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Silva, Leonardo; Mendes, Antonio Jose; Gomes, Anabela; Fortes, Gabriel – IEEE Transactions on Education, 2023
Contribution: Students' problem-understanding abilities and their relationship with programming learning were investigated using a methodology little explored in the existing literature. Background: Problem comprehension is an ability used during software development. Current research points to conflicting results on students' ability to interpret…
Descriptors: Programming, Comprehension, Computer Software, Electronic Learning
Milos Ilic; Goran Kekovic; Vladimir Mikic; Katerina Mangaroska; Lazar Kopanja; Boban Vesin – IEEE Transactions on Learning Technologies, 2024
In recent years, there has been an increasing trend of utilizing artificial intelligence (AI) methodologies over traditional statistical methods for predicting student performance in e-learning contexts. Notably, many researchers have adopted AI techniques without conducting a comprehensive investigation into the most appropriate and accurate…
Descriptors: Artificial Intelligence, Academic Achievement, Prediction, Programming
Pearson, 2020
Programming and coding skills are in high demand, and can provide access to employment in growing fields. But a high percentage of undergraduates who enroll in relevant programs do not persist until they achieve competency in the subject and employment in the field. Revel for "Introduction to Java Programming" aims to give students an…
Descriptors: Introductory Courses, Programming, Computer Science Education, Electronic Learning
Fay, Derek; Armstrong, Mark; McEldoon, Katherine; Ridley, Julia – Pearson, 2020
Programming and coding skills are in high demand, and can provide access to employment in growing fields. But a high percentage of undergraduates who enroll in relevant programs do not persist until they achieve competency in the subject and employment in the field. Revel is an interactive learning environment intended to help students prepare for…
Descriptors: Introductory Courses, Programming, Computer Science Education, Electronic Learning
Bodaker, Liat; Rosenberg-Kima, Rinat B. – Journal of Research on Technology in Education, 2023
The COVID-19 pandemic raised the need to examine online learning methods also in young children. This study examined elementary school children's performance and attitudes during and toward an online programming learning activity utilizing the pair-programming Agile method that may foster 21st-century skills, including collaboration and…
Descriptors: Electronic Learning, Cooperative Learning, Programming, Computer Science Education
Gabbay, Hagit; Cohen, Anat – International Educational Data Mining Society, 2022
The challenge of learning programming in a MOOC is twofold: acquiring programming skills and learning online, independently. Automated testing and feedback systems, often offered in programming courses, may scaffold MOOC learners by providing immediate feedback and unlimited re-submissions of code assignments. However, research still lacks…
Descriptors: Automation, Feedback (Response), Student Behavior, MOOCs
Fehaid Lafi Alshammari – Journal of Education and e-Learning Research, 2024
Microlearning is a modern learning modality that has been adopted in recent years for student education. This study aimed to reveal the effect of video-based microlearning on the development of programming skills and technology acceptance among intermediate school students. The study used a quasi-experimental design for two groups. A technology…
Descriptors: Foreign Countries, Middle School Students, Programming, Computer Science 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
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
Garcia, Fabrício Wickey da Silva; Oliveira, Sandro Ronaldo Bezerra; Carvalho, Elielton da Costa – Informatics in Education, 2023
The contents taught in the programming subjects have a great relevance in the formation of computing students. However, these subjects are characterized by high failure rates, as they require logical reasoning and mathematical knowledge. Thus, establishing knowledge through the subject of algorithms can help students to overcome these difficulties…
Descriptors: Teaching Methods, Algorithms, Undergraduate Students, Computer Science Education
Krouska, Akrivi; Troussas, Christos; Sgouropoulou, Cleo – Education and Information Technologies, 2022
The closure of educational institutions due to the COVID-19 pandemic leads imperatively to the utilization of technological advances and the Internet for enabling the continuity of learning. To this direction, Mobile Game-based Learning (MGbL) can be beneficial to teaching and learning; since, from technological perspective, most students prefer…
Descriptors: Game Based Learning, Electronic Learning, COVID-19, Pandemics
Somyürek, Sibel; Brusilovsky, Peter; Çebi, Ayça; Akhüseyinoglu, Kamil; Güyer, Tolga – International Journal of Information and Learning Technology, 2021
Purpose: Interest is currently growing in open social learner modeling (OSLM), which means making peer models and a learner's own model visible to encourage users in e-learning. The purpose of this study is to examine students' views about the OSLM in an e-learning system. Design/methodology/approach: This case study was conducted with 40…
Descriptors: Student Attitudes, Self Evaluation (Individuals), Peer Evaluation, Electronic Learning
Schwarzenberg, Pablo; Navon, Jaime; Pérez-Sanagustín, Mar – Journal of Computing in Higher Education, 2020
The flipped classroom gives students the flexibility to organize their learning, while teachers can monitor their progress analyzing their online activity. In massive courses where there are a variety of activities, automated analysis techniques are required in order to process the large volume of information that is generated, to help teachers…
Descriptors: Models, Blended Learning, Teaching Methods, Electronic Learning