The onset of the COVID-19 pandemic has forced traditional classrooms and in-person pedagogy to move to a virtual setting. Seeing no end in sight, institutions were forced to also conduct the examinations remotely. Not being able to follow the same question pattern as that in a pen and paper-based exam, the exam itself had to be innovatively structured to aptly assess a candidate. In scenarios such as a job interview as well, when it is not possible to judge a person based on body language (as that cannot be any seen on a Zoom meeting!) we have swiftly moved to technology to take over and perform that task for us. The technology used known as performance assessment technology is not an innovation that has been birthed in the lockdown, but one that has found a much larger customer base just recently.
What is Performance Assessment Technology?
The definition is pretty self-explanatory based on the name itself, so instead let us focus on how it works. The generic algorithm goes this way: an answer received from the candidate is compared with a large database of answers and using matching techniques in machine learning, the accuracy of the given answer is calculated. Here, the additional modifications are made based on any additional parameters for judgment – response time, method of the answer, the difficulty level of question, etc. The assessment scoring makes use of set parameters to award a score, and many times also uses a feedback loop to train the dataset further for every iteration. In a different application, the assessment tool can be used to first collect the data from the user and then simply label the data according to categories, not just right and wrong. Based on the cumulative labels, the overall performance can be surmised.
The personal and traditional method of analyzing a performance has a major drawback – bias. If a single person is to judge the performance of a subjective test, it is inevitable for a little partiality or bias to creep in. In the case of a machine, it can't play favorites and hence remain completely objective even for a complex assessment such as that of an interview candidate. Performance evaluation technology thus came into being to ensure precision in the process and eliminated bias to make it a more transparent system. Starting from just calculating scores in an objective test, to analyzing more complicated answers to personal response questions, the system is ever-evolving and inching towards automating most of it. One of our esteemed client- a tech startup, Interview Mocha has delved the technology with unique patented advancements. From creating an inventive approach for augmenting an answer which uses the feedback method as mentioned before, to creating a specialized programming assessment platform Inteview Mocha has made valuable contributions to the field.
Let us look at the various domains where this technology is being used currently:
Subjective answer tests: In a subjective answer, any assessment algorithm has to first fetch out the keywords that answer the given question. The technique is then to compare those words to an answer base by word to word comparison and analyzing the degree of accuracy achieved. The scope for an alternative keyword being used has to be present for a fair judgment. In conditions where it is required to assess millions of candidates with essay-type questions, the automated system acts as a blessing. In the system, the presence of feedback helps to keep the process in check. If a particular answer is answered differently by everyone, the system will consider that to modify its answer database and then evaluate.
Job Interviews: Owing to the current situation and the compulsion to work remotely, many companies have shifted the recruitment process online as well. An aptitude test and the rest of it can be proctored remotely, but conducting an interview makes it very inorganic and it is next to impossible to fairly judge the character of the interviewee. Thanks to performance assessment and real-time updates, subtle traits such as body language can also be factored in in the interview process. Issues such as the use of unfair means are checked upon through artificial intelligence-powered remote proctoring. All the aspects of a candidature are thoroughly examined before making a recommendation to select a recruit.
Performance Review: Keeping track of all employee's performances is a very important and crucial task, relating directly to the proper functioning of the firm. It is essential to have assessed the person very intricately and impartially, as the entire system of appraisals, terminations, promotions, all depends on a fair assessment. For an organization of thousands, it is a blessing to have the process automated and have evaluation tech supporting a Human Resource representative. A machine run assessment helps point out an employee's weaknesses and strengths accurately, expectations and goals can be very clearly communicated, and it helps an employee align better with the bigger picture of the company. The information collected through the analysis also helps make for structured data to be shared with the board of directors, which it otherwise impossible to collate and maintain.
Specialized Tests: Software companies have one of the most important criteria in assessing their employees and prospective recruits in the form of a technical test. A designing firm requires a certain minimum standard of the designers, a university sets the criteria in the form of an entrance test. In short, all institutions have specialized tests that their members must pass. The tests which are not objective take a great deal of patience and skill to assess and give an unbiased verdict. Take for example a programming test. The test might be for a particular language, but a candidate using alternative logic may be able to crack the code. It will be a blunder to label him wrong for the answer. The need for impartial assessment has made the presence of performance evaluation technology indispensable in many organizations these days.
The major drawback that is faced by this technology is the absence of human touch to the entire process. Leaving the job of judging someone to a machine completely is a tad careless with the insecurity around the integrity of a machine always being drawn into question. Further, evaluation technology is in itself still quite young and in a nascent stage. It will take years before it is perfected and used extensively even in trivial matters.
The development and consequent progress of this technology have made a lot of tasks easier and have also added an extra sense of accountability in the process. New and improved ways to evaluate performance are sure to come up and enhance the process even more.
The content of this article is intended to provide a general guide to the subject matter. Specialist advice should be sought about your specific circumstances.