Analogy mapping for different learning style of learners in programming

Sukamto, Rosa Ariani; Megasari, Rani

doi:10.1109/icsitech.2017.8257189

Cited by 1 publication

(2 citation statements)

References 6 publications

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“…These findings applied to a CS1 are related to the teaching-learning processes of programming in studies carried out in children as presented by Pérez et al [76,77], Sukamto and Megasari [7], or through metaphors by Chibaya [78].…”

Section: Initial Processing Stagementioning

confidence: 64%

“…The scientific literature reports few experiences in the use of analogies for teachinglearning in a CS1, one of which is Collece 2.0, a programming learning environment that has been extended with mixed reality techniques and uses the analogy of roads and traffic signs for the study of recursion concepts [4][5][6]. In turn, Sukamto and Megasari [7] developed a model that converts source code into analogy images using state machines for teaching programming.…”

Section: Introductionmentioning

confidence: 99%

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Discovery Model Based on Analogies for Teaching Computer Programming

2021

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Teaching the fundamentals of computer programming in a first course (CS1) is a complex activity for the professor and is also a challenge for them. Nowadays, there are several teaching strategies for dealing with a CS1 at the university, one of which is the use of analogies to support the abstraction process that a student needs to carry for the appropriation of fundamental concepts. This article presents the results of applying a discovery model that allowed for the extraction of patterns, linguistic analysis, textual analytics, and linked data when using analogies for teaching the fundamental concepts of programming by professors in a CS1 in university programs that train software developers. For that reason, a discovery model based on machine learning and text mining was proposed using natural language processing techniques for semantic vector space modeling, distributional semantics, and the generation of synthetic data. The discovery process was carried out using nine supervised learning methods, three unsupervised learning methods, and one semi-supervised learning method involving linguistic analysis techniques, text analytics, and linked data. The main findings showed that professors include keywords, which are part of the technical computer terminology, in the form of verbs in the statement of the analogy and combine them in quantitative contexts with neutral or positive phrases, where numerical examples, cooking recipes, and games were the most used categories. Finally, a structure is proposed for the construction of analogies to teach programming concepts and this was validated by the professors and students.

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