How would you teach undergraduate students data analysis in the days of generative AI (chatGPT, copilot etcetera)?

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Remigiusz Żulicki

I would start right away to teach data analysis using GNU R, without spreadsheets. There are good learning materials, as https://r4ds.had.co.nz/ (Tidyverse approach) or https://github.com/matloff/fasteR (base R). Generative AI is not relevant here in my opinion, first you need to understand data summarization, filtering, grouping, ploting, all the basics. Then statisitical inference. Maybe in your next courses it would be good for students to teach them SPSS / SAS / whatever is used in the industry. Spreadsheets are great for accounting tasks.

Rudra Tiwari

To technically teach the process of writing code, a good approach is to start with a simple programming language that allows the students to quickly learn the basics of coding, such as syntax, variables, control structures, and functions. As the students progress, more advanced concepts can be introduced, such as data structures, algorithms, and software design patterns. The implications of generative AI on this process are significant, as AI systems can generate code that is both efficient and error-free. This has the potential to significantly speed up the development process, but also means that coders will need to have a deeper understanding of the underlying algorithms and models used in these systems.

The answer to whether to begin teaching data analysis with GUI tools or dive straight into programming depends on the audience and the desired outcome. For a general audience who just wants to quickly analyze data, GUI tools like Excel or Google Spreadsheets may be the best choice. However, for individuals who want to develop their data analysis skills further, learning to program is the more effective approach, as it provides greater flexibility and control over the analysis process. Additionally, programming provides a foundation for more advanced topics like machine learning and big data analysis, which are essential for many data-driven careers.

Saif ul Islam

Highlight the role of generative AI: Explain how generative AI models like GPT-3 and others are used for data analysis, including text generation and sentiment analysis. Also, discuss the limitations of generative AI models and the ethical considerations that come with the use of AI in data analysis.

Yair Suari

Thank you all for answering

As Saif ul Islam I think you should use generative AI while mentioning the limitations.

I also think that since the actual coding will be less demanding in future years you have to pay more attention to principles and theory, things like object and data structures etcetera. This is why I think seeing your results is more important than ever and therefore I would mix spreadsheets and coding.