Situational Judgement Tests (SJTs) or Ai interview automation?
From one recruiter to another and one employer to another, the ways candidates are selected vary greatly. But ask anyone involved in the process, and most will agree that what happens at the early candidate screening stage, is critical to getting the best outcomes. Traditionally, it’s also been the most time-consuming and costly part of the hiring process.
Long before a face-to-face interview, recruiters need to screen candidates to decide, from potentially thousands of applicants, who should proceed to the next steps in the hiring cycle. But before they’ve even met a candidate, can recruiters really assess someone’s ability and suitability for the job they’re applying for? Yes, they can, especially with tools like the situational judgement test.
Choosing the best assessment solution for your recruitment tools suite.
In contemporary recruiting, a suite of tools and technologies can help take the hard work and the guesswork out of the hiring process. Talent assessment tools, like situational judgement tests for managers or situational judgement tests for customer service, help recruiters identify the best candidates faster – talent who will be the best fit for the role and the team, work most productively and stay in the role longer.
While traditionally a time-consuming manual review of applications and CVs would begin the hiring process, recruiters have embraced technologies that can automate these processes from the outset.
In this article, we compare two top of the funnel tools recruiters are using to assess candidates: traditional situational judgement tests (SJTs) and the next generation text interview platform.
Sapia Ai-enabled automated interviews could provide the answers you’re looking for, helping to connect to the best talent faster and more cost-effectively.
So, what is a situational judgement test?
Situational judgement tests are used to assess a candidate’s judgement and ability to respond appropriately to the real-world situations they would be likely to encounter in the workplace.
Candidates are presented with a workplace scenario and then they are required to choose or rank the best (or worst) paths to resolve the challenge, conflict or opportunity. They are a type of psychological aptitude test that provides insight and assessment of a candidate’s job-related skills.
What do situational judgement tests measure?
While the challenging scenarios presented to candidates are hypothetical, the best tests are designed around the role they are applying for.
Reflecting real situations they could encounter, the scenarios may involve working with other team members or supervisors, interacting with customers or dealing with day-to-day challenges.
Situational judgement tests date back to the 1940s. While the ways they are delivered may have changed, they remain a popular way to assess skills such as problem-solving and interpersonal skills. They are also useful in assessing soft skills and practical, non-academic intelligence.
Situational judgement tests are customised to the role and the organisation. Generally, they would be looking to assess a candidate’s aptitude for a role by measuring competencies that might include:
- Communication skills – clarity, persuasiveness, empathy
- Organisation and planning – solving the problem, staying cool under pressure
- Teamwork – collaboration, encouraging others, prioritising team needs over the individual, implementing solutions
- Decision making – exercising discretion, analysing the situation, demonstrating solid judgment
- Customer focus – listening, recognising, delivering
- Initiative – taking responsibility, demonstrating leadership, stepping up
- Ambition – drive to achieve
How does a situational judgement test work?
As they are produced by a range of different providers, SJTs can be delivered in a number of ways. As they are also tailored to suit specific roles and companies, tests can vary in their length, structure and format. While some may be paper-based, most tests are delivered digitally.
The tests provide candidates with a workplace scenario – as a written description or as a video or digital animation – and a challenge related to that scenario. Typically, candidates are then presented with four or five possible paths of action in multiple-choice format to deal with the situation described.
Different approaches are used for candidates to provide their answers. Some may require candidates to choose both the most desirable and the least desirable action. Others may ask candidates to choose just one preferred option or rank all actions in terms of effectiveness.
What benefits can SJTs bring to the hiring process?
Situational judgement tests are typically used before the interview stage and often used in combination with a knowledge-based test.
SJTs are designed to help recruiters and hiring managers to:
- filter candidates from large talent pools
- identify candidates who are likely to perform best in the role
- provide candidates with further insight into the demands of the role
- identify candidates who will be a good cultural fit
- assess candidates’ aptitude and judgement against realities of the role
- understand a candidate’s aptitude for the particular job
- help reduce staff turnover by making more informed decisions
Sapia – the smarter way to assess candidates
Since 2013, Australian recruitment technology specialist Sapia has worked to solve a problem for every recruiter and employer. That is how to get to the right talent faster while consistently improving the candidate experience.
