How to rate programming skills in programming experiments?

Kleinschmager, Sebastian; Hanenberg, Stefan

doi:10.1145/2089155.2089161

Cited by 16 publications

(3 citation statements)

References 13 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…This result is in line with a similar finding by Siegmund et al, which also highlighted self-estimated comparison as a differentiating factor among students [72]. In the same vein, Kleinschmager and Hanenberg found self-estimated comparison, at least, as effective as pretests or university grades in its predictive power of efficacy [41]. Our shared experience questionnaire provides a proven basis for others to use to capture several dimensions of programming experience.…”

Section: Perspectives and Conclusionsupporting

confidence: 91%

Correlates of programmer efficacy and their link to experience: a combined EEG and eye-tracking study

Peitek

Bergum

Rekrut

et al. 2022

Proceedings of the 30th ACM Joint European Software Engineering Conference and Symposium on the Foundations of Software Enginee

View full text Add to dashboard Cite

Background: Despite similar education and background, programmers can exhibit vast differences in efficacy. While research has identified some potential factors, such as programming experience and domain knowledge, the effect of these factors on programmers' efficacy is not well understood. Aims: We aim at unraveling the relationship between efficacy (speed and correctness) and measures of programming experience. We further investigate the correlates of programmer efficacy in terms of reading behavior and cognitive load. Method: For this purpose, we conducted a controlled experiment with 37 participants using electroencephalography (EEG) and eye tracking. We asked participants to comprehend up to 32 Java sourcecode snippets and observed their eye gaze and neural correlates of cognitive load. We analyzed the correlation of participants' efficacy with popular programming experience measures. Results: We found that programmers with high efficacy read source code more targeted and with lower cognitive load. Commonly used experience levels do not predict programmer efficacy well, but selfestimation and indicators of learning eagerness are fairly accurate. Implications: The identified correlates of programmer efficacy can be used for future research and practice (e.g., hiring). Future research should also consider efficacy as a group sampling method, rather than using simple experience measures. CCS CONCEPTS• Human-centered computing → Empirical studies in HCI ; HCI design and evaluation methods.

show abstract

Section: Perspectives and Conclusionsupporting

confidence: 91%

Correlates of programmer efficacy and their link to experience: a combined EEG and eye-tracking study

Peitek

Bergum

Rekrut

et al. 2022

Proceedings of the 30th ACM Joint European Software Engineering Conference and Symposium on the Foundations of Software Enginee

View full text Add to dashboard Cite

show abstract

“…We use this self estimation as a measurement of skill instead of a pretest, since it is a faster and be er estimator [21,30,49]. e warm-up program is placed in the same environment as the programming problems and contains several tasks designed to let the participants use every control of this test environment.…”

Section: Rq3: Evaluationmentioning

confidence: 99%

Debugging data flows in reactive programs

Banken

Meijer

Gousios

2018

Proceedings of the 40th International Conference on Software Engineering

View full text Add to dashboard Cite

Reactive Programming is a style of programming that provides developers with a set of abstractions that facilitate event handling and stream processing. Traditional debug tools lack support for Reactive Programming, leading developers to fallback to the most rudimentary debug tool available: logging to the console. In this paper, we present the design and implementation of RxFiddle, a visualization and debugging tool targeted to Rx, the most popular form of Reactive Programming. RxFiddle visualizes the dependencies and structure of the data ow, as well as the data inside the ow. We evaluate RxFiddle with an experiment involving 111 developers. e results show that RxFiddle can help developers nish debugging tasks faster than with traditional debugging tools. CCS CONCEPTS •So ware and its engineering → So ware testing and debugging; Data ow languages; So ware maintenance tools;

show abstract

“…However, for novice programmers who are studying at university and are about to enter society, course learning is the main way to improve their programming skills [8][9]. Therefore, it is more important whether these courses can measure the programming skills of novice programmers Around 2013, our country introduced the concept of outcome-based education (OBE) to guide the reform of engineering education, making the concept of OBE practical in China.…”

Section: Introductionmentioning

confidence: 99%

Can University Marks Measure Programming Skills for Novice Programmers? An Exploratory Study

Fanghui Zha,

Yong Wang

et al. 2023

Journal of Internet Technology

View full text Add to dashboard Cite

<p>Programming skills are the key ability of programmers. For novice programmers who are new and have little experience in programming, it is important to measure and improve their programming skills. In practice, novice programmers learn programming knowledge and coding ability at university, and course learning is the main way for novice programmers to improve programming skills. However, can university marks be used to measure the programming skills of programming novices? To answer this question, in a controlled experiment, we compare university marks of novice programmers with their performance in programming tasks. The results showed that there were 7 courses with significant correlation among the 13 courses, among which the software engineering course had the most significant correlation.</p> <p> </p>

show abstract

How to rate programming skills in programming experiments?

Cited by 16 publications

References 13 publications

Correlates of programmer efficacy and their link to experience: a combined EEG and eye-tracking study

Correlates of programmer efficacy and their link to experience: a combined EEG and eye-tracking study

Debugging data flows in reactive programs

Can University Marks Measure Programming Skills for Novice Programmers? An Exploratory Study

Contact Info

Product

Resources

About