Digital and future literacies are increasingly central to how students learn, communicate, and participate in higher education. For many learners entering FFUR courses, online and blended delivery provides flexible, accessible pathways into university while helping them build the digital skills and confidence needed for ongoing study.

As digital tools and emerging technologies such as GenAI shape the ways students engage with learning, FFUR courses continue to draw on enabling pedagogies that prioritise equity, relational learning, and student‑centred design. High‑quality online and blended approaches create opportunities for active participation, authentic assessment, strong teacher presence, and inclusive access, ensuring students feel supported, capable, and connected as they begin their higher education journey.

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Online and Blended FFUR Delivery Modes

Many established providers offer their FFUR units through online and flexible delivery models that ‘blend’ face to face with online learning opportunities. Online and ‘blended’ learning spaces open pathway opportunities for students who would otherwise be unable to access uto enter undergraduate study. This includes students who live significant distances from campuses, are unable to afford travel and time away from work and caring responsibilities and/or who live with a disability which could impact participation. Providers of online FFUR offerings embrace practices that are underpinned by the ethos of ‘Enabling’ and transition pedagogies, while also addressing challenges specific to online cohorts.

As FFUR programs adapt to GenAI, online courses face challenges in verifying student identity and using assessments that show learning without requiring campus attendance. Strategies such as varied assessment types, process-focused tasks, whole of course-level assessment, interactive online oral exams, and proctored tests can help maintain academic integrity. It is also important to follow core principles: ensure assessments align with learning outcomes, foster teacher presence and connection in online spaces, and teach academic intregrity as a skill (Dollinger et al, 2025).

Online and blended courses play an important role in ensuring that FFUR courses are flexible and inclusive. Like all FFUR courses, online and blended approaches should:

Be underpinned by the types of enabling pedagogies which sit at the core of practice

This includes values around inclusion, social justice, and approaches that are fundamentally student-centred and strengths based (Bennett et al., 2018)

Examples of this in online and blended modes include:

  • Providing opportunities for digital community building and sharing from the outset. This could include engaging students in a discussion of class etiquette to co-develop rules of conduct for interacting online. You could also offer an ongoing ‘Casual Chat’ page where students can choose to share news or appropriate updates from their personal lives.
  • Orientation or ‘Week 0’ activities that provide the opportunity for students to practice engaging through the LMS in a low-stakes way that can allow early identification of additional needs.
  • Incorporating an Introductions page as part of your online course, where students can ‘meet’ each other, offer information about their personal or professional history and share what they hope to achieve in studying the course. This page could also link to the AIATSIS Map so students can acknowledge and share the land they live and work on.
  • Inviting students to draw connections between weekly concepts learned and their own lives and experiences. Carefully chosen videos are a useful resource that can offer real life examples to learn about discipline concepts.
  • Recognising the importance of cultural safety for Aboriginal and Torres Strait Islander students and other diverse communities and embedding Aboriginal and Torres Strait Islander knowledges and perspectives.
Embed academic literacies within discipline-specific contexts and provide opportunities for both active and dialogical learning

Online FFUR courses should be designed so that students are not passive recipients of content but engage through doing, discussing and reflecting. Active learning includes scaffolded tasks such as problem-based activities, low-stakes quizzes, collaborative group work, and authentic assessment tasks that allow practice and application. Dialogical learning emphasises reciprocal exchange between students and educators as well as peer-to-peer dialogue and building knowledge collectively rather than transmitting it one-way (Motta and Bennett, 2018).

Examples of this in online and blended modes include:

  • Short ‘micro-lessons’ either interactively or through videos that are ‘just in time’ academic literacies relevant to that week. Units can include a weekly, interactive asynchronous page devoted to academic literacies that are expanded upon in synchronous learning opportunities and encourage students to keep a glossary of key terms that is added to throughout the course.
  • Synchronous interactive H5P activities embedded into weekly modules, such as drag and drop, quizzes with feedback and interactive scenarios.
Be designed for equitable access

This involves using quality assurance standards that emphasise inclusivity, accessibility, and the core principles of UDL, providing multiple means of engagement, representation, and expression. At the FFUR level, UDL also requires recognising digital equity as a real challenge for many students. This includes issues such as limited access to appropriate hardware, software, internet connectivity, safe study spaces, and the digital literacies needed to participate effectively. Institutions share responsibility for addressing these challenges (Stone, 2016) through initiatives such as laptop‑loan schemes, discounted devices through the student union, and 24‑hour Wi‑Fi in secure study areas on campus.

