1 Generative AI in Education: A Call for Curriculum Development by Cari Morrow A thesis submitted in partial fulfillment of the requirements for the degree of MASTER OF EDUCATION with an emphasis in CURRICULUM AND INSTRUCTION WEBER STATE UNIVERSITY Ogden, Utah March 31, 2026 Approved Katarina Anderson, Ph.D. Jessie Nixon, Ph.D. Gisela Martiz Wheeler, Ph.D. 2 Table of Contents Generative AI in Education: A Call for Curriculum Development .........................................5 Literature Review ..........................................................................................................................7 Phases of AI Learning ..............................................................................................................7 Effects of Exposure and Education on AI ................................................................................8 Concerns Regarding Student AI Use ........................................................................................9 Plagiarism ............................................................................................................................9 Creative Thinking, Critical Thinking, and Effort ..............................................................10 Data Information, Student Privacy, and Equal Access ......................................................10 Data Privacy .......................................................................................................................11 Teacher Concerns ............................................................................................................... 11 Solutions .................................................................................................................................12 Teaching Ethical Usage and Developing Guidelines .........................................................12 Teaching Data Literacy, AI Literacy, and Critical Thinking Skills ...................................12 Teacher Training ................................................................................................................13 Methods.........................................................................................................................................13 Design Considerations ............................................................................................................13 Design Procedure....................................................................................................................15 Step 1: Current Utah State Curriculum requirements ........................................................17 Step 2: Existing Classes .....................................................................................................19 Steps 3-6: Design ...............................................................................................................22 Step 7: Usability Testing ....................................................................................................27 Results ...........................................................................................................................................28 Discussion .....................................................................................................................................30 Redesign Considerations....................................................................................................31 References .....................................................................................................................................38 Appendix .......................................................................................................................................44 3 Abstract Since its emergence in 2022, generative AI has been both a challenge and a new opportunity in the world of K-12 Education. AI has the potential to help students who have historically been hard to differentiate for, or aide with one-on-one instruction, while at the same time, there are concerns about academic integrity, data privacy, and over reliance. Students have already adopted the technology and are using it despite lacking knowledge of how or permission to use the resource for academic work. Teachers feel a lack of knowledge about how to help or prevent student use. The purpose of this thesis was to develop a generative AI curriculum outline for high school students to address both opportunities and concerns regarding generative AI in a scholastic setting. Using backward design, the curriculum outline was developed to focus on key areas like effective prompting, data privacy, and digital literacy. Currently available state and national frameworks, including the U.S. Department of Labor AI Literacy Framework and the Utah Artificial Intelligence Framework were used to guide the curriculum outline design. An input survey was sent to educators, AI professionals, and policymakers to gather input from the three guiding groups. The results indicated strong support for teaching generative AI skills to high school students with an emphasis on ethics, privacy protection, and critical thinking skills. This thesis adds to the growing body of research on AI in an educational setting by providing a useable curriculum outline that aligns with both educational standards and workforce needs. 4 Acknowledgements I couldn’t have finished this project without the support of a few very important people in my life. First, to my husband, Jordan; thank you for your patience through all of this. Your intricate knowledge of AI, ideas, and the resources you shared with me made a huge and I’m so grateful for how willing you were to help every step of the way. To my kids, thank you for your patience and understanding while I worked on this. I know this process took time away from you, and I appreciate your support more than you probably realize. And to Dr. Anderson, thank you for your guidance, feedback, and encouragement throughout this entire process. Your direction helped shape this project into something I’m truly proud of. I’m so thankful for all of you. 5 Generative AI in Education: A Call for Curriculum Development Humans all have differing approaches to effort and gratification (APA Dictionary of Psychology, n.d.). Some people prefer quick rewards, like a piece of candy, even if it means accepting less of the reward (one piece of candy now vs. two pieces of candy, if the person