Supporting Novices and Advanced Students in Acquiring Multiple Coding Skills

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 the other half (experimental group) problems were selected adaptively, based on their performance. In a previous paper, we discussed the general findings from the study. In this paper we present further analyses and focus on differences between low performing students and students with higher pre-existing knowledge. We hypothesized that: (H1) novices will benefit more than advanced students, and (H2) advanced students in the experimental group will benefit more than those in the control group. The results confirmed H1 and revealed that this version of PyKinetic was more beneficial for novice learners. Moreover, novices showed evidence of learning multiple skills: code writing, debugging and code tracing. However, we did not have enough evidence for hypothesis H2

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

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