How to Incorporate Generative AI Although there is always space for exploration and experimentation, incorporation of GenAI into teaching and learning should be purposeful and in alignment with fundamental learning objectives and/or skills for job readiness. As with all course expectations, communication is key. In this section Where to start GenAI Directives in outlines and courses Incorporating AI into learning activities and assessment strategies Where to start The permitted or prohibited use of GenAI in instructional activities and assessments must be explicitly communicated to students. Where possible, it is recommended that course, program and/or Faculty teams discuss the use of GenAI with the goal of arriving at a consistent approach or directive across courses in order to reduce student confusion. Directives should be clearly articulated in the course outline, in the course shell in the LMS and discussed with students during the first class of the semester. Faculty should consider reiterating the directive as part of assessment instructions. Resource / Using GenAI in this course Consider using this slide deck as part of your introduction on your first day of class. Slides that require personalization are noted with a green sticky note. Please select only one of slides 11, 12 or 13 according to your course policy on using GenAI. Note If you are not already signed into your DC Microsoft Office 365 account, you will be prompted to login. Enter your DC email address and current network password. Follow the prompts to authenticate. Then click Download to save the PPT to your device. Using GenAI in This Course (PPT) DOWNLOAD PPT GenAI Directives in outlines and courses Including a statement in the course outline and in the DC Connect course shell establishes a concrete directive on the use of GenAI in the course. Sample directives include: Sample 1 The use of generative AI is not permitted in this course Using generative AI to aid in or fully complete your coursework will be considered a breach of academic integrity and Academic Policy ACAD-101 Academic Integrity will be applied. Sample 2 The use of generative AI is permitted in specific components of this course Review the course outline/assignment specifications closely to determine where you are permitted to use generative AI. It is your responsibility, as the student, to be clear on when, where, and how the use of generative AI is permitted. In all submissions in which you use generative AI, you must cite its usage. Failing to cite the use of generative AI is academic misconduct. In all other aspects of your work, the use of generative AI will be considered a breach of academic integrity and Academic Policy ACAD-101 Academic Integrity will be applied. If you are uncertain if you have used GenAI and/or cited appropriately, please speak with the library or your professor. Sample 3 The use of generative AI is permitted in this course In all submissions in which you use generative AI, you must cite its use. Failing to cite the use of Generative AI is considered a breach of academic integrity and Academic Policy ACAD-101 Academic Integrity will be applied. However, it is important to understand that all large language models are known to make up incorrect facts, fake citations and inaccurate outputs, and image-generation models can occasionally create offensive products. You are responsible for any inaccurate, biased, offensive, or otherwise unethical content you submit regardless of whether it originally comes from you or a Generative AI source. If you are uncertain if you have used GenAI and/or cited appropriately, please speak with the library or your professor. Examples of other faculty classroom policies around AI Classroom Policies for AI Generative Tools Incorporating AI into learning activities and assessment strategies GenAI presents opportunities to teach, challenge and assess students in different ways. Wilfred Laurier University has curated a list of ideas and opportunities for integration of GenAI into various learning activities and assessment strategies: Teaching Student engagement and Universal Design for Learning (UDL) in the classroom can be supported and improved, and learning enhanced through active learning using GenAI tools. Some examples may include: Concept Mapping A concept map is a visual representation of information and relationships. Concept maps can take the form of diagrams, flow charts, tables, and more. Supporting Integrity Because concept maps combine multiple modes of information through diagrams, drawings, and text, they are excellent ways for students to show their thinking process but are too multimodal for AI to complete well. Concept maps, diagrams, and notes can be included as assignment components. Multiplying the ways students are asked to represent their learning can diminish the usefulness of academically dishonest AI use as well as support more authentic assessment of learning. Concept maps can be assigned after an assignment has been completed as a means for students to represent the knowledge and understanding they realized through the assignment. Ask students to develop a concept map over time, adding to it or revising it at the end of each week or unit, or at midterm and end of term based on new course content students read, watched, listened