Cultivating Critical AI Literacy and Trustworthy Learning Practices in Online and Blended Courses

Introduction

As artificial intelligence tools become increasingly embedded in education, students and educators are no longer just users of technology; they are participants in systems that shape knowledge production, decision-making, authorship, and truth. In this context, developing critical AI literacy is not optional but essential. Learners must understand not only how AI systems function, but also the social, ethical, and epistemological implications of relying on them in academic spaces. In online and blended learning environments, where technology already mediates interaction, assessment, and content delivery, the presence of AI introduces new questions about credibility, authorship, bias, transparency, and trust. Cultivating critical AI literacy, therefore, becomes fundamental to sustaining meaningful learning, protecting academic integrity, and maintaining trust between learners, educators, and institutions. This reflection explores how pedagogically responsible AI integration can be supported through intentional design, strong social presence, and community trust.

Understanding AI Beyond the Tool: From Usage to Literacy

Many students approach AI as a productivity shortcut: drafting, summarizing, generating, or translating content. However, critical AI literacy requires moving beyond functional use to informed awareness and evaluation. Siau and Wang (2020) emphasize that Artificial Intelligence does not simply execute commands; it interprets patterns from data shaped by human decisions, historical biases, and power structures. Therefore, using AI uncritically risks reinforcing misinformation, inequality, and epistemic injustice.

In online learning spaces where students increasingly rely on AI to support writing, coding, research, and even reflection, educators must guide learners to ask deeper questions, such as:

• Who created this system, and what data trained it?
• Whose perspectives are missing or underrepresented?
• What assumptions does the algorithm reproduce?
• How might this output mislead, manipulate, or oversimplify knowledge?

Through explicit instruction and classroom dialogue, students can begin to see AI not as an omniscient source, but as a constructed, fallible, and contestable tool (Siau & Wang, 2020).

Developing Critical AI Literacy

Critical AI literacy extends beyond the ability to use AI tools; it involves understanding how these systems function, questioning their outputs, and recognizing their limitations. Students must be trained to evaluate AI-generated content, identify bias, verify claims, and understand that AI systems are trained on historical data that often reflects social inequalities and epistemological biases (Siau & Wang, 2020).

Rather than positioning AI as an unquestionable authority, it should be reframed as a probabilistic support system that requires human judgment. Instructors can foster this mindset by designing tasks that require students to compare AI outputs with peer-reviewed sources, justify why certain outputs are trustworthy or problematic, and reflect on how prompts shape the responses generated. These practices support meta-cognitive awareness and reinforce the idea that critical thinking, not convenience, remains at the heart of learning (Siau & Wang, 2020).

This directly addresses the need for students to:

• Evaluate outputs rather than accept them as fact

• Identify bias and cultural framing in AI responses

• Fact-check information with credible sources

• Understand how training data shapes responses

• Recognize AI’s lack of contextual and ethical reasoning

AI, Trust, and Epistemic Responsibility

Trust is a cornerstone of successful online learning communities. Learners must trust the content, the instructor, the platform, and each other. However, when AI begins to generate answers, feedback, translations, and even grading suggestions, this trust can become destabilized. Students may either over-trust AI (seeing it as neutral and authoritative) or distrust the entire learning ecosystem.

Siau and Wang (2020) argue that this tension makes it essential to frame AI as an assistant rather than an authority. Cultivating critical AI literacy helps students understand that:

• AI outputs are probabilistic rather than factual
• AI does not possess consciousness, intention, or moral judgment
• AI reflects dominant patterns, not universal truths
• Human responsibility is never removed from decision-making

By reinforcing human agency, instructors transform AI from a source of dependence into a site of critical inquiry, encouraging students to verify, challenge, compare, and expand upon AI-generated content rather than submitting to it (Siau & Wang, 2020). This practice not only protects academic integrity but also strengthens students’ sense of epistemic responsibility, their accountability as knowledge producers rather than passive consumers.

Designing for Ethical and Transparent AI Practices

In blended and online courses, critical AI literacy must be supported at the level of instructional design and not left to individual curiosity. According to Siau and Wang (2020), institutions and educators have an ethical obligation to ensure that AI integration is transparent, fair, and human-centered.

