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Nikolaos Pellas – Journal of Educational Computing Research, 2024
Educational technologists and practitioners have made substantial strides in developing affordable digital and tangible resources to support both formal and informal computer science instruction. However, there is a lack of research on practice-based assignments, such as Internet of Things (IoT) projects, that allow undergraduate students to…
Descriptors: Computation, Thinking Skills, Learning Motivation, Academic Persistence
Chengliang Wang; Xiaojiao Chen; Yifei Li; Pengju Wang; Haoming Wang; Yuanyuan Li – Journal of Educational Computing Research, 2025
This study explored the impact of MetaClassroom, a virtual immersive programming learning environment designed based on the three-dimensional learning progression (3DLP) concept, on students' multidimensional development. Utilizing a quasi-experimental research design, this study compared students' programming learning achievements (PLA),…
Descriptors: Programming, Computer Science Education, Metacognition, Computer Simulation
Busra Ozmen Yagiz; Ecenaz Alemdag – Education and Information Technologies, 2025
Resilience is a critical personality trait that allows one to deal with difficulties, learn from failures, and maintain a positive attitude during task performance. However, it has not been understudied in a complex and challenging educational domain. The current research intends to address this gap by analyzing the specific characteristics of…
Descriptors: Foreign Countries, Undergraduate Students, Resilience (Psychology), Programming
Amanpreet Kaur; Kuljit Kaur Chahal – Education and Information Technologies, 2024
Research so far has overlooked the contribution of students' noncognitive factors to their performance in introductory programming in the context of personalized learning support. This study uses learning analytics to design and implement a Dashboard to understand the contribution of introductory programming students' learning motivation,…
Descriptors: Learning Analytics, Introductory Courses, Programming, Computer Science Education
Antti-Jussi Lakanen; Ville Isomöttönen – Informatics in Education, 2023
This research investigates university students' success in their first programming course (CS1) in relation to their motivation, mathematical ability, programming self-efficacy, and initial goal setting. To our knowledge, these constructs have not been measured in a single study before in the Finnish context. The selection of the constructs is in…
Descriptors: Foreign Countries, College Students, Student Motivation, Self Efficacy
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
Flores, Rejeenald M.; Rodrigo, Ma. Mercedes T. – Journal of Educational Computing Research, 2020
Wheel-spinning refers to the failure to master a skill in a timely manner or after a considerable number of practice opportunities. Several past studies have developed wheel-spinning models in the areas of Mathematics and Physics. However, no models have been made for the context of novice programming. The purpose of this study was to develop…
Descriptors: Mastery Learning, Novices, Programming, Computer Science Education
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
Ernst Bekkering – Information Systems Education Journal, 2025
Undergraduate research can stimulate students' interest, especially in STEM disciplines. This research can be formally offered in different formats such as Undergraduate Research Experiences (UREs). One of these is Course-based Undergraduate Research Experiences (CUREs), which are offered as an integral part of scheduled courses. CUREs have been…
Descriptors: Undergraduate Students, Research Training, Computer Science Education, Student Interests
Gorman, Garry; McKelvey, Nigel; Dowling, Thomas C. – International Journal of Game-Based Learning, 2022
This paper describes a growth mind-set intervention with Junior Cycle Coding students in a disadvantaged school in Ireland. This intervention builds on the work of O'Rourke et al. (2016) and applies findings to a computer programming setting where gamification is used to incentivise growth mind-set behaviour in students learning to code. Data…
Descriptors: Game Based Learning, Coding, Computer Science Education, Disadvantaged Schools
Alex Fegely; Cory Gleasman; Tammi Kolski – Educational Technology Research and Development, 2024
Computer science teaching standards for grades K-8 have been implemented in nearly all U.S. states, and the core subject area teachers (e.g., math, science, English, social studies) have been asked to integrate these standards into their instruction. Thus, it is important that K-8 pre-service teachers of all subjects are both prepared and…
Descriptors: Educational Technology, Robotics, Shared Resources and Services, Preservice Teacher Education
Philip Sands – ProQuest LLC, 2021
Over the past 20 years, the field of computer science has experienced a growth in student interest. Despite this increase in participation rates, longstanding gender gaps persist in computer science. Recent research has examined a wide variety of individual factors (e.g., self-efficacy, sense of belonging, etc.) that impact student interest and…
Descriptors: Computer Science Education, Gender Differences, Prior Learning, Programming
Chen, Chen; Sonnert, Gerhard; Sadler, Philip M.; Malan, David J. – Journal of Computer Assisted Learning, 2020
Massive open online course (MOOC) studies have shown that precourse skills (such as precomputational thinking) and course engagement measures (such as making multiple submission attempts with assignments when the initial submission is incorrect) predict students' grade performance, yet little is known about whether these factors predict students'…
Descriptors: Computation, Thinking Skills, Assignments, Predictor Variables
Weston, Timothy J.; Dubow, Wendy M.; Kaminsky, Alexis – ACM Transactions on Computing Education, 2020
While demand for computer science and information technology skills grows, the proportion of women entering computer science (CS) fields has declined. One critical juncture is the transition from high school to college. In our study, we examined factors predicting college persistence in computer science- and technology-related majors from data…
Descriptors: Females, Academic Persistence, High School Students, Computer Science Education
Assignon, Selom – ProQuest LLC, 2018
The problem of low student completion rates in distance learning courses remains one of the major issues that institutions of higher learning face. Efforts by school administrators to reverse this trend have so far produced mixed results. The rapid expansion of distance learning has encouraged many institutions to move more courses online,…
Descriptors: Academic Achievement, Computer Science Education, Online Courses, Distance Education
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