Investigating the effects of learning activities in a mobile Python tutor for targeting multiple coding skills

Abstract Mobile devices are increasingly being utilized for learning due to their unique features including portability for providing ubiquitous experiences. In this paper, we present PyKinetic, a mobile tutor we developed for Python programming, aimed to serve as a supplement to traditional courses...

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Bibliographic Details
Main Authors: Geela Venise Firmalo Fabic (Author), Antonija Mitrovic (Author), Kourosh Neshatian (Author)
Format: Book
Published: The Asia-Pacific Society for Computers in Education (APSCE), 2018-12-01T00:00:00Z.
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042 |a dc 
100 1 0 |a Geela Venise Firmalo Fabic  |e author 
700 1 0 |a Antonija Mitrovic  |e author 
700 1 0 |a Kourosh Neshatian  |e author 
245 0 0 |a Investigating the effects of learning activities in a mobile Python tutor for targeting multiple coding skills 
260 |b The Asia-Pacific Society for Computers in Education (APSCE),   |c 2018-12-01T00:00:00Z. 
500 |a 10.1186/s41039-018-0092-x 
500 |a 1793-7078 
520 |a Abstract Mobile devices are increasingly being utilized for learning due to their unique features including portability for providing ubiquitous experiences. In this paper, we present PyKinetic, a mobile tutor we developed for Python programming, aimed to serve as a supplement to traditional courses. The overarching goal of our work is to design coding activities that maximize learning. As we work towards our goal, we first focus on the learning effectiveness of the activities within PyKinetic, rather than evaluating the effectiveness of PyKinetic as a supplement resource for an introductory programming course. The version of PyKinetic (PyKinetic_DbgOut) used in the study contains five types of learning activities aimed at supporting debugging, code-tracing, and code writing skills. We evaluated PyKinetic in a controlled lab study with quantitative and qualitative results to address the following research questions: (R1) Is the combination of coding activities effective for learning programming? (R2) How do the activities affect the skills of students with lower prior knowledge (novices) compared to those who had higher prior knowledge (advanced)? (R3) How can we improve the usability of PyKinetic? Results revealed that PyKinetic_DbgOut was more beneficial for advanced students. Furthermore, we found how coding skills are interrelated differently for novices compared to advanced learners. Lastly, we acquired sufficient feedback from the participants to improve the tutor. 
546 |a EN 
690 |a Python tutor 
690 |a Mobile learning 
690 |a Programming skills 
690 |a Code writing 
690 |a Code tracing 
690 |a Novice students 
690 |a Information technology 
690 |a T58.5-58.64 
690 |a Education 
690 |a L 
655 7 |a article  |2 local 
786 0 |n Research and Practice in Technology Enhanced Learning, Vol 13, Iss 1, Pp 1-24 (2018) 
787 0 |n http://link.springer.com/article/10.1186/s41039-018-0092-x 
787 0 |n https://doaj.org/toc/1793-7078 
856 4 1 |u https://doaj.org/article/f08c2b66a9b54901ad11ba1e76790cbe  |z Connect to this object online.