to, or thought about. Students can also be given other students’ concept maps to add to or revise. These activities can be done individually, in pairs, or in groups. Incorporating Generative AI Ask generative AI to summarize a large concept or course topic in writing. Students can then be challenged to interrogate the output as they create concept maps that that are robust, relevant to the course, inclusive, and equitable by, for example: making decisions about what content to include and exclude, filling in gaps, making connections, adding citations, and addressing biases. Have students use a generative AI output such as an AI-generated Infinite Conversation to create a concept maps that shows connection and/or plots fundamental arguments, as well as reveals gaps, exposes biases, and shows superficiality. Students can then be tasked with making improvements to the original concept map through further research or by integrating their course-based learning. Content Summaries A content summary provides a synopsis and the most salient or pertinent components of a journal article, book, film, or other source material. Supporting Integrity Students can be asked to include specific types of connections in their content summaries, for example, connections between the source material and specific course content, one or more specific course materials, other courses they’ve taken, personal experiences, a pop-culture reference, a specific artifact (image, song, artifact), etc. Request that content summaries speak to the source material’s relevance to the course, a specific unit or theme of the course, a specific assignment or research question, etc. Students can be asked to comment on source materials’ credibility, currency, objectivity, etc. Incorporating Generative AI Have generative AI summarize the last course essay or another piece of course material. Ask students to point out the shortcomings and missed nuance of the AI output and then have them reflect on how nuance shapes their overall understanding of a topic. Have generative AI summarize several pieces of course or essay content and build a wider literature review. Consider prompts such as: What themes has the generative AI tool focused on? What themes has it ignored? What do its biases and gaps appear to be and why are those important for understanding the topic? Experiments An experiment is a procedure or other activity carried out to make a discovery, test a hypothesis, illustrate a known fact, or practice skills. Supporting Integrity Generative AI can’t be of assistance if its use is prohibited, especially during an experiment that is directly observed. Generative AI is of limited assistance during experiments that require physical manipulations or interpersonal interactions. Incorporating Generative AI Students can use generative AI to identify materials and/or steps necessary to carry out an experiment or to augment opportunities for success. Students can consult generative AI after a failed experiment to troubleshoot the ‘why’ of the failure. Infographics Infographics are visual representations of ideas, information, and data. Supporting Integrity Focus grading rubrics on how concepts are illustrated and connections between information rather than the artistic product, which can be assisted, or components designed, by generative AI. Incorporating Generative AI Have a generative AI tool output a base graphic for students to augment, correct, and build out based on set criteria. Explore having generative AI create images for infographics. PowerPoint’s “Slide Designer” is a generative AI tool that’s readily available for students to experiment with. It creates slide designs based on slide content. Timelines A timeline is a visual representation of a chronological sequence. Students can either create their own timelines or critique and edit sourced timelines. Supporting Integrity Ask students to include specific types of connections in their timelines to diminish meaningful assistance from generative AI. For example, ask students to draw connections with other course materials, specific course materials, other courses, personal experiences, a pop-culture reference, a specific artifact (image, song, artifact), etc. Incorporating Generative AI Use generative AI to produce a timeline or to identify the precipitators of a historical events (e.g. “Summarize the causes of the French Revolution”) and have students use this output to consider how narrative and perspective are subject to bias, how generative AI and the historical cannon privilege some stories while erasing others, etc. This example of an artist who harnesses AI to “simulate time travel” selfies is an example of how someone can tell AI how to construct elements of a scene that are inspired and informed by course content. If you are using GenAI in your courses, such as ChatGPT: Explain to students WHY you are using the tool - Think how you will introduce the tool. What knowledge & skills will they gain? Why is it important to them? What are their current and future benefits? Demonstrate understanding – Some students may be less comfortable with technology than others. You may have to provide more detailed and direct support to guide these students into using GenAI. Do not mandate that students use Generative AI - Provide