By Melissa Poremba
School Librarians are the Information Experts
For decades, all school librarians have been saying the same thing: our ‘brand’ is more than books – it is information, regardless of its format. This foundation perfectly positions us to guide students through the intricacies of the modern information landscape, which now includes generative artificial intelligence (GenAI). Data from the Digital Education Council Global AI Student Survey (Digital Education Council, 2024) found that 69% of students report using GenAI for information searching, yet 58% admit they don’t feel confident in their GenAI knowledge and skills. This gap is our opportunity! School librarians are not just positioned to teach information literacy – it is our mandate (Armstrong et al., 2023; Asselin et al., 2003). Our expertise in guiding students through the complexities of information evaluation, source analysis, and ethical use is more critical than ever in a GenAI-enhanced world.
GenAI Literacy: The New Kid on the Block
It is important to note that generative AI is fundamentally different from the legacy or traditional AI that we have been exposed to for a number of years. A useful analogy is that legacy AI, such as GPS, recommendation systems or industrial robots, is like playing in an orchestra where one relies on sheet music and the conductor, so the outcome is predictable and rule-bound; however, generative AI, such as ChatGPT or Midjourney, is more like jazz improvisation: dynamic, creative, and sometimes unpredictable (Autor, 2024). Therefore, while there are already documents available for teaching AI literacy (for example see: British Columbia Ministry of Education and Childcare, 2024; School Library Systems of New York, 2024), GenAI literacy requires specific skills. According to the Modern Language Association of America (2024) the following are some of the skills that one must possess to be GenAI literate:
- a basic understanding of how GenAI technologies work
- can distinguish between AI and GenAI
- credit GenAI contributions in your work through appropriate citation or attribution
- discuss your process transparently with your instructors and peers
- use flexible strategies to adapt to new and evolving GenAI tools
- evaluate the relevance, usefulness, and accuracy of GenAI outputs
- monitor your own learning as you use GenAI tools
- understand the potential harms of GenAI, both those inherent to the technology and those that arise from misuse.
The good news is that most school libraries already have scope and sequence documents which address research skills within information literacy skill instruction, so now they can incorporate these new GenAI literacies into the existing frameworks. However, a unique challenge is that most GenAI tools have age restrictions that must be respected. For students over 13 years of age, parental permission is typically required. Onboarding everyone simultaneously – teaching similar concepts to both younger and older students – adds another layer of complexity, although eventually, AI literacy will be embedded more naturally within the existing curriculum. Creating and implementing this new GenAI literacy curriculum is also challenged by each school’s unique IT ecosystem, policies, and varying levels of staff comfort. Many staff and students are hesitant about GenAI, due to legitimate concerns about bias, hallucinations (when the AI makes up information), deepfakes, academic integrity, misinformation, the use of personal information in training data, copyright, and intellectual property rights. Research from Carroll and Borycz (2024) suggests that librarian-led information literacy training helps students develop a more nuanced understanding of AI’s limitations and best uses in inquiry-based work. The Canadian Association of Research Libraries’ updated Digital Literacy Framework echoes this, noting that the “transformational impact of AI on the information environment adds new complexities, underscoring the need for students to be taught digital literacy” and that “libraries are uniquely positioned to teach digital literacy to our students” (2024). Thus, the skills and knowledge of school librarians are essential to better equip students with the ability to understand how GenAI tools create information, their potential problems, and how to critically evaluate their output.
The Right Tool for the Task
A critical component of AI literacy involves assessing the tools themselves as existing ones are constantly updating and more are constantly emerging. There are options specifically designed for education, such as FlintK12, SchoolAI, and MagicSchool, which offer features tailored to teachers and students, including data privacy, educational guardrails, and administrator oversight. These platforms provide purpose-built educational tools and research activities that allow teachers to monitor and assess student interaction.
