Artificial intelligence in teaching

• Artificial intelligence (AI) in this context refers to generative AI, such as language models or image-generation services.
• AI is guided by prompts, i.e. commands in plain language sentences. These prompts may include questions, background information and instructions for the AI that help in getting the desired answer.
• The use of AI is measured by tokens. Tokens are a numeric unit utilized by the language model that can represent a character or string, a word or even a short sentence.
• AI outputs should always be checked, as the response may contain errors, outdated information or be incomplete.

On May 30th, 2024, the University of Helsinki’s Academic Affairs Council published the revised guidelines on the use of AI in teaching (pdf). Please note that they may be further specified in the light of future regulation and technological developments.

University policy on the use of AI and large language models in teaching and learning:

1. As a rule, large language models may be used in teaching and in support of writing. On pedagogical grounds, course teachers can restrict or prohibit the use of large language models on their courses.
2. Teachers and students are responsible for the accuracy of the language and content of their written work. The use of large language models must be indicated as defined by course teachers and in accordance with the principles of research integrity.
3. In maturity tests, the use of large language models is not permitted.
4. Faculty councils, degree programme steering groups and the Language Centre may draw up supplementary guidelines on the use of artificial intelligence.
5. The use of large language models on courses must be primarily based on the services provided by the University. The accessibility and information security of services must be kept in mind when using large language models. Students cannot be required to use services other than those provided by the University.
6. If students use large language models on courses, components thereof, or in examinations where it has been prohibited in advance, or fail to report the use of large language models as instructed, this constitutes cheating, which will be handled according to the same principles as other cases of cheating.

The guidelines state that course coordinators decide the extent to which AI can be used in their courses. Please note that AI can never be used for maturity tests.

The University of Helsinki has two generative AI services, CurreChat developed at the University and Micorosoft's Copilot with commercial data protection. Copilot is available without restriction to both teachers and students. CurreChat is freely available to staff, while students may use it on courses registered with the service.

CurreChat is more suitable for educational use in terms of both data protection and features, and future development of CurreChat will focus specifically on educational use. For more information on the differences between the services and on security, see the IT HelpDesk guide Generative AI at the University.

Tell your students if you have used AI tools to aid the production of course materials or learning tasks, or if they contain AI-generated components.

Introducing CurreChat on your course

CurreChat is available at curre.helsinki.fi/chat. The service requires login with university credentials.

Teachers can activate the courses they are responsible for directly from the service. Activation creates a course area where enrolled students can use CurreChat for the duration of the course. Conversations students have in CurreChat are not visible to teachers or administrators, nor are they stored in the system.

In the course settings, the teacher can change the course duration and the token limit available to students during the course, add teachers to the course, and create course-specific prompts.

Prompts are instructions for the AI, guiding its behavior during conversations. With course-specific prompts, the teacher can create tasks for students or otherwise direct the use of AI in the course. In CurreChat, prompts can include extensive text-based supplementary materials that the AI can utilize in its responses.
 

Artificial intelligence can enhance and assist the production of learning materials and courses in many ways. In all cases, it is important to check the content carefully. Provide the artificial intelligence tool with as much background information as possible about the scope of the course, the target group, and the topics you want the answers to cover.  For example, you can ask generative artificial intelligence to: 

• Generate ideas for the course structure, lecture content, and learning assignments. You can ask GenAI to evaluate your course plan, for example, from the perspective of constructivist alignment.
• Create a lecture outline or a slide show template on a specific topic. Create assignments on a specific topic for group work, exam questions, discussion topics, or create images to be used as part of the teaching materials.
• Create practical examples of a topic being taught, explaining difficult concepts in more general terms.
• Review your own content and provide further ideas, correct grammatical errors, or translate text from one language to another. 

Generative AI is becoming increasingly integrated into the learning management systems used in university teaching:

• Moodle's question generator can be used to create multiple-choice questions on the course topic directly in the course area's question bank. Teachers can use GenAI in Moodle's text editor to generate text or images directly in Moodle.  
• Thinglink offers the possibility to create both regular and 360° images with the help of artificial intelligence. In addition, it is possible to create interactive scenario tasks using text materials such as scientific articles.
• When producing videos, artificial intelligence can assist with language translation, subtitling, or speech generation from a given text.  

To ensure transparency, students should be informed about the use of artificial intelligence in the production of teaching materials. As an example: "Artificial intelligence has been used to assist in the creation of exam questions, and teachers have checked the accuracy of the questions and answer options." 

AI guides teachers to design learning assignments that are more applied in nature and geared to higher levels of expertise (cf. Bloom’s taxonomy). With easier and faster information-seeking, learning focuses instead on the analysis and assessment of the content acquired, the justification of interpretations made and the creation of new knowledge. This means teachers have to carefully consider the learning assignments they give to students and what kind of guidance and instruction they need. AI-generated output can easily answer a simple open-ended question or at least provide a good basis for a general essay assignment. This means that practising appropriate referencing becomes increasingly important.