alternative options for students or give them the option of submitting prompts to you or share your login credentials. Remember, using GenAI should be both relevant and meaningful for the student, not just for the faculty. Don’t depend on these tools working in a live class - Sometimes the servers are overloaded or the tech is just not working the way you need it to. If your entire class connects to ChatGPT at the same time, they may be blocked. Make sure to have a back-up plan. Learn how to write better prompts – see the section on How to Write a Prompt to Engage with Generative AI for guidance. Learning Students can use generative AI tools to enhance their learning experience and support parts of their ideation, research, and writing processes, while doing other parts themselves grounded in disciplinary and course-specific topics and methods. In connection with the suggestions below, faculty could require students to submit screenshots of the AI outputs and describe how they built on that. Ideation and brainstorming - generate initial ideas for research topics and questions that students then refine and build on themselves. For example, AI could help students move from broad ideas to more specific questions that they then refine and address according to disciplinary and course context. Initial research - use AI platforms to do basic research to obtain an overview of a topic, and to help them focus later work based on concepts and keywords they have learned. For example, they can use perplexity.ai or other AI tools for research and analysis by inputting research questions or topics and finding sources and key terms to explore. Improving grammar and other aspects of writing – students can input parts of their writing into ChatGPT or other tools to receive feedback on common grammatical errors and tone. ChatGPT can not only edit writing, but explain what it changed and why, which could be a useful way for students to learn. Adding creative elements to assignments - Students could use generative AI tools to add more creative elements to their work, such as using image generators like Stable Diffusion to create images that they add to slide presentations, games, apps, portfolios, blog posts, and more. There are also AI tools that can generate music or sound effects that could be used for student-created videos or games. Students could also use AI text generators to create draft scripts for videos that they can edit and refine to provide more details and information to better fit with the course context and learning objectives of assignments. Assessment Novel and authentic assessment strategies can ease concerns around academic integrity, particularly in a digital learning environment. GenAI can provide opportunities to support UDL by providing multiple means of representation and expression, and personalization during assessments. Consider these options: Assessed Active Learning & Participation Active learning is an approach to instruction that engages students with course content through discussions, debates, simulations, games, role playing, problem solving, one minute papers, etc. (explore 226 active learning techniques). In this way, responsibility for learning and metacognitive skill development is shifted toward the learner and away from the instructor. Active learning can take place in the classroom, online, and outside of the classroom and can be assessed as a part of participation grades or through submitted learning artifacts in engagement portfolios collected through MyLS DropBox throughout the term. Supporting Integrity When active learning takes place in synchronous in-person or online settings, the opportunities for generative AI to provide meaningful and timely assistance is diminished. Choose and create activities that permit active learning time to be technology-free time. When active learning takes place in any setting, have students engage in activities that encourage making deep connections, referencing student-generated content (e.g. discussion board posts, student presentation content, peer feedback, etc.) and incorporating course-specific content (e.g. lecture materials, guest lecture content, field trips, previous in-class activities, etc.) Require work associated with learning activities (e.g. discussion notes, debate outline, problem proofs/solutions, personal reflection on the activity, etc.) to be included in a portfolio diminishes the extent to which generative AI can be productively used. Focus active learning on very recent events, discoveries, publications, etc. Generative AI output is only as current as the dataset the tool was trained on thus limiting its ability to process questions related to current events. Incorporating Generative AI Students can compete to develop the most meaningful, complete, inclusive, or course relevant definitions of course concepts with half the class using generative AI and half of the class using other tools and resources Have generative AI produce a case study, scenario, problem, poem, image, song, etc. for students to analyze, comment on, interrogate, or solve. To add complexity, students can be asked to do this from a particular framework, point of view, era, etc. or using instructor-created prompts. Annotated Bibliographies A bibliography is an alphabetized list of sources, such