55 percent. That’s the percentage of engineering candidates that are interviewed by an engineer but do not receive an offer, based on average 2022 pass through rates.
For teams looking to secure top talent and optimize their engineers’ time, being able to fairly and accurately predict who has the right skills for the job is critical. While many use pre-hire assessments and interviews to solve this problem, they don’t always deliver results you can trust.
In this article, we’ll explore four common problems with coding questions, and provide actionable insights to help technical hiring teams make the right hires, faster.
1. Low validity or reliability
The problem: Validity, in the context of hiring assessments, refers to how accurately a coding question or technical assessment measures the specific technical skill that it’s intended to measure. Reliability, on the other hand, refers to how consistently a coding question measures the skill it’s intended to, across a large volume of candidates.
Coding questions that lack validity or reliability can result in assessments that fail to accurately measure a candidate’s technical abilities. Inconsistent results may not only lead to poor hiring decisions but also erode the credibility of the assessment process.
The solution: To improve the validity and reliability of your coding questions, focus on creating realistic coding questions that thoroughly test the essential skills required for the role. Questions for technical assessments and interviews should be written by subject-matter experts (SMEs) and validated by Industrial-Organizational (IO) Psychologists.
2. Poor alignment to the seniority of the role
The problem: When coding questions don’t align with the seniority of the role being filled, you risk assessing candidates based on criteria that are not relevant to their job responsibilities. Algorithmic questions, for instance, are appropriate for evaluating core programming knowledge among new grad and early career candidates—but they are much less relevant to senior-level candidates who are years past their formal CS
education. Experienced and senior-level candidates end up frustrated if asked only these types of questions, which likely have little relevance to their everyday work.
The solution: Engage Industrial-Organizational (IO) Psychologists to conduct a job analysis for each role you’re hiring for. A job analysis will show you which job-relevant skills you need to assess for in your hiring process. Your coding questions, in turn, should assess the specific skills identified in the job analysis. This will ensure that your assessments are accurate and evaluate candidates based on their ability to perform the tasks they’ll encounter in their role.
3. Unclear or bias-laden question wording
The problem: Coding questions with unclear or bias-laden wording can lead to confusion among candidates and result in an uneven playing field. When professionals aren’t involved to develop these questions, the writing might suffer from a lack of clarity or use culturally-specific language and examples. Biased questions can alienate potential talent and create a negative impression of your organization among candidates.
The solution: Invest time in carefully crafting clear, concise, and unbiased questions. Review your coding questions for any ambiguous language or potential biases, and revise them as needed. Consider seeking feedback from multiple team members to ensure your questions are clear and free from unintentional biases. Ideally, engage a vendor whose team includes both technical SMEs and IO Psychologists to ensure
that your coding questions will provide a strong signal of candidates’ skills while avoiding biased wording.
4. Questions that get leaked as soon as you launch your assessment
The problem: It’s extremely common for coding questions to be leaked on platforms like LeetCode. When coding questions are leaked online, the effectiveness of your assessments is compromised, as candidates can easily find answers to the questions before or even during the assessment. This breach of confidentiality can lead to poor hiring decisions and a loss of credibility for your hiring process.
The solution: Utilize a technical hiring platform that creates and maintains validated technical assessments that include many variations of equivalent difficulty to reduce the impact of question leaks and minimize plagiarism in your technical evaluation process. The platform should also include plagiarism-detection tools to help identify any instances of cheating during the assessment process.
Conclusion
By addressing these four main problems with coding questions, you can create a more effective technical hiring process that leads to better candidate selection. Enhancing the validity and reliability of your questions, aligning them with the roles you’re filling, ensuring clear and unbiased question wording, and preventing question leaks are crucial steps to improve the overall quality and effectiveness of your pre-hire assessments and interviews. Ultimately, this will help you attract and retain top-tier technical talent that can drive your organization forward.
Want to learn more about creating and maintaining effective coding questions? Register for our May 10th webinar, How to optimize your tech hiring questions with the resources you’ve got, where you’ll get an expert perspective from an IO Psychologist.