How Are Adaptive Assessments Driving Success in Higher Ed?

Why are assessments important in education? The obvious answer is: to see how much of a concept or subject a learner has understood. But it doesn’t just end there. Assessments help educators to determine the kind of support the learner needs to progress in the curriculum. But most traditional assessments — whether they are formative, summative, or diagnostic — often lose sight of this objective. They are not equipped to deal with the unique needs of each learner. That’s where something like adaptive assessments can help.

Adaptive assessments equip educators to understand and cater to the unique needs of each learner. While traditional assessments have a one-size-fits-all approach, adaptive assessments adjust their difficulty level based on the learner’s response. These adaptive assessments are designed to guide each learner in their learning journey by challenging and supporting them as needed making it a responsive system that truly meets learners’ requirements.

 

What Is an Adaptive Assessment and How Does It Work?

An adaptive assessment is a form of computer-based testing that adjusts according to the test-taker’s abilities, progressing based on the user’s performance. For instance, when a learner answers questions on a particular topic with ease, the assessment will present questions of increasing difficulty.

The development of an adaptive assessment begins with assembling a comprehensive question bank. Once a bank is created for each topic, every question is categorized by its difficulty level. Various methods can be employed to achieve adaptability, including branching techniques, rule-based systems, and Item Response Theory (IRT). Following the creation of the question bank, pilot tests are conducted to gather data for calibration. For example, when testing a specific number of students, the adaptive assessment should be capable of delivering multiple unique sequences of questions tailored to each individual. Typically, this model is not AI-driven; rather, it follows a predefined structure based on the insights gained from the pilot tests.

 

How Will Learners Benefit from This Technology?

Adaptive assessments allow learners to progress according to their abilities. If a learner demonstrates proficiency in topic A, the test moves on to topics B and C, preventing time spent on strengths and focusing instead on areas needing improvement. This effectively identifies the individual’s knowledge and skill level while highlighting the gaps between their current abilities and the desired outcomes.

In a traditional two-hour test, you would complete the entire assessment regardless of how many questions you answered correctly. Afterward, you would evaluate your overall skills, pinpoint weaknesses, and focus on them before attempting the test again. However, with adaptive assessments, the experience is tailored to your performance in real time. If you find yourself struggling with certain questions, the test automatically adjusts by lowering the difficulty level and presenting easier questions. This dynamic approach allows for a more personalized testing experience, utilizing a calibration process to assess key parameters for each question, such as difficulty and discrimination, ensuring that the assessment accurately reflects your abilities.

 

What Are the Future Trends in Assessment?

One promising trend in adaptive assessments is the introduction of Generative AI. GenAI addresses one of the biggest challenges of adaptive assessments: creating comprehensive question banks. By using AI and machine learning to build and curate these banks, IRT can enhance adaptive assessments, making them more personalized and applicable for high-stake exams and formative and continual assessments. This innovation reduces the complexities that once deterred institutions from adopting adaptive assessments, paving the way for more user-centric and advanced assessment models.

Advancements in cloud infrastructure are also transforming adaptive assessments. With enhanced capabilities to handle large datasets efficiently and cost-effectively, cloud technology makes it easier and more affordable for institutions to implement these assessments. This allows you to leverage these tools to offer adaptive solutions with minimal investment, encouraging widespread adoption and positioning your organization as a leader in innovative assessment strategies.

 

How Can Educators Start with Adaptive Assessments?

To develop comprehensive frameworks for advanced platforms, you can harness readily available tools and accelerators to streamline the process. By effectively integrating these tools, your solution and implementation teams can significantly reduce time-to-market, allowing your organization to deliver faster and more efficient solutions to clients without needing deep technical expertise. As these frameworks and tools become more sophisticated, you’ll be able to decrease market entry time, offering greater value to your customers and end-users. This approach enhances operational efficiency, accelerates innovation, and secures long-term benefits for your organization and its stakeholders.

Adaptive assessments represent a big advancement in educational evaluation, going from traditional static methods to dynamic, personalized testing systems. As technology evolves and becomes more accessible, these assessments will be a cornerstone of higher education, creating effective adaptive learning platforms that can cater to learner needs.

Adopting adaptive assessments offers a strategic opportunity to elevate the quality of your evaluation processes. By leveraging these technologies, you can provide more personalized and accurate assessments that meet the diverse needs of students. This positions your institution at the forefront of educational innovation, ensuring better student outcomes and more effective use of resources.

Want to know more about how Magic EdTech can build you an adaptive testing platform or upgrade your existing assessment platform? Fill out this form to get the conversation going.