Category: Instructional Design

Planning with Purpose: Designing Certificate Programs That Align with Market and Mission
Higher education is seeing a surge of interest in non-degree credentials. Learners are seeking faster, more affordable pathways to workforce advancement. Employers are increasingly open to (and in some cases requesting) alternatives to traditional degrees. And with new federal policy expanding Pell Grant eligibility to non-degree programs, institutions are feeling the urgency to act.

But not all certificate programs are created equal. And while the trend line is clear, the strategy behind how institutions respond is anything but. This moment presents an opportunity, but only for those willing to plan with purpose and set realistic expectations.

What’s driving demand for short-term credentials?

Recent data underscores a clear increase in interest:
- Undergraduate certificate enrollment grew 33% and graduate certificate enrollment grew 21% from Fall 2020 to Fall 2024, according to National Student Clearinghouse data.
- Google search volume for certificates has increased 19% from 2020 to 2025, according to Google Trends data.
Today’s learners are drawn to programs that offer accelerated timelines, reduced costs, and clear pathways to meaningful career outcomes. Many working adults are looking to upskill or pivot careers, and a certificate can be a more practical option than a full degree.

On the employer side, organizations want proof of skills and are increasingly willing to collaborate with institutions on curriculum design. In fact, according to a 2022 employer survey from Collegis and UPCEA, 68% of respondents said they would be interested in teaming up with an institution to develop non-degree credentials to benefit their workforce.

Certificates are a piece of the puzzle — not the whole strategy

Despite the interest, many institutions struggle to meet enrollment goals for certificate programs. Strong market trends do not automatically translate into high enrollment volume. The reality is that most certificates serve niche audiences and deliver modest numbers. When treated as stand-alone growth drivers, they often fall short.

The institutions that see the most strategic value from certificates do so by positioning them within a larger enrollment and academic ecosystem. For example, we’ve helped our partner institutions find success in using certificate interest as a marketing funnel to drive engagement in related master’s programs. Once a prospective student engages, enrollment teams can advise them on the best fit for their career goals, which, for some students, is enrolling in the full degree program.

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What a strategic certificate model looks like

A certificate program with purpose isn’t just a set of courses — it’s a product with clear value to both learners and the institution. Key elements of a strategic approach include:
1. Workforce alignment: Programs must be rooted in real-time labor market data. What skills are employers seeking? Which certifications are valued? Aligning with reputable industry certifications is a proven way to ensure relevance and employer recognition.
2. Accessibility: Pricing should reflect the certificate’s value relative to degree programs, and eligibility for financial aid must be prioritized. Lack of aid is a significant barrier to enrollment for many prospective learners.
3. Laddering and stackability: Certificates should not be terminal unless intentionally designed that way. They should stack into larger degree pathways or offer alumni incentives for continuing their education.
4. Delivery speed and flexibility: Busy adult learners expect quick starts, clear outcomes, and minimal red tape. Institutions need streamlined onboarding and agile curriculum design.
5. Internal collaboration: Designing certificates in isolation often leads to friction. Academic, enrollment, and marketing teams must be aligned on purpose, target audience, and outcomes.
6. Employer engagement: Employers want to be part of the development process and seek assurance that certificate programs teach the skills they need. Their involvement enhances the recognition and credibility of the credential.
The role of institutions: Balance mission with market

Certificate programs are not a shortcut to growth. But they can be a smart strategic lever when grounded in data and designed to complement an institution’s broader mission. They offer colleges and universities an opportunity to:
- Expand access to underserved learners
- Respond more nimbly to labor market shifts
- Strengthen ties with regional employers
- Drive awareness and enrollment for degree programs
The key is alignment. When certificate offerings reflect both market demand and institutional mission, they can play a powerful role in expanding reach and impact.

Plan with purpose, execute with intent

Certificates are more than just a trending credential. They’re a tool to serve learners in new ways. But institutions must resist the urge to chase quick wins. Success requires thoughtful design, realistic expectations, and cross-functional collaboration.

With the right foundation, certificate programs can do more than fill a gap. They can open doors for learners, employers, and institutions alike. Collegis supports this effort with integrated services in market research, instructional design, and portfolio development — empowering institutions to make informed, mission-aligned decisions that deliver impact.

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Higher ed is evolving — don’t get left behind. Explore how Collegis can help your institution thrive.
Amber Arnseth oversees program and market research as a skilled problem-solver with an ability to integrate and contextualize data for partners into actionable recommendations. The research she and her team conduct help inform and strengthen our partners’ strategic portfolio and program decisions.

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October 22, 2025
Centering Accessibility and UDL in Faculty Development

I’m excited to share my latest publication on the open-access platform, EdTechBooks! I co-wrote a chapter with my former colleagues at the University of California, Berkeley’s Center for Teaching and Learning. It’s titled Centering Accessibility and UDL in Faculty Development of Online Instructors. It appears in the book, Advancing Accessibility: Practical Strategies for Instructional Designers & Educators. See chapter 8 for our contribution. It was such a joy to collaborate with my former colleagues on this.

