1. AI Episode 1: Intro to Artificial Intelligence in Teaching
  2. AI Episode 2: What Does An AI Teaching Assistant Look Like?
  3. AI Episode 3: Implications for Thought Leaders and Policy Developers
  4. Introducing Simulations into Teacher Preparation Programs
  5. Assistive Technology to Support Writing
  6. Enhancing Instruction and Empowering Educators with AI Tools and Technology
  7. So, AI Ruined Your Term Paper Assignment?
  8. Step by Step Use of Chat GPT
  9. CIDDL ChatGPT: Summarizing Text
  10. CIDDL ChatGPT: Solving Multiple Choice Questions
  11. Equity, Diversity, and Access to Technology in the Age of Artificial Intelligence
  12. CIDDL ChatGPT: Writing Programs
  13. CIDDL ChatGPT: Solving Word Problems
  14. Artificial Intelligence: Positives and Negatives in the Mathematics Classroom
  15. AI to Support Literacy
  16. Using the AI Bill of Rights to Guide Education’s use of AI and the European Commission’s “Ethical Guidelines for Teaching and Learning” to Guide the Future of AI in Education Part 1 of 2
  17. Using the AI Bill of Rights to Guide Education’s use of AI and the European Commission’s “Ethical Guidelines for Teaching and Learning” to Guide the Future of AI in Education Part 2 of 2
  18. Three Free & Easy Tools to Support Tiered Reading in Your Classroom
  19. The Question of Equity in the Age of ChatGPT
  20. CIDDList: 5 AIs You Need to Check Out This Summer!
  21. Mixed Reality Simulations, Personalized Learning, AI, and the Future of Education with Dr. Chris Dede
  22. Foundations for AI and the Future of Teaching and Learning from the US Department of Educational Technology
  23. Apple Enters the AR/VR/MR/XR Scene
  24. ChatGPT, AIs, and the IEP?
  25. There’s An AI for That: A Site Dedicated to Curating AIs
  26. UDL, Design Learning, and Personalized Learning
  27. Embracing the Future: How Teachers Can Harness AI at the Beginning of the School Year
  28. Empowering Special Education Faculty: Navigating the AI Landscape in Higher Education for 2023-2024.
  29. CIDDList: Back-to-School Checklist for Technology in Teacher Preparation Courses
  30. Cracking the Code: Students with Disabilities in the Computer Sciences 
  31. UNESCO Discusses Artificial Intelligence
  32. AI-integrated Apps for Those with Visual Impairments: Camera-Based Identifiers and Readers
  33. Publishers Respond to Generative AI
  34. K-12 Generative AI Readiness Checklist
  35. CIDDL Talks How AI Will Change Special Education at TED
  36. Re-designing and Aligning an Intro to Special Education Class to the UDL Framework through Technology Integration: Minimizing Threats and Distractions
  37. Resources for Learning About AI Going Into 2024
  38. Artificial Intelligence in Education 2023: A Year in Review
  39. Revolutionizing Mathematics Education in K-12 with AI: The Role of ChatGPT
  40. Image Generating AI and Implications for Teacher Preparation
  41. Are We There Yet? AI for Statistical Analysis
  42. Answers to Your AI Questions: A Conversation with Yacine Tazi
  43. Emerging Trends in Special Education Technology: A Doctoral Scholar Symposium
  44. 2024: A Space Odyssey? How AI and Technology of the Present Compares to HAL9000 and the Predictions of 2001: A Space Odyssey
  45. Using ChatGPT for Writing Lesson Plans
  46. Updates in the World of AI
  47. CIDDList: Exploring GPTs Available with ChatGPT Plus
  48. Prompt Engineering for Teachers Using Generative AI: Brainstorming Activities and Resources
  49. Understanding the AI in Your Classroom
  50. Jump on the MagicSchool.ai Bus!
  51. Using AI-Powered Chatbot for Reading Comprehension
  52. The Impact of Artificial Intelligence on Cognitive Load
  53. Apple Intelligence: How Apple’s AI for the Rest of Us Will Impact Special Education Personnel Preparation

UDL, Designing Learning, and Personalized Learning

Dr. Basham is a professor of special education at the University of Kansas, the Principal Investigator of CIDDL, the senior advisor at CAST, and a co-founder of the UDL Implementation and Research Network. His research interests include UDL, instructional design and technology, STEM education, and innovation.  His work focuses on developing future-ready learning environments that are equitable, beneficial, and meaningful for all learners.

The problem highlighted in this brief

How do we support UDL-Based Environments? This brief explores personalized learning (Basham et al., 2016), the integration of technology, and truly designing learning to support all learners. Personnel preparation programs need to work with their future educators to accept variability (Basham et al., 2016) in their learners as part of human nature which furthers the ideals of inclusion (Basham, 2022). 

Why does this topic matter to teacher preparation?

