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Spot work done by a generative AI platform

Spot work done by a generative AI platform

Description

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.

Didactic benefits

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.

Prompt

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. “Write 200 words about the evolution of the academic field information systems. Please write it in an academic tone.

Bloom's Taxonomy

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.

Principles for digitally supported PBL

If you are not yet familiar with the principles for digitally supported PBL here at Aalborg University, we encourage you to read more about them via the link above.

The case can support the following principle(s):

Variation

Variation as a principle is fulfilled through varying the usage of digital tools to achieve learning. The variation can be achieved at lecture, course, semester or even programme level. Variation is not a principle limited to teaching but can also be fostered by supporting variation in group project work.