In the digital age, fast moving organizations can no longer afford to hire employees just as per their resumes and the recruiters’ gut instincts. That’s why use of assessments in pre-hiring has become very popular, not just for IQ skills, but for coding skills as well. The goal here is to use an assessment which lets you dig deep into a candidate’s skills in ways that can’t be achieved through group discussions and long interviews, without bias.
However, the most popular form of assessment is MCQ-based which falls short of capturing the hands-on skills of the candidates applying for a coding role. Since the candidate selects a response from a list of alternatives rather than supplying or constructing a response, multiple choice question-based assessment only tests knowledge and recall and not creativity, unique thinking or the ability to construct. While hiring coders, it is necessary to test the candidate’s skills in real-world situations, customized to your organizational needs. This cannot be achieved entirely through MCQ based assessments and for this, Coding Simulator based assessments should be used.
In coding simulator based assessments, candidates are asked to write a code from scratch, and then the code is evaluated on various parameters. These tests are designed to not only to check common coding techniques, but also analytical, interpretational and holistic thinking skills.
Simulator based tests create a real-time environment to check the candidates’ capability to work on real life projects. Doing so gives you insights into the candidate’s skills and their problem-solving abilities; both extremely crucial for programmers. While MCQ based tests only focus on candidate’s knowledge of theories, simulator based test enables you to test candidates’ understanding of these concepts by requiring them to use these concepts in practical applications.
Correlation between MCQ and Coding Tests
Mettl has conducted online tests for 100+ companies with 60,000+ candidates, and we have done some analysis on our end to present a few interesting insights.
It has been observed that the candidates who have performed well in technical MCQ based tests might not perform well in a simulator based test as well. Over the years, we have seen poor correlations between the performance in MCQ based test and simulator based tests.
Only 20-30% of the good performers in the MCQ test are also able to score well in coding tests. So, while most of the candidates recall programming concepts, however very few can apply them to real-world situations. The key here is recalling v/s understanding and application, and it is understanding and application that needs to be determined.
Simulator based assessments enable you to filter out the very best candidates from the lot. These assessments allow you to gain insight into the quality of code written by the candidate and answer lot many other questions
- Does the candidate know how to code?
- Does the candidate follow coding best practices?
- Is the candidate efficient enough at coding?
For the effective and valid evaluation of the candidates’ programming skills, following parameters should be measured through coding simulators.
Following are the parameters:
- The correctness of the code: with an online coding assessment, you can design various test cases to check the correctness of the code, if the code runs all type of test cases like basic, corner, necessary etc.
In Mettl we make sure that every question should have at least 10 to 12 tests cases covering from basic to boundary cases.
- Code Quality: Use of best practices as per industry standards in the code. In Mettl we use tools like ‘Static Code Analysis to check if the code adheres to the industry standards.
- Code Scalability: Code complexity, Time complexity, CPU usage, Processing time, time taken to submit the final code.
For different job profiles, different coding skill sets are required; for a trainee level, you might just evaluate the candidate on basic programming fundamentals but for a developer role you will also focus into coding style, code efficiency, data structures etc. Different parameters measured through these simulators let you dig deep and evaluate the candidate’s coding skills are per the organization’s requirement.
Using coding simulator based assessment enables you to identify candidates with strong coding skills, and also sharpen the identification, by simultaneously evaluating the code on various quality and efficiency parameters, which is not possible through manual intervention. Automated assessments remove subjectivity from the evaluation process and provide detailed feedback of the candidate’s coding skills in a timely manner, resulting in more efficient hiring process.