While ChatGPT has become almost synonymous with GenAI, school librarians can direct students to many other publicly available tools. To address concerns about hallucinations, students can improve the reliability of responses by using “grounded” tools such as Perplexity, Google Gemini, and Microsoft Co-Pilot. These tools can incorporate web search results into their responses alongside their training data. Some also offer ‘deep research’ options where students can capitalize on the opportunity to observe as the tool identifies and performs each step in its ‘thinking.’ “You can see that the AI is actually working as a researcher, exploring findings, digging deeper into things that ‘interest’ it, and solving problems” (Mollick, 2025).
There is an entire of class of GenAI-powered research tools such as Scite, Consensus, Research Rabbit, and STORM from Stanford designed specifically to assist with research. While most have age requirements that high school students won’t meet until graduation, school librarians can demonstrate them to introduce students to what will be available in post-secondary education. Teachers may be enticed to use these tools for their own research during AQ courses, PD, or other continuing education programs; NotebookLM is particularly useful for these applications. One tool designed specifically for research, Elicit, can be used by students over 13 with parental permission. Engaging with and analyzing its feature-rich interface can show students some of the more advanced techniques in gathering, vetting, and organizing information. (For a comparison of traditional library databases with AI-powered academic search tools, see Texas A&M University Libraries, 2025).
As stated, students must learn to evaluate each tool’s strengths, weaknesses, and suitability for different tasks (Hervieux & Wheatley, 2020). Indeed, sometimes the best course of action is a combination of tools. Academic libraries have been proactive in curating this ever-evolving landscape, regularly updating tool reviews and support materials – resources that school librarians can adapt for their own communities. (For excellent examples, see: Georgetown University Library, 2025; McGill Libraries, 2024; University of Alberta Library, 2025; University of Waterloo Library, 2025. For instructional videos for students, see: University of Calgary Libraries and Cultural Resources, 2024. For a more academic treatment, see Archambault & Rincón, 2024.)
Academic Integrity: It’s About the Task, Not the Tool
The conversation around GenAI and academic integrity is nuanced. Most teachers are comfortable with students using tools for spelling and grammar correction, but many of these now offer features that can substantially rewrite or even generate entire assignments. However, the real issue often isn’t the tool itself, but the function it performs.
A helpful analogy for students is comparing the use of GenAI tools to using tools like park assist, a calculator, or an escalator. There is nothing inherently wrong with using them, unless the student is being assessed on their driving, numeracy skills, or fitness level in climbing stairs. A crucial part of AI literacy is knowing when to use AI and, just as importantly, when not to use it. This distinction requires teachers to be very intentional and clear about the skills they are teaching and assessing. The AI Assessment Scale (Perkins et al., 2024) is a tool that can help students understand that using GenAI is not necessarily an ‘all or nothing’ decision in schoolwork. Ultimately, whether students can use GenAI depends on the teacher’s judgment regarding the skill being taught and assessed. Further, any use of GenAI must be acknowledged, and school librarians and teachers will need to provide templates and guidelines for how to do this.
Assessment: It’s About the Journey
Despite efforts by teachers to delineate the acceptable extent of GenAI assistance, students can succumb to the temptation to let GenAI do the work, especially for writing tasks like research reports. This issue makes it even more important for teachers to collaborate with school librarians to design research assignments that emphasize the process of research rather than the traditional final written product.
This focus on process represents a newer paradigm for both teachers and students and necessitates increased focus on the steps and stages involved, particularly in documentation. Teachers need to demonstrate techniques for collecting, analyzing, and interacting with research materials at different points in the process. This documentation becomes critical if a teacher suspects unauthorized AI generation when a final report is assigned. It is also necessary to teach students to be transparent in their use of GenAI. This goes beyond simple citations; while much attention has been given to citing AI-generated information, students should first consider whether they should be citing it at all unless they have verified and interacted with the original source.
