There are different types of AI tools that have the potential to enhance education and allow for innovative approaches to the educational process. Please go through the following tabs to explore what factors you need to take into account when considering the use of GenAI in the classroom.
For help with generating prompts for educational design, consider this website of the VU ('Vrije Universiteit Amsterdam'). For more general information on how to write effective prompts, visit this website.
When (re)designing a course, an important model to keep in mind is the constructive alignment triangle. This model shows that the course's intended learning outcomes should align with the teaching and learning activities of the course, as well as with the assessment methods (both formative and summative). When you as a teacher plan on using an AI tool in your course, for instance in the assessment, it is important that students learn to work with this tool during the course's teaching and learning activities. Depending on whether the use of an AI tool is a goal in itself or merely used as an aid in teaching and learning, it can be included in the learning outcomes.
If you want to adapt your courses and programmes to the rapid and continuous advancement of AI tools, it is good to question whether all current learning outcomes (on both course and program level) are still relevant. Since the rapid dispersion of AI in different fields of work can change the demands of the future workfield, it is recommended to reassess which (new) competencies students would need in order to succeed in their future careers and whether the learning outcomes address these. As AI tools can help with some of the lower-level cognitive tasks students have to perform, you could decide to formulate learning outcomes to focus on higher cognitive levels. Lastly, skills related to working with AI tools, such as effective prompting, may be a relevant addition to learning outcomes of programmes or courses.
Practically, consider whether the wording and verbs of the learning outcomes have to change to reflect the students’ learning process better. For example, consider the change from 'a student can write a policy document' to 'a student can develop a policy document'. The product the student ultimately hands in is the same, but the focus is more on the process rather than the outcome.
Whether or not students still need to learn a certain skill when readily available AI tools can do this for them is a question without a clear-cut answer. If it is important that your students learn skills for which they could also use an AI program, there are ways to prevent or limit the use of an AI tool. For instance, if you want students to learn writing skills you can have them work on their assignment in an ‘AI-free’ environment such as a classroom or an exam hall. Even if learning a specific skill is not the main goal of your course, it is still important for students to be able to competently judge the output of an AI tool. Therefore, learning a skill, at least to a certain degree, is still necessary and important.
The availability of GenAI tools may have an impact on assessment. There are concerns that students may generate (parts of) an essay using GenAI. There are tools available that promise they can detect when a piece of text is AI-generated. The performance of these types of tools is not foolproof, however, and can lead to situations where a student is accused of AI plagiarism without having done so (false positives).
A good way to deal with this concern is to reshape assessment practices in such a way that the focus is more on continuous assessment (combining formative and summative practices in a course) and feedback rather than merely high-stakes summative assessment at the end of a course. For instance, looking at the capabilities of GenAI to quickly generate feedback, students could be asked to interact with such a tool and document the outcome to give insight into their learning process. For such process-oriented assessments, you may ask students to try out different prompts and ask them to critically reflect and evaluate the output they receive.
AI can be used to enhance student learning. For example, students learning how to program computer code often struggle with writing correctly formatted syntax that does what they envision it to do. AI tools that have been trained on datasets that include programming languages can quickly debug code and offer suggestions for improvement. In this way students receive quick feedback without having to wait for their teacher.
AI tools can enhance student learning regarding different types of skills, such as writing skills and analytical or critical thinking. It is important to emphasize to students that results from an AI tool can function as a starting point, but always require further evaluation and adaptation from the students themselves. Assignments should be designed in such a way that such behavior is stimulated. In addition, always be clear to students up front about when they are and are not allowed to use AI in your courses and how they are required to report on their use of AI.
AI can also be used to create personalized learning experiences for students, for example through the use of adaptive learning environments such as SlimStampen. When used correctly and responsibly, AI programs can tremendously help students in the development of their skills and knowledge.