We need to teach pre-service personnel to be design thinkers, considering the needs of their students, with the goal of supporting all learners. UDL empowers learners by giving them a voice in their education (Zhang et al., 2022). In teacher preparation, we need to facilitate the codesign process necessary to implement the UDL framework with pre-service educators so that they have the knowledge to effectively collaborate with other stakeholders when they enter the classroom and school setting (Zhang et al., 2022).

About This Brief

Dr. Basham shares the exciting innovations on the horizon of education, including personalized learning, design thinking, UDL, and Artificial Intelligence (AI). He shares how to bring these concepts into personnel preparation programs and how teaching future educators and related service personnel to think in this way will lead to supporting all students, with or without disabilities. 

Research and Practice Context


The Universal Design for Learning (UDL) framework centers around variability and providing meaningful engagement, representation, and expression at the forefront of instructional design, in order to support the needs of all learners (Rose, 2000). 

Personalized learning means that the learning is centered around flexibility and mastery, where learners drive their instruction with regard to how, what, when, and where they learn (Basham et al., 2016)

The following are key insights shared by Dr. Basham on this research. The interview focused on six questions about personalized learning, UDL, and designing learning in teacher preparation as well as recommendations for teacher educators to incorporate these ideas.  

Q1: What issues are you trying to address through your work with personalized learning or AI or UDL as it relates to personnel preparation and/or education systems?

Dr. Basham discusses how, oftentimes, we think of future educators as practitioners. When higher education faculty transform their thinking about future educators to one where they are designers, it opens the door to change how we think about the classroom and education systems as a whole. 

Traditionally, educators implement supports for students “as needed”, providing them to students with identified disabilities and other marginalized populations (Title I, English Language Learners, etc.; Basham, 2022). What Dr. Basham’s research hopes to promote is the idea that by designing learning from the onset to support all learners, through personalized learning, we can address the individual needs of the diverse student population and provide all students with a quality education (Zhang et al., 2020). 

Dr. Basham: “The educators take on a different role, one of being a designer, that means looking at your goals, at your students, and contextualizing those things together, intermixing that with database decision making and how to support the outcomes that are being desired.”

Q2: Can you walk us through how your work supports outcomes for students with disabilities?

The idea of supporting all learners is what drives Dr. Basham’s research. In a personalized learning environment, one way to ensure that the innovative approach is truly learner-centered is through the use of flexible instructional practices and alignment to UDL (Zhang et al., 2020). And, it is easy to rush to integrate technology to support these efforts, Basham and colleagues (2016) determined that technology is just a tool that supports the implementation of personalized learning. 

There is no shortage of innovations and technologies to support students with disabilities, from video modeling, game-based learning, augmented reality, utilizing mobile technologies, etc. (Basham, Blackorby, et al.., 2020). Dr. Basham’s philosophy is that, rather than focusing on the technologies and applying them to students with disabilities, we need to focus on all students and design our instruction with the intent of supporting all learners. With the UDL framework (Rose, 2000), teachers are encouraged to design learning environments and experiences to support the variability of the classroom (Basham, Gardner, et al., 2020). The key to designing learning environments is to be proactive in the creation of learning experiences and finding ways to overcome barriers to learning (Basham, Gardner, et al., 2020).The idea of supporting all learners is what drives Dr. Basham’s research. In a personalized learning environment, one way to ensure that the innovative approach is truly learner-centered is through the use of flexible instructional practices and alignment to UDL (Zhang et al., 2020). And, it is easy to rush to integrate technology to support these efforts, Basham and colleagues (2016) determined that technology is just a tool that supports the implementation of personalized learning. 

Dr. Basham: “Placing students with disabilities at the center of the discussion and designing for the kids on the margins… helps to support the design of better technologies and better innovations for ALL kids.”

Dr Basham: “All technology is a tool… it’s how we utilize those tools to support our own creations or to support humanity is a critical component of what we should be doing and talking about.”

Q3: How do you integrate technologies into your teacher preparation program?

The idea of putting the human at the center of the goals is a concept Dr. Basham has been researching and discussing in several publications (i.e., Basham, 2022; Basham Marino, 2013; Marino et al., 2014). Technology as a means to personalize learning dates back to Skinner, where his “teaching machine” provided students an opportunity to work at their own pace independently (Basham et al., 2016). Though technology offers great support with personalizing learning for all students, it is not the answer. Rather, it puts the pedagogical and procedural responsibility on the students and teachers (Basham et al., 2016). 

Dr. Basham explains with design thinking, a concept he stresses within his personnel preparation courses, we start to consider teaching from the perspective of human behavior. And when framed this way, technology, evidence-based practices, and high-leverage practices all begin to make sense. 

Dr. Basham: “I frame the integration of technology around the human condition around the goals that we’re trying to accomplish.”

Q4: How can we better prepare educators for using these technologies in the field?

Designing learning in a UDL-rich environment is complex (Basham, Hall, et al., 2020). Past research on the topic shows that this process should be iterative, and collaborative, involve multiple stakeholders, and empower teachers to use their pedagogical knowledge and knowledge of how students learn (Zhang, Jackson, et al., 2022). Dr. Basham suggests that, in teacher preparation, we need to encourage our future educators to be designers of instruction to further the success of all learners. He shared that our role is not to necessarily teach all the technologies that exist and the specific devices, but rather to teach teachers how to understand what is happening within their classrooms. His philosophy is that, through design thinking, we can help to close the research-to-practice gap that we so frequently see between higher education and k-12 classrooms.  

