Mining Shapes of Expertise in Online Social Q&amp;A Communities

Kumar, Varun; Pedanekar, Niranjan

doi:10.1145/2818052.2869096

Cited by 15 publications

(7 citation statements)

References 7 publications

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“…We operationalized the construct of experience with frequency of coding challenges over the last year, general, Java-related, and professional programming experience in years, but also reputation on StackOverflow.com. We included the latter because developers rely on it, draw on the knowledge from experts at different levels, and developer expertise is well represented by good questions and answers on it (Abdalkareem, Shihab & Rilling, 2017;Pal, Harper & Konstan, 2012;Kumar & Pedanekar, 2016). For similar reasons, we also operationalized experience with the number of pull requests on GitHub.com as they are positively correlated to several experience measures (Rahman & Roy, 2014).…”

Section: Experiencementioning

confidence: 99%

A theory on individual characteristics of successful coding challenge solvers

Wyrich

Graziotin

Wagner

2019

PeerJ Computer Science

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Background Assessing a software engineer’s ability to solve algorithmic programming tasks has been an essential part of technical interviews at some of the most successful technology companies for several years now. We do not know to what extent individual characteristics, such as personality or programming experience, predict the performance in such tasks. Decision makers’ unawareness of possible predictor variables has the potential to bias hiring decisions which can result in expensive false negatives as well as in the unintended exclusion of software engineers with actually desirable characteristics. Methods We conducted an exploratory quantitative study with 32 software engineering students to develop an empirical theory on which individual characteristics predict the performance in solving coding challenges. We developed our theory based on an established taxonomy framework by Gregor (2006). Results Our findings show that the better coding challenge solvers also have better exam grades and more programming experience. Furthermore, conscientious as well as sad software engineers performed worse in our study. We make the theory available in this paper for empirical testing. Discussion The theory raises awareness to the influence of individual characteristics on the outcome of technical interviews. Should the theory find empirical support in future studies, hiring costs could be reduced by selecting appropriate criteria for preselecting candidates for on-site interviews and potential bias in hiring decisions could be reduced by taking suitable measures.

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Section: Experiencementioning

confidence: 99%

A theory on individual characteristics of successful coding challenge solvers

Wyrich

Graziotin

Wagner

2019

PeerJ Computer Science

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“…In contrast to other forms of knowledge sharing platforms like peerproduced encyclopedia Wikipedia or the discussion forums of Reddit, Stack Overflow follows the Community Question Answering (CQA) structure. This structure means that interaction on the platform is primarily organized in the form of questioning and answering where professional and enthusiast programmers provide solutions to each other's authentic programming problems [4]. The answers provided may only provide a resource for the question asker, as is the case for oft-repeated simple questions [7], but in other cases, they may also be useful for other interested users who can search using both free-text and tags.…”

Section: Cqa and Stack Overflowmentioning

confidence: 99%

Knowledge Sharing in Tension: Interacting and Documenting on Stack Overflow

Hillman

Seredko

Nivala

et al. 2021

Proceedings of the Eighth ACM Conference on Learning @ Scale

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This exploratory paper examines a tension between interacting and documenting as knowledge sharing tasks on Stack Overflow, a platform that supports informal learning at scale in the domain of programming. The study works with platform data in the form of the text of posts and accompanying metadata along with 16 interviews with users. Drawing on trace ethnography as an approach to maintaining an interpretive stance while combining several types of data, this preliminary analysis discusses two interrelated particularities of the tension. The discussion of these particularities, platform mechanics and competing temporalities, helps to unpack a tension that is both a phenomenon of analytic interest and a member's concern for users of the platform.

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“…We operationalized the construct of experience with frequency of coding challenges over the last year, general, Java-related, and professional programming experience in years, but also reputation on StackOverflow.com. We included the latter because developers rely on it, draw on the knowledge from experts at different levels, and developer expertise is well represented by good questions and answers on it (Abdalkareem et al, 2017;Pal et al, 2012;Kumar and Pedanekar, 2016). For similar reasons, we also operationalized experience with the number of pull requests on GitHub.com as they are positively correlated to several experience measures (Rahman and Roy, 2014).…”

Section: Experiencementioning

confidence: 99%

Peer Review #2 of "A theory on individual characteristics of successful coding challenge solvers (v0.1)"

2019

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Background. Assessing a software engineer's ability to solve algorithmic programming tasks has been an essential part of technical interviews at some of the most successful technology companies for several years now. We do not know to what extent individual characteristics, such as personality or programming experience, predict the performance in such tasks. Decision makers' unawareness of possible predictor variables has the potential to bias hiring decisions which can result in expensive false negatives as well as in the unintended exclusion of software engineers with actually desirable characteristics. Methods. We conducted an exploratory quantitative study with 32 software engineering students to develop an empirical theory on which individual characteristics predict the performance in solving coding challenges. We developed our theory based on an established taxonomy framework by Gregor (2006). Results. Our findings show that the better coding challenge solvers also have better exam grades and more programming experience. Furthermore, conscientious as well as sad software engineers performed worse in our study. We make the theory available in this paper for empirical testing. Discussion. The theory raises awareness to the influence of individual characteristics on the outcome of technical interviews. Should the theory find empirical support in future studies, hiring costs could be reduced by selecting appropriate criteria for preselecting candidates for on-site interviews and potential bias in hiring decisions could be reduced by taking suitable measures.

show abstract

Mining Shapes of Expertise in Online Social Q&A Communities

Cited by 15 publications

References 7 publications

A theory on individual characteristics of successful coding challenge solvers

A theory on individual characteristics of successful coding challenge solvers

Knowledge Sharing in Tension: Interacting and Documenting on Stack Overflow

Peer Review #2 of "A theory on individual characteristics of successful coding challenge solvers (v0.1)"

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