This can be encouraged through:

• Open discussion of when and how AI may be used in coursework
• Clear policies distinguishing support from misconduct
• Reflective tasks asking students to analyze AI’s strengths and weaknesses
• Comparative work between human and AI-generated outputs
• Critical reflection on bias, hallucination, and misinformation

Instead of banning AI or fully embracing it without limits, this approach teaches discernment. Students learn to see AI as an object of study itself—one that reveals broader questions about power, surveillance, authorship, and control in digital society (Siau & Wang, 2020).

Social Presence, Trust, and Responsible AI Use

Social presence is a critical mediator between technological use and ethical behavior. When learners feel seen, valued, and emotionally connected within an online community, they are more likely to engage responsibly and transparently (Garrison et al., 2000; Swan & Shih, 2005). Trust reduces the perceived need to cheat and increases accountability to the group.

In communities where dialogue is encouraged and reflection is shared openly, students feel safer discussing their use of AI tools, concerns, and uncertainties. This promotes collective norm-building around responsible use rather than isolated decision-making driven by fear of punishment.

Instructors can support this by:

• Modeling transparent AI use themselves

• Encouraging open discussions about ethical dilemmas

• Normalizing mistakes as learning tools

• Establishing shared values at the group level

This aligns with research suggesting that community trust directly influences participation, honesty, and long-term engagement in collaborative environments (Richardson et al., 2017).

Blending Synchronous and Asynchronous Modalities

A thoughtful combination of synchronous and asynchronous activities can further support critical AI engagement. Synchronous sessions encourage real-time dialogue, group reflection, and ethical debates. Asynchronous forums allow for slower, more structured critical thinking and academic feedback.

For example:

• Students may use AI tools asynchronously, then critically discuss their findings in live sessions

• Real-time debates can address emerging AI ethical challenges

• Peer feedback can focus on how AI was (or wasn’t) effectively used

This blended model discourages passive consumption and promotes intentional, reflective engagement.

Connections to Other Themes

Relation to Lia – Group Learning and Collective Responsibility

While Lia emphasized collaboration in human groups, critical AI literacy expands the idea of collective responsibility into the digital realm. If group work builds empathy, tolerance, and shared meaning (Dron & Anderson, 2014), then AI literacy ensures that technology does not undermine that human connection but rather supports it transparently. In other words, ethical AI use must be embedded within the same principles of respect, dialogue, and collective accountability that define effective group learning. Lia’s application of Salmon’s Five-Stage Model can be strengthened through AI by using it as a scaffold at each stage (e.g., AI-supported introductions in Stage 2, AI-curated resources in Stage 3, and AI-facilitated debate prompts in Stage 4), provided that human facilitation and reflection remain central.

Relation to Andreas – Reflection, Identity, and Critical Distance

Andreas’ reflection on learning, self-awareness, and identity connects strongly to AI literacy. To use AI critically, learners must be aware of their own thinking, values, and intentions. When students reflect on why they used AI, what they accepted or rejected, and how it shaped their thinking, AI becomes a mirror revealing cognitive habits rather than a silent, invisible author. This metacognitive awareness strengthens autonomy instead of eroding it. Andreas’ comparison raises a critical point: while AI may generate more up-to-date, tool-rich course designs, it can easily miss deeper pedagogical sequencing, affective dimensions, and epistemological intent, positioning AI best as an enhancer or co-creator rather than a replacement for instructional expertise.

Relation to Mary – Enhancing Accessibility Through AI-Supported Course Revision (Mary)

Mary’s reflection introduces a vital dimension: the use of AI to enhance inclusion and accessibility in online and blended learning environments. AI can support instructors in revising learning materials to align with WCAG guidelines, ensuring that content is accessible to learners with visual, auditory, cognitive, or physical impairments. This application reframes AI not as a threat to pedagogy, but as a tool for inclusion and equity. In low-connectivity contexts, AI-generated modular content (PDFs, transcripts, lighter file formats) can make education more sustainable and globally accessible. However, as with all AI uses, these adaptations require human validation to ensure cultural accuracy, precision, and appropriateness (Popescu et al., 2014).

Relation to Social Presence and Third Spaces

Online learning spaces operate as “third spaces,” i.e., hybrid environments where personal, academic, and technological identities intersect. In this space, AI becomes a powerful participant. Without critical awareness, it can distort authenticity and voice. With critical literacy, however, students reclaim ownership of meaning, ensuring that their online presence remains human, grounded, and accountable rather than algorithmically replaced.