Dr. Basham: “Being able to teach them how to not learn the individual sort of technologies or the individual sorts of practices but to learn how to be again better designers in an environment, to learn the actions, and to understand what’s kind of going on in an environment.”

Q5: What implications do you see for future research, and what are some questions we might be asking?

The ethical implications of AI and machine learning are a hot topic that we’ve been discussing within CIDDL recently. The framework set forth by the Blueprint for an AI Bill of Rights (White House, 2022) contains five principles to consider which include safe and effective systems, algorithmic discrimination protections, data privacy, notice and explanation, and human alternatives. The full spectrum of ethical issues is obviously unknown, given this is a still developing field. What is important is that AI will change our roles as researchers, teacher-educators, teachers, and teachers, and the way in which we design our classrooms and assignments (Goldman, 2023)

Dr. Basham: “As we approach our next round of research we have to start thinking about how are the machines helping support us?... I think the other thing we need to kind of get into are the ethics around this. ”

Q6: What else should teacher preparation programs consider moving forward?

Q7: Are there any specific technologies you would suggest?


With the launch of ChatGPT at the end of 2022, the impacts of AI on education are being seen, discussed, and theorized. In a previous CIDDL blog “So AI Ruined Your Term Paper”, Dr. Basham discussed how educators can shift their thinking from focusing on banning AI to thinking about the purpose of your assignment and the learning goals and focusing on the principles of UDL to guide the learning activity.  He suggests teaching students to fact check AI, use it to develop case studies, or find alternative ways to show understanding such as presentations and annotated videos.

Dr. Basham truly embodies the UDL framework and the ideals behind design thinking in the coursework he teaches and his research. His hope is that we can utilize a personalized learning environment to fully support all students by making the learning meaningful to them. 

Dr. Basham’s projects include:

Center for Innovation, Design, and Digital Learning

CIDDL’s mission is to further faculty’s capacity to use educational technology within their personnel preparation programs. 

Project COOL: A Scalable UDL Coaching Model

Project COOL’s mission is to improve classroom instruction training for teachers through resource procurement and a professional learning community of coaches. 

Project CORGI: Co-Organize Your Learning

CORGI is a collection of digital graphic organizers developed to build higher-order thinking skills. 

Learning Designed

Micro-credentials in the area of UDL.


Basham, J.D., Fulchini Scruggs, A., & Vasquez, E. (2023, January 5). So AI Ruined Your Term Paper. CIDDL. https://ciddl.org/so-ai-ruined-your-term-paper-assignment/

Basham, J. D. (2022). Reenvisioning the Future with Universal Design for Learning. State Education Standard, 22(1), 32-36.

Basham, J. D., Gardner, J. E., & Smith, S. J. (2020). Measuring the implementation of UDL in classrooms and schools: Initial field test results. Remedial and Special Education, 41(4), 231-243.

Basham, J. D., Hall, T. E., Carter Jr, R. A., & Stahl, W. M. (2016). An operationalized understanding of personalized learning. Journal of Special Education Technology, 31(3), 126-136.

Basham, J. D., & Marino, M. T. (2013). Understanding STEM education and supporting students through universal design for learning. Teaching exceptional children, 45(4), 8-15.

Goldman, S. R. (2023, March 22). Using the AI Bill of Rights to Guide Education’s use of AI and the European Commission's “Ethical Guidelines for Teaching and Learning” to Guide the Future of AI in Education Part 1 of 2. CIDDL. https://ciddl.org/using-the-ai-bill-of-rights-to-guide-educations-use-of-ai-and-the-european-commissions-ethical-guidelines-for-teaching-and-learning-to-guide-the-future-of-ai-in-education-part-1-of-2/   

Rose, D. (2000). Universal design for learning. Journal of Special Education Technology, 15(4), 47-51.

White House. (2022). Blueprint for an AI Bill of Rights–Making Automated Systems work for the American People.

Zhang, L., Basham, J. D., Carter Jr, R. A., & Zhang, J. (2021). Exploring Factors associated with the implementation of student-centered instructional practices in US classrooms. Teaching and Teacher Education, 99, 103273.

Zhang, L., Jackson, H. A., Yang, S., Basham, J. D., Williams, C. H., & Carter, R. A. (2022). Codesigning learning environments guided by the framework of Universal Design for Learning: a case study. Learning Environments Research, 1-19.

Zhang, L., Basham, J. D., & Yang, S. (2020). Understanding the implementation of personalized learning: A research synthesis. Educational Research Review, 31, 100339.

Suggested Citation

Goldman, S.R. & the CIDDL Team. (2023). CIDDL Research and Practice Brief #18: UDL, Designing Learning, and Personalized Learning with Dr. James Basham. The Center for Innovation, Design, and Digital Learning.