Abstract

This chapter examines the conceptualization and design of an online professional development initiative at the University of California, Berkeley, aimed at equipping faculty with strategies for creating accessible and inclusive online courses. The online instructor training emphasizes integrating accessibility and Universal Design for Learning (UDL) principles into every aspect of course creation. Rather than treating accessibility as an afterthought, the training embeds these principles into the modules on course design fundamentals, content organization, assessments, instructional delivery, and community building.

The initiative employs an asynchronous training site to guide instructors through key elements of online course design, including backward mapping, establishing module-level objectives, implementing active learning techniques, and incorporating formative and summative assessments. Each module highlights specific accessibility practices. We also address reducing technical barriers and enhancing flexibility by providing multiple means of representation, expression, and engagement. By encouraging adaptable learning paths and accessible materials, the training ensured that faculty understand how pedagogical design intersects with technological access to support diverse learners. Key themes included inclusive planning, essential accessibility features for online environments, adaptable content design, and reduced access friction.

We conclude by emphasizing the importance of intentionality in creating accessible courses that empower more students to succeed. An online course accessibility and inclusion checklist for college instructors is provided. Recent campus accessibility initiatives are also discussed, including the Finding Spaces podcast and a Pop-up Proctoring Pilot Project. The chapter’s intended audience includes instructors, faculty developers, instructional designers, and other academic support staff.

Reference

Rogers, S., Allen, T., Bradley, A. M., Cohn, J. D., Gomas, C. A., & Kearns, J. J. (2025). Centering Accessibility and UDL in Faculty Development of Online Instructors. In R. M. Reese & A. Lomellini (eds), Advancing Accessibility: Practical Strategies for Instructional Designers and Educators. https://doi.org/10.59668/2204.23923

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October 18, 2025
My new consulting company! | Teacherrogers
On July 1, 2025, I founded Futurescape Instructional Design, LLC. This was the day after I lost my job. I had wanted to create a consulting company after retirement, but the job loss jump-started this venture! This is my third company, so I’m not a novice. I collaborated with generative AI (GenAI) to come up with a name that reflected both my instructional design background and futures thinking training. I also relied on GenAI to help me write the outline for my business plan. I was thrilled with the outcome. This blog describes my new company.

Executive Summary

Futurescape Instructional Design, LLC, founded by Dr. Sandra Rogers, is dedicated to transforming teaching and learning to meet tomorrow’s needs. We offer comprehensive instructional design services and foresight-building workshops, informed by futures thinking strategies, for academic institutions, education nonprofits, educational technology corporations, and individual educators. Our dual-focus approach enables individuals and organizations to deliver high-quality learning experiences today while also anticipating and shaping the future of education.

Mission Statement

Our company’s mission is to support educators and institutions in their efforts to enhance teaching and learning practices and environments in the short term, ultimately improving students’ long-term learning outcomes through research-based instructional design and future-focused thinking.

Goals
1. By improving their course designs, course material, and built-in learner support (e.g., orientation modules, learning strategy guides, help page), our instructional design services will positively impact our clients’ teaching methods and learning environments.
2. By training them on futures thinking strategies and practices, our clients will become meta-aware of signals and drivers of possible futures. They will learn how to analyze, manipulate, prioritize, and act on them to prepare for digital transformations and related changes now and on the horizon.
Instructional Design Overview

Our instructional design services draw upon 30 years of educational experience, advanced academic credentials, and research-based best practices. We serve K-16 institutions, education nonprofits, education technology companies, and individual educators to help them build accessible, effective, inclusive, and engaging learning experiences. The service includes a client intake survey, a memorandum of understanding, timelines, a feedback process, and accessibility compliance guidelines.

Services Offered

The following services address the myriad of instructional design work. They can be provided singly or in combination. The client must complete an intake survey and provide sample content and syllabus before the initial meeting. For on-site work, the client will cover travel expenses and per diem.
- Prep Time – The designer’s review of content, context, and stakeholders’ needs takes place in advance of the initial meeting. It relies on information and material provided during the initial point of contact and via the Client Intake Survey.
- Course Design Consultations – One-on-one or whole group consultation for instructional design and related aspects to build high-quality, research-based courses. Guidance, per client request, could include structuring content, optimizing instructional strategies, integrating technology, creating a community of inquiry, designing for equity and inclusion, and aligning objectives with desired outcomes.
- Course Design and Development – First, the designers will consult with the client to understand desired outcomes for the course design. Course material will be collected; the syllabus will be used as a plan of action. Second, backwards mapping of course outcomes to assessments, content (including media plans), and strategies will be a collaborative process. Prototyping of a course module will be shared for feedback and approval before the actual course design begins. Course design generally takes six months because it involves work from both the instructor and the designer. Fast-track builds can be created in three months if the instructor has the time.
- Course Redesigns – Revitalize existing courses to improve access, engagement, equity, inclusion, learning outcomes, and relevance. The designer will meet with the client to understand project parameters and provide recommendations before starting the project. Course redesigns can include items listed separately in services offered (e.g., quality review, course remediation, or custom course document creation). Course redesigns can be accomplished in 1-3 months, depending on how much time the instructor has available.
- Quality Assurance Reviews – Clients will provide or otherwise select a rubric for quality assurance (QA) reviews. The review consists of a comprehensive course evaluation for instructional alignment, usability, inclusion, effectiveness, and compliance with accessibility standards. A QA review also checks to see if links are broken and whether the link title matches the linked content. Feedback is shared via a QA checklist. Items approved for revision or replacement are discussed.
- Content and Course Remediation for WCAG 2.1 AA Compliance – Ensure courses are accessible to learners and compliant by remediating course pages and materials to meet Web Content Accessibility Guidelines (WCAG) 2.1 AA standards per ADA Title II regulations. The new regulations require courses to be 100% accessible by April 2026. The designer can remediate content and share standards to avoid facing similar issues with new material or course designs. Content remediation is a lengthy process. For example, one PDF can take 10 minutes if it doesn’t include a lot of images. However, a PowerPoint with numerous images can take an hour.
- Job Aids – This service provides custom creations of course documents (e.g., guides, rubrics, syllabi) and/or ancillary videos (e.g., virtual tours, tutorials, explainers). Creating material requires a consultation with the client before production. Media production is a lengthy process. For example, a 3-minute video could take an hour to produce the final version. Clients will be invited to share feedback on document and video creation for guidance and approval.
To learn more, especially about the futures thinking workshops, visit my new company website. I’m happy to share that I have my first client and a few prospective ones. Reach out if you’re interested!
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September 9, 2025
Building a Course from Scratch: When Time is Not on Your Side – Faculty Focus

