Publication Date
In 2025 | 1 |
Since 2024 | 2 |
Since 2021 (last 5 years) | 5 |
Since 2016 (last 10 years) | 9 |
Since 2006 (last 20 years) | 14 |
Descriptor
Computer Science Education | 15 |
Difficulty Level | 15 |
Programming | 8 |
Foreign Countries | 6 |
Problem Solving | 6 |
Cognitive Processes | 5 |
Student Attitudes | 4 |
Coding | 3 |
College Faculty | 3 |
College Students | 3 |
Teacher Attitudes | 3 |
More ▼ |
Source
Computer Science Education | 15 |
Author
Publication Type
Journal Articles | 15 |
Reports - Research | 11 |
Reports - Evaluative | 3 |
Reports - Descriptive | 1 |
Tests/Questionnaires | 1 |
Education Level
Postsecondary Education | 9 |
Higher Education | 8 |
Elementary Secondary Education | 1 |
High Schools | 1 |
Secondary Education | 1 |
Audience
Location
Australia | 2 |
Israel | 2 |
Colombia | 1 |
Finland | 1 |
Pennsylvania | 1 |
United Kingdom | 1 |
Laws, Policies, & Programs
Assessments and Surveys
What Works Clearinghouse Rating
Renske Weeda; Sjaak Smetsers; Erik Barendsen – Computer Science Education, 2024
Background and Context: Multiple studies report that experienced instructors lack consensus on the difficulty of programming tasks for novices. However, adequately gauging task difficulty is needed for alignment: to select and structure tasks in order to assess what students can and cannot do. Objective: The aim of this study was to examine…
Descriptors: Novices, Coding, Programming, Computer Science Education
Pelánek, Radek; Effenberger, Tomáš – Computer Science Education, 2022
Background and Context: Block-based programming is a popular approach to teaching introductory programming. Block-based programming often works in the context of microworlds, where students solve specific puzzles. It is used, for example, within the Hour of Code event, which targets millions of students. Objective: To identify design guidelines…
Descriptors: Programming, Computer Science Education, Puzzles, Problem Solving
K. Ann Renninger; Ruth C. Elias; Mariko J. Kamiya; Jennifer N. Paige; Raymond A. Youngblood – Computer Science Education, 2025
Background and Context: Integrating computer science (CS) and math in classrooms is an increasingly recognized way for schools to address national CS mandates. There is a need to understand how professional development (PD) can support teachers to integrate. Objective: We examined math teachers' interest, and confidence, in math, CS, and student…
Descriptors: Faculty Development, Teacher Workshops, Computer Science Education, Mathematics Instruction
Frede, Christiane; Knobelsdorf, Maria – Computer Science Education, 2021
Background and Context: Considerable numbers of Computer science (CS) undergraduate majors struggle in Theory of Computation (ToC) courses, which strengthen bimodality beliefs of student performance. Reasons for students struggling are assumed to be manifold but substantial ground is based on studies providing singular insights into this matter.…
Descriptors: Computer Science Education, Academic Achievement, Introductory Courses, Computation
Espinal, Alejandro; Vieira, Camilo; Guerrero-Bequis, Valeria – Computer Science Education, 2023
Background and context: Transfer is a process where students apply their learning to different contexts. This process includes using their knowledge to solve problems with similar complexity, and in new contexts. In the context of programming, transfer also includes being able to understand and use different programming languages. Objective: This…
Descriptors: Block Scheduling, Computer Science Education, Programming Languages, Coding
Morrison, Briana B.; Margulieux, Lauren E.; Decker, Adrienne – Computer Science Education, 2020
Background and Context: Subgoal labeled worked examples have been extensively researched, but the research has been reported piecemeal. This paper aggregates data from three studies, including data previously unreported, to holistically examine the effect of subgoal labeled worked examples across three student populations and across different…
Descriptors: Computer Science Education, Instructional Materials, Instructional Effectiveness, Problem Solving
Hamouda, Sally; Edwards, Stephen H.; Elmongui, Hicham G.; Ernst, Jeremy V.; Shaffer, Clifford A. – Computer Science Education, 2020