Assessment design should also acknowledge students’ varied learning contexts and be suitable for online and flexible modes of study. This includes maintaining authenticity, academic integrity, and enabling principles.

Examples of this in online and blended modes include:

  • Using a consistent layout, structure, and navigation across the LMS for all courses, regardless of discipline. This is especially important in FFUR courses, where students may have little prior experience with an online LMS. Consistent design makes the “hidden curriculum” more visible by demystifying the online environment and reducing students’ cognitive load. Stone (2017) highlights that clear, consistent structure and intuitive navigation support student retention: when learners can easily find their materials, know how to move through the course, and access support services, they are more likely to complete successfully.
Focus on relationality

Teachers should be actively engaged and visible across all teaching spaces, including online environments. Research consistently shows that strong teacher‑presence is essential for building students’ sense of belonging, identity and community. FFUR programs take a broad view of ‘teacher‑presence’, extending it to include visibility and connection with institutional support services as well.

A collaborative approach to online learning that integrates support services, the people behind those services, and provides these supports just in time is more likely to strengthen students’ institutional knowledge and contribute to retention (Stone, 2016). Embedding opportunities for connection and support also helps cultivate online community and enhance students’ sense of belonging (Irwin & Hamilton, 2019).

Examples of this in online and blended modes include:

  • Providing a visible and active teacher-presence, for example, by using LMS analytics to provide personalised messages to students are inactive or who should be congratulated on their efforts.
  • Posting weekly or regular announcements or videos that address key issues in the course as they arise and provide important updates and expectations.
  • Maintaining a clear presence in discussion forums by responding to posts, weaving concepts together and modelling academic language and conduct.
  • Building community by providing opportunities for students to share their own experiences and relate those experiences to content, achieved through platforms like discussion forums or Padlets.
  • Using break out rooms in facilitate group work or problem-solving activities that require interactivity and using group messages to acknowledge progress within the course.
  • Collaborating with support services by incorporating shared resources or linking to services in context, providing drop ins or in-class time facilitated by support services, and embedding support service details within courses including photographs alongside information.
  • Strengthening institutional relationships through consistent branding and layout to emphasise the connection between FFUR courses and undergraduate courses within the institution.
Be flexible in conjunction with clear expectations

High quality asynchronous learning material and engagement opportunities should exist alongside opportunities for synchronous interaction with peers and educators. Accompanying this, there should be clear articulation around how and when students should engage with material to ensure the most ideal student experience.

Examples of this in online and blended modes include:

  • Clear communication about expectations in terms of what is required and what is good to do.  This could include consideration to communication channels, weekly checklists and indication of participation norms.
  • Balancing clear expectations with opportunities for autonomy. For example, making asynchronous learning materials available well in advance of required completion, with guidance as to pacing; structuring catch-up or conceptually less challenging content at peak assessment periods.
  • Using the LMS to engage meaningfully with students showing signs of disengagement or challenges including reduced interaction, reduced attendance, extension applications, or late assessment submissions.
  • Building opportunities for flexibility where possible. For example, provide submission or engagement windows, and recordings of sessions that do have fixed times.
Maintain quality standards and continuous improvement

Educators should remain responsive to current research on best practice in FFUR courses. Recent literature highlights the importance of ongoing student feedback and the continuous improvement of units and courses based on insights from students and staff, performance against agreed evaluation metrics, and developments in technology and pedagogy. This includes embedding student voices through co‑design processes.

Courses should also be benchmarked against recognised sector frameworks for online learning (e.g., TEQSA Online QA Toolkit, 2017; ACODE TEL Benchmarks, Sankey et al., 2024) to ensure quality is monitored and enhanced.

Examples of this in online and blended modes include:

  • Implementing course review processes that specifically evaluate online components.
  • Providing regular professional development opportunities for educators.
  • Establishing clear institutional guidelines for online delivery.
  • Using learning analytics and qualitative student feedback to identify and action improvements.
  • Facilitating student co‑design forums to inform ongoing refinement.
Rethink engagement and success

As with on-campus delivery modes, educators must reconsider what student engagement and success look like in online FFUR spaces. Learning analytics can be helpful in identifying when students may benefit from check-ins or additional support. However, analytics alone cannot capture the depth of engagement or whether transformational learning is occurring.

Understandings of success in FFUR should shift from metrics-driven ideas of completion and transition into undergraduate courses to more nuanced understandings of success as non-linear. This recognition is especially critical for online learning environments, where attrition rates are typically higher and transition rates into undergraduate study lower. These metrics are shaped by factors outside the unit or course itself, including the important low-stakes nature of online FFUR education, positive attrition, and the lived experience of compounding disadvantage (Allen, 2025).

