At Laurea, the Arene traffic light model for the use of artificial intelligence is applied in learning assignments. Take into account Arene’s traffic light model and its use in course modules. The course teacher may limit usage according to the course’s learning outcomes and provide implementation-specific instructions. Note that the use of the traffic lights can be course-specific or vary between individual learning tasks.
The orange light is always the default for essay assignments requiring source references.
Learn more about the traffic light model here: Introduction to the traffic light model and detailed information
Examples of learning tasks in relation to Arene’s traffic lights:
Blue light
The blue traffic light means that the use of artificial intelligence has been deliberately and intentionally included in the learning task. AI functions as part of the learning process, and its use is one of the skills practiced and assessed in the assignment. The student must describe how AI was used and what impact it had on their thinking and the final outcome.
Requiring AI supports students’ AI literacy, critical thinking, and workplace skills. According to Laurea’s guidelines, AI is not seen as a shortcut to answers but as a tool whose use must be justified, evaluated, and reflected upon. When AI use is made visible and assessable, the student learns to understand both its possibilities and limitations.
Example:
A learning situation in which a student uses AI for ideation, generating alternatives, or creating drafts and critically evaluates the quality, reliability, and applicability of AI-generated content in relation to the learning objectives.
Red light
The red traffic light means that the use of AI is entirely prohibited in that learning situation. The aim is to assess the student’s own competence, thinking, language skills, or understanding without external support.
According to Laurea’s guidelines, restricting AI use is justified when it would jeopardize the reliability of assessment or the achievement of learning objectives. The red level protects the core of learning in situations where independent thinking, internalization of knowledge, or personal competence is central.
Example
A learning situation where the student’s personal competence or understanding is assessed in such a way that external assistance would distort the picture of the student’s actual skills.
Yellow light
The yellow traffic light indicates that AI use is allowed and accepted, provided it is disclosed openly according to the teacher’s instructions. AI acts as a tool supporting learning, but the actual demonstration of competence is based on the student’s own thinking and understanding.
According to Laurea’s AI guidelines, transparency is a key principle: the student must be able to describe how and for what AI was used. The yellow level guides responsible AI use and prevents wrongdoing by making usage transparent. At the same time, it supports the student’s metacognitive skills, i.e., the ability to reflect on their own learning process.
This light always applies to source-referenced essay assignments, unless otherwise stated in the task instructions.
Example
A learning situation in which AI is used, for example, to structure thoughts, clarify concepts, or support the writing process, but where the student is responsible for the content’s meaning, sources, and conclusions.
Green light
The green traffic light means that AI use is freely allowed, and there is no need to report its use separately. AI use does not affect assessment because the central learning objective of the task is not related to AI use or AI competence.
This level corresponds to Laurea’s principle that AI can support everyday learning and work in the same way as other digital tools. When AI use does not provide essential added value to the competence being assessed, detailed reporting of its use is not pedagogically appropriate.
Example
A learning situation where AI is used routinely to support work, for example to clarify instructions or improve text fluency, without affecting the core content or assessment of the learning task.
Cases of misconduct
If a teacher suspects fraudulent use of AI (A submission may be deemed fraudulent if, with sufficient probability, it was produced by AI or AI use has not been disclosed or has not been referenced correctly) in their course, they may arrange an alternative way for the student to demonstrate their competence in which AI cannot be used.
If a student refuses the alternative competence demonstration, Laurea’s degree regulations’ misconduct procedure will be followed.