waits until later). Other people rush through tasks, like finishing an exam quickly, at the expense of accuracy. Some people love the intrinsic reward of hard work and sacrifice to ensure something is done well and completely (Shenhav & Greene, 2017). Friedman and Abramson (2013) suggest that to set students up for success, educators should create a path of least resistance. This could involve optimizing classroom layout or providing tools to streamline tasks. For many students today, the path of least resistance is the use of generative AI tools like ChatGPT (http://chatgpt.com). While there is no doubt students will use these tools to minimize effort and increase gratification, educators currently lack a unified strategy on how to address the use of generative AI by students (Manszka, 2024). Some school districts in Seattle and New York, for example, have even gone as far as banning ChatGPT on their computers and internet servers due to concerns about cheating and plagiarism (Huang, 2023; Manszka, 2024). However, banning generative AI may not be the right solution. Instead, there is a need to develop a curriculum that teaches students how to use generative AI ethically (Fist, 2023; Halaweh, 2023; Huang, 2023, Wetzel & Kani, 2025), assess outputs using digital literacy skills (Chang et al., 2020), and incorporate it as a valuable tool, akin to a graphing calculator (Halaweh, 2023). One of the biggest concerns teachers have relates to academic integrity when students use generative AI tools like ChatGPT (Manszka, 2024). Fisk (2023) highlights concerns, such as students generating responses without researching or writing on their own, potentially undermining critical thinking and learning skills. Teachers worry students may misuse ChatGPT 6 to produce assignments without understanding or citing the source, thus violating academic integrity (Halaweh, 2023). Additionally, teachers question the quality of AI-generated content and whether students can distinguish between accurate and erroneous information (Fisk, 2023). In a study focusing on U.S. high schools conducted by Manszka (2024), it was noted that teachers feel ill-prepared to integrate generative AI into their classrooms, as most have not received formal training and have instead relied on self-teaching. This same study also discovered that English teachers were the most likely to oppose the use of AI due to concerns about the need to alter curriculum, for example, making assignments handwritten or putting essays through AI software to ensure the essays were written by the student and not by AI. Despite lack of formal training, teachers have been encouraged to use AI to make their workload easier (Halaweh, 2023). Some studies suggest that teachers and professionals alike do use generative AI daily (Fisk, 2023). As exemplified by teachers themselves and their own use of AI as professional tool, students will need generative AI skills upon graduation and teachers should prepare students to use AI in a productive and ethical way before they leave our schools (Fisk, 2023; Wetzel & Kani, 2025). The next goal of K-12 education, therefore, is to prepare students for the world after graduation, whether that be college or a career (NEG, 2025). Wetzel and Kani (2025) argue that teaching students the appropriate use of generative AI leads to students having positive thoughts, and more importantly, behaviors towards generative AI. Authors of a different study emphasize the need for organizations to allocate resources for AI implementation, training, and maintenance as part of their strategies (Joosten et al., 2024). The need to teach students how to properly prompt generative AI to get the most accurate and appropriate results is another skill students need to be taught in order to effectively use AI as a tool (Fisk, 2023). Teachers may even benefit from student use of AI, as they may have an easier 7 time evaluating creativity and critical thinking if all students use ChatGPT, since original ideas will be the only unique aspects of students’ work (Halaweh, 2023). It is also clear that schools must take steps to address teacher concerns about plagiarism and cheating while also preparing students to use generative AI tools effectively and ethically. Developing a curriculum that teaches students about various AI tools, how to prompt AI appropriately and effectively, how to use digital literacy skills to evaluate AI outputs for incorrect information, often called hallucinations, and how to cite AI appropriately, are all critical for the successful use of generative AI in both a classroom and professional setting. As these skills are taught and then implemented by students, teacher concerns regarding the use of generative AI should also be alleviated (Westzel & Kani, 2025). Creating a curriculum that trains students how to use generative AI is the most robust way for educators to alleviate their own concerns while also preparing their students with skills required after graduation. To that end, in this study, I developed a unit curriculum to be implemented in 9-12 classrooms. The unit includes teaching students how to prompt AI correctly, how to use digital literacy skills to assess outputs and look for hallucinations, how to protect their privacy, and how to determine what is and is not an ethical way to use generative AI. Literature Review Phases of AI Learning While not much direct research has been done on K-12 students and their experiences with generative AI, we can extrapolate what student experiences might look like by looking at the several studies focused on teacher and higher education students’ engagement with the tool. Zhai (2024), for example, shows the evolution of teacher exposure to generative AI. They found that use of and attitudes toward AI were directly influenced by exposure and training on 8 generative AI. At the beginning of a user’s journey into the world of generative AI, users tended to show interest, but apprehension as they learned how generative AI worked and the issues that occurred when using AI. Users at this stage often discovered generative AI through social media or a conversation with a peer, sparking curiosity about its potential applications in both their personal and professional lives. Next, they moved into stage two where their attitudes shifted to a more optimistic view, and they transformed from passive learners to more active learners. The same study reported that users