Examples of this in online and blended modes include:

  • Tracking multiple forms of engagement and recognising that engagement may be intermittent due to competing life commitments. Educators can use LMS data and short, personalised communications to reach out to students whose engagement patterns suggest they may need support, and to open dialogue about available services or potential ‘re-entry’ points into the unit.
  • Incorporating reflection tasks that encourage students to map out their progress, celebrate achievements, and identify areas for further growth helps students redefine what success means for them. In FFUR online contexts, many successes happen off-screen, between modules, or after the unit concludes, and may not be quantifiable in metrics such as transition into undergraduate study.
  • Using strengths based and inclusive language helps students stay motivated, build confidence and understand their learning in ways that acknowledge achievements beyond narrow or quantitative measure.
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When I was doing Open Foundation, I did a mixed approach to my classes. It worked really well for me. I was working at the time and the online component really me to keep those regular hours at work without committing too much time elsewhere and spending so much time travelling.

Tahnee
FFUR Student

Open Foundation was the first step in me changing my life and fulfilling the potential that I had.

Dom
FFUR Student

… the lecturers treated me like an adult, and spoke to me in ways that empowered me. I felt happy, elevated and capable. I was excited to finally start my university career.

Kristen
FFUR Student

Generative AI in Equity Education

Artificial Intelligence (AI) holds significant potential to enhance equity and inclusion in teaching and learning within higher education, primarily by offering personalised support, increasing accessibility, and democratising access to knowledge. However, its integration must be carefully managed to mitigate substantial risks of reinforcing existing biases and creating new forms of exclusion.

The integration of Generative AI (GenAI) tools into equity education settings, such as FFUR offerings, should:

  • Empower both educators and students through the responsible and ethical use of GenAI in teaching and learning.
  • Cultivate strong digital and AI literacies that set FFUR students up for success in future study and professional settings.
  • Consider and address the unique challenges faced by equity students to bridge educational gaps (James & Andrews, 2024) and where GenAI can support or empower these students.

GenAI in Curriculum Design and Delivery

The rise of GenAI has prompted a rethinking of how academic literacies are delivered in FFUR courses. As GenAI becomes a prevailing feature in educational, professional, and societal spheres, students will need to develop strong critical AI literacy skills. Therefore, educators must not determine how these competencies are integrated and emphasised within their curricula (Pike & Ulpen, 2025)

Integrating GenAI into higher education curriculum design and delivery is a complex but necessary undertaking, moving beyond mere technological adoption to a fundamental reimagining of educational purpose and practice. This shift necessitates a focus on several key principles that ensure GenAI is leveraged responsibly, ethically and actively in a society where it is ubiquitous (Lodge et al., 2023).

The following principles should be considered when integrating GenAI into FFUR curriculum design and delivery:

Ensure regulatory compliance and academic integrity by design
Situate development of GenAI literacy within discipline contexts
Promote transparency, trust, courageous experimentation, and collaborative learning
Be conscious of the issues and embed opportunities to address them.

James and Andrews (2024) suggest that incorporating GenAI tools into FFUR courses can help students from underrepresented cohorts close gaps in cultural capital and demonstrate their understanding more effectively in higher education settings. These tools can enhance comprehension, support clear expression of ideas in academic contexts, offer writing feedback, suggest additional resources, and simplify complex content (Crawford et al., 2023), providing students with opportunities to strengthen language proficiency and overall academic performance.

Tishcoff et al. (2024) also outlines how GenAI has the potential to make learning more accessible for students. Potential benefits include:

Enhanced Accessibility and Accommodations

AI can serve as a powerful assistive technology for students with diverse needs. This includes helping neurodivergent students organise and reprocess material, supporting students with communication disabilities or those learning in a second language, and aiding students in various aspects of learning and assessment.

Personalised Learning and Support

AI offers opportunities for personalised student support, including personalised learning paths and content. AI tutoring chatbots, mock interviews with AI avatars, and real-time feedback systems can be accessed at any time, catering to individual learning preferences and schedules.

Despite its potential, GenAI presents significant challenges that could exacerbate existing inequalities if not addressed proactively, including:

Widening Digital Divide and Inequitable Access

GenAI risks widening existing digital divides, particularly for marginalised, low-income communities and countries (Liu, 2024). Equitable access requires deliberate interventions to provide AI tools and infrastructure for all students and staff.

