Assessing knowledge and skills with AI in e-learning

In the world of education, there is a lot of discussion about Artificial Intelligence (AI). Teachers and students/trainees see both advantages and disadvantages. Many teachers are struggling with the fact that "AI is taking over the writing of essays or other student assignments." They type into ChatGPT what they want an essay to be about, and voilà: an essay of reasonable quality is generated in a few seconds. How can you still assess what students actually know?

This is certainly an interesting development. But doesn't it simply require us to approach the assessment of knowledge and skills in a more creative way? Is it really necessary to write an essay to test knowledge? Or are there other ways that cannot be easily produced by ChatGPT? Because the fact remains: AI is here to stay. What we can change is how we deal with it. It actually offers enormous opportunities to simplify the work of teachers, especially when it comes to assessing knowledge and skills!

In this blog, we choose to focus primarily on the benefits of AI in assessing knowledge. Naturally, we will provide a critical perspective where we feel it is appropriate.

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Automated assessments in e-learning

The possibilities of AI in automated assessment systems are revolutionary! AI makes the work of teachers much less repetitive and time-consuming because it offers a more efficient and objective way to evaluate the work of trainees or students.

For example, AI can evaluate tests and essays on a large scale and provide immediate feedback. The ability of AI to analyze text, detect plagiarism, and grade answers is impressive! Teachers can now focus more on other crucial aspects of education and teaching, such as lesson planning and providing personal feedback to students.

Another important advantage of using AI for grading assessments is its consistency. It does not get tired and is not biased, which ensures that every student is assessed fairly. However, it remains important to balance automation with the human factor. AI can handle routine grading tasks well, but humans are still truly needed for assessing complex or creative assignments.

Personalized follow-up after e-learning assessments

Adaptive learning systems use AI to continuously assess student progress and adjust content and pace accordingly. If a student excels in one area but struggles with another, the system can provide extra support for the challenging topic while simultaneously allowing faster progress in areas where the student is strong. This personalization ensures that students receive the right level of challenge and support, which prevents boredom or frustration (and potential dropout).

In addition, AI can also identify where a student's interests lie. Based on this, AI can adapt follow-up assignments or, for example, lesson materials to the subject that appeals to the student. This, of course, also increases intrinsic motivation.

Detecting plagiarism and cheating in e-learning

Maintaining academic integrity is becoming increasingly important with the growth of online education and the emergence of tools like ChatGPT. Although we previously wrote that teachers often feel students are making things too easy for themselves or even "cheating" by having ChatGPT write their essays, AI can actually also contribute to detecting things like plagiarism. AI can identify similarities in writing style and content online, making it easier for teachers to recognize plagiarism.

AI tools can also evaluate the way a student types and interacts with a test or exam. This can include looking at typing speed, the use of keyboard shortcuts, pauses between keystrokes, and other aspects of the student's keyboard behavior.

This analysis can help detect irregularities or suspicious activities during an online test, such as the use of unauthorized tools or copying answers from other sources (such as ChatGPT).

How do we see the future?

To harness the full potential of AI in assessment, continuous research is essential. This research can, for example, focus on refining algorithms, addressing ethical questions, and ensuring that AI continues to evolve to meet the dynamic needs of education.

To make optimal use of the possibilities of AI in e-learning assessments, continuous research and development are essential—improving algorithms, addressing ethical issues, and ensuring that these tools continue to evolve to meet the changing needs of education. In addition, we must strive for user-friendly interfaces so that teachers and students can seamlessly work with AI-supported assessment tools.

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