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Dorottya Demszky; Jing Liu; Heather C. Hill; Dan Jurafsky; Chris Piech – Educational Evaluation and Policy Analysis, 2024
Providing consistent, individualized feedback to teachers is essential for improving instruction but can be prohibitively resource-intensive in most educational contexts. We develop M-Powering Teachers, an automated tool based on natural language processing to give teachers feedback on their uptake of student contributions, a high-leverage…
Descriptors: Online Courses, Automation, Feedback (Response), Large Group Instruction
Connolly, Cornelia; Hijón-Neira, Raquel; Grádaigh, Seán Ó. – International Journal of Mobile and Blended Learning, 2021
Research on the role of mobile learning in computational thinking is limited, and even more so in its use in initial teacher education. Aligned to this there is a need to consider how to introduce and expose pre-service teachers to computational thinking constructs within the context of the subject area they will teach in their future classrooms.…
Descriptors: Electronic Learning, Computation, Thinking Skills, Preservice Teacher Education
Hellings, Jan; Haelermans, Carla – Higher Education: The International Journal of Higher Education Research, 2022
We use a randomised experiment to study the effect of offering half of 556 freshman students a learning analytics dashboard and a weekly email with a link to their dashboard, on student behaviour in the online environment and final exam performance. The dashboard shows their online progress in the learning management systems, their predicted…
Descriptors: Learning Analytics, College Freshmen, Student Behavior, Electronic Learning
Denis Zhidkikh; Ville Heilala; Charlotte Van Petegem; Peter Dawyndt; Miitta Jarvinen; Sami Viitanen; Bram De Wever; Bart Mesuere; Vesa Lappalainen; Lauri Kettunen; Raija Hämäläinen – Journal of Learning Analytics, 2024
Predictive learning analytics has been widely explored in educational research to improve student retention and academic success in an introductory programming course in computer science (CS1). General-purpose and interpretable dropout predictions still pose a challenge. Our study aims to reproduce and extend the data analysis of a privacy-first…
Descriptors: Learning Analytics, Prediction, School Holding Power, Academic Achievement
Utamachant, Piriya; Anutariya, Chutiporn; Pongnumkul, Suporn – Smart Learning Environments, 2023
Apart from good instructional design and delivery, effective intervention is another key to strengthen student academic performance. However, intervention has been recognized as a great challenge. Most instructors struggle to identify at-risk students, determine a proper intervention approach, trace and evaluate whether the intervention works.…
Descriptors: Intervention, Learning Analytics, Learning Management Systems, Programming
Saadati, Zohreh; Zeki, Canan Perkan; Barenji, Reza Vatankhah – Interactive Learning Environments, 2023
The study of online higher education learning and academic achievement has increasingly emphasized self-regulated learning (SRL). Few studies so far have investigated the blockchain-based learning management system (LMS) and adaptive SRL intervention in online higher education. This paper aimed to develop a blockchain-enabled LMS as a…
Descriptors: Graduate Students, Metacognition, Programming, Technology
Sonia Triana-Vera; Omar López-Vargas – Contemporary Educational Technology, 2025
This research aimed to determine the effects of motivational scaffolding and adaptive scaffolding on academic and online self-efficacy in learners interacting with a multimedia learning environment within the field of technology. The study involved 146 students from four tenth-grade classes at a public institution in the municipality of Soacha…
Descriptors: Self Efficacy, Electronic Learning, Scaffolding (Teaching Technique), High School Students
Xiao-Ming Wang; Wen-Qing Zhou; Gwo-Jen Hwang; Shi-Man Wang; Tong Huang – Educational Technology & Society, 2024
Knowing the factors affecting students' learning achievement in digital learning is a crucial educational issue nowadays. However, recent research has paid less attention to how an individual's internal factors (prior knowledge) influence their learning achievement through cognitive engagement, and previous studies generally employed students'…
Descriptors: Electronic Learning, Prior Learning, Cognitive Processes, Learner Engagement
Yong, Su Ting; Gates, Peter – International Journal of Virtual and Personal Learning Environments, 2022
A study was conducted to explore student self-efficacy, motivation, and performance in learning programming online. A questionnaire was administered to 132 students in a Foundation in Engineering programme using the Computer Programming Self-Efficacy Scale and Intrinsic Motivation Inventory. Then, exam performance and Moodle logs were used to…
Descriptors: Emergency Programs, Distance Education, Electronic Learning, Programming
Nikola M. Luburic; Luka Z. Doric; Jelena J. Slivka; Dragan Lj. Vidakovic; Katarina-Glorija G. Grujic; Aleksandar D. Kovacevic; Simona B. Prokic – IEEE Transactions on Learning Technologies, 2025
Software engineers are tasked with writing functionally correct code of high quality. Maintainability is a crucial code quality attribute that determines the ease of analyzing, modifying, reusing, and testing a software component. This quality attribute significantly affects the software's lifetime cost, contributing to developer productivity and…
Descriptors: Intelligent Tutoring Systems, Coding, Computer Software, Technical Occupations
Construction and Analysis of a Decision Tree-Based Predictive Model for Learning Intervention Advice
Chenglong Wang – Turkish Online Journal of Educational Technology - TOJET, 2024
The rapid development of education informatization has accumulated a large amount of data for learning analytics, and adopting educational data mining to find new patterns of data, develop new algorithms and models, and apply known predictive models to the teaching system to improve learning is the challenge and vision of the education field in…
Descriptors: Decision Making, Prediction, Models, Intervention
Hsu, Ting-Chia; Abelson, Hal; Patton, Evan; Chen, Shih-Chu; Chang, Hsuan-Ning – International Journal of Computer-Supported Collaborative Learning, 2021
In order to promote the practice of co-creation, a real-time collaboration (RTC) version of the popular block-based programming (BBP) learning environment, MIT App Inventor (MAI), was proposed and implemented. RTC overcomes challenges related to non-collocated group work, thus lowering barriers to cross-region and multi-user collaborative software…
Descriptors: Self Efficacy, Behavior Patterns, Student Behavior, Programming
da Cruz Alves, Nathalia; Gresse von Wangenheim, Christiane; Martins-Pacheco, Lúcia Helena – Informatics in Education, 2021
Creativity has emerged as an important 21st-century competency. Although it is traditionally associated with arts and literature, it can also be developed as part of computing education. Therefore, this article presents a systematic mapping of approaches for assessing creativity based on the analysis of computer programs created by the students.…
Descriptors: Creativity, 21st Century Skills, Computer Science Education, Programming
Fleischer, Yannik; Biehler, Rolf; Schulte, Carsten – Statistics Education Research Journal, 2022
This study examines modelling with machine learning. In the context of a yearlong data science course, the study explores how upper secondary students apply machine learning with Jupyter Notebooks and document the modelling process as a computational essay incorporating the different steps of the CRISP-DM cycle. The students' work is based on a…
Descriptors: Statistics Education, Educational Research, Electronic Learning, Secondary School Students
Sabarinath, Roshni; Quek, Choon Lang Gwendoline – Education and Information Technologies, 2020
Programming in schools is no longer a novel subject. It is now quite commonly found in our schools either in formal or informal curriculum. Programmers use creative learning tactics to solve problems and communicate ideas. Learning to program is generally considered challenging. Developing and implementing new methodologies in teaching programming…
Descriptors: Computer Science Education, Programming, Peer Evaluation, Coding