Conclusion

Artificial intelligence is reshaping education, but its impact will depend on how consciously and critically it is integrated. As Siau and Wang (2020) stress, AI must not replace human thinking but rather provoke it. In online and blended learning contexts, cultivating critical AI literacy is essential to preserving trust, integrity, and human agency. By teaching students to interrogate AI, question its authority, and reflect on its influence, educators empower them not only as learners but as ethical participants in a technologically mediated world. Ultimately, the question is not whether AI should be used in education, but how, and more importantly, who remains in control. Through critical AI literacy, the answer can (and should) remain: the human learner.

References

Dron, J., & Anderson, T. (2014). Teaching crowds: Learning and social media. Athabasca University Press.

Garrison, D. R., Anderson, T., & Archer, W. (2000). Critical inquiry in a text-based environment: Computer conferencing in higher education. The Internet and Higher Education, 2(2–3), 87–105.

Popescu, A., Fistis, G., & Borca, C. (2014). Behaviour attributes that nurture the sense of e-learning community perception. Procedia Technology, 16, 745–754.

Richardson, J. C., Maeda, Y., Lv, J., & Caskurlu, S. (2017). Social presence in relation to students’ satisfaction and learning in the online environment: A meta‐analysis. Computers in Human Behavior, 71, 402–417.

Salmon, G. (2000). E-moderating: The key to teaching and learning online. Kogan Page.

Siau, K., & Wang, W. (2020). Building trust in artificial intelligence, machine learning, and robotics. Cutter Business Technology Journal, 33(2), 47–53.

Swan, K., & Shih, L.-F. (2005). On the nature and development of social presence in online course discussions. Journal of Asynchronous Learning Networks, 9(3), 115–136.

Introduction:
In this topic, we explored how trust, motivation, and intentional structure shape effective collaboration in online and blended learning environments. Our discussions and readings examined the foundational role of social presence in helping learners feel visible, connected, and willing to engage meaningfully with others. We then looked at how collaborative learning networks are formed, how groups develop over time, and how teachers can support this process through clear facilitation, motivational strategies, and well-designed activities. Practical frameworks such as Salmon’s (2000) five-stage model of online group development, Wlodkowski’s (2004) motivational principles, and the Community of Inquiry framework (Garrison et al., 2000) helped us understand how emotional expression, communication, and group cohesion contribute to deeper learning.

We also examined the practical side of collaboration—from defining group roles and communication norms to establishing ground rules that promote fairness, accountability, and shared ownership of work. Insights from interdisciplinary project-based learning illustrated how diverse groups navigate expectations, distribute tasks, and overcome challenges when working across different professional cultures. Together, these perspectives highlight that collaborative learning is not merely dividing tasks; it is a social, cognitive, and emotional process that relies on trust, structure, and ongoing reflection to create meaningful and sustainable learning communities.

The Role of Social Presence in Building Trust and Collaboration in Online Learning Communities (Sally)

Social presence plays a foundational role in the creation of meaningful, trusting, and collaborative online learning communities. In digital environments—where physical cues and spontaneous interaction are limited—the ability to appear “real,” visible, and emotionally engaged becomes essential for learners to feel connected and willing to participate.

1. Social presence strengthens community building:
Being authentically present in an online space allows learners to feel seen and valued, which directly contributes to stronger community bonds. When students sense emotional expression, open communication, and group cohesion, they become more comfortable entering dialogue, sharing perspectives, and negotiating meaning with others. This kind of engagement strengthens the resilience of learning communities, as members become more motivated to contribute and more supportive of one another (Garrison, Anderson, & Archer, 2000). A high degree of social presence doesn’t just enhance participation—it reinforces a shared identity as a learning group.

2. High social presence increases trust and reduces isolation:
A strong perception of social presence significantly increases student trust, satisfaction, and perceived learning. Trust is critical in collaborative learning because it lowers the emotional risk of participation. Students who feel connected to their peers are more willing to share incomplete ideas, ask questions, and engage in problem-solving without fear of judgment or criticism. This becomes especially important in asynchronous contexts, where feelings of isolation can easily emerge if social cues are weak or inconsistent (Swan & Shih, 2005). When trust is established, students shift from passive recipients of content to active co-creators of knowledge, resulting in more meaningful collaboration and deeper learning.