as books, journal articles, websites, newspaper databases and other documents that are relevant to a course or project. An annotated bibliography provides a brief (approximately 150 word) summary and assessment of each source. Supporting Integrity While generative AI can produce relevant and well-written annotated bibliographies, these are unlikely to include very recent sources (sources published in the last 12-24 months) and its assessments of sources may not be course- or assignment-specific, speak to the relevance of the article to the student’s research topic, or address the reliability of the sources. Incorporating Generative AI Have students design a question and ask generative AI to produce an output (e.g. essay, article, op-ed, etc.) based on an annotated bibliography that the student created or that they asked generative AI to create. Next, have students take the output and review it for accuracy and completeness before correcting and adding both content and citations to improve upon the generative AI output. Consider adding an assignment component that asks students to reflect on what they learned during this process. Have AI generate an annotated bibliography for a topic that is course-adjacent and have students critique what’s generated using what they’ve learned in the course to date. Case Studies A case study is an in-depth, detailed, and multi-faceted presentation and/or examination of a particular event, scenario, person, group, or organization within a real-world context. Supporting Integrity While generative AI tools like ChatGPT can write and analyze cases in ways that are stylistically in-line with case writing style, its outputs lack depth and its ability to find novel solutions to complex problems is limited. Use case studies focused on very recent events (i.e. no more than 18 months old). Generative AI output is only as current as the data set it was trained on thus limiting its ability write and analyze very current cases. Have students analyze an imaginary case study. Incorporating fictional or fictitious characters, imaginary places, and fantastical events into a case study can frustrate the ability of generative AI to produce meaningful output. Incorporating Generative AI Have generative AI write a case study and have students correct it, expand upon it, consider it from gendered lenses or Indigenous perspectives make it more inclusive, add citations, add relevant academic references, or analyze it in one or more course-specific manners. For example, using ChatGPT, begin your query with “write a case study about” to get output in a more traditional case writing style (e.g. “write a case study about a small food service business trying to attract new customers with limited marketing budget”). After students write their own case studies, have generative AI solve them using different input instructions to help students see their cases from different perspectives. Have generative AI summarize sections of student-written case studies to help students see salient points more easily as they build their executive summaries. Close Reading with Questions Students read an instructor-selected text and respond to questions focused on specific content, skills, and learning outcomes. Supporting Integrity Create prompts that focus on making connections with personal experiences (e.g. How does this relate to something you learned or experienced in a previous week’s class? Outside of class? In another course? When you were younger?) and with student-generated content (e.g. How does this relate to a class discussion, discussion board post, student presentation, etc.?) Have student engage in social reading via whole class or small group book clubs or literature circles. Social reading gives students opportunities to design their own learning, gain confidence in discussions, analyze and critique their peers’ arguments, consider perspectives different from their own, and develop social skills and connections. Have students engage in social annotation. Social annotation requires learners to comment on assigned text with or without reading prompts, review and engage with the comments of others, connect the assigned text with prior knowledge, and position the assigned text within the context of personal experience. Incorporating Generative AI Have generative AI produce a summary of a chosen text and have students interrogate it for bias, relevancy to the course, authenticity, etc. Have students compare their answers to prompts with generative AI’s answers to the same prompts and then consider questions such as: What are the similarities and differences? How do you feel about generative AI’s answers? To what extent do self-authored answers versus generative AI’s answers impact your knowledge, understanding, skills, and progress toward learning outcomes? This can be used as a synchronous/in-class learning activity, as a graded or ungraded assessment, or as a learning artifact for inclusion in a portfolio. Collaborative Essays / Assignments Students work in pairs, groups, or teams to produce a specific end product such as an essay, report, case study, prototype, presentation, poster, etc. Supporting Integrity Require students to reference the sources used to produce the end product. Language model generative AI mines a huge sample