Sapia’s text-based interview platform uses artificial intelligence, machine learning and natural language processing to provide reliable personality insights into every candidate. While SJTs can be expensive time-consuming to create, administer and assess, Sapia’s platform can provide like-for-like personality and job-fitness tests with far greater ease and at a fraction of the cost.
Why organisations are turning to interview automation over situational judgement tests
Here is feedback from a customer after running a pilot using SJTs:
Often situational judgement tests don’t accurately represent what the job is really about. There are so many aspects that need to be considered within a real-world situation. Feedback from the SJTs pilot groups is that they often felt as though they were being forced into specific areas that may not be job-related. There needs to be more flexibility for a candidate to say: “I would do this, but I would also do a bit of that”. Having an experience that gives flexibility in answering. It enables candidates to have that open-ended answer to express what was important to them.
How Sapia’s interview automation works
Smart Interviewer is Sapia’s machine learning interview platform. With learning from analysing more than 165 million words in text-based interviews with more than 700,000 candidates, Smart Interviewer combines standard interview questions related to past behaviour and situational judgement to reliably assess personality traits. The questions can be customised to the specific role family – sales, retail, call centre, service etc– and specific requirements relating to the employer’s brand and employment values.
Candidate assessment at scale
The scientific foundation of Sapia’s Ai interview platform is that language forms the framework for the knowledge, skills and personality we possess. Through a simple text-based conversation, Smart Interviewer provides valuable candidate insights. It can predict a candidate’s suitability for a role and guide their progression through the recruitment process. It delivers the insights that recruiters and employers need to make better hiring decisions at scale.
Enhancing the candidate experience – 99% satisfaction
Improving the candidate experience is a priority for every recruiter and employer. The effect of a poor experience can cause lasting damage to reputations and brands. Sapia is the only conversational interview platform with 99% candidate satisfaction feedback. Candidates enjoy the process, appreciate the opportunity and value the personalised feedback. Something that’s simply not practical with most high-volume recruitment briefs.
Candidates know text and trust text
As text is a familiar, non-confrontational way to connect, candidates enjoy the text interview experience. Unlike SJTs that lock them into choosing options from pre-determined answers, candidates appreciate the open-ended questions . Here they are empowered by the opportunity to tell their story in their words.
While questions are customised to the role, some typical examples include:
• What motivates you? What are you passionate about?
• Not everyone agrees all the time. Have you had a peer, teammate or friend disagree with you? What did you do?
• Give an example of a time you have gone over and above to achieve something. Why was it important for you to achieve this?
• Sometimes things don’t always go to plan. Describe a time when you failed to meet a deadline or personal commitment. What did you do? How did that make you feel?
• In sales, thinking fast is critical. What qualifies you for this? Provide an example.
Tackling bias and taking CVs out of the equation
Sapia provides blind-screening at its best, effectively reducing opportunities for bias from the assessment process to ensure every candidate is playing on a level field. Candidates recognise and appreciate the opportunity to tell their story without the subjective biases of a human interview or a cursory review of their CV. For top of the recruitment funnel interviews, Sapia removes CVs from the process altogether.
Find out more about Sapia’s Ai-powered candidate assessment tool and how it could replace your time-consuming and costly SJTs today.
You can leave us your details to get a personalised demo OR try out Sapia’s Chat Interview right now, here.
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And we’re just getting started 🚀
Take a look at the highlights of 2024
All-in-one hiring platform
This year, with the addition of Live Interview, we’re proud to say our platform now covers screening, assessing and scheduling.
It’s an all-in-one volume hiring platform that enables our customers to deliver a world-leading experience from application through to offer.
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Every 15 seconds, a candidate is interviewed with Sapia.ai.
This year, we’ve saved hiring managers and recruiters hours of precious time that can now be used for higher-value tasks.
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Our platform allows candidates to be their best selves, so our customers can find the people that truly belong with them. They’re proud to use a technology that’s changing hiring, for good.