then progressed into the third phase of learning where they began to explore AI in more detail, using it to help in more ways than before and see it as more than an object or tool, but as a partner. Michel-Villarreal et al. (2023) encourages the thought process of generative AI being a partner more than a tool to be able to use it to the best of its ability. Users in the third stage usually received their learning and instruction through professional development or online tutorials and honed the skills they had learned regarding generative AI (Zhai, 2024). Users finished their generative AI learning journey in the fourth stage where they began to brainstorm ways to innovate using generative AI. During this final stage, users begin to mentor other users and really push the technology to its limits. The four stages of AI learning should be considered when teaching AI skills to K-12 student learners and we should take care not to push students too fast or skip any of the phases of learning. Effects of Exposure and Education on AI Research of higher education students seems to follow a similar pattern to Zhai’s four stages. Escalante et al. (2023) explored student perception and the effectiveness of using ChatGPT to give essay feedback vs. human feedback. The study showed that the longer the exposure to ChatGPT, the more students interacted with it and liked the feedback. As time went on, and students continued their exposure and learning of generative AI, the more their 9 preference for generative AI increased. A similar study of elementary pre-service teachers was done using AI to make reading comprehension questions for children (Yang & Appleget, 2024). Results mirrored the students in the essay feedback study: the more the exposure the pre-service teachers had to generative AI, the more likely they were to want to use it in the future and feel acceptance toward generative AI to help them with their future careers. More research was done with pre-service teachers using the Technology Acceptance Model (TAM) that showed positive perceived enjoyment was tied to ease of use, which was tied to positively affecting behavior toward generative AI (Zhang et al., 2023). Extrapolating this to K-12 students would suggest that they need exposure to, and instruction on generative AI rather than to ban its use completely. Concerns Regarding Student AI Use Many of the studies focused on teacher and higher education students also highlighted some concerns related to student use of generative AI in academic settings. Some of the concerns included those related to academic integrity such as cheating, and plagiarism (Escalante et al., 2023; Fisk, 2023; Halewah, 2023; Michel-Villarreal et al., 2023, Manszaka, 2024; Yang & Appleget, 2024). Others related to ethical and privacy concerns (Batta, 2024; Halaweh, 2023; Michel-Villarreal et al., 2023; Zhang et al., 2023), equitable access amongst all schools and students (Batta, 2024; Michel-Villarreal, 2023; Morgan, 2023), loss of critical thinking, creativity, and effort from students (Fisk, 2023; Halaweh, 2023; Joosten et al. 2024; Leitner, 2023; Yang & Applegat, 2023), misinformation or AI hallucinations (Chang et al., 2020; Fisk, 2023; Gillani et al., 2023; Wetzel & Kani, 2025), and lack training for teachers (Manszka, 2024; McGehee, 2024; Michel-Villarreal et al., 2023; Zhang et al., 2023). Plagiarism 10 With regards to plagiarism, Manszka (2024) specifically mentioned English teacher concerns with copy and paste behavior from generative AI, while Escalante et al. (2024) discussed how it is possible for AI outputs to evade AI detection software. Warnings concerning the loss of active learning, specifically regarding students relying too heavily on generative AI for answers rather than diving into research and exploration of a topic (Fisk, 2023; Yang & Appleget, 2024), along with concerns on how to accurately cite AI when it is used as a research source (Michel-Villareal et al., 2023) were all mentioned as issues related to academic integrity and cheating. Creative Thinking, Critical Thinking, and Effort Closely tied to academic integrity is lack of student creative thinking, critical thinking, and effort. Fisk (2023) mentioned concerns relating to student reliance on AI to do the work for them, skipping some of the essential tasks related to critically thinking through a topic. Building on these concerns, Leitner et al. (2023) noted that students may face challenges in transferring AI outputs to real-world scenarios. AI hallucinations may also pose a problem when students skip the critical thinking process or use copy and paste behaviors. Hallucinations are incorrect outputs given by AI and studies suggest that teaching students the critical thinking skills of digital and AI literacy can help students identify hallucinations and take steps to correct the misinformation (Chang, 2020; Fisk, 2023; Gillani et al., 2023; Wetzel & Kani, 2025). Both critical and creative thinking are also imperative to the learning process which is why concerns persist about the loss of these skills tied to AI use. Students who use AI may no longer fully immerse themselves in learning, leaving a gap between content and application (Joosten et al., 2024). Data Information, Student Privacy, and Equal Access 11 Data information, student data privacy, and equal access to generative AI are three other concerns found in the research. Michel-Villarreal et al. (2023) warned that if adoption is uneven among states, districts, and schools, some students may be left behind, increasing digital divides (i.e. those that have access to and training on both technological hardware and software) (North Carolina Department of Information Technology, n.d.). Other learning divides that may be affected by uneven AI use include students with language barriers or learning disabilities. These students can be aided immensely with AI use and curated lessons geared toward their specific needs (Escalante et al., 2023). Social divides may be affected as well because AI skills are becoming a job requirement in many industries. If some students graduate with these skills while others don’t, we may inadvertently reinforce divides between the haves and have nots (Morgan, 2023). Data Privacy While social, learning, and digital divides may increase, so will data privacy issues. Students who were granted access to AI in the classroom will need to take steps to reduce the risks that relate to the collection, storage, and use of their personal data by AI systems (MichelVillarreal et al., 2023). Teacher Concerns Finally, teachers' concerns about their own training and education in AI were noted in several studies. Teachers reported a lack of support and a lack of formal training on AI (Manszka, 2024; McGhee, 2024) and an apprehension toward AI (Zhang et al., 2023). As we explored earlier, the more teachers were exposed and taught how to use AI, the more likely they were to accept it for academic use (Zhai, 2024). In addition to exposure, teacher training and policy guidance will help with adoption (Michel-Villarreal et al., 2023). 