In this proposal for a learning activity, you can prompt some answers from a chatbot that students can use in class. This learning activity is called “Spot work done by a generative AI platform” and the idea is that you bring text exerts from both a generative AI and a textbook, article or essay written by a human being and let the students attempt to identify what work is conducted by a human being and what is conducted by a large language model. After a blind identification, you can engage the students in a dialogue about characteristics as well as strengths and weaknesses of both.

The benefits of engaging the students in a learning activity where they attempt to identify and characterize a text written by a large language model has several didactic benefits. Through this learning activity, your students will become aware of the strengths and weaknesses of generative AI and possibly the limitations and use cases of a large language model. This will enhance the critical thinking capabilities of your students. Furthermore, the learning activity can open for a discussion regarding how their professional identity will be transformed by AI in the future. Lastly, depending on how you design the learning activity, it might improve your students’ feedback, evaluation, and assessment competencies.

In this learning activity, a prompt will not be provided as it depends on the subject you are teaching. When you are prompting the chatbot, for instance, ChatGPT or Bing, instead of simply writing “Write a text about information systems”,  you are encouraged to use the tips and tricks about designing and engineering a good prompt. For instance, you should be specific and provide context to your prompt:

”Please compose a concise 200-word essay that traces the historical development of the academic field of information systems. Focus on key milestones, such as the transition from manual to computerized systems, the impact of the internet, emerging trends in data analytics and recent AI development. Employ an academic tone, incorporating relevant terminology and citing significant theories or models that have shaped the field.”

The above prompt is designed for Microsoft Copilot Chat (in Creative Mode). The prompt might work with other large language models, but you will need to test it.

The suggested learning activity aligns with multiple layers from Bloom’s taxonomy:

Understanding:
Students need to comprehend the nuances, strengths, and weaknesses of both generative AI and human-generated text.

Analyzing:
The core of this activity lies in the analyzing stage. Students are expected to critically analyze and compare text excerpts, discerning the differences between AI-generated and human-generated content. This involves breaking down information into parts, understanding the relationships, and making distinctions.

Evaluating:
Engaging in a dialogue about the strengths and weaknesses of both generative AI and human-generated text requires students to evaluate the qualities, merits, and weaknesses of each. They are assessing the value and significance of the content they have analyzed.