of text taken from the internet and uses it to generate outputs. Requiring both academic and non-academic references from a combination of specified and students’ choice materials can discourage students from submitting AI-generated assignments. Require students to engage with feedback. Build an instructor, TA, or peer review process into assignments and require students to make revisions or otherwise respond to feedback in a staged submission process. Incorporating Generative AI Use generative AI as collaborator. Have students and their AI collaborator give each other feedback on their writing. This can help students reflect on how their writing style is unique, improve their ability to communicate what they want to say, identify biases in generative AI outputs, and find an authentic voice in their writing. Students can be asked to produce a reflection on the positive and negative impacts generative AI had on their ability to communicate effectively and authentically. Juxtapose generative AI and human collaboration. Have pairs of students, each student with their own research question, collaborate with a generative AI tool and each other to produce a final product. Students work together to coach a generative AI tool for assistance with each research question and also give feedback to each other at various points through the assignment process. Students can be asked to use track changes to show how their essay (or other final product) was improved along the way. After assignment submission, students can be asked to reflect on the process of working with the generative AI tool and their student partner with prompts such as: What worked well and what didn’t? How did your student partner help you produce a better final product? How did the generative AI tool help you produce a better final product? What were the benefits and drawback of your student partner versus your generative AI partner? Generative AI can be used to suggest effective wording or alternate phrasing for written assessments. Exams and Tests Exams and tests assess knowledge, proficiency, or skill in at a particular point in time. Supporting Integrity Write questions that include student-generated content (e.g. discussion board posts, student presentation content, peer feedback, etc.) or course-specific content (e.g. lecture materials, guest lecture content, field trips, experiments and other in-class activities, etc.). Create questions that focus on making connections with personal experiences (e.g. How does this relate to something you learned or experienced in a previous week’s class? Outside of class? In another course? When you were younger?) and with student-generated content (e.g. How does this relate to a class discussion? Discussion board posts? A student presentation? etc.) Build in metacognitive pieces that ask students to reflect on the process of learning, how they arrived at their answers, and what techniques they used to study and grow their knowledge. Ask students to include specific types of connections in their answers. For example, ask them to draw connections between specific course materials, personal experiences, a pop-culture reference, a specific artifact (image, song, artifact), etc. Require students to include student-generated and course-specific content in their responses. Require students to submit graphs, calculations, diagrams, etc. that must be produced by the student in order to arrive at an answer. Use very current topics, events, issues, publications, etc. in questions or require their reference in answers. Generative AI data sets typically lag by about 12-18 months. Consider incorporating low-stakes, multiple-attempt, and two-stage testing into your teaching practice. De-centering grades can decrease the temptation to cheat, encourage self-evaluating knowledge, understanding and skills, and identify learning gaps. Have students write some exams and tests in person. Incorporating Generative AI If the test or exam is “open book” require students to cite the resources they use, including generative AI. Find more strategies for take home open book” exams later in this resource. Experiments An experiment is a procedure or other activity carried out to make a discovery, test a hypothesis, illustrate a known fact, or practice skills. Supporting Integrity Generative AI can’t be of assistance if its use is prohibited, especially during an experiment that is directly observed. Generative AI is of limited assistance during experiments that require physical manipulations or interpersonal interactions. Incorporating Generative AI Students can use generative AI to identify materials and/or steps necessary to carry out an experiment or to augment opportunities for success. Students can consult generative AI after a failed experiment to troubleshoot the ‘why’ of the failure. Fact Sheets and Policy Briefs Fact Sheets ask students to identify and communicate relevant information or evidence to illuminate or frame a particular issue, problem, need, event, or subject. Policy Briefs typically include the additional step of making a recommendation or a rank-ordered set of recommendations to a policymaker. Supporting Integrity Ask students to produce fact sheets or policy briefs on very current topics. Generative AI data sets typically lag by about 12-18 