Conference Agenda

The capacity to plan, manage, monitor and reflect on one’s learning—i.e. to engage in self-regulated learning (SRL)—is vital to academic success; seminal research identified fourteen SRL strategies and showed that learners’ achievement was strongly predicted by their use of SRL strategies (Zimmerman and Martinez-Pons, 1986); this difference in achievement can be accounted for by strategy presence, frequency and consistency (Nandagopal and Ericsson, 2012). Empirical evaluations indicate that most SRL tools do not demonstrably improve actual SRL behaviour—most studies did not directly measure changes in students’ SRL strategies (Edisherashvili et al., 2022), highlighting a gap in understanding of whether these tools are truly helping students internalise better self-regulatory practices or just providing short-term performance boosts. This talk describes STARS, a co-designed digital tool for mobile and desktop to help bridge this gap. In particular, it supports learners in deploying a set of SRL strategies, helping them to (i) internalise standards (ii) set specific learning goals (iii) self evaluate their work against a standard and (iv) develop a plan to close the gaps between their work and the required standard. We used an action research methodology to evaluate STARS with undergraduate learners across three disciplines: computing, social care, and sustainable community development as well as postgraduate learners in STEM and humanities. We report on results to date including recorded learner behaviour as well as learner reflections. Our findings suggest the need for a means to overcome barriers including the need to integrate digital scaffolds into core assignments to reduce the initial effort barrier and increasing student agency in strategy selection to enhance long-term value.

Problem

Learning content is higher education’s primary teaching medium, yet most of it fails basic accessibility standards. The 2025 WebAIM Million analysis found that 94.8% of the top one million web pages had detectable WCAG failures [1]. Only 18% of disabled adults over 25 hold a bachelor’s degree — half the rate of non-disabled peers. The European Accessibility Act took effect in June 2025 and the US DOJ’s Title II rule requires WCAG 2.1 AA by April 2026 [2], yet most institutions still lack a structured way to address the overlapping layers of content accessibility.

In many institutions that I worked with, accessibility is treated as a single condition — content is either accessible or it is not. But that misses the reality. A lecture recording might be available on the LMS but lack captions or transcript. A handbook may include alt text but still be written in dense, impenetrable language. Even clearly written readings can be locked into fixed-layout formats that cannot resize or reflow. These are different problems, and they need different responses.

Framework and Methodology

The Hierarchy of Effective Learning Content was developed over five years of hands-on work with more than 100 higher education institutions, including accessibility audits, staff training, and content remediation projects. One pattern kept coming up: institutions were investing in higher-level interventions — readability, adaptable formats, UDL — while foundational issues around availability and basic digital accessibility remained unresolved. The framework organises these requirements into five levels arranged as a dependency chain, modelled on Maslow’s hierarchy, where each level creates the conditions for the next.

The five levels are: Availability (can learners reach the content across formats, devices?), Digital Accessibility (does it conform to WCAG [3] for assistive technology users?), Readability (is it written in plain language with clear headings?), Adaptability (can learners resize text, adjust spacing, or use text-to-speech?), and Universal Design for Learning (was it designed from the start for learner variability?). The framework draws on international standards, sector data (WebAIM, Jisc Digital Experience Insights), cognitive load research, and UDL evidence.

Implementation and Impact

Across institutions, one thing was consistently clear: staff are subject matter experts, not accessibility experts, and they should not need to be. The hierarchy gives them a starting point. It is not a checklist — it is a dependency chain. Investing in UDL when students cannot even reach the content is building on a foundation that does not exist. The framework has been developed into a whitepaper, a modular presentation system, and a five-part reflective workshop where teams audit their practices level by level.

The evidence at the top level is strong: a 2025 longitudinal study of 2,473 learners across 87 facilities found full UDL implementation produced a 37.4% increase in overall performance and 42.8% for previously disengaged learners [4]. But those gains depend on the lower levels being in place. Learner variability is the norm, not the exception. The hierarchy exists to help institutions design for that reality, from the foundation up.

This session will present inclusive practices embedded in an online class. Specific practices that deal with course structure, visual and multiple modes of learning, and assessment can make a course more accessible, understandable, and welcoming to students, as noted in the CAST UDL Guidelines (2024).

In terms of course structure, we revised a course so that the names and sequences of learning activities mirror main course concepts and processes. The course, whose topic of experiential learning is new and difficult for many students, frames the learning activities in terms of the experiential learning cycle and also explains this structure directly to students as they move through, to make the abstract concept of experiential learning concrete.

In terms of visual and multiple modes of learning, the course includes strategic visuals that enhance key concepts, providing alternatives to text. A key aspect that supports visual learning and inclusiveness is a course map that uses an appropriate metaphor to show how the course progresses. The course map highlights the pieces of the course and how they fit together; it helps students see how different learning activities contribute to the purpose and focus of the course. Videos and AI interactive activities offer students additional ways to engage with information.

In terms of assessment, the course uses a labor-based rubric, something which has been shown to create a more supportive environment less focused on grades and more focused on student effort and instructor feedback. In a processed-based course in which students need to go through stages and incorporate feedback, assuring a passing grade based on student engagement helps to create a more equitable experience for students, one in which they can focus more fully on exploring their learning. Additionally, the labor-based rubric is explained using student-friendly content and language, as suggested by Pacansky-Brock et.al. (2020).

Although we will illustrate these practices using examples from a course on credit for prior learning, the practices are applicable to many fields and can be used to promote inclusion and support students by making learning activities transparent.

Key findings have been positive. As a result of embedded inclusive practices, students are engaging in course learning activities more quickly with better results.

CAST (2024). CAST Universal Design for Learning Guidelines version 3.0. Retrieved from https://udlguidelines.cast.org

Pacansky-Brock, M., Smedshammer, M., & Vincent-Layton, K. (2020, June 18). “Shaping the Futures of Learning in the Digital Age: Humanizing Online Teaching to Equitize Higher Education.” Current Issues in Education. https://cie.asu.edu/ojs/index.php/cieatasu/article/view/1905/870

The aim of the presentation is to explore a problem of practice in Higher Education regarding Assistive Technology (AT) for Students with disabilities (SWD). AT has a powerful voice internationally in inclusion, as the UNCRPD, the SDGs, and UDL advocate for the role of AT in inclusive Education. One way SWDs are supported in Education is through the provision of recording tools that help them supplement their notes. This 'reasonable accommodation' that our Irish Disability law supports, so SWDs can have the right to these recording tools, has now advanced with the introduction of AI. Each Irish University has an AI recording tool that embeds AI in various ways, depending on the tool, and offers new ways to support neurodiverse and sensory-impaired students. AI can convert recordings into transcripts and generate quizzes from recordings, for example, both useful ways to engage with information and to self-evaluate their learning. In light of AI's progress in enhancing AT in education, there is concern about AI and how it uses and stores information. With the introduction of AI, does this remove learning effort from our students? How do we gauge if AT is enabling or doing too much? The presentation will explore these questions.