12 Solutions So, what does the research suggest be done to quell these concerns? Studies suggest that the answer is to teach kids how to appropriately use AI rather than banning AI use (Fisk, 2023). The curriculum should focus on ethical usage (Fisk, 2023; Wetzel & Kani, 2025), proper citation (Wetzel & Kani, 2025), critical evaluation of AI outputs (Chang et al., 2020; Fisk, 2023; Halaweh, 2023; Wetzel & Kani, 2025), as well as prompt creation (Wetzel & Kani, 2025). Teaching Ethical Usage and Developing Guidelines Teaching ethical usage should be paired with clear ethical guidelines and policies on the state, district, and school levels. All students and teachers should know what is and is not allowed for AI usage (Batta, 2024; Halaweh, 2023; Michel-Villarreal et al., 2023; Zhang et al., 2023). Guidelines should address plagiarism, data privacy (Halaweh, 2023), informed consent (Michel-Villarreal et al., 2023), guidance to shape both student and teacher behavior toward AI (Zhang et al., 2023), and fairness amongst all students in access and education regarding AI (Batta, 2024). Teachers’ focus should switch to how students use AI (Fisk, 2023), perhaps as an idea generator akin to traditional writing prompts (Joosten et al., 2024) and then looking for originality amongst student submissions (Fisk, 2023). Creating guidelines at state levels can ensure equal access as well by allocating funds fairly, so all districts can invest in the tools, equipment, and software needed to make AI available to all students regardless of the economic status (Batta, 2024; Michel-Villarreal et al., 2023; Morgan, 2023). Teaching Data Literacy, AI Literacy, and Critical Thinking Skills Students should be taught critical evaluation skills through instruction on data and AI literacy (Fisk, 2023; Gillani et al., 2023; Halaweh, 2023; Joosten et al., 2024; Leitner et al., 2023; Li et al., 2025; Witte et al., 2025; Yang & Appleget, 2024). Teaching students how to read, work 13 with, and understand data (i.e. data literacy skills) enables students to question outputs, analyze responses, and draw proper conclusions (Witte et al., 2025). Teaching these critical thinking skills and helping students apply them through practice can help students connect the concepts being taught in class, and researched through AI, to real world scenarios (Joosten et al. 2024). Leitner et al (2023) specifically noted that teaching specific AI skills was also necessary to help students connect abstract ideas like search trees, which are a visual and logical ways to see how AI finds possible solutions, to real world applications. Li et al. (2025) address some solutions to plagiarism concerns by suggesting that students should be taught skills like verifying sources, identifying bias, and checking for erroneous or inaccurate information, which are all different forms of critical thinking and evaluation. Teacher Training Finally, none of this will be possible if teachers do not also receive AI training (Manszka, 2024; McGehee, 2024; Michel-Villarreal et al., 2023; Touretzky et al., 2019; Zhang et al., 2023). For teachers to change their mindset toward student use of AI, studies show they too need exposure and education regarding AI (Touretzky et al., 2019; Zhang et al., 2023). McGehee (2024) suggests allocating time and giving structured training to teachers to help them become more accepting of AI use. Teaching teachers how to use AI to benefit themselves by curating lesson plans to certain students or freeing up time by making a visual presentation, will help teachers, especially those with anxiety toward AI, become more accepting (Zhang et al., 2023). In addition, teaching teachers the skills that will be taught to students will ease fears of improper use, create cohesiveness and acceptance amongst staff regarding the new AI policies, and help them to teach the skills to students across disciplines (English, 2016; Touretzky et al. 2019). Methods 14 Design Considerations The plan for the curriculum outline is to serve as a guide for teachers rather than as lesson plans for them to follow. The goal of this outline is to give teachers a roadmap to follow so that one topic can flow easily into the next. Concepts build on and tie to each other, helping teachers easily connect one concept to the next. Because technology changes so quickly, creating an outline, rather than lesson plans, helps the curriculum remain useful and adaptable over time. The curriculum outline focuses on the following areas: introducing several generative AI platforms, teaching how to effectively prompt AI, and explaining how to protect student privacy when using generative AI. Next, the outline also includes a section on AI ethics, which includes appropriate and inappropriate uses of generative AI in a scholastic setting, plagiarism, and how to appropriately cite AI as a source. Finally, I included digital literacy skills - specifically those skills that help students identify incorrect information. These topics are recommended across several studies: the need for AI literacy (Mintz et al., 2023; Morgan, 2024; Touretzky et al., 2019), prompting skills (Fisk, 2023; Halaweh, 2023; Joosten et al., 2024), data privacy and awareness (Halaweh, 2023; Michel-Villarreal et al., 2023; Mintz et al., 2023), and explicit instruction in AI ethics (Escalante & Pack, 2023; Halaweh, 2023; Manszka, 2024; MichelVillarreal et al., 2023). These skills were also chosen as they help alleviate the most common concerns educators have as students use AI (Halaweh, 2023; McGehee, 2024; Michel-Villarreal et al., 2023; Yang & Appleget 2024; Zhang et al., 2023). Design Procedure To determine if any of the curriculum outline topics are already being taught in Utah schools, the first thing I did when developing this