AI helps produce responses that sound convincing to assignments asking the student to reflect on learning material. It is not enough to ask students to keep a learning journal outlining their challenges and including critical reflection. This is such a well-established type of text that AI tools such as ChatGPT can generate a response largely on the student’s behalf if the student attaches their lecture notes to a prompt and requests a reflective summary.

Hence, the teacher should experiment with AI tools to see the responses they produce to the planned learning assignments, and then consider how the assignments could be developed with appropriate instructions to make learning more meaningful. In several of the examples listed below, AI can help students complete assignments more quickly. This means you should outline assignments so that students are guided towards achieving the targeted learning outcomes of the course regardless of the means they use to complete the assignment.

Examples of learning assignments:

• AI-generated text can be used as a basis, but the student’s own comments and thoughts must be clearly separated from it.
• Students can be asked to apply information in case-based or problem-based learning.
  • As part of the assignment, the original and follow-up questions posed to the AI tool must be documented. At the same time, students practise using AI as part of information-seeking and assess the output critically.
  • Students can be asked to use source material provided by the teacher and report their reasoned solutions so as to make the learning process visible.
• The conventions of academic writing should continue to be followed: sources must be mentioned, direct quotations clearly indicated and the student’s own comments distinguished from others’ work.
• When exploring and seeking information on a new topic, the processing of information can be supported with follow-up questions (e.g., students can be asked for applied examples or to consider any unclear issues). AI can help with this, but the role of the assignment in the course should be minor or the assignment should not affect assessment.
• Process writing and the use of interim feedback

Instructions for AI use

The basic premise is that AI-generated text cannot be presented as one’s own. It can be referred to under the name of the AI model and the date of the generated text. Students are responsible for their own texts, and plagiarism is strictly prohibited.

The teacher should provide instructions on how to use artificial intelligence (AI) in course assignments and how to report its use:

• When providing guidance, consider whether a certain type of use is recommended or prohibited, and explain the reasons to the students.
• AI-powered services can be used for various purposes, such as language translation, text editing, or idea generation. Students may also find it difficult to ascertain if a service is using AI in the background. Therefore, it is advisable to instruct students to cite not only to their sources of information but also to the tools they have used and specify how they have used them in completing their assignments.
• Similarly, you can instruct students on what kind of AI use does not need to be reported if it is not relevant to the learning objectives of the assignment.

You can instruct students on how to use AI in the following way, for example:

• Distinguish the text produced by AI from your own and add a reference to the name of the AI model or the service used, and the date when the material was generated.
• Write down (e.g., in a footnote) the applications you used and their use, for example, if you used a service for idea generation, language checking, or text editing.

At the moment, it is not possible to reliably determine whether an answer has been produced by an artificial intelligence or a student. There are online services that assess whether a text is generated by AI, but even their response is only an estimation. The way AI has been used, for example, for proofreading or translation of one's own text, can affect this estimation. Additionally, it should be noted that a teacher is not allowed to input a student's answer into external services outside of the university, since they may not necessarily comply with GDPR requirements.

Note that there are differences in the levels of data protection of the AI services provided by the University. For more information see the IT HelpDesk guide  Generative AI ath the University. In any case teachers are not allowed to input any learning assignments or other materials student produce to the AI services. The process of using AI on a course should therefore be planned so that only students themselves input their owen materials to these services. When using CurreChat on a course the teacher can guide the the process by creating instructive prompts that when used, instruct the language model how to reply or give feedback to students' prompts. For example, CurreChat can be instructed to pay special attention to certain details, or give hints on the student might improve their answer based on an exemplar answer.
 

When information acquisition and assignment completion become easier, students may not learn to the same extent or in as much depth as they would if they read a certain amount of background information. If the assignment is such that AI can complete it easily, it should not significantly affect the overall course grade.

Learning depends increasingly on what happens during the course in addition to information-seeking. Can the learning process (what and how I learn) be made more visible to both the students themselves and the teachers? If students learn less at the information acquisition stage, learning can be supported with other assignments during the course.

Examples of assignments that guide students to explore, understand and apply knowledge and skills:

• Reading groups
• Panel discussions, role-based discussions
• Seminar-style work: Presentations, videos and teaching sessions given by students, followed by questions from the other participants
• Small-scale intermediate tests and questions assessed automatically in Moodle can be used as before. Although answers can be found in the course material and online, these can support the review of specific questions and themes and enable students to assess their own skills.

Examples of how to deepen learning after the information acquisition stage:

• In flipped learning (see, e.g., Talbert 2017), information is acquired and the topic explored during remote periods, while the information is applied and the topic examined collaboratively in depth in contact teaching.
• Peer assessment and self-assessment help delve deeper into the topic.
• Online discussions based on previous messages; if necessary the teacher can guide the discussion with follow-up questions in a direction relevant to learning.
• Project-based courses