Key points:
The search for precise information has long been an angular competence of the library and teaching in class research. When cleaning certain materials on a backup player, I came across an article that I wrote for the September / October 1997 issue of Book reportA newspaper directed to secondary school librarians. There is a generation, “asking the librarian” was a typical and often necessary part of the student's research process. The digital tide has swept new tools, habits and expectations. Today's students rarely align the reference office. Instead, they consult their phones, their generative AI bots and their intelligent search engines that promise answers in a few seconds. However, educators must still teach students the ability to be critical information consumers, whether produced by humans or generated by AI tools.
The teachers have not stopped assigning projects on wolves, genetic engineering, drug addiction or Harlem rebirth, but the way students approach these duties have changed considerably. They no longer “surf the web”. Now they are committed to systems that summarize, synthesize and even generate real -time research responses.
In 1997, a search for keywords could produce an eccentric mixture of werewolves, punk groups and dark city names alongside academic content. Today, a student can receive a summary of a paragraph, with quotes, created by a generative AI tool formed on billions of documents. To a student of the eighth year, if the answer seems polite and is labeled “generated by AI”, it must be true. Students must learn how AI can hallucinate or just go wrong.
This presents new challenges and opportunities, for educators from kindergarten to 12th year and librarians to help students assess the validity, objective and ethics of the information they encounter. The issues are higher. The tools are smarter. The role of the educator is more important than ever.
Teach the new nucleus four
To help students become critical information consumers, educators must always focus on four essential evaluation criteria, but these must now be supervised in the context of the content generated by AI and advanced research systems.
1. The purpose of information (and algorithm behind)
Students must learn to question not only Why A source was created, but Why was it shown to them. Does the summary of the site, extract or AI try to inform, sell, persuade or entertain? Has it a priority by an algorithm set for clicks or precision?
A modern extension of this conversation includes:
- Has the answer been written or summarized by a generative AI tool?
- Has the site been stimulated due to paid promotion or commitment measures?
- Does the tool used (for example, Chatgpt, Claude, Perplexity or Google's Gemini) quote sources, and can they be verified?
Understanding both the purpose of the content and the function of the tool that would recover it is now a double responsibility.
2. The credibility of the author (and the credibility of the model)
Students must still ask: who created this content? Are they an expert? Do they quote reliable sources? They must also ask:
- This original content or the text generated by Ai-Ai?
- If it comes from an AI, what sources have it been formed?
- What biases can be anchored in the model itself?
Today's research often starts with a chatbot that cannot cite its sources or check the truth of its results. This makes students to retrace information with original sources even more essential.
3. Information currency (and its training data)
Students must still check when something has been written or for the last update. However, in the AI era, students must understand the cutting dates of training data sets and if the search tools are connected to real -time information. For example:
- The free version of Chatgpt (at the beginning of 2025) can only contain information until mid-2023.
- An in -depth research tool can include academic preparations of 2024, but not articles of reading reviews published yesterday.
- Most tools do not include digitized historical data which is always in handwritten form. It is available in a digital format, but potentially not yet useful data.
This difference is important, especially for rapidly evolving subjects such as public health, technology or current events.
4. The wording and the results
The title of a website or an academic article is always important, but we must now attend the framing of AI summaries and search results. Are research terms refined, biased or manipulated by algorithms to correspond to a popular phrasing? A paraphrase a source in a way that deforms its meaning? Students must be taught to:
- Compare summaries to complete texts
- Use advanced search features to control the relevance
- Recognize the tone, the bias and the framing in the materials generated by the Ai-Généré and the Man
Beyond the Internet: Print, databases and important librarians
It is more tempting than ever to count only on the internet, or now, on an AI chatbot, for answers. Just like in 1997, the best sources are not always the fastest or the easiest to use.
Finding the capital of India on Chatgpt can feel effective, but cuts it over in an almanac or reliable encyclopedia reinforces the triangulation of sources. Likewise, the visualization of a photo of the first atomic bomb on a database organized as the national archives provides a more reliable context than to draw it from a random research result. With Deepfake, internet proliferating photographs, the use of a renowned image database is essential, and students must learn how and where to find such resources.
In addition, teachers can encourage students to seek balance using:
- Printing sources
- Academic databases based on the subscription
- Digital standards organized by librarians
- Assistants of research on AI assembled such as icilicit or consensus
An effective strategy is the continuous use of research pathfinders that list sources in several formats: books, magazines, organized websites and confidence AI tools. Encourage assignments that require various sources and types of sources help strengthen research resilience.
Internet assignments: always a trap
Then, as now, it is imprudent to demand that students use only specific sources, or only a generative AI, for research. A well -balanced approach promotes information collection from all potentially useful and reliable sources, as well as information control.
Students must learn to go beyond the first AI response or the web result, so that they strengthen essential skills in:
- Deep reading
- Source assessment
- Contextual comparison
- Critical synthesis
Teachers must avoid giving duties that limit students to a single type of source, in particular AI. Instead, they should encourage students to explain why they selected a particular source, how they checked their claims and what alternative points of view they met.
Use of ethical and academic integrity
Generative AI tools introduce powerful possibilities, including important reductions, as well as a new border of plagiarism and non -critical thinking. If a student submits a summary produced by Chatgpt without examination or quote, have they really learned something? Do they even understand the content?
To fight against this, schools must:
- Update academic integrity policies to resolve the use of generative AI, including a clear direction for students about the time of not using such tools.
- Teaching the quotation standards for the content generated by AI
- Encourage original analysis and synthesis, not just copying and collage of responses
A responsible prompt could be: “Use a generative AI tool to locate sources, but summarize their arguments in your own words and cite them directly.”
In closing: the role of the librarian is more critical than ever
Today's information landscape is more complex and more powerful than ever, but more subject to automation errors, biases and superficiality. Students need more than access; They need advice. This is where the school librarian, the media specialist and the digital literacy teacher must collaborate to ensure that students are fully prepared for our world rich in data.
Although the tools have evolved, from cards catalogs to Google research to AI Copilotes, the fundamental need remains to teach students to ask good questions, to assess what they find and to think deeply about what they believe. Some things have not changed – just like in 1997, the best advice to conclude a research lesson remains, “And if you need help, ask a librarian.”