I recently found myself in a the all-too-familiar situation where I was handed a course at the last minute. The course consisted of a catalog description and course outcomes with no teaching materials. There was very little time to develop a student-ready course while also trying to manage my workload and protect my mental well-being. What steps can you take if you find yourself in a similar scenario? Focus on the non-negotiables: accessibility, effectiveness, and alignment with key learning outcomes by applying core principles of course design, including Universal Design for Learning, backward design, and Bloom’s Taxonomy.

When facing rapid course creation, begin by setting your mindset regarding the expectations for developing a last-minute course. Even without the bells and whistles typically found in a fully designed course, a basic course can be accessible, inclusive, and high-quality. The goal is to create a student-ready course with appropriate content and assessments that align with the course learning outcomes and description. Aim for completion over perfection, prioritizing the non-negotiables.

Establish Your Course Framework and Weekly Structure

Most existing courses already have an approved catalog course description, a set number of credits, and established course outcomes. Based on this information, the first step is to identify any essential content and the timeframe, based on the number of weeks the course runs and the credit hours. Doing so will help ensure alignment with the expected student and faculty workload. Once this is established, you can begin the course design by building the course framework. The core of the framework is the syllabus. The syllabus should include your contact information, grading policies, course schedule, and course expectations. Then use the schedule to organize the required content into weekly modules.

Stick to simple technology tools and avoid adding extras that could take time away from the non-negotiables. This includes curriculum creep. Focus only on the essential content that aligns with the course learning objectives. To save time, use a consistent structure for each weekly module, such as an overview or introduction, required reading and/or media, one active learning task, plus a low or medium-stakes formative assessment. Create a clear rubric for repeat assignments like discussions, reflection, or writing assignments. This will allow you to apply the same criteria across each module and reduce the time of making numerous rubrics.

Apply Instructional Design Frameworks for Accessible, Inclusive Learning

The next step in the process of course design is to apply proven instructional design frameworks such as backward design, Universal Design for Learning, and Bloom’s Taxonomy. Utilizing backward design principles can help the instructor deliver a course with a clear vision of what students are expected to learn and achieve from each lesson, module, and the course overall (Stapleton-Corcoran, 2023). Universal Design for Learning is a “framework to improve and optimize teaching and learning for all people” (Casebolt & Humphrey, 2023, p. 2). This includes accessibility features such as headers, alt text, and captions. Keep presentation slides simple by using a white background, dark font, and avoiding unnecessary images. Not only will this make the slides more accessible, but it will also reduce the time required to create them. Throughout the course remain flexible, allow students multiple ways to express their learning, including multimedia options, and provide various means of engagement and representation (CAST, n.d.). As a time-saving option, if weekly videos are not feasible, add weekly micro-lecture audio recordings throughout the course. These do not need to be added at the start of the course but can be introduced week by week.

When developing the assessments, consider using Bloom’s Taxonomy. Bloom’s Taxonomy framework consists of six major categories of cognitive processes: remember, understand, apply, analyze, evaluate, and create. Bloom’s Taxonomy can be applied across disciplines and helps ensure that assessments and activities progress in complexity and rigor, supporting student learning step-by-step (Attia, 2021). Free online tools are available to help create assessments aligned with the desired level of Bloom’s Taxonomy.

Efficiently Upload Your Course in the LMS

The final step is to upload the course into the learning management system such as Canvas or Blackboard. While it may be tempting to start building each module directly in the learning management system, doing so could lead to unnecessary revisions and time-consuming fixes. Instead, consider using backward course design to frame the entire course prior to uploading online. Once the framework is established using backward course design and the modules are formatted consistently, content can be uploaded efficiently by duplicating page templates for elements such as introductions, lectures or instructions, quizzes, and discussions.

After the course has begun, track any necessary revisions and gather early student feedback, such as through a check-in during week two or three. If the opportunity arises to teach the course again, these insights will allow for continuous improvement towards an ideal version. If this is not possible, the course shell can be passed on to another faculty member, thereby benefiting future students.