3. Social presence can be intentionally fostered through design:
Social presence is not something that emerges automatically; it must be intentionally supported through thoughtful instructional design and facilitation. Educators can foster it by integrating structured introductions, video-based reflections, peer feedback cycles, collaborative writing spaces, and low-stakes synchronous check-ins that humanize interaction and make participation feel safer. Research on instructor immediacy shows that behaviors such as maintaining a warm tone, responding promptly, and communicating approachability significantly strengthen students’ sense of community and engagement (Richardson, Maeda, Lv, & Caskurlu, 2017). When these design choices are embedded consistently, learners experience online spaces as relational rather than transactional, making collaborative work more genuine, supportive, and productive.

Overall, social presence functions as the connective tissue of online collaboration: it enables trust, fosters belonging, and creates the interpersonal conditions required for deep, shared learning. These dimensions of social presence highlight that effective collaboration does not arise spontaneously—it must be intentionally nurtured through design and shared expectations. This provides a natural transition to the next section, where Lia outlines a practical, structured activity for establishing group rules that support equitable participation, clear communication, and sustained teamwork.

A Practical Activity for Defining Group Rules During Class (Lia)

Collaborative learning only succeeds when expectations, responsibilities, and communication processes are explicitly defined. Lia’s activity offers a concrete, structured way to co-create group norms that support fairness and accountability.
Activity Structure:

1. Group Formation – instructor-assigned, self-selected, or randomized.
2. Small-Group Discussion (≈45 minutes) – teams examine roles, communication, transparency, and reflection.
3. Whole-Class Sharing – groups compare decisions and refine rules.

Topics for Discussion:

• Roles & Responsibilities: rotating leadership, editors, presenters, and shared responsibility for final outcomes.
• Communication: meeting schedules, platforms (email, chat, shared docs), expectations for attendance, agendas, and notes.
• Transparency: shared folders, version history, consensus-building, and equitable workload distribution.
• Reflection: individual or group reflection on successes, challenges, and plans for future improvement.

A written agreement (signatures, date) reinforces commitment.
This type of structured rule-setting reflects what Salmon (2000) emphasizes: early stages of online collaboration must focus on socialization, clarity, and scaffolding to ensure that later stages—knowledge construction and development—happen effectively.

Creating Motivating Learning Environments (Mary)

Drawing on Wlodkowski’s (2004) framework for adult learning motivation, Mary highlights that learning environments—whether F2F, hybrid, synchronous, or asynchronous—must intentionally support. I found the following aspects integral to the learning environment from the framework:

• Inclusion: ensuring every learner feels respected and welcomed.
• Attitude: cultivating interest and positive disposition toward learning tasks.
• Meaning: connecting activities to learners’ real experiences and needs.
• Competence: enabling learners to experience growth, mastery, and self-efficacy.

These four motivational conditions directly reinforce group collaboration by fostering commitment, persistence, and interpersonal respect—key elements for any successful online learning community.

The Relevance of Thinking Together (Rotich)

Rotich emphasizes the conceptual vocabulary of collaborative thinking through three interrelated processes:

• Cooperate: moving in the same direction by sharing goals freely.
• Collaborate: actively working together—“laboring together”—to produce shared outcomes.
• Coordinate: organizing how tasks, roles, and sequences of work unfold.

These distinctions align with Dron and Anderson’s (2014) argument that collaborative learning requires not only joint effort but also structured interaction, mutual influence, and shared responsibility. Thinking together is not merely intellectual alignment; it is a social, negotiated act that deepens understanding and strengthens community.

Networked Collaborative Learning (Andreas)

Andreas situates collaboration in the context of an interdisciplinary engineering project where students from multiple fields (electrical engineering, computer science, business, physics) form small learning communities. In such environments, ground rules become essential for managing complexity and ensuring balanced participation.

Benefits of Ground Rules:

• Clarify expectations and reduce conflict.
• Support fair task distribution and equitable contributions.
• Foster communication, feedback, and mutual support.
• Help students leverage discipline-specific strengths.
• Maintain focus on learning processes—not just tools.

