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Use Cases: Generative AI

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Use Cases: Generative AIadutta

Generative AI is a new technology in the early stages of adoption by the general public. It has significant potential, but also can exhibit incorrect hallucinations such as erroneous data production, falsifications and inaccuracy.

List of Use Cases

All the use cases listed below require full oversight and evaluation of any generative AI output by the instructors and students using these tools. 

1. Generate text, visual and audio content

Content production using highly publicized tools such as ChatGPT, GPT4, DALL-E, Stable Diffusion and many others is one of the most familiar applications of generative AI.  The quality of the generated content can be controlled by adjusting the design of the text prompts submitted to each tool. These tools have been used to produce lesson plans, course syllabi, email, proposals, conference presentations, resumes, assignments, surveys, images, videos, etc.  

Tools to help with this use: ChatGPT, Dall-E.

2. Brightspace AI capabilities

Bentley’s Brightspace LMS has an ongoing AI implementation process. Upcoming tools include auto-generators for quiz questions and course outlines, based on existing content in the course. 

A full list of Brightspace AI development projects is available here.

3. Write Code

Microsoft’s Github Copilot is impacting how software developers and engineers create and maintain the code in their programs. This type of virtual coding assistant can provide real-time coding suggestions and facilitate a programmer’s learning and training process, similar in some ways to the experience of working with a human coding partner or tutor.   

Virtual coding assistants can help to reduce the amount of time it takes to write code and minimize coding errors.  However, these tools do make mistakes and are not currently capable of replacing the need for developers’ application planning and coding design expertise, awareness of human factors design and usability issues, systems engineering skill, domain knowledge and intuition, etc. 

4. Write Excel spreadsheet formulas

Microsoft’s Copilot for Excel can assist with the development of complex formulas.  Review this Microsoft documentation to learn more about this application. 

5. Facilitate the ideation process for a project

The primary goal of many ideation processes is to generate many diverse, open-ended ideas in a relatively brief period of time, with the expectation that many of the ideas might eventually be viewed as impractical and discarded at a later stage in the planning process.  

Because of their conversational natural language capabilities, AI chatbots can contribute to any open-ended brainstorming process and follow any preferred direction of thought, limited only by the prompt engineering capabilities of the human participants and the underlying model on which the chatbot is based. 

6. Auto-grade assessments

Educational software vendors are beginning to integrate AI-assisted grading features into their assessment products.  These new capabilities can take a “first-pass” at grading both open-ended abstract assignments (e.g., essays) and close-ended assessments (e.g., matching questions), creating additional available time for instructors to provide detailed reviews and more in-depth feedback to students. 

Examples of tools include Turnitin, Perusal, Gradescope, etc. 

7. Analyze data and text

AI tools can be used to harvest data, determine correlations and trends, group and categorize data, visualize information, and for the analysis of large data sets.  The higher-level analytical capabilities of AI tools can also be applied to literature reviews, writing abstracts, and finding relevant academic literature. Premium AI tools such as the new ChatGPT Advanced Data Analysis plugin can accomplish data cleaning and data file input (rather than just chat input). Another possible application of generative AI is the creation of synthetic data sets that can be used to train new machine learning models. 

A few other examples of generative AI tools with data analysis capabilities include Microsoft’s Copilot for Excel and Tableau GPT. 

8. Conversationally troubleshoot technical and research issues

Similar to existing online chat apps provided by many service vendors (e.g., tech support, shopping site, travel and hospitality sites, etc.), AI chatbots and copilots such as Bing Copilot and ChatGPT can provide interactive assistance with technical issues, questions about research topics, and queries for unknown information. 

9. Enhance learning with chatbot feedback

Both students and instructors can enhance their own individual learning process, by conversationally engaging an AI chatbot, using a judicious selection of prompts, to: 

  • Review concepts 
  • Generate examples of concepts 
  • Brainstorm 
  • Obtain feedback for written input 
  • Generate data and information visualizations in real time that facilitate understanding 

10. Translate content in other languages

Google Translate, Bing Microsoft Translate, DeepL and Azure AI Translator are some examples of real-time language translation tools that can be used to facilitate the accessibility of instructional content, like summarizing conversations and videos.

What other use cases have you explored?

Let us know!


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