Reflecting on my experience of developing a course from scratch and minimal time I was reminded of the importance of focusing on the non-negotiables: accessibility, effectiveness, and alignment with key learning outcomes. By applying established course design frameworks of backward design, Universal Design for Learning, and Bloom’s Taxonomy, I was able to deliver a high-quality, student-ready course, despite the limited time available. If you find yourself in a similar situation or looking to refine an existing course, focusing on these core principles ensures that the course is not only functional but also effective in supporting student success. The lesson here is clear: even in the face of urgency, thoughtful course design can help you meet both immediate needs and long-term educational goals.

Kristen Pornter-Lauerman, MDA, RDH, is a doctoral student at the University of the Pacific in Health Science Education. She currently serves as a Program Director in Dental Hygiene, With a background in healthcare administration and dental hygiene, Kristen is dedicated to fostering growth and innovation within dental education.

Dr. Julia VanderMolen, CHES® is an Associate Professor for the Public Health program at Grand Valley State University. The contributions of her research are to examine the benefits of assistive technology, UD and UDL, and disabilities in public health. She is an active member of the Disability section of the American Public Health Association (APHA).

References

Attia, A. S. (2021). Bloom’s taxonomy as a tool to optimize course learning outcomes and assessments in architecture programs. Journal of Applied Science and Engineering, 24(3), 315-322.

Casebolt, T., & Humphrey, K. (2023). Use of universal design for learning principles in a public health course. Annals of Global Health, 89(1), 48.

CAST. (n.d.). UDL guidelines. Retrieved June 15, 2025, from https://udlguidelines.cast.org/

Stapleton-Corcoran, E. (2023). Backwards design. Center for the Advancement of Teaching Excellence at the University of Illinois, Chicago. Retrieved June 15, 2025, from https://teaching.uic.edu/resources/teaching-guides/learning-principles-and-frameworks/backward-design

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August 20, 2025
Building a Course from Scratch: When Time is Not on Your Side – Faculty Focus

I recently found myself in a the all-too-familiar situation where I was handed a course at the last minute. The course consisted of a catalog description and course outcomes with no teaching materials. There was very little time to develop a student-ready course while also trying to manage my workload and protect my mental well-being. What steps can you take if you find yourself in a similar scenario? Focus on the non-negotiables: accessibility, effectiveness, and alignment with key learning outcomes by applying core principles of course design, including Universal Design for Learning, backward design, and Bloom’s Taxonomy.

When facing rapid course creation, begin by setting your mindset regarding the expectations for developing a last-minute course. Even without the bells and whistles typically found in a fully designed course, a basic course can be accessible, inclusive, and high-quality. The goal is to create a student-ready course with appropriate content and assessments that align with the course learning outcomes and description. Aim for completion over perfection, prioritizing the non-negotiables.

Establish Your Course Framework and Weekly Structure

Most existing courses already have an approved catalog course description, a set number of credits, and established course outcomes. Based on this information, the first step is to identify any essential content and the timeframe, based on the number of weeks the course runs and the credit hours. Doing so will help ensure alignment with the expected student and faculty workload. Once this is established, you can begin the course design by building the course framework. The core of the framework is the syllabus. The syllabus should include your contact information, grading policies, course schedule, and course expectations. Then use the schedule to organize the required content into weekly modules.

Stick to simple technology tools and avoid adding extras that could take time away from the non-negotiables. This includes curriculum creep. Focus only on the essential content that aligns with the course learning objectives. To save time, use a consistent structure for each weekly module, such as an overview or introduction, required reading and/or media, one active learning task, plus a low or medium-stakes formative assessment. Create a clear rubric for repeat assignments like discussions, reflection, or writing assignments. This will allow you to apply the same criteria across each module and reduce the time of making numerous rubrics.

Apply Instructional Design Frameworks for Accessible, Inclusive Learning

The next step in the process of course design is to apply proven instructional design frameworks such as backward design, Universal Design for Learning, and Bloom’s Taxonomy. Utilizing backward design principles can help the instructor deliver a course with a clear vision of what students are expected to learn and achieve from each lesson, module, and the course overall (Stapleton-Corcoran, 2023). Universal Design for Learning is a “framework to improve and optimize teaching and learning for all people” (Casebolt & Humphrey, 2023, p. 2). This includes accessibility features such as headers, alt text, and captions. Keep presentation slides simple by using a white background, dark font, and avoiding unnecessary images. Not only will this make the slides more accessible, but it will also reduce the time required to create them. Throughout the course remain flexible, allow students multiple ways to express their learning, including multimedia options, and provide various means of engagement and representation (CAST, n.d.). As a time-saving option, if weekly videos are not feasible, add weekly micro-lecture audio recordings throughout the course. These do not need to be added at the start of the course but can be introduced week by week.

When developing the assessments, consider using Bloom’s Taxonomy. Bloom’s Taxonomy framework consists of six major categories of cognitive processes: remember, understand, apply, analyze, evaluate, and create. Bloom’s Taxonomy can be applied across disciplines and helps ensure that assessments and activities progress in complexity and rigor, supporting student learning step-by-step (Attia, 2021). Free online tools are available to help create assessments aligned with the desired level of Bloom’s Taxonomy.

