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Peabody, Michael R. – Measurement: Interdisciplinary Research and Perspectives, 2023
Many organizations utilize some form of automation in the test assembly process; either fully algorithmic or heuristically constructed. However, one issue with heuristic models is that when the test assembly problem changes the entire model may need to be re-conceptualized and recoded. In contrast, mixed-integer programming (MIP) is a mathematical…
Descriptors: Programming Languages, Algorithms, Heuristics, Mathematical Models
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Sapounidis, Theodosios; Stamovlasis, Dimitrios; Demetriadis, Stavros – IEEE Transactions on Education, 2019
Contribution: Prior studies on tangible versus graphical user interfaces have reported controversial findings concerning children's preferences. This paper shows that their preference profiles in the domain of introductory programming are associated with gender and age for both interfaces. Background: The relevant literature mainly consists of…
Descriptors: Preferences, Profiles, Robotics, Introductory Courses
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Alexandron, Giora; Armoni, Michal; Gordon, Michal; Harel, David – ACM Transactions on Computing Education, 2014
In this article, we discuss the possible connection between the programming language and the paradigm behind it, and programmers' tendency to adopt an external or internal perspective of the system they develop. Based on a qualitative analysis, we found that when working with the visual, interobject language of live sequence charts (LSC),…
Descriptors: Programming Languages, Attitudes, Usability, Problem Solving
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Shehane, Ronald; Sherman, Steven – Journal of Instructional Pedagogies, 2014
This study examines detailed usage of online training videos that were designed to address specific course problems that were encountered in an online computer programming course. The study presents the specifics of a programming course where training videos were used to provide students with a quick start path to learning a new programming…
Descriptors: Teaching Models, Programming Languages, Computer Science Education, Visual Learning