Algorithmic Bias and Discrimination

GenAI is not a neutral tool; it reflects and reproduces the cultural, linguistic and epistemological assumptions embedded in its data. Rather than merely viewing these biases as technical flaws, educators can examine how such tools intersect with the structural inequalities already present in higher education (Grammatica, 2025).

Reinforcing Over-reliance and Undermining Critical Thinking

There is a risk that GenAI could lead to an over-reliance on technology, potentially causing the atrophy of essential cognitive skills like critical thinking, intellectual development, creativity and originality of expression. Therefore, GenAI tools should be used in an educative mode to extend cognitive abilities and support ethical intellectual habits (James, & Andrews, 2024)

Artificial Intelligence, Academic Integrity and Secure Assessment

Assessment provides evidence of students’ achievement of learning outcomes and supports their ongoing learning. While inappropriate use of GenAI tools can undermine confidence that assessments reflect genuine learning, they also prompt educators to refine assessment and prepare students to engage with GenAI ethically and authentically (NAEEA Executives, 2023).

As GenAI becomes increasingly capable of performing well in assessments, there is a growing recognition across the sector that “unsupervised assessments are no longer able to assure attainment of learning outcomes” (Liu & Bates, 2025, p.11). Delivering this assurance will require a focus on assessment “security at meaningful points across a course to inform decisions about progression and completion” (Lodge et al 2023)

As Pike & Ulpen (2025) highlight, the various tensions that can exist from an equity perspective when incorporating secure assessment into curriculum, FFUR educators face the challenge of ensuring student attainment of learning outcomes without creating new barriers for equity cohorts. To preserve the principles of equity education, approaches should be educative rather than punitive by utilising feedback loops, account for different learning modes, and emphasise critical literacy skills to develop an understanding of how GenAI works and when to apply it responsibly.

TEQSA’s toolkit outlines a number of potential approaches “to ensure the integrity, fairness and validity of academic assessments” (TEQSA, 2024, p.43)

Case Study

Context

Treesa, a FFU educator in literacy-intensive subjects, faced challenges as generative AI use grew among students. Many learners were from equity cohorts, including those with neurodiversity, mental health challenges, and past literacy difficulties. Initially, AI use was prohibited, but this punitive approach disproportionately affected students needing the most support and created barriers to progression.

Problem

Early assessments designed to scaffold academic literacy were showing signs of GenAI influence, yet detection tools only flagged outputs above 350 words. Students unfamiliar with technology often used AI unknowingly through integrated tools, while others relied on it due to low confidence in their writing skills. The strict “no AI” policy led to increased academic integrity concerns, delayed feedback, and higher intervention referrals.

Intervention

Treesa shifted from prohibition to “somewhat permitted AI use”, reframing AI as an educative tool rather than a punitive trigger. Key steps included:

  • Week 2–4: Introducing AI guidelines and library resources on ethical use and referencing.
  • Week 6: Providing feedback on early assessments, including advice on maintaining integrity when using AI.
  • Week 10: Transforming the final assessment question into an AI prompt. Students generated outputs, critically reviewed structure, ideas, and sources, and learned how to acknowledge and reference AI contributions.

The assessment rubric was updated to include explicit criteria for AI use and academic integrity. Marks were adjusted for unacknowledged AI outputs, hallucinated sources, and lack of critical engagement. A feedback comment bank supported consistent, constructive feed-forward across the marking team.

Outcomes

The approach yielded significant improvements:

  • Timely feedback restored, reducing delays in learning support.
  • No academic integrity referrals and minimal incomplete grades.
  • Positive student experience, with feedback from students appreciative for explicit assessment.
  • Improved communication quality in submissions, as AI-supported students produced clearer, more structured work.

Key Insight

Embedding AI use within enabling pedagogy—through structured guidance, transparency, and critical literacy—can transform AI from a threat to academic integrity into a tool for equity, confidence-building, and authentic learning.

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The Fee-Free Uni Ready Best Practice Guide cover image.

Fee Free Uni Ready Pathways: Developing Stronger, More Equitable Universities and Communities

This comprehensive Best Practice Guide is designed to guide higher education practitioners in the design and delivery of high-quality FFUR courses through best practice. Prepared by the University of Newcastle in collaboration with higher education institutions and educational experts across Australia, this guide provides evidence based recommendations developed in line with current and contemporary research. Filled with practical, real world advice and implementable processes, this guide is useful for all higher education providers, whether they are in the process of designing FFUR courses or have offered them in the past.
pdf 46.11MB Download the Best Practice Guide