Efficiently Upload Your Course in the LMS

The final step is to upload the course into the learning management system such as Canvas or Blackboard. While it may be tempting to start building each module directly in the learning management system, doing so could lead to unnecessary revisions and time-consuming fixes. Instead, consider using backward course design to frame the entire course prior to uploading online. Once the framework is established using backward course design and the modules are formatted consistently, content can be uploaded efficiently by duplicating page templates for elements such as introductions, lectures or instructions, quizzes, and discussions.

After the course has begun, track any necessary revisions and gather early student feedback, such as through a check-in during week two or three. If the opportunity arises to teach the course again, these insights will allow for continuous improvement towards an ideal version. If this is not possible, the course shell can be passed on to another faculty member, thereby benefiting future students.

Reflecting on my experience of developing a course from scratch and minimal time I was reminded of the importance of focusing on the non-negotiables: accessibility, effectiveness, and alignment with key learning outcomes. By applying established course design frameworks of backward design, Universal Design for Learning, and Bloom’s Taxonomy, I was able to deliver a high-quality, student-ready course, despite the limited time available. If you find yourself in a similar situation or looking to refine an existing course, focusing on these core principles ensures that the course is not only functional but also effective in supporting student success. The lesson here is clear: even in the face of urgency, thoughtful course design can help you meet both immediate needs and long-term educational goals.

Kristen Pornter-Lauerman, MDA, RDH, is a doctoral student at the University of the Pacific in Health Science Education. She currently serves as a Program Director in Dental Hygiene, With a background in healthcare administration and dental hygiene, Kristen is dedicated to fostering growth and innovation within dental education.

Dr. Julia VanderMolen, CHES® is an Associate Professor for the Public Health program at Grand Valley State University. The contributions of her research are to examine the benefits of assistive technology, UD and UDL, and disabilities in public health. She is an active member of the Disability section of the American Public Health Association (APHA).

References

Attia, A. S. (2021). Bloom’s taxonomy as a tool to optimize course learning outcomes and assessments in architecture programs. Journal of Applied Science and Engineering, 24(3), 315-322.

Casebolt, T., & Humphrey, K. (2023). Use of universal design for learning principles in a public health course. Annals of Global Health, 89(1), 48.

CAST. (n.d.). UDL guidelines. Retrieved June 15, 2025, from https://udlguidelines.cast.org/

Stapleton-Corcoran, E. (2023). Backwards design. Center for the Advancement of Teaching Excellence at the University of Illinois, Chicago. Retrieved June 15, 2025, from https://teaching.uic.edu/resources/teaching-guides/learning-principles-and-frameworks/backward-design

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August 20, 2025
A Values-Based Approach to Using Gen AI – Faculty Focus

As a learning designer in a centralized teaching and learning unit, it’s my job to explore new technologies, particularly AI. But I’ll admit, I didn’t jump right in. As Generative AI (GenAI, a subset of AI that can produce content, ideas, and data by learning from existing data and patterns) has become prevalent, so have a wide range of concerns about its usage: authenticity, critical thinking, bias, representation, plagiarism, and sustainability, to name a few.

For a while, I felt paralyzed. How am I supposed to make decisions about this emerging technology that I don’t fully understand? But scholars like Maha Bali reminded me that we need to engage with AI in order to discuss its implications and influence its outcomes. As leaders, educators, users, and creators, we have choices. So, here’s how I have been thinking through when and how I’m going to use GenAI in a way that aligns with my values.

I value originality.

I create original work as a learning designer, as well as personally as a writer and artist, and I don’t want GenAI to train on my work. If I use GenAI, I will use a proprietary tool from my university (e.g., CoPilot), a tool with a paid subscription (like ChatGPT Plus), or another tool that won’t use my work.

I value transparency.

Working in digital learning, I am a partner on academic content. I respect my instructors’ hard-earned expertise and original work, and I won’t use their work with GenAI tools without their permission. In addition, if instructors’ content appears on platforms that use GenAI, I will inform them where and how it is used. As GenAI use increases in our course development processes, I will discuss the advantages and disadvantages of using specific tools, and we will work together to decide whether and how GenAI will be applied.

I value collaboration.

I work with amazing instructors to create online courses and other digital learning experiences. With a team of experts, I guide instructors through the process of brainstorming, outlining, and developing academic materials that we organize into a guided, accessible experience. My teammates and I bring a broad range of skills to this complex work, and we collaborate to create unique and valuable learning experiences. GenAI can help us with parts of this process, but I won’t use GenAI to replace our work with material that lacks the rich human experience and expertise that informs effective teaching and learning.

I value scholarship.

Higher education centers on the exchange, synthesis, and development of ideas. We build on others’ work while crediting them for their contributions. We do this to support our arguments, demonstrate our scholarship, and contribute to an ongoing conversation. While I can use GenAI for research, I can’t depend on it to accurately quote or cite others. Therefore, I won’t assume what GenAI writes or cites is accurate, and I will do my own research. In addition, if I use AI in my work (or in collaborative work), I will cite it.

I value sustainability.

Estimates vary on how much energy GenAI uses, and it depends on what you’re using it for. We do know that simple text queries don’t use as much energy as generating images or video requires. Is it worth using GenAI to create an image of your dog as an astronaut, or a dress composed of hundreds of kittens? As much as I love cute animals, I will minimize using GenAI to create images or videos, particularly for nonessential tasks. Additionally, I will weigh the impact of saving significant time and energy on essential tasks against the potential sustainability costs.

