The benefits of AI-powered assessment in higher education are undeniable and manifold: its impressive scalability, greater efficiency, less admin, and data analytics and progress tracking insights which enable educators to identify individual learning needs and analyse wider trends.
AI-powered assessment is clearly the future of grading and evaluation.
But where to start?
Let’s look at the best practices for implementing and using AI-powered assessment tools in higher education.
Start with well-defined educational goals
Look before you leap. What problems are you trying to solve? Whether it's improving student engagement, personalised learning, or efficient grading, having well-defined objectives will help you choose the right automated grading systems for you and your institution.
Choose tools that align with your objectives and the needs of your courses, ones that offer user-friendly interfaces and integrate seamlessly with your existing learning management system (LMS).
STEM was initially ill-served in the field of digital assessment. We’ve worked hard to redress the situation.
Do your homework
Research is imperative. Who’s been here before? Where has this tech worked well elsewhere?
Look for robust evidence – peer reviews, case studies, and efficacy research.
Here is a good example of a case study video with Graide
You could reach out to educators who are currently using AI-powered assessment in higher education.
Consider the following lines of enquiry:
· What's working for them?
· What isn't?
· What do they wish they'd known before committing to their current system?
Look for possible trial periods
Some make the case for starting small, perhaps beginning with piloting implementation in a specific course or department before scaling up.
This allows you to assess the effectiveness of the tools and make any necessary adjustments before full-scale deployment. Then you can put the tools to the test, see them in action, have a play while you gather insights and observations from users.
Involving staff in these early trials will help with buy-in down the line – far better than imposing tech later on that no one knows very much about or really wanted in the first place.
Bring everyone on board
Once you have chosen the right tech, after possibly trialling it with a smaller group of users, get everyone else on board. Explain the rationale behind choosing one AI grading tool over another.
The advantages of using AI-powered assessment are undeniable. Sell the key benefits in terms of time saved on marking and admin, things which take up so much of an academic’s day. Our efficacy research at the University of Birmingham showed that “the median grading times were reduced by 74%, and the number of words of feedback given increased by a factor of 7.2. We estimate that a university, with 3500 STEM students, using Graide could save over £240,000 a year.”
You may want to develop working parties to drive adoption of the new system, setting up tech champions and mentors to help others less confident than themselves. They can support implementation in those early stages, troubleshooting, helping colleagues, identifying common pinch points.
Provide training and support
To fully leverage AI-powered assessment tools, faculty, staff, and students need training.
Check out what training and support vendors provide as part of the package, in the form of in-person or online training.
They might offer:
· Blog content
· Later support: email / helpdesk / contact person*
*You want someone who will quickly and enthusiastically answer your email queries or phone calls. Aftercare is something some companies do really well while others fall short.
Of course, you will want to tell students about how the tools work. Explain what the tech does for them. They have so much to gain.
One significant advantage of AI-powered assessment is that it removes bias, ensuring fairer and more objective assessment. And students really value the quick turnaround time of work, along with better, more detailed feedback. I know that I, as a student, wanted to learn where I’d got things wrong so I could quickly put them right.
Validate the AI system
Validation is a crucial step in developing and deploying AI systems. You will want to test the tech, assessing and confirming that it performs as intended, meeting specified requirements, and operating effectively and safely within its intended context.
Validation involves running the algorithm on cases where the “right” answer is known, to see if the AI system functions as intended.
Other areas for consideration include usability, accuracy, efficiency, and ethics. Is student data properly protected? Is the software GDPR-compliant? Is it clear who the data controller is?
Continually review and refine
You will also want to continually monitor the performance of the AI-powered assessment tools. Regularly assess their impact and make adjustments accordingly.
Are they contributing to improved learning outcomes, increased efficiency, or other desired outcomes? Are students benefiting from them?
This is something the working party can look at. Collect feedback from both instructors and students regarding their experiences with the AI tools. Use this feedback to make improvements and refine your implementation strategy over time.
It is important to keep an eye on improvements: the tech evolves all the time to help educators. Stay informed about the latest developments in AI-powered assessment tools and consider how these advancements could enhance your educational practices.
...To stay up-to-date on grading practices, read our articles.
Here are some of our most popular ones:
It’s clear that the demands on teachers in higher education aren’t getting any lighter. Leaning on AI assessment means they can lean into more human feedback and assessment, and have time for other commitments. I know that’s what I most valued as both a student and educator.
All the best with the new academic year. Don’t hesitate to get in touch if you think we can help out your college or university with AI-powered assessment.
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