curriculum outline was to look through current 15 Utah State Curriculum requirements and see where these skills are already incorporated into other courses (Step 1). Next, I studied existing AI curricula (Step 2), particularly curricula that is specific to high school students. I looked at how current curricula is organized (e.g., the flow of the curriculum) and decided if anything could be modified or added. Doing this helped me decide if the outline I created should just supplement existing courses and curricula or if a standalone curriculum outline was needed. I then determined the best and most logical order to teach the skills (Step 3). Figure 1 shows some possibilities for content organization and order that I originally had in mind. 16 Figure 1 Generative AI Curriculum Flow Possibilities 17 To help determine the organization of the curriculum outline, I used the curriculum building technique of backward design (“Backward Design”, n.d.). I began by identifying the performance skills students should have by the end of the curriculum outline (Step 4) and worked backward to ensure the correct skills were being taught to achieve that goal (Step 5). Finally, I drafted a curriculum outline (Step 6) and had several teachers and AI professionals review the outline and complete a Google survey to give feedback (Step 7). I took any suggestions and feedback they gave me and incorporated feedback given in the Google survey (see Appendix A) to achieve a final curriculum outline (Step 8). The curriculum followed the pattern UEN uses for a curriculum outline (see Figure 2 for an example) and I made it available via a publicly viewable Canva website (https://ai-curriculum-resources.my.canva.site/ ). The following section outlines the procedure in detail. Figure 2 College and Career Awareness Utah Strands and Standards Step 1. Current Utah State Curriculum requirements 18 I started the design process by looking through the current Utah State curriculum strands and standards. To narrow down which classes I needed to look through, I found the list of courses for the Business Management and Entrepreneurship Pathway and the Digital Technology Pathways (Utah State Board of Education [USBE], n.d.). Business Management and Entrepreneurship only had one pathway within it (USBE, 2025b) while Digital Technology had four pathways (USBE, 2025c-e). After looking through the pathways, I made a master list of classes and eliminated any crossover classes. For instance, all five pathways have CCA, or College and Career Awareness, so I ensured it was only on my list once. Next, I read through the strands and standards for each class and found fifteen courses that had at least one strand or standard that correlated with the standards identified in Figure 1. Those courses were: Database Development, Cloud Computing 1, Cyber Forensics, Exploring Computer Science, Data Analytics, Computer Programming 1, Computer Science Investigations, Business Finance and Marketing Capstone, Web Development 1, Digital Business Applications, Exploring Business Finance and Marketing, Business Communications 1, Business Communications 2, Digital Literacy, and CCA (see Table 1 for a list of USBE courses listed by strands and standards) Table 1 USBE Course Strands and Standards with AI Alignment Course Strand and Standard Strand and Standard Data Base Development Cloud Computer 1 Cyber Forensics Strand 1 Standard 1 Strand 3 Standard 2 Strand 1 Standard 3 Strand 5 Standard 1 Strand and Standard Strand and Standard Strand and Standard 19 Exploring Computer Science Data Analytics Computer Programming 1 Computer Science Investigations Business Finance and Marking Capstone Web Development 1 Business Law Digital Business Applications Exploring Business Finance and Marketing Business Communication 2 Business Communication 1 CCA Strand 2 Standard 5 Strand 2 Standard 1 Strand 5 Standard 2 Strand 6 Standard 2 Strand 5 Standard 1 Strand 5 Standard 2 Strand 5 Standard 1 Strand 5 Standard 2 Strand 5 Standard 3 Strand 1 Standard 1 Strand 1 Standard 1 Strand 2 Standard 1 Strand 1 Standard 2 Strand 4 Standard 2 Strand 2 Standard 3 Strand 1 Standard 3 Strand 5 Standard 3 Strand 6 Standard 1 Strand 4 Standard 3 Strand 4 Standard 4 Strand 2 Standard 3 Strand 4 Standard 1 Strand 4 Standard 2 Strand 1 Standard 2 Strand 4 Standard 2 Strand 2 Standard 4 Digital Literacy Strand 2 Standard 2 Strand 4 Standard 1 Strand 4 Standard 2 Step 2: Existing Classes I identified two AI classes currently offered to teachers and students in Utah. One was offered to all teachers on the USBE Canvas page. The other is an experimental course being taught to students at Bountiful High School in the Davis School District. 20 I completed the USBE Canvas course geared to teachers entitled “AI for K-12 Utah Education (Virtual)” (USBE, 2025a) which had three modules. Module 1 included lessons entitled “Learn: Basics of AI” and “Explore: AI Curiosity”. This module asked teachers to identify why we should teach and incorporate AI, what AI does and how it works, and how to prompt AI. Module 2 was geared towards how AI can help teachers in the classroom, with a large focus on prompting, and Module 3, had teachers develop a lesson plan to teach an AI skill. The course provided a link to the “Artificial Intelligence Framework for Utah P-12 Education: Guidance on the Use of AI in Our Schools” (USBE, 2024). Within this document was a student learning section that included the following student guidelines: 1. Aiding Creativity 2. Collaboration 3. Communication 4. Content Creation and Enhancement 5. Tutoring It also included a list of guiding principles which were: 1. We use AI to help all of our students achieve their educational goals 2. We reaffirm adherence to existing policies and regulations 3. We educate our staff and students about AI 4. We explore the opportunities of AI and address the risks 5. We use AI to advance academic integrity 6. We maintain student and teacher agency when using AI tools 7. We commit to auditing, monitoring, and evaluating schools’ use of AI 21 After seeing a Utah AI framework, I decided to see if there was a national one and came across one published by the U.S. Department of Labor (U.S. Department of Labor, Employment and Training Administration, 2026). This framework included the following topics: 1. Understand AI Principles 2. Explore AI Uses 3. Direct AI Effectively 4. Evaluate AI Outputs 5. Use AI Responsibly The framework also included ways to effectively deliver those topics to students: 1. Enable Experiential Learning 2. Embed Learning in Context 3. Build Complementary Human Skills 4. Address Prerequisites to AI Literacy 5. Create Pathways for Continued Learning 6. Prepare Enabling Roles 7. Design for Agility Lastly, I communicated with a teacher who is experimenting with an AI class at Bountiful High School in the Davis School District. He said he is working with a company called Skills Struck, who was hired by the Governor of Utah, to help develop an AI curriculum for the state. He is also working with a teacher at the Davis Catalyst Center. The two of them thought of a three-level approach to AI literacy: 1. A basic class like digital literacy where they cover the basics of AI literacy, like ethics and privacy, but keep everything simple. 