Artificial intelligence (AI) has captured the attention of the world in the past year, spurred by the launch of widely available tools such as ChatGPT, Bard and Perplexity AI.
The education and learning sectors have been uniquely impacted by this new technology. While most conversations have, perhaps fairly, been around the negative impact of AI within education and learning (specifically by generative AI and concerns around cheating and test fraud), AI also holds massive potential for positive change, particularly in the assessment space.
The prospect of vastly improved efficiency and quality of assessment creation is a benefit of using AI that cannot be ignored. As more time can be saved on the production of traditionally administrative-heavy tasks, such as building high-quality question banks, the trickle-down effects will allow for enhanced learning programs, performance insights and assessment formats.
From an organizational standpoint, this means that improving assessment and learning programs is no longer tied to limits on time, money or resources. Below, we’ve identified key areas where AI can be leveraged by learning leaders to develop and improve skills assessments for employees, which can ultimately improve outcomes for learners.
Better Authoring
The use of generative AI to develop assessment questions and build item banks more efficiently is currently one of the biggest pull factors for incorporating AI into assessment programs. This speeds up assessment creation by decreasing the time spent on the administrative task of creating high-volume item banks, and has the potential to aid in creating better quality content, which allows for more time to be spent on delivering high-impact learning programs. In this use case, AI acts as a productivity booster as well as a cost saver, as assessments are produced faster and more cost-effectively than by traditional methods.
Deeper Insights
AI-enabled reporting and analytics can provide rich insights into performance assessments. This can deliver a deeper understanding of both group and individual performance, much more than traditional reporting. It equips leaders to identify knowledge gaps, make appropriate adjustments to assessments as well as learning programs, and develop targeted learning resources to better support assessment-takers on their learning journeys.
AI-enabled reporting can also allow for immediate real-time feedback and scores, allowing leaders to put insights to use instantly.
Personalized Learning
AI can be leveraged to provide more personalized learning experiences. Based on individuals’ performance analytics, it can intelligently recommend personalized learning pathways, adapt training content based on individual progress and provide ongoing support and guidance.
Cheating Prevention
Most people are aware of the potential threat of and negative impact that AI can have on the world of education through the prospect of cheating. This concern also impacts the corporate training world, as learners could potentially use AI-enabled tools to cheat in assessments or tests. Interestingly, however, AI has the promise to help detect and prevent cheating through AI-enabled plagiarism detection tools, proctoring, and monitoring and data analytics.
Fairer Assessments
A lot has been written in relation to the potential for bias within AI, given the bias within Large Language Models source data. While this is absolutely true, AI can also be a very effective tool in detecting and reviewing content at scale for bias — from socioeconomic and geographic bias to confirmation or affinity bias — in a way that would not necessarily be sustainable for organizations from a cost point of view otherwise.
Alongside this, using AI to standardize tone of voice and language used across large question banks, some of which may have source material that has not been updated over time, can create a better, more consistent and ultimately, more equitable experience for test-takers. By eliminating bias from assessments, learning leaders can ensure that learners are being fairly and authentically assessed based on their skills and knowledge — in doing so, helping to improve assessment equity.
Rethinking Assessments
The dawn of AI assistance opens up an opportunity for learning leaders to completely rethink assessments and the skills of the future. AI tools can save time and make up for limited resources when it comes to assessment creation, yes, but more importantly, it allows learning leaders to turn their attention to the bigger questions. Questions like: What will an AI-enabled future mean for the skills demanded in the workforce? And are traditional assessment formats suited to identifying these new skill sets?
With the landscape of work and skills undergoing a significant change due to AI, so too will the requirements of assessments, likely giving rise in popularity to a newer generation of assessment formats yet to be designed, but also formats like observational assessments and performance-based testing. It’s this paving the way for better assessments and shifting to the skills of the future that we hope learning leaders will be able to focus on in an AI-enabled world.
The Future of Assessments Is Unlimited
In conclusion, these uses of AI have the potential to make assessments more efficient and effective for learning leaders. Leveraging AI to support assessment creation comes with many opportunities for efficiency, fairness and innovation. The end result being higher-quality testing, better learning programs and, ultimately, improved outcomes for assessment takers.
