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Secil Caskurlu; Yasin Yalçin; Jaesung Hur; Hui Shi; James D. Klein – TechTrends: Linking Research and Practice to Improve Learning, 2025
This exploratory qualitative study examined how instructional designers use data to make decisions during the instructional design process. Participants included full-time instructional designers (n = 9) who were involved in one or more phases of the ADDIE (Analysis, Design, Development, Implementation, Evaluation) across different job sectors,…
Descriptors: Data Use, Instructional Design, Decision Making, Data Collection
Duncan Culbreth; Rebekah Davis; Cigdem Meral; Florence Martin; Weichao Wang; Sejal Foxx – TechTrends: Linking Research and Practice to Improve Learning, 2025
Monitoring applications (MAs) use digital and online tools to collect and track data on student behavior, and they have become increasingly popular among schools. Empirical research on these complex surveillance platforms is scant, and little is known about the efficacy or impact that they have on students. This study used a multi-method…
Descriptors: High School Students, COVID-19, Pandemics, Progress Monitoring
SeHee Jung; Hanwen Wang; Bingyi Su; Lu Lu; Liwei Qing; Xiaolei Fang; Xu Xu – TechTrends: Linking Research and Practice to Improve Learning, 2025
This study presents a mobile application (app) that facilitates undergraduate students to learn data science using their own full-body motion data. The app captures a user's movements through the built-in camera of a mobile device and processes the images for data generation using BlazePose, an open-source computer vision model for real-time pose…
Descriptors: Undergraduate Students, Data Science, Handheld Devices, Open Source Technology
Majdi Beseiso – TechTrends: Linking Research and Practice to Improve Learning, 2025
Predicting students' success is crucial in educational settings to improve academic performance and prevent dropouts. This study aimed to improve student performance prediction by combining advanced machine learning (ML) approaches. Convolutional Neural Networks (CNNs) and attention mechanisms were used for extracting relevant features from…
Descriptors: Prediction, Success, Academic Achievement, Artificial Intelligence
Harun Cigdem; Semiral Oncu – TechTrends: Linking Research and Practice to Improve Learning, 2025
Despite efforts to implement innovative approaches such as flipped learning leveraging computer technology, the challenge of student failure persists. Understanding the factors that contribute to student success in flipped engineering courses remains a critical issue. This study addresses this issue by investigating the impact of student…
Descriptors: Gamification, Flipped Classroom, Learner Engagement, Learning Readiness
Gyeonggeon Lee; Xiaoming Zhai – TechTrends: Linking Research and Practice to Improve Learning, 2025
Educators and researchers have analyzed various image data acquired from teaching and learning, such as images of learning materials, classroom dynamics, students' drawings, etc. However, this approach is labour-intensive and time-consuming, limiting its scalability and efficiency. The recent development in the Visual Question Answering (VQA)…
Descriptors: Artificial Intelligence, Computer Software, Teaching Methods, Learning Processes
Viet-Ngu Hoang; Will Connell; Radhika Lahiri; H. Nadeeka De Silva; Xuan-Hoan Pham – TechTrends: Linking Research and Practice to Improve Learning, 2025
Dashboards have become a crucial element of contemporary business operation and management; therefore, it is desirable for business students to acquire knowledge of them. This article investigates the effectiveness of designing learning activities around investment dashboards in the context of introductory business analytics (IBA) courses. We…
Descriptors: Introductory Courses, Business Education, Management Systems, Statistics Education
Conrad Borchers; Clémence Darriet; Joshua M. Rosenberg; Francesca López – TechTrends: Linking Research and Practice to Improve Learning, 2025
Public Internet Data Mining methods enable studying educational institutions' public-facing communication. Multiple online data sources can illuminate differences in how different audiences are addressed online, opening the door for critical inquiry into emerging issues of representation and targeted advertising. The present study presents a case…
Descriptors: School Districts, Advertising, Social Media, Web Sites

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