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We’ve continued to push the boundaries in leveraging ethical AI for hiring, with new products on the way for Coaching, Internal Mobility & Interview Builders.
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Situational Judgement Tests vs. AI Chat Interviews: A Modern Perspective on Candidate Assessment
Choosing the right tool for assessing candidates can be challenging. For years, situational judgement tests (SJTs) have been a common choice for evaluating behaviour and decision-making skills. However, they come with limitations that can make the hiring process less effective and less inclusive.
AI-enabled chat-based interviews, such as Sapia.ai, provide organisations with a modern alternative. They focus on understanding candidates as individuals and creating a hiring experience that is both fair and insightful while enabling efficient screening and selection.
This shift raises important questions: Are SJTs still a tool that should be considered for volume hiring? And what do AI assessments offer in comparison?
1. The Static Nature of SJTs
Traditional SJTs use predefined multiple-choice questions to assess behavioural tendencies and situational knowledge. While useful for screening, these static frameworks lack the flexibility to adapt based on real-world performance data or evolving role requirements.
Once created, SJTs don’t adapt to new data or evolving organisational needs. They rely on fixed scenarios and responses that may not fully reflect the dynamic realities of modern workplaces, and as a result, their relevance may diminish over time.
AI-enabled chat interviews, on the other hand, are inherently adaptive. Using machine learning, these tools can continuously refine their models based on feedback from real-world outcomes such as hiring or turnover data. This ability to evolve ensures the assessments align with organisations’ needs.
2. Richer Data Through Open-Ended Responses
One of the main critiques of SJTs is their reliance on multiple-choice responses. While structured and straightforward, these options may not capture the full scope of a candidate’s thinking, communication skills, or problem-solving ability. The approach is often limiting, reducing complex human behaviour to a few predefined choices.
AI-enabled chat interviews work more holistically and dynamically. These tools provide a more complete picture of a person by allowing candidates to answer questions in their own words. Natural language processing (NLP) analyses their responses, offering insights into personality traits, communication skills, and behavioural tendencies. This open-ended format lets candidates express themselves authentically, giving employers a deeper understanding of their potential.
3. The Candidate Experience: Stressful or Supportive?
SJTs often include time constraints and rigid formats, which can create pressure for candidates. This is especially true when candidates feel forced to choose options that don’t fully reflect how they would actually behave. The process can feel impersonal, even transactional.
In contrast, chat-based interviews are designed to be conversational and low-pressure for candidates. By removing time limits and adopting a familiar chat interface, these tools help candidates feel more at ease. They also frequently include personalised feedback, turning the assessment into a valuable experience for the candidate, not just the employer.
4. Addressing Bias and Fairness
Traditional SJTs are prone to transparency issues, as candidates can often identify and select the “best practice” answers without revealing their true tendencies. Additionally, static test designs can unintentionally embed bias; due to the nature of the timed test, SJTs have been found to disadvantage some groups.
AI chat interviews, when developed ethically within a framework like Sapia.ai’s FAIR Hiring Framework, eliminate explicit bias by relying solely on the content of a candidate’s responses. Their machine learning models are continuously validated for fairness, ensuring that hiring decisions are free from subjective judgments or irrelevant demographic factors.
5. An Assessment That Improves Over Time
Workplaces are constantly changing, and hiring tools need to keep up. SJTs’ fixed nature can make them less effective as roles evolve or organizational priorities shift. They provide a snapshot but not a dynamic view of what’s needed.
AI-enabled chat interviews are built to adapt. With feedback loops and continuous learning, they incorporate real-world hiring outcomes—like retention and performance data—into their models. This ensures that assessments stay relevant and effective over time.
Rethinking Candidate Assessment
As hiring demands grow more complex, so does the need for tools that can capture the whole person, not just their response to hypothetical scenarios. While SJTs have played an important role in hiring practices, they are increasingly being replaced by tools like AI-enabled chat interviews.
These modern approaches provide richer data, adapt to changing needs, and create a richer and more engaging experience for candidates. Perhaps most importantly, they emphasise fairness and inclusivity, aligning with the growing demand for unbiased hiring practices.