As mentioned, instead of evaluating only a final report, teachers can consider assessment strategies that capture the process. These could include:
- interviews with students, querying them about their research
- oral presentations, demonstrations, or poster sessions where students present findings and defend their position
- research portfolio compilation
- creation of a product (website, video, infographic, fact sheet, podcast) that demonstrates their process and findings
- peer-assessment
- resource analysis (verify every source referenced by the GenAI tool to ensure existence and quality)
- concept mapping
- reflection papers or journals commenting on the research process, challenges, and learning.
What constitutes ‘research’ varies depending on the students’ age and stage, as well as the academic discipline. Shifting to assessment of the process or journey aligns with the principle that in K–12 education, uses of GenAI should always begin with human inquiry and conclude with human reflection, insight, and empowerment (Washington Office of Superintendent of Public Instruction, 2024). By having students engage with GenAI output, we can empower them to discover its limitations for themselves rather than being lectured to about the dangers. Some strategies to consider are:
- assign students a research topic where GenAI output might reasonably be expected to be biased, have them experiment with prompting to obtain results, and then critically analyze the output by referencing other sources.
- assign students to research a topic using traditional methods and sources, or after class lessons, and then research the same topic using GenAI and critically evaluate the differences.
- provide a rubric the teacher would use for student research projects and have students prompt and grade AI-generated output using the rubric to evaluate its performance.
- require students to compare resource suggestions or output results from different GenAI tools, as well as with subscription databases and print resources.
- have students construct citations for resources themselves, then compare them to citations created by GenAI, and to those made by citation management tools such as MyBib or Zotero.
- students have been taught not to use full questions when searching traditional interfaces such as a library catalogue, subscription database, or search engine, but now they can use natural language when querying GenAI tools thus they could experiment with the output obtained by interchanging tools and techniques.
While devising such new approaches represents a paradigm shift for school librarians, an ironic twist is that GenAI tools, particularly those designed for education, can be prompted for suggestions on how to use GenAI in the research skill being covered, including being asked to devise an assessment tool or rubric.
The Research/Inquiry Process
While there are various models for research/inquiry, they all share basic steps (Canadian School Libraries, 2022). The interactive nature of research connects well with the fact that students often need to experiment with prompts to get the best response. Prompt engineering is an important new skill students need to learn. Many GenAI tools now feature the ability to suggest related or refined prompts, further aiding this iterative process.
GenAI is particularly effective at helping students brainstorm research questions or project ideas. By providing 039text or a topic, students can prompt GenAI tools to suggest various questions, approaches, or methods which can accelerate the initial stages of research and inspire novel directions. For example, asking GenAI for research questions on a topic can quickly generate a list for refinement. While GenAI can hallucinate, it also often provides creative suggestions that students might not conceive on their own.
GenAI-powered tools can help students find open-access academic articles, summarize key points, and suggest other relevant sources such as books, videos, and websites. Tools such as Elicit, Consensus, and Connected Papers are specifically designed to search scholarly databases and recommend or synthesize articles. GenAI can also aid in developing a key skill for students, learning to read scholarly peer-reviewed articles by providing clarifications, analogies, definitions, quizzes, or summaries. These tools can save time and help students explore a wider range of research more efficiently than manual searching alone.
For many teachers and students, their key concern is that GenAI tools can hallucinate and invent sources. However, verifying sources is a skill school librarians have always taught; this is simply a new application of established principles like SIFT or CRAAP. CTRL-F by CIVIX offers excellent, ready-made lessons for teaching this skill.
It is vital for students to understand that articles in subscription databases are not accessible to GenAI tools, even research-focused ones. Thus, it is still critical that school librarians continue to teach traditional database searching methods. It is, however, still possible to include GenAI in suggesting keyword strings and Boolean operators for the search. Most database vendors prohibit downloading articles for uploading to GenAI. However, these vendors are developing their own interactive GenAI tools supported by Retrieval Augmented Generation (RAG), with features like natural language searching and article querying. JSTOR, for instance, has such a tool; EBSCO had a beta program in 2024 with the promise of AI Reference Assistance and Literature Review in 2025.
