The Use of Python Tutor on Programming Laboratory Session: Student Perspectives

Karnalim, Oscar; Ayub, Mewati

doi:10.22219/kinetik.v2i4.442

Cited by 8 publications

(12 citation statements)

References 14 publications

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“…Hence, it can be stated that the use of PythonTutor negatively affects student performance for completing laboratory task on that week. This finding contradicts the result proposed in [21] which stated that most students from group 2 (a group which acted as the intervened group on the 1st week) felt that the use of PythonTutor affected the most on that week. When discovered further, sometimes, it is natural that such contradiction exists, considering that student perspective and the actual result might not always be in-sync to each other.…”

Section: The Results Of Evaluating Pythontutor's Impact In Lecture Wecontrasting

confidence: 90%

“…We would argue that such negative correlation is caused by the fact that most students on the group 1 had never used the tool before they took BDS course [20]. Therefore, they might feel that such tool mitigated them for completing their task, considering that PythonTutor UI is not intuitive enough for students [20], [21].…”

Section: The Results Of Evaluating Pythontutor's Impact In General Pementioning

confidence: 99%

“…It is important to note that our work is different with works proposed in [20] and [21] that also evaluate the impact of PythonTutor. On the one hand, our work is dif-ferent with a work proposed in [20] since our work is more focused on laboratory session instead of theory session.…”

Section: Related Workmentioning

confidence: 91%

“…Further, the work in [20] is focused on introductory course while our work is focused on basic data structure course. On the other hand, our work is different with a work proposed in [21] since our work evaluates the impact of PythonTutor through student performance rather than student perspective. Our work will complement the work in [21] by providing a more-objective result (the result of work in [21] is rather subjective since it relies on questionnaire survey toward the students).…”

Section: Related Workmentioning

confidence: 95%

See 3 more Smart Citations

A Quasi-Experimental Design to Evaluate the Use of PythonTutor on Programming Laboratory Session

Karnalim

Ayub

2018

Int. J. Onl. Eng.

Self Cite

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Abstract-Educational tool is one of the prominent solutions for aiding students to learn course material in Information Technology (IT) domain. However, most of them are not used in practice since they do not properly fit student necessity. This paper evaluates the impact of an educational tool, namely PythonTutor, for completing programming laboratory task regarding data structure materials. Such evaluation will be conducted in one semester by implementing a quasi-experimental design. As a result, six findings can be deducted which are: 1) PythonTutor might positively affect student performance when the students have used such tool before; 2) Sometimes, student perspective regarding the impact of educational tool is not always in-sync with actual laboratory result; 3) the impact of PythonTutor might be improved when similar data representation is used consequently for several weeks; 4) the correlation between the use of PythonTutor and student performance might not be significant when the control and intervened group share completely different characteristics; 5) the students might experience some difficulties when they are asked to handle a big task for the first time; and 6) the students might be able to complete a particular weekly task with a promising result if the students have understood the material well.

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Section: The Results Of Evaluating Pythontutor's Impact In Lecture Wecontrasting

confidence: 90%

Section: The Results Of Evaluating Pythontutor's Impact In General Pementioning

confidence: 99%

Section: Related Workmentioning

confidence: 91%

Section: Related Workmentioning

confidence: 95%

See 2 more Smart Citations

A Quasi-Experimental Design to Evaluate the Use of PythonTutor on Programming Laboratory Session

Karnalim

Ayub

2018

Int. J. Onl. Eng.

Self Cite

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“…Programming-oriented educational tool puts more stress on technical knowledge such as how to write a program. At CS undergraduate major, it has been frequently used for learning Introductory Programming; such tool is proved to be effective for teaching undergraduate students [6][7][8][9]. Most programming-oriented educational tools are either program visualization or visual programming tool.…”

Section: Related Workmentioning

confidence: 99%

Introducing a Practical Educational Tool for Correlating Algorithm Time Complexity with Real Program Execution

Kurniawati

Karnalim

2018

JITeCS

Self Cite

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Algorithm time complexity is an important topic to be learned for programmer; it could define whether an algorithm is practical to be used on real environment or not. However, learning such material is not a trivial task. Based on our informal observation regarding students’ test, most of them could not correlate Big-Oh equation to real program execution. This paper proposes JCEL, an educational tool that acts as a supportive tool for learning algorithm time complexity. Using this tool, user could learn how to correlate Big-Oh equation with real program execution by providing three components: a Java source code, source code input set, and time complexity equations. According to our evaluation, students feel that JCEL is helpful for learning the correlation between Big-Oh equation and real program execution. Further, the use of Pearson correlation in JCEL shows a promising result.

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C Tutor usage in relation to student achievement and progress: A study of introductory programming courses in Portugal and Serbia

Alves

Gajić

Henriques

et al. 2020

Comp Applic In Engineering

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Previous research studies on introductory programming courses in engineering education in Portugal and Serbia have indicated that although high motivation and high expectations seem to be reported by students, many students may fail the course. This prompted a further inquiry into student attitudes, behavior, and achievement, and it also led to the introduction of C Tutor, a widely known program visualization tool, into courses in both countries. As a result, in the present study, self‐reported student achievement (grades), self‐reported student progress (knowledge improvement and confidence), and self‐reported usage and helpfulness of C Tutor were investigated. Anonymous data about students and their experience in the course, which also included the usage of C Tutor, were collected in a survey in Portugal and Serbia. Quantitative methods, including descriptive statistics, clustering, statistical testing of independence, and partial correlation analysis, were applied in analyses of survey data. The distribution of grades differed between the two countries, but overall attitudes were similar. Various uncovered patterns involving student attitudes and usage of C Tutor may serve as a starting point for new research studies.

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The Use of Python Tutor on Programming Laboratory Session: Student Perspectives

Cited by 8 publications

References 14 publications

A Quasi-Experimental Design to Evaluate the Use of PythonTutor on Programming Laboratory Session

A Quasi-Experimental Design to Evaluate the Use of PythonTutor on Programming Laboratory Session

Introducing a Practical Educational Tool for Correlating Algorithm Time Complexity with Real Program Execution

C Tutor usage in relation to student achievement and progress: A study of introductory programming courses in Portugal and Serbia

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