Investigating the effects of learning activities in a mobile Python tutor for targeting multiple coding skills. (2018)
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.
KeywordsAdvanced students; Code tracing; Code writing; Mobile learning; Novice students; Programming skills; Python tutor
ANZSRC Fields of Research39 - Education::3904 - Specialist studies in education::390405 - Educational technology and computing
46 - Information and computing sciences::4612 - Software engineering::461204 - Programming languages
46 - Information and computing sciences::4613 - Theory of computation::461301 - Coding, information theory and compression
13 - Education::1302 - Curriculum and Pedagogy::130212 - Science, Technology and Engineering Curriculum and Pedagogy
46 - Information and computing sciences::4606 - Distributed computing and systems software::460608 - Mobile computing
Rights© The Author(s). 2018 Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.
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Fabic GVF; Mitrovic, Antonija; Neshatian K (Springer Science and Business Media LLC, 2019)The overarching goal of our project is to design effective learning activities for PyKinetic, a smartphone Python tutor. In this paper, we present a study using a variant of Parsons problems we designed for PyKinetic. Parsons ...
Fabic GV; Mitrovic, Antonija; Neshatian K (APSCE, 2018)We present our study on PyKinetic with various activities to target several skills: code tracing, debugging, and code writing. Half of the participants (control group) received the problems in a fixed order, while for ...
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