22 2. An AI applications class where students “use AI to solve real world problems”. The teacher said his “dream [was] to have kids compare/contrast models, master prompt engineering, context engineering, build custom GPTs, using Claude's project mode, learn Notebook LM, manage a complex task by using an AI workflow using multiple models focusing on their strengths, maybe even a little vibe coding. Basically, building AI workflows and tools to solve problems” (R. Frandsen, personal communication, November 19, 2025). 3. The third level is AI Design, where students will start training their own AI model. Define this concept. What is “AI model”? Steps 3 -6: Design After reviewing the current curriculum and the Utah Artificial Intelligence Framework (USBE, 2024) and the U.S. Department of Labor AI Literacy Framework (U.S. Department of Labor, Employment and Training Administration, 2026), I determined no existing course could be modified to include a whole AI Literacy curriculum. Therefore, I decided to develop a new AI curriculum outline. To determine the most logical order to teach the curricula, I used the technique of backward design (Backward design, n.d.) to decide the performance skills students should be able to accomplish at the end of the curriculum outline. Using the state and national AI frameworks as a guide, and ChatGPT as a thinking partner, the following eight performance skills were identified: 1. AI Comparison: Students will use two or more generative AI platforms to perform the same academic task (i.e. research a historical event). Students should be able to make note of the differences in quality, structure, and accuracy. 23 a. Topics Covered: Introduction of various generative AI platforms and digital literacy skills. b. Utah AI Framework Alignment: Aiding creativity, content creating and enhancement, exploring opportunities of AI, and educating students about AI. c. U.S. AI Framework Alignment: Understand AI principles, explore AI uses, and evaluate AI outputs. 2. Privacy Checklist: Students will create a checklist of information that is and is not safe to input into AI and maintain personal privacy. a. Topics Covered: Protecting student privacy when using generative AI. b. Utah AI Framework Alignment: Adherence to existing policies and regulations, maintain agency when using AI tools, educate students about AI, and explore the opportunities of AI and address the risks. c. U.S. AI Framework Alignment: Use AI responsibly. 3. Prompt Engineering: Students will start with a weak prompt and improve it through three or more revisions. Students should be able to explain how the prompt has changed and how the prompt became better. a. Topics covered: Effective prompting. b. Utah AI Framework Alignment: Aiding creativity, content creation and enhancement, communication, and using AI to help all our students achieve their educational goals. c. U.S. AI Framework Alignment: Direct AI effectively and understand AI principles. 24 4. AI Accuracy: Students will use AI to answer a research question. They will then be able to fact check three or more of the facts using other credible sources. Students should identify any hallucinations or inaccurate facts they encounter. a. Topics Covered: Digital literacy skills. b. Utah AI Framework Alignment: Tutoring, communication, exploring the opportunities of AI and addressing the risks, and educate staff and students about AI. c. U.S. AI Framework Alignment: Evaluate AI outputs, understand AI principles, and use AI responsibly. 5. Bias and Misinformation Detection: Students will prompt AI on a controversial or complex topic. Students should be able to identify bias, tone changes, and missing perspectives by rewriting the output for neutrality and accuracy. a. Topics Covered: Digital literacy skills and hallucinations. b. Utah AI Framework Alignment: Communication, content creation and enhancement, aiding creativity, exploring the opportunities of AI and addressing the risks, and maintaining student and teacher agency when using AI tools. c. U.S. AI Framework Alignment: Evaluate AI outputs and understand AI principles. 6. AI Ethics Case Study: Students will analyze several scenarios involving the use of AI in an academic setting. Students will be able to identify ethical and unethical academic uses of AI. a. Topics Covered: AI ethics within education. b. Utah AI Framework Alignment: Use AI to advance academic integrity, reaffirm adherence to existing policies and regulations, maintain student and teacher 25 agency when using AI tools, and explore the opportunities of AI and address the risks. c. U.S. AI Framework Alignment: Use AI responsibly. 7. AI Citation: Students will use AI to assist with an assignment and properly cite AI in APA or MLA formats. Students should submit an AI drafted copy and a final copy with their own edits and ideas included. a. Topics Covered: AI ethics, plagiarism, and proper citation. b. Utah AI Framework Alignment: Use AI to advance academic integrity, communication, content creation and enhancement, and adherence to existing policies and regulations. c. U.S. AI Framework Alignment: Use AI responsibly and direct AI effectively. 