months. Incorporating Generative AI Generative AI is good at summarizing and can be employed to identify salient information to include in a fact sheet or policy brief. Students can be asked to be fact-check and verify information gleaned from generative AI. When working on a policy brief, students can “compete” with generative AI to produce the most persuasive and compelling recommendation. Individual Research Essays A structured written response to a complex or probing research question(s). Supporting Integrity Focus on the process of writing rather than the final written output and have students submit research questions, drafts, outlines, and references along with the finished essay. These can be submitted for review as set points during the course of the project or collected with the final essay submission. Ask students to include specific types of connections in their essays. For example, ask them to draw connections with other course materials, specific course materials, other courses, personal experiences, a pop-culture reference, a specific artifact (image, song, artifact), etc. Scaffold essay components, have students respond to peer and instructor feedback at each stage or at specific points in the project, and add a reflective component that asks students to reflect on how feedback contributed to producing a better final product. Incorporating Generative AI If use of generative AI is permitted, require students to both cite it in the body of the essay and include all of its raw outputs based on their queries as appendices. Generative AI can be used to suggest effective wording or alternate phrasing as a means of improving the effective communication of ideas and information As above, scaffold essay components but incorporate generative AI tools and feedback alongside instructor and peer feedback. Students can map the development of their essay through drafts and write a concluding reflection on the roles of both generative AI and peer or instructor feedback in their essay development process. Literature Reviews A literature review is a comprehensive summary of scholarly work on a particular topic, concept, or theory. Supporting Integrity Ask students to include an assessment of relevancy (e.g. to course topics, course themes, student discussion board posts, etc.) for each source in their literature. While generative AI can write summaries and broad overviews of common topics, it’s not able to assess relevance. Have students assess the authority, reliability, and currency of each source, something generative AI is not well suited to do. Ask students to include specific types of connections in their literature reviews. For example, ask students to draw connections with course topics, specific course materials, personal experiences, a reference, etc. Incorporating Generative AI Ask generative AI to produce a literature review on a particular topic, concept or theory. Have students assess the literature review for bias, currency, omissions, etc. and then revise it. As an extension of the above, have students work on the same topic, concept and theory in pairs or groups and then have them compare the results of their generative AI literature reviews, assessments, and improvements. Ask students to reflect on which group’s final product was the best and why. Observational Assessment In an observational assessment evaluative information about knowledge, skill, and ability is obtained through direct observation by an evaluator (e.g. instructor, TA, lab assistant, peer, or self.) Supporting Integrity Generative AI cannot provide assistance if its use isn’t permitted during the assessment. Students can be asked to submit a personal reflection on their preparation for the assessment, what helped or hindered their performance during the assessment, what they would do differently if they could repeat the assessment, and what steps they can take to improve their performance going forward. Incorporating Generative AI Students can use generative AI as a preparatory tool to advance knowledge and hone skill before they engage in an observational assessment. For example, they can ask generative AI to summarize the steps necessary to complete a particular task or to identify common task errors as a means of studying. Open Book "Take Home" Exams or Tests In an open book “take home” exam or test students have permission to access course materials and other aids while completing the assessment. Questions require students to apply, analyze, and evaluate course materials in creating their responses. Supporting Integrity Write questions that include student-generated content (e.g. discussion board posts, student presentation content, peer feedback, etc.) or course-specific content (e.g. lecture materials, guest lecture content, field trips, previous in-class activities, etc.). Require students to include student-generated and course-specific content in their responses. Incorporating Generative AI Have students use generative AI to create a topic outline or bulleted skeleton of an answer and then improve upon it with course-based learning. If use of generative AI is permitted, have students cite generative AI contributions, submit the queries they made to generative AI along with the raw outputs that resulted, and provide a reflection on their use of generative