Source List of Student Learning Outcomes (SLOs)

Locate information

Students will be able to apply AI tools, such as Research Rabbit, to conduct preliminary literature scans and identify relevant research themes for an academic topic (Jocelyn Ireland, MVCC). Secondary mappings: ACRL Searching as Strategic Exploration.

Students will be able to implement effective strategies for creating prompts for generative AI tools (Hervieux and Wheatley, 2024). Secondary mappings: GE Ethical Dimensions, ACRL Research as Inquiry, ACRL Searching as Strategic Exploration.

Students will evaluate real-world AI tools, analyzing their capabilities and limitations. They will assess how well these tools meet specific needs and discuss their potential impact on society (LibraryReady.AI PreK-12 AI Curriculum, 2024). Secondary mappings: GE Ethical Dimensions, ACRL Research as Inquiry, ACRL Information Creation as a Process.

Students will adapt their work process to include AI tools as appropriate to enhance their creative work, engage in tasks, or develop AI agents. They will critically evaluate the ethical implications of AI-generated content, considering issues like copyright, intellectual property, and the role of human creativity in the age of AI-generated production (LibraryReady.AI PreK-12 AI Curriculum, 2024). Secondary mappings: GE Ethical Dimensions, ACRL Information Creation as a Process, ACRL Information Has Value.

Students will be able to use AI systems to support research processes, such as identifying themes, connections, or directions for further investigation, while maintaining responsibility for verification, interpretation, and synthesis of information (Jocelyn Ireland, MVCC, adapted). Secondary mappings: GE Ethical Dimensions, ACRL Research as Inquiry, ACRL Information Creation as a Process.

Students will use AI to create insights and improve processes (Kennedy, 2023). Secondary mappings: ACRL Searching as Strategic Exploration.

Students will evaluate AI’s cultural, global, and environmental impacts, including bias, access inequities, and implications for equity. They will examine AI’s energy use and ecological footprint, and consider ethical trade-offs between innovation and sustainability (Reda, SUNY Westchester, 2025). Secondary mappings: GE Ethical Dimensions, ACRL Information Has Value, ACRL Scholarship as Conversation.

Students will understand core AI principles, including machine learning, natural language processing, and neural networks (AI Literacy in Teaching and Learning: A Durable Framework for Higher Education). Secondary mappings: GE Evaluate Information, ACRL Information Creation as a Process.

Students will gain practical experience with AI technologies through interactive sessions and workshops (AI Literacy in Teaching and Learning: A Durable Framework for Higher Education). Secondary mappings: GE Evaluate Information, ACRL Searching as Strategic Exploration, ACRL Information Creation as a Process.

Students will effectively integrate AI tools into their daily learning activities, including studying, personalized learning, and review of work (AI Literacy in Teaching and Learning: A Durable Framework for Higher Education). Secondary mappings: ACRL Searching as Strategic Exploration, ACRL Research as Inquiry.

Students will leverage AI tools to enhance their research capabilities (AI Literacy in Teaching and Learning: A Durable Framework for Higher Education). Secondary mappings: ACRL Research as Inquiry, ACRL Searching as Strategic Exploration.

Students will apply AI tools to project-based learning to enhance critical thinking and problem-solving skills in addressing real-world problems (AI Literacy in Teaching and Learning: A Durable Framework for Higher Education). Secondary mappings: ACRL Research as Inquiry, ACRL Searching as Strategic Exploration.

Students will identify, describe, and explain the components, requirements, and/or characteristics of AI (Southworth et al., 2023). Secondary mappings: GE Evaluate Information, ACRL Information Creation as a Process.

Students will select and/or utilize AI tools and techniques appropriate to a specific context and application (Southworth et al., 2023). Secondary mappings: ACRL Searching as Strategic Exploration, ACRL Research as Inquiry.

