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Multimedia System for Self-learning C/C++ Programming Language

Part of the Learning and Analytics in Intelligent Systems book series (LAIS,volume 7)

Abstract

The C programming language is widely used in computer and industrial engineering. Because of that, such programming language is also widely used as a language to teach programming to industrial engineering students. In Spain, many universities use this language compulsory in the first year, or even in higher courses. Our experience shows that learning computer programming in four months is an arduous task, but curricula require it. Such learning process is also tough by the fact that many students cannot attend classes regularly and, even if they attend, sometimes the class is no longer at the level they require. In this work we develop a series of files in “presentation” format (.ppsx) and videos that allow students to see several explanations about the most complicated programming C topics: functions, arrays, structures, strings, arrays with structures… This multimedia material includes explanations (voice-over), and animations with examples. Students can watch and listen to the explanations whenever and wherever they want (tablet, PC, phone…). Surveys made to students reveal that it is also interesting for students who regularly attend classes, and they prefer to use this course material only at home, outside of regular classes.

Keywords

  • Programming languages
  • Multimedia teaching
  • Autonomous learning
  • C/C++ language

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Source: own construction.

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Source: own construction.

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Acknowledgments

The authors would like to express their gratitude to the University of Málaga, supporting this work under the PIE17-175 project entitled “Autoaprendizaje de programación de ordenadores”.

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Correspondence to José Galindo .

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Galindo, J., Galindo, P., Corral, J.M.R. (2020). Multimedia System for Self-learning C/C++ Programming Language. In: Serrhini, M., Silva, C., Aljahdali, S. (eds) Innovation in Information Systems and Technologies to Support Learning Research. EMENA-ISTL 2019. Learning and Analytics in Intelligent Systems, vol 7. Springer, Cham. https://doi.org/10.1007/978-3-030-36778-7_7

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