and class sizes in postsecondary institutions have increased, instructors have sought automated and lightweight means to identify students who are at risk of performing poorly in a course. This identification must be performed early enough in the term to allow instructors to assist those students before they fall irreparably behind.…
Descriptors: Prediction, Low Achievement, Tests, Scores
Wu, Pengfei; Yu, Shengquan; Wang, Dan – Educational Technology & Society, 2018
The present study uses a text data mining approach to automatically discover learner interests in open learning environments. We propose a method to construct learner interests automatically from the combination of learner generated content and their dynamic interactions with other learning resources. We develop a learner-topic model to discover…
Descriptors: Data Collection, Data Analysis, Educational Technology, Technology Uses in Education
Paassen, Benjamin; Hammer, Barbara; Price, Thomas William; Barnes, Tiffany; Gross, Sebastian; Pinkwart, Niels – Journal of Educational Data Mining, 2018
Intelligent tutoring systems can support students in solving multi-step tasks by providing hints regarding what to do next. However, engineering such next-step hints manually or via an expert model becomes infeasible if the space of possible states is too large. Therefore, several approaches have emerged to infer next-step hints automatically,…
Descriptors: Intelligent Tutoring Systems, Cues, Educational Technology, Technology Uses in Education
Becerra-Alonso, David; Lopez-Cobo, Isabel; Gómez-Rey, Pilar; Fernández-Navarro, Francisco; Barbera, Elena – Distance Education, 2020
This article describes the development of an application for the grading and provision of feedback on educational processes. The too, named "EduZinc," enables instructors to go through the complete process of creating and evaluating the activities and materials of a course. The application enables for the simultaneous management of two…
Descriptors: Grading, Feedback (Response), Student Centered Learning, Educational Technology
Barret, Mandy; Branson, Lisa; Carter, Sheryl; DeLeon, Frank; Ellis, Justin; Gundlach, Cirrus; Lee, Dale – Inquiry, 2019
Artificial intelligence (AI) technology is becoming the basis for business. Most businesses use it to improve the customer experience. The education community is just beginning to find ways to successfully implement AI for staff and students. Artificial Intelligence should be leveraged to create a better student experience. For example, Elon…
Descriptors: Artificial Intelligence, Technology Uses in Education, Higher Education, Educational Opportunities
Van Horne, Sam; Curran, Maura; Smith, Anna; VanBuren, John; Zahrieh, David; Larsen, Russell; Miller, Ross – Technology, Knowledge and Learning, 2018
Instructional technologists and faculty in post-secondary institutions have increasingly adopted learning analytics interventions such as dashboards that provide real-time feedback to students to support student' ability to regulate their learning. But analyses of the effectiveness of such interventions can be confounded by measures of students'…
Descriptors: Chemistry, Science Instruction, Learning Strategies, Questionnaires
Saliyeva, Aigul Z.; Zhumabekova, Fatima N.; Kashkynba?, Bayzhuman B.; Saurbekova, Gulmira; Tauasarova, Danara; Toktarbaev, Darkhan; Sakenov, Janat – International Journal of Environmental and Science Education, 2016
The study covers the issue of students' ability to use digital educational resources in their professional activity in which reflects their future professional work. Levels of students' readiness to use digital educational resources in their professional activity are identified. The Model of students' ability to use digital educational resources…
Descriptors: Educational Technology, Technology Uses in Education, Technological Literacy, Readiness
Mouri, Kousuke; Uosaki, Noriko; Ogata, Hiroaki – Educational Technology & Society, 2018
Seamless learning has been recognized as an effective learning approach across various dimensions including formal and informal learning contexts, individual and social learning, and physical world and cyberspace. With the emergence of seamless learning, the majority of the current research focuses on realizing a seamless learning environment at…
Descriptors: Data Collection, Data Analysis, Second Language Learning, Electronic Publishing