Define key technical terms like “artificial intelligence,” “machine learning,” “large language model,” “neural network,” and “computer vision” (Yale Generative AI Literacy Framework). Secondary mappings: GE Evaluate Information, ACRL Searching as Strategic Exploration, ACRL Information Creation as a Process.

Use GAI-generated outputs to brainstorm new ideas and refine and extend research inquiries (Yale Generative AI Literacy Framework). Secondary mappings: GE Evaluate Information, ACRL Research as Inquiry, ACRL Searching as Strategic Exploration.

Locate and use documentation from tool creators to answer questions about GAI construction/data (Yale Generative AI Literacy Framework). Secondary mappings: GE Evaluate Information, ACRL Information Creation as a Process, ACRL Authority is Constructed and Contextual.

Students will be able to locate information effectively using AI tools appropriate to their need and discipline (Lauren deLaubell, SUNY Cortland). Secondary mappings: ACRL Research as Inquiry, ACRL Searching as Strategic Exploration.

Students will be able to formulate and refine prompts when interacting with AI systems in order to improve the relevance, scope, and usefulness of retrieved information (Jocelyn Ireland, MVCC, adapted). Secondary mappings: ACRL Research as Inquiry.

Evaluate Information

Students will be able to appraise the quality of the output created by an AI tool and question if it is appropriate for the user’s purposes (Hervieux and Wheatley, 2024). Secondary mappings: ACRL Authority is Constructed and Contextual, ACRL Scholarship as Conversation.

Students will be able to distinguish content created by humans and artificial intelligence (Hervieux and Wheatley, 2024). Secondary mappings: GE Ethical Dimensions, ACRL Information Creation as a Process, ACRL Information Has Value.

Students will examine the possibilities and limitations of AI by differentiating between its outputs and that of more traditional formats (Lauren deLaubell, SUNY Cortland). Secondary mappings: ACRL Information Creation as a Process, ACRL Scholarship as Conversation.

Students will be able to evaluate the impact of using AI on their learning and research outcomes (Jocelyn Ireland, MVCC, adopted from EDUCAUSE). Secondary mappings: GE Ethical Dimensions, ACRL Searching as Strategic Exploration, ACRL Research as Inquiry.

Students will be able to identify and explain the fundamentals of AI, including machine learning, natural language processing, and neural networks (Jocelyn Ireland, MVCC). Secondary mappings: ACRL Searching as Strategic Exploration.

Students will demonstrate using AI tools critically by questioning the results of AI searches and recommendations. They will identify how AI tools can introduce bias or mistakes, and why human oversight (HiTL – Human-in-the-Loop) is necessary to ensure accuracy (LibraryReady.AI PreK-12 AI Curriculum, 2024). Secondary mappings: ACRL Information Creation as a Process.

Students will critically assess the effectiveness and reliability of various AI tools (AI Literacy in Teaching and Learning: A Durable Framework for Higher Education). Secondary mappings: ACRL Authority is Constructed and Contextual, ACRL Searching as Strategic Exploration.

Students will carefully evaluate AI output for inaccuracies and hallucinations (AI Literacy in Teaching and Learning: A Durable Framework for Higher Education). Secondary mappings: ACRL Searching as Strategic Exploration, ACRL Authority is Constructed and Contextual.

Students will recognize, identify, describe, define and/or explain applications of AI in multiple domains (Southworth et al., 2023). Secondary mappings: GE Ethical Dimensions, ACRL Authority is Constructed and Contextual, ACRL Information Has Value.

Students will assess the context-specific value or quality of AI tools and applications (Southworth et al., 2023). Secondary mappings: ACRL Authority is Constructed and Contextual, ACRL Searching as Strategic Exploration.

Students will fact-check AI claims in order to verify accuracy (Lauren deLaubell, SUNY AI Fellows for the Public Good). Secondary mappings: ACRL Searching as Strategic Exploration, ACRL Authority is Constructed and Contextual.