8. AI Guide: Students will create a student guide to AI that explains privacy, ethics, prompting, and data verification. This can be an infographic, video, or other presentation. a. Topics Covered: Effective prompting, protecting student privacy, ethics, and digital literacy skills. b. Utah AI Framework Alignment: Communication, aiding creativity, educating students about AI, exploring the opportunities of AI, addressing the risks, and using AI to help all students achieve their educational goals. c. U.S. AI Framework Alignment: Explore AI uses, evaluate AI outputs, and use AI responsibly. After determining the performance skills students should be able to do at the end of each strand, I examined the AI courses I came across during research, such as “AI for K-12 Utah Education (Virtual)” (USBE, 2025a). This class introduced AI models first, which is a logical 26 first step. For this reason, I decided to start the curriculum outline by understanding what the different AI models are, their strengths and weakness, and which platform is best for which tasks. The U.S. Department of Labor’s AI model (U.S. Department of Labor, Employment and Training Administration, 2026), under instruction suggestions, says teachers should address essentials to AI Literacy, such as teaching students how to protect their privacy. Protecting privacy is critical to teach before allowing students to use AI consistently. Students need to know exactly what should and should not be entered into AI to protect their data and privacy. Therefore, I decided that privacy protection will be added as the second module in the AI curriculum outline. Again, referring to the USBE AI course, prompting was taught early on and this is a logical next step for my AI curriculum outline, as students will need prompting skills throughout the rest of the class. As a reminder, digital literacy is a graduation requirement in Utah, and most 8th grade students have already taken this digital literacy. The digital literacy course covers many of the digital literacy skills identified as necessary for students to use AI so, after prompting, I came to the conclusion that students should be given a refresher unit on the digital literacy skills they already know. This would include skills like how to look for accurate outputs, bias, and misinformation. Lastly, I decided to add a module on AI ethics and proper citation, as well as a module on acceptable scholastic use. As performance skill 8 combines almost all the content, performance skill 8 will serve as a capstone project at the end of the curriculum outline. Figure 3 shows the final AI curriculum outline prototype developed at the end of this process. Figure 3 27 Curriculum Outline Prototype Step 7: Usability Testing After developing the outline, I sent a feedback survey to 18 AI professionals across the United States to gather perspectives from AI professionals outside education. For educator feedback, I sent the survey to ten educators interested in developing an AI curriculum within the Davis School District in Utah. I also sent this survey to the 21 legislators with current bills regarding education or AI. Feedback from these three groups, industry experts, educators, and policy makers, helped to develop a relevant and practical curriculum outline from many different aspects. Results 28 After conducting usability testing (Krug, 2014), a total of 12 participants completed the survey: five AI professionals, six educators, and one person who identified as an educator but is also a policy maker. Most participants (N=9) identified as being very familiar with Generative AI tools, while three responded they were somewhat familiar. All participants agreed that high school students should learn about Generative AI. Almost all survey participants (N=11) think that it is extremely important for students to understand how Generative AI works before using it. One participant only thought understanding AI before using it was very important as opposed to extremely important (see Table 2 for more demographic data). Table 2 Survey results Participant Identifying Role Participant 1 Educator Participant 2 Participant 6 AI Professional AI Professional AI Professional AI Professional Educator Participant 7 Educator Participant 8 Educator Participant 9 Educator Participant 10 Participant 11 Educator Participant 3 Participant 4 Participant 5 Educator Familiarity with Generative AI Somewhat Familiar Very Familiar Very Familiar Very Familiar Very Familiar Very Familiar Very Familiar Somewhat Familiar Very Familiar Somewhat Familiar Very Familiar Should High School Students Learn AI? Yes Should Students Use AI in School? Yes Importance of Understanding AI Before Use (1-5) 5 Yes Yes 5 Yes Yes 5 Yes Yes 5 Yes Yes 5 Yes Yes 5 Yes Yes 5 Yes Not Sure 5 Yes Yes 4 Yes Yes 5 Yes Yes 5 29 Participant 12 AI Professional Very Familiar Yes Yes 5 After completing the demographic survey portion, survey participants were then asked to rate the importance of several curriculum topics to be included in a high school AI curriculum. Across all the topics, the majority of responses were rated as very important or extremely important. Topics receiving the most extremely important votes included: • Protecting personal data and privacy • Avoiding plagiarism and citing AI use • Evaluating AI-generated content for accuracy (digital literacy) • Ethical implications of AI in school and society All results can be seen in Figure 4. Figure 4 Topics ordered by importance survey results Respondents were then asked to order the curriculum in the order they think it should be taught. Responses varied. However, several sections were often listed earlier in the sequence than others. These topics included digital literacy and introduction to AI platforms. Effective prompting was commonly listed later in the curriculum sequence (see Figure 5) 30 Figure 5 Order of curriculum survey results The survey concluded with open ended questions asking survey participants to suggest additional topics, list concerns, and create performance skills. Respondents listed topics like career considerations related to AI, AI agents and automation, and societal implications of AI. Concerns listed included potential overreliance on AI, the need for teacher training, and district or policy restrictions on AI tools. Respondents suggested writing effective AI prompts, evaluating AI generated content, building or testing AI assistants, and comparing work completed with and without AI assistance and possible performance tasks. Discussion The purpose of this project was to create a curriculum to give our students AI skills and to ensure that AI is used responsibly within education. The participants for the survey were chosen to get perspectives from industry professional - those who will be hiring our future students, teachers – those that are currently teaching our future