Background and Context: Recursion in binary trees has proven to be a hard topic. There was not much research on enhancing student understanding of this topic. Objective: We present a tutorial to enhance learning through practice of recursive operations in binary trees, as it is typically taught post-CS2. Method: We identified the misconceptions…
Descriptors: Computer Science Education, Programming, Coding, Student Attitudes
Gal-Ezer, Judith; Trakhtenbrot, Mark – Computer Science Education, 2016
Reduction is one of the key techniques used for problem-solving in computer science. In particular, in the theory of computation and complexity (TCC), mapping and polynomial reductions are used for analysis of decidability and computational complexity of problems, including the core concept of NP-completeness. Reduction is a highly abstract…
Descriptors: Computer Science Education, Problem Solving, Computation, Difficulty Level
Ben-David Kolikant, Yifat; ma'ayan, Ze'ev – Computer Science Education, 2018
Higher-education students now have more alternatives for searching for information than previous generations had. The Internet is a vast ocean of information sources, albeit with diverse reliability and quality. In Web 2.0 platforms, any participant can be a content creator. This reality is challenging for both the instructors and the students. We…
Descriptors: Computer Science Education, Higher Education, Internet, Web 2.0 Technologies
Gluga, Richard; Kay, Judy; Lister, Raymond; Kleitman, Simon; Kleitman, Sabina – Computer Science Education, 2013
To design an effective computer science curriculum, educators require a systematic method of classifying the difficulty level of learning activities and assessment tasks. This is important for curriculum design and implementation and for communication between educators. Different educators must be able to use the method consistently, so that…
Descriptors: Computer Science Education, Cognitive Development, Difficulty Level, Test Items
Rountree, Janet; Robins, Anthony; Rountree, Nathan – Computer Science Education, 2013
We propose an expanded definition of Threshold Concepts (TCs) that requires the successful acquisition and internalisation not only of knowledge, but also its practical elaboration in the domains of applied strategies and mental models. This richer definition allows us to clarify the relationship between TCs and Fundamental Ideas, and to account…
Descriptors: Fundamental Concepts, Concept Formation, Computer Science Education, Undergraduate Students
Mason, Raina; Cooper, Graham – Computer Science Education, 2013
This paper reports on a series of introductory programming workshops, initially targeting female high school students, which utilised Lego Mindstorms robots. Cognitive load theory (CLT) was applied to the instructional design of the workshops, and a controlled experiment was also conducted investigating aspects of the interface. Results indicated…
Descriptors: Programming, Introductory Courses, Cognitive Processes, Difficulty Level
Shuhidan, Shuhaida; Hamilton, Margaret; D'Souza, Daryl – Computer Science Education, 2010
Learning to program is known to be difficult for novices. High attrition and high failure rates in foundation-level programming courses undertaken at tertiary level in Computer Science programs, are commonly reported. A common approach to evaluating novice programming ability is through a combination of formative and summative assessments, with…
Descriptors: Teacher Attitudes, Secondary School Teachers, College Faculty, Multiple Choice Tests
Oliver, Dave; Dobele, Tony; Greber, Myles; Roberts, Tim – Computer Science Education, 2004
This paper describes an exercise in determining the cognitive difficulty of the assessment tasks in six computing courses within an Information Technology (IT) degree, importing Bloom's taxonomy from the field of educational psychology as an analytical framework. Three of the six courses comprise a Programming stream and three a Data…
Descriptors: Computer Science Education, Courses, Difficulty Level, Cognitive Processes
Mannila, Linda; Peltomaki, Mia; Salakoski, Tapio – Computer Science Education, 2006
In this paper, we present the results from a two-part study. We analyze 60 programs written by novice programmers aged 16-19 after their first programming course, in either Java or Python. The aim is to find difficulties independent of the language used, and such originating from the language. Second, we analyze the transition from a…
Descriptors: Programming, Programming Languages, Syntax, Learning Problems