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Lokkila, Erno; Christopoulos, Athanasios; Laakso, Mikko-Jussi – Informatics in Education, 2023
Prior programming knowledge of students has a major impact on introductory programming courses. Those with prior experience often seem to breeze through the course. Those without prior experience see others breeze through the course and disengage from the material or drop out. The purpose of this study is to demonstrate that novice student…
Descriptors: Prior Learning, Programming, Computer Science Education, Markov Processes
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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
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Anael Kuperwajs Cohen; Alannah Oleson; Amy J. Ko – ACM Transactions on Computing Education, 2024
Collaboration is an important aspect of computing. In a classroom setting, working with others can increase a student's motivation to attempt more challenges, reduce the difficulty of complicated concepts, and bring about greater overall success. Despite extensive research in other domains, there has been minimal exploration within computing on…
Descriptors: College Students, Help Seeking, Student Behavior, Programming
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Singla, Adish; Theodoropoulos, Nikitas – International Educational Data Mining Society, 2022
Block-based visual programming environments are increasingly used to introduce computing concepts to beginners. Given that programming tasks are open-ended and conceptual, novice students often struggle when learning in these environments. AI-driven programming tutors hold great promise in automatically assisting struggling students, and need…
Descriptors: Programming, Computer Science Education, Task Analysis, Introductory Courses
Mohammed Alzaid – ProQuest LLC, 2022
Distributed self-assessments and reflections empower learners to take the lead on their knowledge gaining evaluation. Both provide essential elements for practice and self-regulation in learning settings. Nowadays, many sources for practice opportunities are made available to the learners, especially in the Computer Science (CS) and programming…
Descriptors: Learning Analytics, Self Evaluation (Individuals), Programming, Problem Solving
Saira Anwar; Ahmed Ashraf Butt; Muhsin Menekse – Grantee Submission, 2022
This work-in-progress research paper examines the relationship between two aspects of students' engagement and academic performance. With the boom of technology-mediated learning environments, many educational applications are integrated into STEM courses. However, the effectiveness of these applications in the learning environments is contingent…
Descriptors: Learner Engagement, Academic Achievement, College Freshmen, Engineering Education
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Rodrigues, Luiz; Pereira, Filipe D.; Toda, Armando M.; Palomino, Paula T.; Pessoa, Marcela; Carvalho, Leandro Silva Galvão; Fernandes, David; Oliveira, Elaine H. T.; Cristea, Alexandra I.; Isotani, Seiji – International Journal of Educational Technology in Higher Education, 2022
There are many claims that gamification (i.e., using game elements outside games) impact decreases over time (i.e., the novelty effect). Most studies analyzing this effect focused on extrinsic game elements, while fictional and collaborative competition have been recently recommended. Additionally, to the best of our knowledge, no long-term…
Descriptors: Game Based Learning, Novelty (Stimulus Dimension), Familiarity, Learning Processes
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Qian, Yizhou; Lehman, James – Journal of Educational Computing Research, 2020
This study implemented a data-driven approach to identify Chinese high school students' common errors in a Java-based introductory programming course using the data in an automated assessment tool called the Mulberry. Students' error-related behaviors were also analyzed, and their relationships to success in introductory programming were…
Descriptors: High School Students, Error Patterns, Introductory Courses, Computer Science Education
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Pereira, Filipe D.; Oliveira, Elaine H. T.; Oliveira, David B. F.; Cristea, Alexandra I.; Carvalho, Leandro S. G.; Fonseca, Samuel C.; Toda, Armando; Isotani, Seiji – British Journal of Educational Technology, 2020
Tools for automatic grading programming assignments, also known as Online Judges, have been widely used to support computer science (CS) courses. Nevertheless, few studies have used these tools to acquire and analyse interaction data to better understand the students' performance and behaviours, often due to data availability or inadequate…
Descriptors: Introductory Courses, Programming, Outcomes of Education, Student Behavior
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Ahadi, Alireza; Hellas, Arto; Lister, Raymond – ACM Transactions on Computing Education, 2017
We describe a method for analyzing student data from online programming exercises. Our approach uses contingency tables that combine whether or not a student answered an online exercise correctly with the number of attempts that the student made on that exercise. We use this method to explore the relationship between student performance on online…
Descriptors: Data Analysis, Online Courses, Computer Science Education, Programming
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Hughes, Michael C.; Jadud, Matthew C.; Rodrigo, Ma. Mercedes T. – Computer Science Education, 2010
In Java, "System.out.printf" and "String.format" consume a specialised kind of string commonly known as a format string. In our study of first-year students at the Ateneo de Manila University, we discovered that format strings present a substantial challenge for novice programmers. Focusing on their first laboratory we found…
Descriptors: Foreign Countries, Computer Science Education, Programming Languages, Introductory Courses
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Blikstein, Paulo; Worsley, Marcelo; Piech, Chris; Sahami, Mehran; Cooper, Steven; Koller, Daphne – Journal of the Learning Sciences, 2014
New high-frequency, automated data collection and analysis algorithms could offer new insights into complex learning processes, especially for tasks in which students have opportunities to generate unique open-ended artifacts such as computer programs. These approaches should be particularly useful because the need for scalable project-based and…
Descriptors: Programming, Computer Science Education, Learning Processes, Introductory Courses
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Pilkington, Colin; Gelderblom, Helene – African Journal of Research in Mathematics, Science and Technology Education, 2010
Many learners find the study of introductory computer programming difficult. This is also true of children with attention deficit hyperactivity disorder (ADHD) and, in order to support them, we need an improved understanding of how they learn programming. This study explored strategies for constructive learning of introductory programming by…
Descriptors: Teaching Methods, Attention Deficit Hyperactivity Disorder, Programming, Introductory Courses
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Jadud, Matthew C. – Computer Science Education, 2005
Syntactically correct code does not fall from the sky; the process that leads to a student's first executable program is not well understood. At the University of Kent we have begun to explore the "compilation behaviours" of novice programmers, or the behaviours that students exhibit while authoring code; in our initial study, we have…
Descriptors: Introductory Courses, Programming, Student Behavior, Educational Technology
International Association for Development of the Information Society, 2012
The IADIS CELDA 2012 Conference intention was to address the main issues concerned with evolving learning processes and supporting pedagogies and applications in the digital age. There had been advances in both cognitive psychology and computing that have affected the educational arena. The convergence of these two disciplines is increasing at a…
Descriptors: Academic Achievement, Academic Persistence, Academic Support Services, Access to Computers