AI. Peer Evaluations During peer evaluations students review, assess, and provide feedback on other students’ work. Supporting Integrity Have students write a reflection on the peer feedback received using prompts such as: What do I agree with? What do I disagree with? What will I do (or have I done) to address the feedback? How will (or did) the feedback I received make my next draft (or final product) better? Have students submit a “response to peer feedback” statement with next or final submission explaining how they addressed the feedback they received or why they chose to reject it. Incorporating Generative AI Require students to use generative AI as a peer, offer feedback on its research and writing, and suggest avenues for further exploration that reveal richer connections and application of information. Have students design a question and have generative AI write an article based on that question. Next, have students engage in a scholarly review of the article generated including comments, corrections, suggestions for improvement, etc. Portfolios A portfolio is a collection of artifacts of learning (e.g. reflections, annotations, discussion board posts, assignments, test answers, etc.) Students engage in a variety of learning activities throughout the term and then compile a portfolio to show evidence of their learning journey. Supporting Integrity Requiring a wide variety of learning activities to be included in a portfolio diminishes the extent to which generative AI can be productively used. Asking students to reflect on their portfolio content and their growth throughout the course helps enrich these collected artifacts of learning while at the same time being an assessment that generative AI cannot complete. Students can be asked to annotate earlier work in their portfolio and draw connections between assessments, course themes, and skills in a concept mapping style as additional means of limiting the productive assistance of generative AI. Incorporating Generative AI Generative AI can be a collaborator or contributor to individual portfolio items and its contributions can be cited. Generative AI can give feedback on portfolio items like written work and provide comments, feedback, and next steps that students can pursue in their research. Students can integrate or ignore the feedback, provide rationale for these decisions, and reflect on other ways to advance their knowledge, understanding, skills, etc. Poster Presentations A poster presentation is a visual representation of student research, typically demonstrating knowledge of theory, literature review, methods, and findings. Supporting Integrity While generative AI can produce poster elements, layout ideas, executive summaries and graphics for poster presentations, the multimodal nature of poster presentations requires students to make and reveal deep connections and organize their thinking. Incorporating Generative AI Generative AI is useful for summarizing key points, drafting executive summaries, and prioritizing information for inclusion on posters. Generative AI can help design graphics and suggest layouts for posters, assisting with the organizational flow of the end produce. For example: Image generators can produce images that can help illustrate concepts or provide visual excitement in a poster; PowerPoint’s Slide Designer feature uses generative AI to suggest layouts based on content. Using it as an idea generator can help students see their information presented in different ways instantly. Presentations Students explain a concept, process, idea, project, experiment, etc. to others orally or audio-visually. Presentations can be delivered live (in person or virtually) or recorded. Supporting Integrity Presentations are excellent ways to augment other written assignments to extend learning and using multiple means to assess student learning holistically. Incorporating Generative AI Generative AI is especially useful for summarizing key points, which can be included on slides. Generative AI can help design graphics and slides for presentations. Image generators can produce images that can help illustrate concepts or provide visual excitement in a presentation. PowerPoint’s Slide Designer feature uses generative AI to suggest layouts for each slide based on its content. Prototyping Students develop a product, proposal, experiment, experience, app, etc. Supporting Integrity While generative AI could be used to assist with various aspects of a prototype project, its ability to be creative is limited. The multifaceted nature of prototyping and testing leads to scaffolded assessments with clear draft and revision stages. Documenting the process by which prototypes were created is inherent in prototyping, and assembling those documents emphasizes the process of creation and revision rather than the final product. Incorporating Generative AI Generative AI, like ChatGPT, can debug and write code as well as natural language text. Generative AI can become a debugging tool used to help diagnose problems with prototypes and code. Generative AI, like ChatGPT, can be used to summarize papers and other text to help identify what is most salient in the writing. This can help improve written communication and guide where to place emphasis in grant proposals, pitches, etc. Reflection