I value critical thinking.

I don’t want the easy answer. I want the complexities, the nuance, the human experience that makes an article or study or creative work unique. I won’t rely on GenAI to create something simplistic, biased, or inaccurate. If I use GenAI, I will use it to generate ideas, answer simple questions, or create an initial outline or template. From there, I will edit and rewrite what it provides, checking for bias, representation, and accuracy. Further, I will advise instructors on how to guide their learners in taking a similar approach.

I’m far from an expert in GenAI, and it’s a moving target. But deciding how I will engage with it has given me some peace of mind in a chaotic, ever-changing world. My best wishes on your own AI journey.

Heather Hans, MLIS is a senior learning designer at Duke University. She is energized by learner-centered design, good UX, and expanding access. She enjoys travel, wildlife gardening, and pie.

References

Bali, M. (2024, June 16). What Can We Refuse in AI? Reflecting Allowed. https://blog.mahabali.me/pedagogy/critical-pedagogy/what-can-we-refuse-in-ai/

Hillier, M. (2023, February 20). Why does ChatGPT generate fake references? TECHE. https://teche.mq.edu.au/2023/02/why-does-chatgpt-generate-fake-references/

Brown University Library. (2025, February 5). Generative Artificial Intelligence: Citation and Attribution with AI Tools. LibGuides at Brown University. https://libguides.brown.edu/c.php?g=1338928&p=9868287

Nicoletti, L., & Bass, D. (2023, June 9). Humans are biased. Generative AI is even worse. Bloomberg.com. https://www.bloomberg.com/graphics/2023-generative-ai-bias/

Duke Learning Innovation & Lifetime Education. (2024, August 12). Generative AI and Teaching at Duke. Duke Learning Innovation & Lifetime Education. https://lile.duke.edu/ai-and-teaching-at-duke-2/

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June 11, 2025
Supporting the Instructional Design Process: Stress-Testing Assignments with AI – Faculty Focus

While many of our conversations have focused on what generative AI means for student assignments and learning outcomes, there’s another question faculty are asking—often individually and quietly: How can we leverage AI in our own academic and administrative work? And more importantly, should we?

The answer, I believe, lies in using AI to help clear space for the work only we can do—the collaboration, connection, and critical guidance that makes education transformative.

That doesn’t mean that we simply use AI as a crutch for answering emails or summarizing meetings. In fact, I believe the true promise of AI comes from using it, in Ethan Mollick’s words, as a “genuine intellectual partner,” one that can enhance classroom discussions, assist with creating engaging instructional materials, and even help develop sophisticated problem sets or simulations that previously required extensive preparation time. As Mollick says, “the focus needs to move from task automation to capability augmentation.”

AI offers many potential applications for faculty work. While faculty should continue to prioritize the importance of maintaining human connection, empathy, and support in our teaching practice, we need to consider other ways AI can augment our work. Perhaps one way is in the design of our courses, the assignments and activities that chart student progress across content and outcomes. But rather than asking AI to develop prompts or notes for us, we can use AI as a tool to help develop our work in surprising ways.

Works in Theory, Wobbles in Practice

We’ve all fallen in love with that one key discussion question or written assignment prompt that just fizzles in the classroom. Despite our best intentions, we may not provide enough information, or we fail to anticipate a blind spot that leads students down fruitless paths. One of the challenges of course design is that all our work can seem perfectly clear and effective when we are knee-deep in the design process, but everything somehow falls apart when deployed in the wild. From simple misunderstandings to complex misconceptions, these issues typically don’t reveal themselves until we see actual student work—often when it’s too late to prevent frustration.

Bridging this gap requires iterative refinement—recognizing that what works in theory or in controlled conditions needs real-world testing, adaptation, and continuous improvement. It’s not just about designing something that works in the lab but ensuring our designs are resilient, adaptable, and responsive enough to thrive in the wild.

While there’s no substitute for real-world testing, I began wondering if AI could help with this iterative refinement. I didn’t want AI to refine or tweak my prompts. I wanted to see if I could task AI with modelling hundreds of student responses to my prompts in the hope that this process might yield the kind of insight I was too close to see.

The Process: AI-Assisted Assignment Stress Testing

After experimenting with systems like Claude and ChatGPT, I’ve discovered they can effectively analyze and refine writing prompts through the creation of simulated student responses. The basic approach works like this. First, provide the AI with information about your course and key characteristics of your student population. Then, share the assignment prompt. The AI internally generates multiple simulated student responses across different skill levels. After, it provides a comprehensive analysis identifying potential issues and opportunities.

You might specify that the analysis include common misinterpretations students might make or any structural or organizational challenges in the prompt. But the AI can also identify content development patterns and potential issues as well as population-specific concerns based on your student demographics. Finally, the AI can even suggest refinements to the prompt.

Seeing What You’re Not Seeing

To test this approach, I uploaded a personal narrative prompt that asks students to connect their life experiences to their academic goals—a common assignment in first-year writing courses.

