Creating certification exam questions was a time-intensive process for one of our clients, requiring up to 18 months of meticulous manual effort from subject matter experts. This extended timeline caused significant challenges, including delays in exam delivery and a heavy workload on certified professionals.
DragonSpears was brought in to address these issues and streamline the process without compromising quality. Through the strategic implementation of machine learning, we reduced the exam creation timeline from 18 months to just 6 months. Our solution enabled the client to generate 3–6 certification exams annually, allowing experts to shift their focus from manual question generation to efficient review and approval.
This case study showcases how DragonSpears applied AI/ML to solve a real-world problem, delivering practical, scalable results. Join us as we dive into the challenges, solutions, and outcomes of this transformative project.
The Challenge
We faced the challenge of reducing the time and effort required to create certification exam questions. Producing these exams typically took 18 months, involving extensive manual work from certified professionals. This lengthy process limited the number of exams that could be produced annually and was a significant drain on resources.
The Solution
We developed a custom-configured OpenAI GPT-4 model designed to generate certification exam questions. This innovative solution could produce high-quality questions, including correct answers, explanations, distractors, and varied difficulty levels, using a wide range of approved data sources.
For the custom GPT model, we limited each response to a single question, enabling subject matter experts (SMEs) to refine requests dynamically on a question-by-question basis. This approach maximized the model’s efficiency within the constraints of free computational limits.
Concerns around LlamaIndexing were mitigated by restricting the types of files the model processed and ensuring all ingested data was clean and reliable. Additionally, involving a greater number of SMEs earlier in the project allowed us to accelerate the training process, improving the model’s ability to generate questions that met varying levels of difficulty with greater precision.
The decision to adopt this technology was driven by the need for efficiency, cutting costs, and the desire to free up subject matter experts to focus on reviewing and approving questions instead of creating them manually. DragonSpears delivered on these expectations and took it a step further delivering a functional prototype that could actually be used by the team.
The Results
After implementing the machine learning model, we saw a dramatic improvement in the exam creation process. The time required to create certification exams was reduced from 18 months to just 6 months. This enabled the production of 3-6 exams annually, a significant increase from previous capabilities.
The time to generate individual questions was reduced to mere seconds, allowing for the creation of exams with 100-275 questions with unparalleled efficiency. These achievements underscored the transformative impact of integrating AI into the exam creation workflow.
Contact DragonSpears for Your Next Software Project
This case study demonstrates the potential of machine learning in solving complex business challenges, such as streamlining exam creation processes. By leveraging cutting-edge technologies and strategic problem-solving, we achieved remarkable results—reducing development time, optimizing workflows, and delivering high-quality outcomes.
At DragonSpears, we specialize in crafting innovative software solutions tailored to your unique business needs. Whether you're looking to harness the power of AI, optimize existing systems, or drive digital transformation, our team is here to guide you every step of the way. Ready to tackle your next big challenge? Partner with DragonSpears and turn your vision into reality.