workforce, and policy makers – those who can decide what we are allowed to teach. The results of the survey support the creation of a curriculum and reinforce the topics chosen from literature and research, such as 31 critical thinking, plagiarism, citation, and digital literacy skills. (Fisk, 2023; Gillani et al., 2023; Halaweh, 2023; Manszka, 2024; Wetzel & Kani, 2025). All survey participants, regardless of their background, believed high school students should learn generative AI skills. Almost all of them believed that they should be able to use it in the classroom and that students need to understand how AI works before they are given freedom to use it as a tool, which is not surprising considering that many of them already had experience with AI. Halaweh (2023) agrees with using AI in the classroom and argues that generative AI should be allowed in academia with strong policies and training around AI. Fisk (2023) would add that AI should be a tool for learning akin to word processing. We have classes to teach these skills, so we must also have a class to teach AI skills. Survey participants felt strongly that skills like privacy, appropriate use, plagiarism and critical thinking of AI outputs should be taught to students. This is supported by research regarding academic integrity, AI hallucinations, and responsible use of AI (Fisk, 2023; Halaweh, 2023; Manszka, 2024; Michel-Villarreal et al., 2023). Research shows that these issues may be resolved by teaching students the skills of citing AI, critically evaluating its outputs, and understanding how to use generative AI (Gillani et al., 2023; Wetzel & Kani, 2025). Redesign Considerations The curriculum outline was developed to give our students the AI skills employers are looking for (Batta, 2024; Fisk, 2023), while simultaneously reducing the concerns teachers have regarding student use and integrity (Halaweh, 2023; Manszka, 2024. To do this, we must start with the basics of introducing students to commonly used AI platforms, including ChatGPT, Claude, Gemini, and Copilot, which can help students familiarize themselves with AI before 32 using it in a school setting (Mintz et al., 2023; Touretzky et al., 2019) (see Figures 6 and 7 for the refined AI curriculum outline). Figure 6 Final Curriculum Outline 33 Figure 7 Final Curriculum Outline with strand, standard, and performance task alignment 34 While the final curriculum starts with introduction to various AI platforms, survey respondents felt strongly that digital literacy skills be taught early on. Such organization will allow students to critically analyze output as they explore the various platforms. Evaluating output for hallucinations and misinformation, which are part of this module, are topics reinforced by researchers such as Gillani et al. (2023) and Joosten et al. (2024) as an important skill for students to learn. In many schools, including the district whose resources were used in this design, digital literacy is a required course for eighth grade students. Because students already take a class on evaluating information, it is my recommendation that the AI literacy curriculum based on the AI curriculum outline that I developed should be taught after digital literacy, either in a subsequent semester, during their eighth-grade year, or as a stand-alone course in ninth grade. Offering this curriculum outline after the digital literacy class will allow students to apply their previous knowledge of digital literacy while being taught the AI literacy curriculum outlined in this paper. Next, I decided that effective prompting should be covered. Research promotes the need for this skill to get the most out of generative AI responses (Li et al., 2025; Wetzel & Kani, 2025). Teaching students how to effectively prompt AI will help them interact with the tool more effectively and get the most effective results. While survey respondents placed effective prompting later in the curriculum, the research supports prompt literacy as an essential skill needed to effectively interact with and use AI. For this reason, I decided that effective prompting will stay as an early learning objective in the curriculum, contrary to the feedback I received. A section on plagiarism, citation, and ethics is included next to ease concerns from teachers about the academic integrity of their students when using generative AI. Teacher concerns were often noted in the literature (e.g., Escalante et al., 2023; Fisk, 2023; Manszka, 35 2024) and teaching students how to properly cite AI should help to reduce these concerns about plagiarism and outright cheating. It should be noted that during the research process, environmental concerns regarding AI were not note. However, in the process of developing the curriculum outline, this concern has become public commonplace. Introducing these concerns and possible ways to use AI in an environmentally positive way could be added to the curriculum when discussing ethics. Lastly, the curriculum outline includes a section on the scholastic use of AI to help students differentiate what is and is not an appropriate way to use AI in their learning process. A broader use of AI may be acceptable once the student enters the workforce. However, in school, students are still learning the skills needed for critical evaluation of AI outputs. Research supports the idea that generative AI aids learning through idea generation, feedback, and personalized tutoring (Batta, 2024; Escalante & Pack, 2023; Michel-Villarreal et al., 2023). Research also shows the need for clearly defined guidelines so that AI doesn’t undermine current forms of learning (Fist, 2023; Halaweh, 2023; Manszka, 2024). Teaching students how to use AI as a learning tool will help them gain pivotal AI skills needed in the workforce as well as supplement their learning. Overall, the results of the survey supported the topics included in the curriculum outline and verified that there is a need for an AI curriculum within K-12 education. Both educators and AI professionals support teaching generative AI skills in high school, even though their perspectives differed on why we need to teach the skills. Educators focused on concerns regarding academic integrity and how to effectively implement AI in the classroom. AI professionals focused on AI being an important industry skill and needing to prepare students to enter the workforce. 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