Do you really code? Designing and Evaluating Screening Questions for Online Surveys with Programmers

TL;DR

This paper develops and evaluates screening questions to accurately identify programmers in online surveys, addressing issues of misclassification and fraud to improve data quality.

Contribution

It introduces a set of effective screening questions for online recruitment of programmers and evaluates their efficacy through empirical testing.

Findings

42% of self-identified programmers failed the screening

Screening questions effectively distinguish programmers from non-programmers

Recommended questions can improve participant selection accuracy

Abstract

Recruiting professional programmers in sufficient numbers for research studies can be challenging because they often cannot spare the time, or due to their geographical distribution and potentially the cost involved. Online platforms such as Clickworker or Qualtrics do provide options to recruit participants with programming skill; however, misunderstandings and fraud can be an issue. This can result in participants without programming skill taking part in studies and surveys. If these participants are not detected, they can cause detrimental noise in the survey data. In this paper, we develop screener questions that are easy and quick to answer for people with programming skill but difficult to answer correctly for those without. In order to evaluate our questionnaire for efficacy and efficiency, we recruited several batches of participants with and without programming skill and tested the questions. In our batch 42% of Clickworkers stating that they have programming skill did not meet our criteria and we would recommend filtering these from studies. We also evaluated the questions in an adversarial setting. We conclude with a set of recommended questions which researchers can use to recruit participants with programming skill from online platforms.