Understand the key steps involved in arriving at GAI-generated information from tool development to output, including the data that goes into it, the process of making it, and how users interact with it to get to output (Yale Generative AI Literacy Framework). Secondary mappings: GE Ethical Dimensions, ACRL Information Creation as a Process, ACRL Research as Inquiry.

Articulate the strengths and limitations of a GAI application based on criteria like data quality, training method, model accuracy, relevance to the task, proprietary vs. open source models, and respect for copyright and intellectual property using the documentation and published materials about the tool (Yale Generative AI Literacy Framework). Secondary mappings: GE Ethical Dimensions, ACRL Authority is Constructed and Contextual, ACRL Information Has Value.

Value the role that humans play in contributing the data that trains GAI and prompting, evaluating, and iterating on GAI outputs to produce high-quality summaries, ideas, or other content (Yale Generative AI Literacy Framework). Secondary mappings: GE Ethical Dimensions, ACRL Authority is Constructed and Contextual, ACRL Information Creation as a Process.

Assess how well GAI-generated outputs meet their needs (Yale Generative AI Literacy Framework). Secondary mappings: ACRL Information Creation as a Process, ACRL Searching as Strategic Exploration.

Recognize when additional research is required to validate GAI outputs (Yale Generative AI Literacy Framework). Secondary mappings: GE Locate Effectively, ACRL Research as Inquiry, ACRL Searching as Strategic Exploration.

Acknowledge the instability of GAI authority (dependent on model, prompt, and output) (Yale Generative AI Literacy Framework). Secondary mappings: GE Ethical Dimensions, ACRL Authority is Constructed and Contextual, ACRL Information Creation as a Process.

Identify strategies to catch confabulation, including researching claims with other methods (Yale Generative AI Literacy Framework). Secondary mappings: GE Locate Effectively, ACRL Searching as Strategic Exploration, ACRL Scholarship as Conversation.

Evaluate the usefulness and potential applications of GAI tools and outputs in the context of subject-specific norms, practices, and content (Yale Generative AI Literacy Framework). Secondary mappings: GE Locate Effectively, ACRL Authority is Constructed and Contextual, ACRL Scholarship as Conversation.

Identify key sources of information on a given GAI tool that may reveal aspects of the training data or tool design that could introduce bias (Yale Generative AI Literacy Framework). Secondary mappings: GE Locate Effectively, ACRL Information Creation as a Process, ACRL Searching as Strategic Exploration.

Discuss the potential for biases and errors in GAI-generated content arising from factors such as training data, algorithmic bias, or confabulation (Yale Generative AI Literacy Framework). Secondary mappings: GE Ethical Dimensions, ACRL Information Creation as a Process, ACRL Authority is Constructed and Contextual.

Ethical Dimensions

Students will be able to critique the relationship between AI and copyrighted or personal data (Rich Kovarovic, Dutchess Community College). Secondary mappings: GE Evaluate Information, ACRL Information Has Value.

Students will critically examine the cultural, global, and environmental impacts of AI, considering its role in reinforcing cultural biases, its unequal distribution across countries, and its potential to either promote or hinder global equity. They will also evaluate the environmental footprint of AI systems, including the energy required for large-scale data centers and the ecological consequences of widespread AI tool deployment. Ethical questions about balancing technological advancement with environmental sustainability will also be explored (LibraryReady.AI PreK-12 AI Curriculum, 2024). Secondary mappings: ACRL Information Has Value, ACRL Scholarship as Conversation.

Students will be able to comment on the impact that AI can have on the environment (Hervieux and Wheatley, 2024). Secondary mappings: ACRL Information Has Value.

Students will be able to critique the bias that can be present in artificial intelligence and algorithms (Hervieux and Wheatley, 2024). Secondary mappings: ACRL Information Creation as a Process, ACRL Scholarship as Conversation.

Students will be able to recognize the paid and unpaid human labor involved in the creation and growth of AI (Rich Kovarovic, Dutchess Community College). Secondary mappings: ACRL Information Has Value, ACRL Information Creation as a Process.

