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Juraj Hromkovic; Regula Lacher – Informatics in Education, 2025
The design of algorithms is one of the hardest topics of high school computer science. This is mainly due to the universality of algorithms as solution methods that guarantee the calculation of a correct solution for all potentially infinitely many instances of an algorithmic problem. The goal of this paper is to present a comprehensible and…
Descriptors: Algorithms, Computer Science Education, High School Students, Teaching Methods
Lee, Hyejeong; Closser, Florentina; Alghamdi, Khadijah; Ottenbreit-Leftwich, Anne; Brown, Matthew; Koressel, Jacob – TechTrends: Linking Research and Practice to Improve Learning, 2023
This study aims to examine the current experiences of high school students in computer science (CS) courses and the factors that motivated them to continue their future enrollment. The participants were 603 high school students in grades 9 through 12 in Indiana, all of whom enrolled in at least one CS course during the 2020-2021 academic year.…
Descriptors: Student Experience, Predictor Variables, Enrollment, Computer Science Education
Prateek Shekhar; Heydi Dominguez; Pramod Abichandani; Craig Iaboni – IEEE Transactions on Education, 2024
Purpose: The presented study was conducted to unpack high school students' motivational influences in engineering/computer science project-based learning (PjBL), using the attention, relevance, confidence, and satisfaction (ARCS) model of motivation as a conceptual framework. Methods: A qualitative research approach was used with student focus…
Descriptors: High School Students, Student Projects, Student Motivation, Learning Motivation
Gayithri Jayathirtha; Deborah Fields; Yasmin Kafai – Computer Science Education, 2024
Background and Context: Debugging is a challenging yet understudied practice within recent collaborative K-12 physical computing contexts. We examined think-aloud interviews and reflections of seven high school student pairs who debugged researcher-designed buggy electronic textile projects. Objective: We asked: (1) What strategies did student…
Descriptors: High School Students, Problem Solving, Cooperation, Small Group Instruction
Trina Johnson Kilty; Kevin T. Kilty; Andrea C. Burrows Borowczak; Mike Borowczak – Problems of Education in the 21st Century, 2024
A computer science camp for pre-collegiate students was operated during the summers of 2022 and 2023. The effect the camp had on attitudes was quantitatively assessed using a survey instrument. However, enrollment at the summer camp was small, which meant the well-known Pearson's Chi-Squared to measure the significance of results was not applied.…
Descriptors: Summer Programs, Camps, Computer Science Education, 21st Century Skills
Mike Karlin; Anne Ottenbreit-Leftwich; Yin-Chan Janet Liao – TechTrends: Linking Research and Practice to Improve Learning, 2024
While a growing emphasis has been placed on broadening participation in computer science (CS) education, an enduring gender gap exists. One reason for this is gender-based CS stereotypes, which serve as gatekeepers and act in exclusionary ways. However, some high schools in the U.S. have still built gender-inclusive CS programs. We conducted a…
Descriptors: High Schools, Computer Science Education, Gender Differences, Stereotypes
Debora Lui; Deborah A. Fields; Yasmin B. Kafai – Cognition and Instruction, 2024
Debugging (or troubleshooting) provides a rich context to foster problem-solving. Yet, while we know much about some problems and strategies that novices face in programming on-screen, we know far less about debugging and troubleshooting in the context of physical computing, where coding issues may overlap with materially embedded problems. In…
Descriptors: Grade 9, STEM Education, Troubleshooting, Public Schools
Chiao Ling Huang; Lianzi Fu; Shih-Chieh Hung; Shu Ching Yang – Journal of Computer Assisted Learning, 2025
Background: Many studies have highlighted the positive effects of visual programming instruction (VPI) on students' learning experiences, programming self-efficacy and flow experience. However, there is a notable gap in the research on how these factors specifically impact programming achievement and learning intentions. Our study addresses this…
Descriptors: Attention, Self Efficacy, Visual Aids, Instructional Effectiveness
Michael Karlin; Anne Ottenbreit-Leftwich; Yin-Chan Janet Liao – International Journal of Computer Science Education in Schools, 2024
A significant gender gap continues to exist within computer science (CS) education, despite nationwide emphasis in the U.S. on improving CS education equity and access. To explore this issue, we conducted an ethnographic case study within a classroom at Forest View High School (FVHS, pseudonym) where girls' participation in CS was consistently…
Descriptors: Computer Science Education, Student Experience, Teaching Experience, High School Students
Ünal Çakiroglu; Seval Bilgi – Interactive Learning Environments, 2024
The aim of this explanatory study is to identify the causes of intrinsic cognitive load in programming process. For this purpose, a method based on two dimensions; programming knowledge types (syntactic, semantic, and strategic) and programming constructs was proposed. The proposed method was tested with high school students enrolled in Computer…
Descriptors: Cognitive Processes, Difficulty Level, Programming, Interaction
Monika Mladenovic; Lucija Medak; Divna Krpan – ACM Transactions on Computing Education, 2025
Computer Science (CS) Unplugged activities are designed to engage students with CS concepts. It is an active learning approach combining physical interaction with visual representation. This research article investigates the impact of CS Unplugged on students' understanding of the bubble sort algorithm. Algorithm visualization, traditionally…
Descriptors: Computer Science Education, Learning Activities, Active Learning, Algorithms
Jill Denner; Heather Bell; David Torres; Emily Green – Computer Science Education, 2024
Background and context: High school students' interest in computing fields is not always sustained in community college due to a disconnect between institutions. Objective: To understand how cross-sector collaborations can align institutional pathways in computing. Research questions: What cross-sector practices can be used to build a computing…
Descriptors: Computer Science Education, Guided Pathways, High Schools, Community Colleges
Anna Fergusson; Maxine Pfannkuch – Journal of Statistics and Data Science Education, 2024
Statistics teaching at the high school level needs modernizing to include digital sources of data that students interact with every day. Algorithmic modeling approaches are recommended, as they can support the teaching of data science and computational thinking. Research is needed about the design of tasks that support high school statistics…
Descriptors: High School Students, Statistics Education, Thinking Skills, Computer Science Education
Ramon Mayor Martins; Christiane G. Von Wangenheim; Marcelo F. Rauber; Adriano F. Borgatto; Jean C. R. Hauck – ACM Transactions on Computing Education, 2024
As Machine Learning (ML) becomes increasingly integrated into our daily lives, it is essential to teach ML to young people from an early age including also students from a low socioeconomic status (SES) background. Yet, despite emerging initiatives for ML instruction in K-12, there is limited information available on the learning of students from…
Descriptors: Artificial Intelligence, Computer Science Education, Socioeconomic Status, Correlation
Jacqueline Nijenhuis-Voogt; Durdane Bayram; Paulien C. Meijer; Erik Barendsen – International Journal of Computer Science Education in Schools, 2024
A context-based approach to education aims to improve students' meaningful learning and uses authentic situations in which scientific concepts are applied. The use of contexts may contribute to the learning of abstract concepts such as algorithms. The selection of appropriate contexts, however, is challenging for teachers. It is therefore…
Descriptors: Secondary Education, Computer Science Education, Secondary School Science, Algorithms