Naslov
Mediated transfer: impact on programming misconceptions

Autori
Žanko, Žana ; Mladenović, Monika ; Krpan, Divna

Izvornik
Journal of computers in education (2197-9987) 10 (2023), 1; 1-26

Vrsta, podvrsta i kategorija rada
Radovi u časopisima, članak, znanstveni

Ključne riječi
Misconceptions ; Mediated transfer ; Programming ; Python ; Micro:bit ; Programming novices ; K-12

Sažetak
Programming misconceptions have been a known issue for programming novices since the beginning of programming education. During the learning process, students develop mental models about programming concepts they learn. Programming misconceptions occur when students develop incorrect mental models. Several factors can contribute to developing or preventing misconceptions, such as the age of students, choice of the programming language, and programming context. Mentioned factors are more critical for younger students. Since block-based programming languages (BPL) eliminate syntax problems and lower abstraction, they could be appropriate for elementary school introductory programming. However, when BPL is used as a first programming language, students have difficulties transferring learned programming concepts to a text-based programming language (TBPL). Nevertheless, the final goal is to introduce students to the “real” TBPL. In this paper, we aimed to discover can we use BPL for mediated transfer to minimise known misconceptions in a TBPL. We conducted the study to analyse the impact of using a BPL MakeCode for micro:bit for mediated transfer of basic programming concepts to the TBPL Python. The study was conducted in the school setting among 49 sixth-graders in elementary school during Informatics lectures, following the national curriculum. Therefore, students were introduced to programming using TBPL Python and afterwards, they switched to BPL MakeCode as mediated transfer tool to TBPL Python. In this paper, we deal with the impact of the mediated transfer on misconceptions in TBPL. The results indicate that the use of BPL significantly decreased the frequency of misconceptions in TBPL Python.

Izvorni jezik
Engleski

Znanstvena područja
Računarstvo, Interdisciplinarne društvene znanosti

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