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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
Brown, Neil C. C.; Altadmri, Amjad – ACM Transactions on Computing Education, 2017
Teaching is the process of conveying knowledge and skills to learners. It involves preventing misunderstandings or correcting misconceptions that learners have acquired. Thus, effective teaching relies on solid knowledge of the discipline, but also a good grasp of where learners are likely to trip up or misunderstand. In programming, there is much…
Descriptors: Novices, Programming Languages, Programming, Error Patterns
McCauley, Renée; Grissom, Scott; Fitzgerald, Sue; Murphy, Laurie – Computer Science Education, 2015
Hundreds of articles have been published on the topics of teaching and learning recursion, yet fewer than 50 of them have published research results. This article surveys the computing education research literature and presents findings on challenges students encounter in learning recursion, mental models students develop as they learn recursion,…
Descriptors: Computer Science Education, Programming, Literature Reviews, Best Practices
Taylor, C.; Zingaro, D.; Porter, L.; Webb, K. C.; Lee, C. B.; Clancy, M. – Computer Science Education, 2014
Concept Inventories (CIs) are assessments designed to measure student learning of core concepts. CIs have become well known for their major impact on pedagogical techniques in other sciences, especially physics. Presently, there are no widely used, validated CIs for computer science. However, considerable groundwork has been performed in the form…
Descriptors: STEM Education, Computer Science Education, Concept Formation, Scientific Concepts
Sorva, Juha – ACM Transactions on Computing Education, 2013
This article brings together, summarizes, and comments on several threads of research that have contributed to our understanding of the challenges that novice programmers face when learning about the runtime dynamics of programs and the role of the computer in program execution. More specifically, the review covers the literature on programming…
Descriptors: Computer Science Education, Programming, Introductory Courses, Misconceptions
Ma, L.; Ferguson, J.; Roper, M.; Wood, M. – Computer Science Education, 2011
The teaching of introductory computer programming seems far from successful, with many first-year students performing more poorly than expected. One possible reason for this is that novices hold "non-viable" mental models (internal explanations of how something works) of key programming concepts which then cause misconceptions and difficulties. An…
Descriptors: Teaching Models, Programming, Misconceptions, Models
Drake, John R. – Journal of Information Technology Education: Innovations in Practice, 2012
Active learning has been championed in academic circles as the pedagogical fix to boring lectures typically found in introduction to information systems courses. However, the literature on active learning is mixed. In this paper, we critically examine active learning research and discover a misplaced emphasis leading to paradoxical findings in…
Descriptors: Classroom Techniques, Learning Theories, Class Activities, Course Objectives
Tangney, Brendan; Oldham, Elizabeth; Conneely, Claire; Barrett, Stephen; Lawlor, John – IEEE Transactions on Education, 2010
This paper describes a model for computer programming outreach workshops aimed at second-level students (ages 15-16). Participants engage in a series of programming activities based on the Scratch visual programming language, and a very strong group-based pedagogy is followed. Participants are not required to have any prior programming experience.…
Descriptors: Foreign Countries, Computer Software, Programming Languages, Computer Science Education
Sajaniemi, Jorma; Kuittinen, Marja; Tikansalo, Taina – Journal on Educational Resources in Computing, 2008
Students' understanding of object-oriented (OO) program execution was studied by asking students to draw a picture of a program state at a specific moment. Students were given minimal instructions on what to include in their drawings in order to see what they considered to be central concepts and relationships in program execution. Three drawing…
Descriptors: Freehand Drawing, Programming, Student Development, Misconceptions
Simon, Beth; Bouvier, Dennis; Chen, Tzu-Yi; Lewandowski, Gary; McCartney, Robert; Sanders, Kate – Computer Science Education, 2008
We report on responses to a series of four questions designed to identify pre-existing abilities related to debugging and troubleshooting experiences of novice students before they begin programming instruction. The focus of these questions include general troubleshooting, bug location, exploring unfamiliar environments, and describing students'…
Descriptors: Troubleshooting, Teaching Methods, Computer Science Education, Programming
Madhyastha, Tara M.; Tanimoto, Steven – International Working Group on Educational Data Mining, 2009
Most of the emphasis on mining online assessment logs has been to identify content-specific errors. However, the pattern of general "consistency" is domain independent, strongly related to performance, and can itself be a target of educational data mining. We demonstrate that simple consistency indicators are related to student outcomes,…
Descriptors: Web Based Instruction, Computer Assisted Testing, Computer Software, Computer Science Education
Rothstein, Richard – School Administrator, 2001
Despite politicians' claims to the contrary, public schools are not holding back the economy, and most future jobs will require only modest skill growth. Economists attribute today's economic growth not to improved schools, but to greater efficiency, downward price pressure, and experimentation with lower interest rates. (MLH)
Descriptors: Computer Science Education, Economic Change, Education Work Relationship, Elementary Secondary Education