Students will be able to apply responsible-use guidelines when using AI tools by protecting personal data, recognizing biased outputs, and citing AI contributions appropriately (Jocelyn Ireland, MVCC). Secondary mappings: ACRL Information Creation as a Process, ACRL Information Has Value.

Students will analyze the role of AI tools in the creation and spreading of information and misinformation online, including how AI systems rank content and the risks of false or biased information. They will explore how algorithms shape the news and content they see on social media (LibraryReady.AI PreK-12 AI Curriculum, 2024). Secondary mappings: GE Evaluate Information, ACRL Information Has Value, ACRL Information Creation as a Process.

Students will evaluate the impact of AI on their learning and research outcomes (AI Literacy in Teaching and Learning: A Durable Framework for Higher Education). Secondary mappings: GE Evaluate Information, ACRL Scholarship as Conversation, ACRL Research as Inquiry.

Students will understand and evaluate the ethical implications of using AI in academia (AI Literacy in Teaching and Learning: A Durable Framework for Higher Education). Secondary mappings: ACRL Information Has Value, ACRL Scholarship as Conversation.

Students will use AI responsibly, understanding data privacy, AI bias, and ethical implications (AI Literacy in Teaching and Learning: A Durable Framework for Higher Education). Secondary mappings: ACRL Information Has Value, ACRL Authority is Constructed and Contextual.

Students will develop personal ethical AI usage policies (AI Literacy in Teaching and Learning: A Durable Framework for Higher Education). Secondary mappings: ACRL Information Has Value, ACRL Scholarship as Conversation.

Students will remain vigilant in their use of AI tools, addressing ethical concerns proactively (AI Literacy in Teaching and Learning: A Durable Framework for Higher Education). Secondary mappings: ACRL Information Has Value, ACRL Authority is Constructed and Contextual.

Students will conceptualize and/or develop tools, hardware, data, and/or algorithms utilized in AI solutions (Southworth et al., 2023). Secondary mappings: GE Locate Effectively, ACRL Information Creation as a Process, ACRL Information Has Value.

Students will develop, apply, and/or evaluate contextually appropriate ethical frameworks to use across all aspects of AI (Southworth et al., 2023). Secondary mappings: ACRL Information Has Value, ACRL Authority is Constructed and Contextual.

Students will trace AI-generated information to its source in order to appropriately cite human knowledge (Lauren deLaubell, SUNY AI Fellows for the Public Good). Secondary mappings: ACRL Scholarship as Conversation, ACRL Authority is Constructed and Contextual.

Assess appropriateness of a GAI tool for their learning or research, such as not using GAI to generate writing for a course on learning to write (Yale Generative AI Literacy Framework). Secondary mappings: GE Evaluate Information, ACRL Information Has Value, ACRL Authority is Constructed and Contextual.

Determine when and how to use and cite GAI outputs (Yale Generative AI Literacy Framework). Secondary mappings: GE Evaluate Information, ACRL Information Has Value, ACRL Information Creation as a Process.

Recognize the social, economic, and environmental implications of GAI tools and their impacts on human labor and human experience (Yale Generative AI Literacy Framework). Secondary mappings: ACRL Information Has Value.

Value the human, environmental, and other resources necessary to power GAI tools, and make deliberate and informed choices about when and how to use AI-generated information (Yale Generative AI Literacy Framework). Secondary mappings: GE Evaluate Information, ACRL Information Has Value, ACRL Searching as Strategic Exploration.

References

State University of New York. (2026). SUNY General Education Framework (SUNY GE): Information literacy. SUNY System Administration. https://system.suny.edu/academic-affairs/academic-policies/general-education/suny-ge/

Association of College and Research Libraries. (2016). Framework for information literacy for higher education. American Library Association. https://www.ala.org/acrl/standards/ilframework