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Welcome back to our four-part series on Google Gemini! In our first post, we explored how AI can help with brainstorming and content creation as well as how we can improve our conversations with AI using prompt chaining.
Continuing the series, here we will explore how AI can do more than just summarize text—it can transform content to suit different audiences and enhance accessibility. Specifically, we’ll show how AI can break down complex academic texts into clear, digestible formats for diverse learners. Whether you’re simplifying dense research, adapting materials for various reading levels, or generating study resources, this post will walk you through practical AI-powered strategies to make academic content more inclusive, engaging, and accessible.
Note: as before we have sample prompt language in italics so you can easily copy and paste them into Gemini.
Activity 2: Adaptive Text Analysis & Accessibility (Going beyond Document Summary!)
AI can not only summarize documents, but it can also change your language level and style to suit different audiences’ accessibility needs, thereby breaking down barriers to possibly complex information. Text Summarization doesn’t JUST have to be about speeding through material. Many struggle with dense academic texts, especially those with learning differences or those who are non-native English speakers.
Step 1: Document Summarization
- Choose an academic article or document from your field
- Ask Gemini:
Please provide a comprehensive summary of this article, including:
– Main arguments
– Key findings
– Methodology
– Implications for the field
Step 2: Simplify Complex Language
- Take a challenging passage from your document and use this prompt:
Please rephrase this passage at a [specify grade level, e.g., 9th grade]reading level.
Highlight key terms that should be retained, and suggest simpler alternatives for complex vocabulary.
- You can then keep changing grade levels or considerations.
More Accessibility-focused prompts
- Format this text to be screen-reader-friendly.
- Convert academic jargon into plain language while preserving key concepts.
- Create alternative text descriptions for any technical diagrams.
Other examples
- Explain this research methodology as if teaching a first-year undergraduate student
- Break down these philosophical arguments into everyday examples
- Transform these statistical findings into plain language insights
Step 3: Generate Study Resources
- Using your summarized content, ask:
Based on this content, please create:
– A list of essential definitions
– Key dates and events
– Important formulas or concepts
– 3-5 suggested related readings for further study
Going further…
There are many different directions to take this beyond what you see in the video. For example, ask any of these:
- Please provide some suggested further reading. (Lit review)
- Who are the most significant authors or texts to be aware of on this topic?
- Has there been anything on this in the news, recently? Please use reliable sources.
- Can you create a specialized vocabulary list for me here?
You can also use AI to present information in multiple formats to support diverse learning preferences. For example, consider different ways learners might interact with the material:
- Ask AI to organize information into concept maps or flowcharts
- Request bullet points that could be easily converted to audio notes
- Generate interactive scenarios or case studies based on the material
Lastly, consider how you can use AI to sift through unstructured data, such as survey results. For example:
- Please find the three more popular points here.
- How would you break these responses down into 3-5 themes?
Conclusion
I hope this helps you see the value in AI for summarization and sorting through text. As with anything with AI, you want it to provide value to YOUR output; not for it to just sub in for you. As such, always consider its work supplemental to your own or a starting point.
A special note on citations and references: When using AI to summarize academic work, always return to the original source material for citations. AI can sometimes misattribute quotes or blend information from multiple sources.
Best practices include:
- Keep track of the original sources you feed into the AI
- Double-check all citations, dates, and quotations against the original texts
- Use AI-generated summaries as a reading aid, but cite from the primary sources
- If you’re using AI to help identify related works, verify these sources exist and are accurately represented
Some helpful AI Citation links:
- How to Cite AI Generated Content – Artificial Intelligence (AI) (Research Guides at Purdue University Libraries)
- How do I cite generative AI in MLA style? (MLA)
- How to Cite ChatGPT and AI in APA Format (Grammarly)
As with any AI assistance, cross-reference key points with the original text you submitted and verify any cited statistics or research findings.
Don’t be afraid to push back and ask where it got its information or tell it it’s wrong when you see something off.
Looking ahead…
In our next post in this AI series, we’ll be looking at Google NotebookLM. Looking forward to showing you this research assistant tool that takes a grounded approach to sources.
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