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Shilo, Gila; Ragonis, Noa – Journal of Further and Higher Education, 2019
A central issue in the design of curricula for all school levels is the development of the learners' high-order thinking skills and metacognitive skills. Among such required skills is the ability to solve problems. The literature dealing with the development of problem-solving skills is vast and primarily addresses the scientific disciplines, even…
Descriptors: Thinking Skills, Metacognition, Problem Solving, Linguistics
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
Hundhausen, C. D.; Olivares, D. M.; Carter, A. S. – ACM Transactions on Computing Education, 2017
In recent years, learning process data have become increasingly easy to collect through computer-based learning environments. This has led to increased interest in the field of "learning analytics," which is concerned with leveraging learning process data in order to better understand, and ultimately to improve, teaching and learning. In…
Descriptors: Learning Analytics, Computer Science Education, Programming, Learning Processes
Kjelvik, Melissa K.; Schultheis, Elizabeth H. – CBE - Life Sciences Education, 2019
Data are becoming increasingly important in science and society, and thus data literacy is a vital asset to students as they prepare for careers in and outside science, technology, engineering, and mathematics and go on to lead productive lives. In this paper, we discuss why the strongest learning experiences surrounding data literacy may arise…
Descriptors: Data Use, Scientific Research, Information Literacy, STEM Education
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
Benjamin, Rebekah George – Educational Psychology Review, 2012
Largely due to technological advances, methods for analyzing readability have increased significantly in recent years. While past researchers designed hundreds of formulas to estimate the difficulty of texts for readers, controversy has surrounded their use for decades, with criticism stemming largely from their application in creating new texts…
Descriptors: Readability, Computer Science, Cognitive Psychology, Cognitive Processes
Carruthers, Sarah; Stege, Ulrike – Journal of Problem Solving, 2013
This article is concerned with how computer science, and more exactly computational complexity theory, can inform cognitive science. In particular, we suggest factors to be taken into account when investigating how people deal with computational hardness. This discussion will address the two upper levels of Marr's Level Theory: the computational…
Descriptors: Problem Solving, Computation, Difficulty Level, Computer Science
Bonestroo, Wilco J.; de Jong, Ton – Interactive Learning Environments, 2012
Self-regulated learners are expected to plan their own learning. Because planning is a complex task, it is not self-evident that all learners can perform this task successfully. In this study, we examined the effects of two planning support tools on the quality of created plans, planning behavior, task load, and acquired knowledge. Sixty-five…
Descriptors: Foreign Countries, Educational Technology, Preferences, Planning
Kolfschoten, Gwendolyn; Lukosch, Stephan; Verbraeck, Alexander; Valentin, Edwin; de Vreede, Gert-Jan – Computers & Education, 2010
Nowadays we need to teach students how to become flexible problem solvers in a dynamic world. The pace in which technology changes and complexity increases requires increased efficiency in learning and understanding. This requires the engineers of tomorrow to quickly gain knowledge and insight outside their prime area of expertise. To transfer…
Descriptors: Instructional Design, Problem Solving, Learning Processes, Efficiency
Holzinger, Andreas; Kickmeier-Rust, Michael; Albert, Dietrich – Educational Technology & Society, 2008
With the increasing use of dynamic media in multimedia learning material, it is important to consider not only the technological but also the cognitive aspects of its application. A large amount of previous research does not provide preference to either static or dynamic media for educational purposes and a considerable number of studies found…
Descriptors: Control Groups, Computer Science Education, Computer Assisted Instruction, Program Effectiveness
Garner, Stuart – Journal of Information Technology Education, 2009
This paper reports on the findings from a quantitative research study into the use of a software tool that was built to support a part-complete solution method (PCSM) for the learning of computer programming. The use of part-complete solutions to programming problems is one of the methods that can be used to reduce the cognitive load that students…
Descriptors: Control Groups, Academic Achievement, Computer Software, Statistical Analysis
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