GenAI tools may even open up new opportunities for students working on research projects. Tools like Otter.ai can facilitate personal interview research by helping with content collection and analysis. Knowledge translation, an important skill, can be aided by GenAI tools that rewrite content for different audiences or reading levels. If a final research report is required, a GenAI tool can act as a peer assessor, providing feedback on the writing. With the efficiency gained from GenAI-assisted retrieval, secondary students might even undertake more literature reviews than previously possible.
With GenAI becoming even more ubiquitous, even a simple Google search results in students being supplied with an ‘AI Overview.’ Adobe Acrobat and Google Scholar have also added extensions to allow GenAI-powered interactive chats and article outlines. At whatever point students encounter GenAI output when searching for information, it is essential that teachers remind them to engage with the output by analyzing, revising, questioning, investigating, and comparing it.
Considerations
The main advantage of using generative AI in research is its potential to improve efficiency and productivity and automate so-called tedious tasks like summarizing, organizing materials, finding sources, and data analysis (Khalifa & Albadawy, 2024). However, school librarians must pause and ask: are ‘efficiency’ and ‘productivity’ our primary goals in K-12 education? Do we still need to ensure students can complete research tasks in the traditional, sometimes ‘hard’ way? These questions must be addressed when developing GenAI scope and sequence guidelines. It seems reasonable to ensure students are well-versed in all forms of information access, new and old, so school librarians and teachers need to balance their instruction even though some may not be entirely comfortable yet.
Perhaps the major issue is how will students acquire the foundational skills needed to critically assess GenAI output? As suggested earlier, it might be helpful to consider introducing these tools after students already know the answer or are capable of judging the output. Let them use GenAI as a source after they’ve researched using lessons, textbooks, or traditional sources. Assign a topic known to produce biased AI output. Give students the rubric for a research report and have them apply it to one generated by AI.
Another approach is to have students make GenAI the focus of their research. Students can investigate the resulting environmental issues, underlying business models, ethical considerations, privacy issues, labour exploitation potential, job elimination or restructuring, climate change mis/disinformation spread, use in war/conflict, spread of misogyny, impact on scholarly research and publication, or the increase in the number of young people turning to GenAI tools for companionship/advice. (For excellent suggestions, see Furze, 2023.) Letting students explore GenAI themselves allows them to reach their own conclusions about its costs versus benefits and discover its limitations firsthand, rather than simply being told about them.
Conclusion
GenAI serves as a valuable tool for inspiration and exploration, but human judgment and verification remain essential in academic research. School librarians are uniquely positioned to guide students through this evolving landscape, teaching them to navigate information ethically and effectively. Rather than viewing generative AI as a threat, school librarians can embrace it as an opportunity to reaffirm their role as information experts, equipping students with the critical literacy skills needed for the 21st century. As education adapts to the rise of GenAI, school librarians can empower students and teachers to approach the complex information landscape with confidence, curiosity, and integrity. While the tools may change, the core mission endures: fostering literate, critical, and creative thinkers ready for the future, with school librarians leading the way in preparing every student to thrive in the age of GenAI.
Acknowledgements
The author wrote this paper based on the research she conducted for her presentation at the OLA Super Conference 2025. It was edited with suggestions from three colleagues (J.J., S.H., and R.B.) and the GenAI tool, NotebookLM.
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Melissa Poremba, BA, BMath, BEd, LIT Dipl., MLIS. Starting her career as a high school math teacher, Melissa Poremba transferred into library work after volunteering at her children’s school library. She has worked in academic, public, and school libraries and is currently the Senior School Librarian at Hillfield Strathallan College, a PreK-12 independent school in Hamilton, ON. She thanks her colleagues in the Science and Social Science departments at HSC, especially J.P.B., for collaborating with her on combining GenAI literacy with traditional information literacy in student research projects. While she loves working on and talking about the topic, she sincerely hopes GenAI is the last disruptive technology she must master before retirement!