For organisations evaluating their assessment tools, the question isn’t just which method is “better.” Understanding the specific needs of your roles, teams, and candidates will help you choose tools that help you make decisions that are both informed and equitable.
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Keeping Interviews Real with Next-Gen AI Detection
It’s our firm belief that AI should empower, not overshadow, human potential. While AI tools like ChatGPT are brilliant at assisting us with day-to-day tasks and improving our work efficiency, employers are increasingly concerned that they’re holding candidates back from revealing their true, authentic selves in online interviews.
As an assessment technology provider, we are responsible for ensuring the authenticity and integrity of our platform. That’s why we’re thrilled to unveil the latest upgrade to our flagship Chat Interview: the AI-Generated Content Detector 2.0. With groundbreaking accuracy and a candidate-friendly design, this innovation reinforces our mission to build ethical AI for hiring that people love.
Artificially Generated Content (AGC) is content created by an AI tool, such as ChatGPT, Claude, or Pi. We initially rolled out the first version of our AGC detector last year and have continued to improve it as our data set has grown and these AI tools have evolved.
What’s New?
Our updated AGC Detector 2.0 achieves an impressive 98% detection rate for AI-assisted responses, with a false positive rate of just 1%. This gives organisations peace of mind that they’re getting the most authentic assessment of every candidate.
This cutting-edge system builds on Sapia.ai’s proprietary dataset of over 2 billion words, derived from more than 20 million interview question-answer pairs spanning diverse roles, industries, and regions. It’s trained on real-world data collected before and after the release of tools like ChatGPT, ensuring it remains robust and reliable even as AI tools evolve.
The Challenge of AI in Chat-based Interviews
Our data shows that around 8% of candidates use tools like GPT-4 to generate responses for three or more interview questions. While these tools may offer a quick way for candidates to complete their interview, they can inadvertently hide a person’s true personality and potential – qualities our customers are most interested in understanding through our platform. In fact, research from Sapia Labs shows that these tools have their own personality traits, which may be quite different from the candidate applying for the role.
For Candidates: Enabling Authenticity
When a response is flagged as potentially AI-generated, the system doesn’t disqualify candidates. Instead, a real-time warning pops up, allowing them to revise their answers or submit them as-is. This ensures that candidates are encouraged to present themselves authentically, reflecting their unique communication styles and sharing their genuine experiences.
For Hiring Teams: Actionable Insights
Responses flagged as AI-generated are highlighted in the candidate’s Talent Insights profile, accessible via Sapia.ai’s Talent Hub or ATS integrations. These insights give hiring teams the transparency to make informed decisions, fostering trust while accelerating hiring timelines.
Built on Unmatched AI Interview Expertise
“Our detection model’s strength lies in its foundation of real-world interview data collected from diverse roles and regions,” says Dr Buddhi Jayatilleke, Sapia.ai’s Chief Data Scientist. This depth of understanding enables the AGC Detector to maintain its industry-leading accuracy – even when candidates subtly modify AI-generated answers to appear more human.
Why This Matters
The AGC Detector 2.0 embodies Sapia.ai’s commitment to ethical AI that amplifies human potential. As our CEO Barb Hyman explains:
“The hiring landscape has fundamentally changed since ChatGPT, but our commitment remains clear: AI should amplify human potential, not penalise it. This breakthrough fosters authentic hiring conversations. Our real-time warning system helps candidates make better choices and gives enterprises confidence in their selection decisions.”
Testing and Validation of the AGC Detector 2.0
The new detector has been rigorously tested on over 25,000 interview responses generated by humans and leading AI models like GPT-4, Claude-3.5, and Llama-3. The results speak for themselves, reinforcing the reliability and fairness of this game-changing technology.
Fairness & Transparency in AI-Enabled Hiring
By detecting AI-generated content while allowing candidates to correct their responses, our AGC Detector 2.0 ensures every applicant has the chance to put their best, most authentic foot forward when applying for a role powered by Sapia.ai. For enterprises, it provides confidence in the integrity of their hiring decisions and ensures they’re connecting with real candidates at scale.