The AI analysis revealed several blind spots in my prompt design. For instance, I hadn’t considered how non-traditional students might struggle with “choice of major” language, since many are career-changers. The AI modeled responses also revealed that students might have difficulty transitioning between personal narrative and academic analysis sections. Most valuable was seeing how different student populations might interpret the same instructions. Career-changers might focus too heavily on work experiences, while others might struggle with how much personal information to share. These insights allowed me to add clarifying language and support materials before any real students encountered these challenges.

The entire process took about 30 minutes but potentially saved hours of student confusion and faculty clarification emails. Of course, AI responses aren’t identical to human student responses, and we should be cautious about viewing AI as an infallible expert or source of absolute truth. But used as an additional lens when developing assignments, this approach can grant course designers a different perspective, one that triggers valuable insights and potentially reduces workload.

If you’d like to try this approach yourself, here’s a template prompt you can use with AI systems.

Course Design Multiplier

This process allowed me to develop targeted support materials for predicted problem areas before students struggle, building proactive scaffolding into course design from the beginning. And by sharing insights gained through AI analysis, departments could collectively improve assignment design practices—particularly valuable for multi-section courses where consistency matters. Over time, we could build a practical library of “what works” that faculty could draw from, including analyses explaining why certain assignments succeed with particular student populations and learning objectives.

AI-assisted assignment analysis offers a promising tool that respects our expertise while expanding our ability to anticipate student needs. While the technology isn’t perfect and will never replace insights gained from direct student interaction, it provides a valuable perspective that helps identify blind spots before students encounter them. This represents just one way thoughtfully implemented AI can help us do more of what matters: creating meaningful learning experiences. By using AI for the predictive work of assignment design, we free more time and energy for the deeply human work of guiding and connecting with our students—the work that only we can do.

Dr. Nathan Pritts is a leader in higher education, specializing in faculty development, instructional innovation, and the integration of emerging technologies in teaching and learning. As Professor and Program Chair for First Year Writing at the University of Arizona Global Campus, he has spearheaded initiatives in strategic implementation of online learning technologies, comprehensive faculty training programs, and the creation of scalable interventions to support both faculty and students in online environments. As author and researcher, Dr. Pritts has published widely on topics including digital pedagogy, AI-enhanced curriculum design, assessment strategies, and the future of higher education.

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March 19, 2025
Supporting the Instructional Design Process: Stress-Testing Assignments with AI – Faculty Focus

While many of our conversations have focused on what generative AI means for student assignments and learning outcomes, there’s another question faculty are asking—often individually and quietly: How can we leverage AI in our own academic and administrative work? And more importantly, should we?

The answer, I believe, lies in using AI to help clear space for the work only we can do—the collaboration, connection, and critical guidance that makes education transformative.

That doesn’t mean that we simply use AI as a crutch for answering emails or summarizing meetings. In fact, I believe the true promise of AI comes from using it, in Ethan Mollick’s words, as a “genuine intellectual partner,” one that can enhance classroom discussions, assist with creating engaging instructional materials, and even help develop sophisticated problem sets or simulations that previously required extensive preparation time. As Mollick says, “the focus needs to move from task automation to capability augmentation.”

AI offers many potential applications for faculty work. While faculty should continue to prioritize the importance of maintaining human connection, empathy, and support in our teaching practice, we need to consider other ways AI can augment our work. Perhaps one way is in the design of our courses, the assignments and activities that chart student progress across content and outcomes. But rather than asking AI to develop prompts or notes for us, we can use AI as a tool to help develop our work in surprising ways.

Works in Theory, Wobbles in Practice

We’ve all fallen in love with that one key discussion question or written assignment prompt that just fizzles in the classroom. Despite our best intentions, we may not provide enough information, or we fail to anticipate a blind spot that leads students down fruitless paths. One of the challenges of course design is that all our work can seem perfectly clear and effective when we are knee-deep in the design process, but everything somehow falls apart when deployed in the wild. From simple misunderstandings to complex misconceptions, these issues typically don’t reveal themselves until we see actual student work—often when it’s too late to prevent frustration.

Bridging this gap requires iterative refinement—recognizing that what works in theory or in controlled conditions needs real-world testing, adaptation, and continuous improvement. It’s not just about designing something that works in the lab but ensuring our designs are resilient, adaptable, and responsive enough to thrive in the wild.

While there’s no substitute for real-world testing, I began wondering if AI could help with this iterative refinement. I didn’t want AI to refine or tweak my prompts. I wanted to see if I could task AI with modelling hundreds of student responses to my prompts in the hope that this process might yield the kind of insight I was too close to see.

The Process: AI-Assisted Assignment Stress Testing

After experimenting with systems like Claude and ChatGPT, I’ve discovered they can effectively analyze and refine writing prompts through the creation of simulated student responses. The basic approach works like this. First, provide the AI with information about your course and key characteristics of your student population. Then, share the assignment prompt. The AI internally generates multiple simulated student responses across different skill levels. After, it provides a comprehensive analysis identifying potential issues and opportunities.

You might specify that the analysis include common misinterpretations students might make or any structural or organizational challenges in the prompt. But the AI can also identify content development patterns and potential issues as well as population-specific concerns based on your student demographics. Finally, the AI can even suggest refinements to the prompt.

