7 Future Directions

As educational technology continues to evolve quickly with AI, we now have more opportunities to explore what these tools can do. I have explored a variety of GenAI platforms such as Edu ChatGPT, Gemini, and Copilot, as well as applied tools like Signapse.ai, Scribe, Goblin Tools, FeedbackFruits, and several others used for automation, drafting, instructional support, and workflow enhancement. My goal has been to understand how these tools can support faculty in their work. TLX has developed an Critical Artificial Intelligence Pedagogy Course for faculty, and I was involved in creating that course. I learned a great deal about AI while building it. Understanding AI literacy is becoming important for everyone, and we need to learn how to use AI ethically. AI should be treated as an assistant, not as your main brain. It can help save time and support our work, but it should not replace our thinking or decision-making.

I often ask myself how AI can support QM and UDL work. The task of maintaining and improving course quality becomes even more important in a world where some institutions may want to build courses quickly or rapid course development models. This makes it even more important to standardize the course design process so that learners receive consistent and reliable learning experiences. The landscape of digital education is changing quickly, shaped by new technologies, new learner expectations, and new instructional approaches. Learners today expect information and services instantly, and at the same time, many institutions face limited resources and funding. Because of this, Quality Matters will remain an essential framework, but the way we apply it will need to adapt to these changes. Working in higher education means supporting pedagogy, but also understanding how crucial technology has become in course design.

In this chapter, I look ahead to the future of QM and online learning, consider emerging trends in quality assurance, and share my vision for the next decade.

QM in the Age of AI and Digital Learning

I personally feel that education has not moved fast enough to keep up with the pace of artificial intelligence development. AI is reshaping how we teach, learn, and design courses, and this shift is significant. Tools such as generative AI, adaptive learning systems, and automated feedback can enhance learner engagement and provide new forms of support. At the same time, AI introduces new responsibilities related to academic integrity, accessibility, transparency, and ethical use. In the context of QM, AI presents opportunities to strengthen alignment, support learner success, and provide more personalized learning pathways. However, faculty and institutions will need guidance on how to use AI responsibly while maintaining the clarity and structure that QM emphasizes. I created the resource Using AI Responsibly: What Students Need to Know so faculty can include it in their courses and help learners understand appropriate ways to use AI.

As a Learning Experience Designer, I see AI as a tool that can reduce repetitive work, offer new ways to present content, and help faculty revise their courses more efficiently. I feel positive about AI when we can teach learners how to use it correctly and ethically. At the same time, the human role in designing meaningful learning experiences will remain essential. The future of QM will involve integrating AI in thoughtful ways that support both instructors and learners.

Emerging Trends in Quality Assurance

Quality assurance is a large and important area in education. My understanding of it began with Quality Matters, which I learned alongside instructional design skills. As technology continues to advance, the future of quality assurance will expand beyond individual course design to include broader and more integrated learning environments. UDL, accessibility standards, microcredentials, and competency-based education are becoming more common across higher education. Many educators are now expected to have at least some understanding of these approaches.

It is important for institutions to focus on consistent learner experiences, program-level alignment, and technology-enhanced learning. These trends will require new approaches to quality assurance and stronger collaboration among faculty, designers, and support units. I hope that TLX will continue to be seen as an important hub for exchanging knowledge and supporting innovative teaching practices. My goal is to keep upgrading my own skills and learning from others so that I can share these insights with the institution and work closely with faculty to build the best possible future for our learners.

I believe that future research will help us build more flexible quality frameworks that balance structure with innovation. Instead of expecting every course to follow the same model, a more agile approach to quality assurance may focus on guiding principles that support diverse teaching styles, authentic assessments, and learner agency. Continuous improvement will remain at the core, but the tools we use will continue to evolve.

My Vision for the Next Decade

There are many challenges happening in the world right now, including in the college and university sectors. With growing pressure to generate revenue, government caps on international students, and limited funding, many institutions are facing difficult decisions. Cutting staff, who are valuable resources that institutions have invested in and developed, creates instability and impacts the quality of education. It is heartbreaking to see these changes across the industry. Looking ahead, I truly hope that senior leadership continues to recognize that building high-quality courses is one of the most important ways to keep learners engaged and returning. Reducing support and resources does not benefit learners, and it risks weakening the learning experience. It is difficult to imagine the future of the sector if this continues.

I hope leaders will see that quality course design should not be viewed as a requirement but as a shared responsibility and a meaningful part of teaching. Faculty need access to practical tools, collaborative communities, and supportive peer review processes that help them grow. These structures depend on staff expertise, and it takes a team to make them work. I hope to see quality frameworks that are flexible, inclusive, and designed to support all learners, especially those who may face barriers in online learning environments. As I plan for my own future graduate studies, I hope to contribute to this work at a deeper level.

I also see Learning Experience Designers playing an even more important role in guiding faculty, shaping digital learning strategies, and ensuring learners receive clear, engaging, and accessible learning experiences. My work with QM has shaped how I understand course design, and my goal is to continue contributing to a culture that values thoughtful decision-making, strong alignment, and meaningful learner engagement.

From my experience, quality in online learning cannot rely on just one model. It develops when faculty, designers, and support teams work together and keep improving their practice. Technology will keep changing, but what matters most is the people who design and support the learning experience. It is their work that helps learners succeed.