How Generative AI is Changing Assessment Design?
“From helping teachers focus on teaching to allowing students to work on far more ambitious projects, AI has the potential to be a great force for good in education,” says the World Economic Forum. Generative AI in assessment (Gen AI) is especially proving to be a disruptive force that is redefining teaching-learning experiences. The applications of this technology are manifold, from course design to data privacy. At the same time, the use of AI isn’t without its challenges. One of the key concerns has been the vulnerability to bias in AI models, which presents a hurdle to achieving accessible, inclusive, and equitable education for all.
Yes, the potential of Gen AI is undeniable, with the GenAI in the education industry expected to witness an explosive CAGR of 39.5% between 2024 and 2033 to reach a value of $7.7 billion by the end of the period. Against this backdrop, GenAI is likely to play a major role in not just facilitating personalized lesson design but also assessment design to ensure better targeted evaluation of learning progress.
From Traditional Assessments to Gen AI Design
Traditional assessments are static and often fail to capture the full spectrum of a student’s knowledge and abilities. A one-size-fits-all approach with standardized tests neglects differences in learning style and pace. Moreover, it focuses on rote learning and reproduction of facts, rather than knowledge assimilation and application. This hinders the development of critical thinking skills, such as problem-solving and socioemotional intelligence, which are essential to preparing students for life and challenges beyond the learning years.
What Gen AI Brings to Assessment Design
Gen AI makes assessments more interactive, relatable, and dynamic. This helps maintain the continuity of learning and assessments. The technology makes assessment design not just faster, easier, and smarter, but also adds greater value via:
Personalized Assessments
Leveraging Gen AI, educators can develop assessments that cater to unique learning goals, expertise levels, and learning styles of individual learners. In addition to creating dynamically adaptive assessments, Gen AI-based tools can be used to develop personalized rubrics. This enhances the evaluation of learning progress, which in turn can help deliver targeted feedback to drive understanding, engagement, and improvement.
Automated Grading
As strides are made in natural language processing (NLP), Gen AI-based evaluation engines will become increasingly capable of grading subjective and long-form answers. This will streamline grading, making the task more efficient and freeing up teachers’ valuable time for more meaningful student interactions.
Eliminating Human Bias
Traditional essay and literary grading is susceptible to human bias and error. Gen AI can revolutionize both written expression and its grading. With access to massive learning patterns and tools of inference, it allows students to express their opinions and points of view freely. On the other hand, eliminating subjective bias in grading creates equitable learning opportunities.
Enhanced Learning Analytics
Gen AI powers learning analytics by combining vast amounts of data from disparate sources for comprehensive analysis. This data can include individual, class-level, school-level, and district-level learning metrics. Gen AI tools can identify industry trends, learning gaps, and learners’ strengths and weaknesses, while also creating custom reports from different stakeholders. These insights help educators refine curricula, teaching methodologies, and learning resources to meet individual learner and broader community level educational needs better.
How to Use Gen AI to Design Assessments
Learning content and assessment developers can leverage Gen AI to design transformative assessments that are engaging and effective. The key to optimizing the use of Gen AI for assessment design is to enter precise prompts.
Generate Scenario-Based Assessments
Assessment developers can use Generative Artificial Intelligence Systems (GAIS) to develop targeted case studies to elicit specific skills, such as critical thinking, collaborative problem solving, etc. For instance, creating a crisis management scenario where students need to devise evacuation plans for a disaster-stricken region.
Discover and Validate Alternative Solutions
STEM subjects usually have multiple ways to solve a particular problem. While human teachers may have limited capacity to gauge all these different ways, and often require a lot of time to do so, Gen AI tools can be given specific questions to discover and validate all alternative solutions. The technology can also rate each solution based on ease, thoughtfulness, and accuracy, to deliver deep insights into learners’ skill levels.
Generate Multifaceted Question Banks
GAIS can help educators develop vast question banks that assess all levels of learning. For instance, for a specific course, teachers may want to evaluate all levels of learning from BLOOM’s taxonomy. These may encourage students to incorporate different types of content in tier answers, such as diagrams, graphs, or maps.
Ideation or Design Development
Having to administer multiple assessments during a course can make educators run dry of ideas or varieties of questions. Generative AI tools can add tremendous value in offering novel ideas and exploring new ways of assessing specific knowledge or skills.
Create Real-World Simulations
One of the most important benefits of Gen AI is offering practical experiences of scenarios that can otherwise be dangerous or even life-threatening. Medical students, for instance, can train on simulated triage and surgical scenarios. This improves their life-saving skills and enhances their responsiveness to stressful situations.
Instant and Constructive Feedback
Gen AI-based evaluation tools offer immediate insights into students’ strengths and weaknesses, giving them opportunities for improvement. In addition to grading during assessments, students can use Gen AI tools for projects. Assistive tools offer constructive feedback to elevate skill application and, therefore, scores for the assignment.
Ethical Considerations: A Responsible Future
To twist a popular phrase, with immense potential comes immense responsibility. This highlights the need to focus on the ethical use of Gen AI in education. Ensuring fairness, transparency, and data privacy can build user trust. On the other hand, giving humans the power to over-ride AI-powered decisions is critical for the education industry.
Educators must embrace Gen AI to deliver adaptive, dynamic, and personalized learning experiences. Improvement opportunities and relatable experiences can foster a deeper understanding and love for learning among learners. This is exactly what the responsible application of Generative AI in assessment design can help achieve.