Seeing What You’re Not Seeing

To test this approach, I uploaded a personal narrative prompt that asks students to connect their life experiences to their academic goals—a common assignment in first-year writing courses.

The AI analysis revealed several blind spots in my prompt design. For instance, I hadn’t considered how non-traditional students might struggle with “choice of major” language, since many are career-changers. The AI modeled responses also revealed that students might have difficulty transitioning between personal narrative and academic analysis sections. Most valuable was seeing how different student populations might interpret the same instructions. Career-changers might focus too heavily on work experiences, while others might struggle with how much personal information to share. These insights allowed me to add clarifying language and support materials before any real students encountered these challenges.

The entire process took about 30 minutes but potentially saved hours of student confusion and faculty clarification emails. Of course, AI responses aren’t identical to human student responses, and we should be cautious about viewing AI as an infallible expert or source of absolute truth. But used as an additional lens when developing assignments, this approach can grant course designers a different perspective, one that triggers valuable insights and potentially reduces workload.

If you’d like to try this approach yourself, here’s a template prompt you can use with AI systems.

Course Design Multiplier

This process allowed me to develop targeted support materials for predicted problem areas before students struggle, building proactive scaffolding into course design from the beginning. And by sharing insights gained through AI analysis, departments could collectively improve assignment design practices—particularly valuable for multi-section courses where consistency matters. Over time, we could build a practical library of “what works” that faculty could draw from, including analyses explaining why certain assignments succeed with particular student populations and learning objectives.

AI-assisted assignment analysis offers a promising tool that respects our expertise while expanding our ability to anticipate student needs. While the technology isn’t perfect and will never replace insights gained from direct student interaction, it provides a valuable perspective that helps identify blind spots before students encounter them. This represents just one way thoughtfully implemented AI can help us do more of what matters: creating meaningful learning experiences. By using AI for the predictive work of assignment design, we free more time and energy for the deeply human work of guiding and connecting with our students—the work that only we can do.

Dr. Nathan Pritts is a leader in higher education, specializing in faculty development, instructional innovation, and the integration of emerging technologies in teaching and learning. As Professor and Program Chair for First Year Writing at the University of Arizona Global Campus, he has spearheaded initiatives in strategic implementation of online learning technologies, comprehensive faculty training programs, and the creation of scalable interventions to support both faculty and students in online environments. As author and researcher, Dr. Pritts has published widely on topics including digital pedagogy, AI-enhanced curriculum design, assessment strategies, and the future of higher education.

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March 19, 2025
Quality Matters Training – Hot Lunch Tray

In May 2017 I completed Quality Matters Reviewer training. I completed it as part of a subscription my K12 district purchased and was the QM Coordinator for that district 2017-2022.It has been a touchstone for me as I lean into online education.

Context

At the time of my initial training, I was an in-person teacher trainer and professional developer working in the Technology Department. I specifically worked with classroom teachers to blend their content online the training was transformational. I have now experienced deep looks at online content and now see how extensive, how detailed a complete course review is. I realize now, I have always been starting the online content shift and never finishing it.

Since my initial training, the QM Rubric(s) and the mindset shift has meant different things to me.

Employment Opportunities

Since completing the training I have added many experiences to my resume. I have been paid for all of these experiences and encourage anyone who can to become a QM certified reviewer. I teacher at two different colleges in instructional designer/technologist courses. I have contracted to create complete online courses for adult professional learning courses. I have contracted to author lectures for online courses based on course and modules objectives. I have contracted to “pre-review” course before colleges submit them for QM Certification. I contract directly with Quality Matters to complete course reviews. And I have implemented a learning management system (LMS) from the request for proposal (RFP) through a two year road map.

Not all of these opportunities were because of my certification, but also the perspective it provided me.

Perspective

Thinking about online course content through the lens of the QM rubric helps me understand what I am and what I should be experiencing in on online course.

Personally, my oldest son transitioned to an online high school in his sophomore year for his unique scheduling needs. Considering the QM rubric, his courses are what they should be; considering what I used to do in my in-person classroom I found the course experience less than…. but this helped me see what is the school learning versus what is the experience learning he has available to him.

Now when I look at online courses I intuitively understand – and am still explaining to many K12 classroom teacher – the academic content is distilled to the most straightforward content and learner experiences only. When a in-person classroom teacher tells me “that isn’t real school” I think to myself, but it is what you say you want to do.

In my son’s situation, school distilled down to the required learning allows he to be immersed in his in-person real world learning.

Professional Learning

In 2021, I guided our longest standing K12 online instructors in the district (Foreign Languages & Physical Education) through a Quality Matters self-review. The self-review differs from a QM review, but in this case we used the opportunity to meet as a professional learning community (PLC) to compare the QM rubric to the most mature online offering. This course had been revised over a number of years. When we applied the rubric to the course we discussed many instructor dispositions and assumptions. These discussions generated a dialogue of improvement in content creation, moving the course into alignment with the rubric. The most interesting part of the process was to listen to these course creators and practitioners discussing the way the students interacted with the content.

As I have reviewed and created online courses I have increased my capacity to view courses from the perspective of author, teacher, and learner. I would recommend this activity to any PLC involved with online courses.

I woudl encourage all educators to consider if either a Quality Matters K12 or Higher Education reviewer course or certification is right for you.

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November 23, 2024