Papers Reflection papers ask students to consider what they have learned in the context of their lived experiences, use what they have learned to inform future action, or consider the real-life implications of their thinking. Supporting Integrity Generative AI can’t connect to meaning, personal experience, or feeling. Reflection and connection with personal experiences is a key way to not only reduce the impact of generative AI tools on academic integrity, but also for students to make meaning from their learning. Incorporating Generative AI Ask generative AI “if-then” questions and have students offer personal reflections on the output or interrogate the output for biases, gaps, and other shortcomings. Scaffolded Assessment A scaffolded assessment is a larger project, case, problem, or assignment broken up into smaller, progressive learning activities (“chunks”) that build toward a final summative assessment. Supporting Integrity Generative AI doesn’t incorporate reflections, make meaningful connections, draw complex conclusions, or handle iterative feedback well. Having students build a scaffolded assessment through brainstorming, outlining, researching, iterative research or literature summaries, and responding to feedback can minimize unauthorized use of generative AI. While generative AI can potentially be used to produce pieces of a scaffolded assignment (such as draft summaries of research sources), it cannot create the varied and iterative steps that lead to a final scaffolded product. Incorporating Generative AI Students can be permitted to use generative AI to produce pieces of a scaffolded assignment (e.g. summaries of research sources, a procedural outline, a timeline, etc.) or as an approved source for basic information about a topic, event, person, procure, etc. Remember to require students to cite generative AI. Generative AI can be used to suggest effective wording or alternate phrasing for written work. Generative AI can be used to check drafts for gaps, problems, and other deficiencies. Three-Minute-Thesis-Style Presentations The Three Minute Thesis (3MT) is a popular competition among research-based graduate students that can also be used as an assessment tool for all students. In a 3MT students are allowed one slide and three minutes to present course content, a specific topic, research, or a project to a general audience. Supporting Integrity Presentations are excellent demonstrations of learning, and the act of summarizing and choosing what to highlight stimulates deep learning. While generative AI can summarize information and provide broad insights into what themes emerge from theses and research papers, they lack the personality and creativity to produce dynamic presentations. Students can be asked to include specific types of connections in their Three-Minute Thesis presentations. For example, connections with other course materials, specific course materials, other courses, personal experiences, a pop-culture reference, a specific artifact (image, song, artifact), etc. Incorporating Generative AI Ask students to paste sections or the entirety of their thesis into a generative AI language model like ChatGPT with the precursor “Summarize:” or “Summarize this:” and have them reflect on the results. Have students regenerate their responses repeatedly to see how the nuance of the output changes and gain new perspectives about what stands out or might be veiled. Have students write a reflection or make a presentation to the class that discusses their findings. Generative AI can help design graphics and slides for presentations. For example, Image generators can produce images to help illustrate concepts or provide visual excitement in a presentation, and PowerPoint’s Slide Designer tool uses generative AI to suggest layouts for each slide based on the slide’s content. Other Strategies Consider making formative assessments collaborative by including peer-to-peer assessment using tools such as Kritik. Consider using video-based assessments with EdTech tools such as Flip, DC Connect Video Note, or Kritik Video Assessment. Require citation, and request if students do use AI, to acknowledge the prompts they used to generate content. See content on Citation and Acknowledgement. Important The course directive on the use of GenAI in assessments should be included in the instructions for the assessment, alongside the academic integrity statement/attestation, and reiterated when the assessment is distributed. References Generative AI in Teaching and Learning | Wilfrid Laurier University (wlu.ca) This work is licensed under CC BY 4.0. Designing assessments (ubc.ca). This work is licensed under CC BY 4.0. Adapting Your Teaching to AI Generated Tools by D. Holton and I. Frank, University of West Florida. This work is licensed under CC BY 4.0. Eaton, S., & Anselmo, L. (2023, January 12). Teaching and Learning with Artificial Intelligence Apps. Taylor Institute for Teaching and Learning, University of Calgary. Laupichler, M. C., Aster, A., Schirch, J., & Raupach, T. (2022). Artificial intelligence literacy in higher and adult education: A scoping literature review. Computers and Education: Artificial Intelligence, 3, 100101. https://doi.org/10.1016/j.caeai.2022.100101 This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.