These insights reflect foundational principles of networked collaborative learning: shared goals, interdependence, and structured coordination (Dillenbourg, 1999). Andreas also notes challenges such as uneven workload or unclear expectations, yet these become opportunities when rules are co-created—enhancing ownership, motivation, and cross-disciplinary learning.

Conclusion

Across all contributions, a shared theme emerges: collaboration thrives when social presence, motivation, structure, and shared responsibility are intentionally cultivated. Whether through designing for trust, establishing group rules, supporting adult learning motivation, or coordinating interdisciplinary teamwork, each element contributes to strong, equitable, and resilient online learning communities. These practices not only support academic success but also develop the communication, empathy, and collaborative problem-solving skills essential for professional life.

References

Anderson, T. (2008). Social software to support distance education learners. In T. Anderson (Ed.), The theory and practice of online learning (pp. 221–241). Athabasca University Press.

Dillenbourg, P. (1999). What do you mean by collaborative learning? In P. Dillenbourg (Ed.), Collaborative learning: Cognitive and computational approaches (pp. 1–19). Elsevier.

Dron, J., & Anderson, T. (2014). Teaching crowds: Learning and social media. Athabasca University Press.

Garrison, D. R., Anderson, T., & Archer, W. (2000). Critical inquiry in a text-based environment: Computer conferencing in higher education. The Internet and Higher Education, 2(2–3), 87–105.

Popescu, A., Fistis, G., & Borca, C. (2014). Behaviour attributes that nurture the sense of e-learning community perception. Procedia Technology, 16, 745–754.

Richardson, J. C., Maeda, Y., Lv, J., & Caskurlu, S. (2017). Social presence in relation to students’ satisfaction and learning in the online environment: A meta-analysis. Computers in Human Behavior, 71, 402–417.

Salmon, G. (2000). E-moderating: The key to teaching and learning online. Kogan Page.

Swan, K., & Shih, L. F. (2005). On the nature and development of social presence in online course discussions. Journal of Asynchronous Learning Networks, 9(3), 115–136.

Wlodkowski, R. J. (2004). Creating motivating learning environments. In M. W. Galbraith (Ed.), Adult learning methods: A guide for effective instruction (3rd ed., pp. 141–164). Krieger Publishing.

Introduction: In this topic, we explored the benefits and challenges of openness in education and learning. Openness can be understood as both an attitude and a practice that transforms how knowledge is created, accessed, and shared. First, we examined the traditional notions of access and inclusion, then moved to the development of Open Educational Resources (OER) and Open Educational Practices (OEP). We also reflected on the role of open licensing (Creative Commons), copyright, and emerging technologies such as generative AI in reshaping the boundaries of education and knowledge.

Today, many universities publish course materials—lectures, textbooks, and course modules—as OERs under Creative Commons licenses that allow users to reuse and adapt content within certain terms. Examples include MIT OpenCourseWare, OpenLearn, MERLOT, Open UBC, and the OER Search Index (OERSI.org). Similarly, millions of media files can be accessed through open repositories such as Openverse, Wikimedia Commons, and Pixabay. These platforms enable educators and learners alike to contribute to the global exchange of knowledge (Wiley & Hilton, 2018).

Open Educational Resources (OER) as a Way of Improving Inclusive and Equitable Access to Education (Lia)

As Lia emphasized, the concept of Open Education is deeply rooted in UNESCO’s call for equitable and inclusive access to knowledge. Following the 2019 UNESCO Recommendation on OER, open education seeks to promote sustainable and resilient knowledge ecosystems by enabling the 5Rs of openness—Retain, Reuse, Revise, Remix, and Redistribute (UNESCO, 2019).

The 2020–2025 post-pandemic context has made this mission even more urgent: open practices now represent both a right and a responsibility toward global equity. In developing contexts such as South Africa or Brazil, OER initiatives (e.g., OpenUCT, Pantheon UFRJ) support lifelong learning opportunities that reduce socioeconomic disparities. However, access alone is insufficient; educators and learners must also be empowered to reuse, repurpose, adapt, and redistribute OERs meaningfully.

AI tools can further scale the reach of open education by translating, adapting, and contextualizing high-quality learning materials for underserved populations (UNESCO, 2023). Yet, as Lia noted, this must be done cautiously to avoid reinforcing the digital divide. The Dubai Declaration on AI and OER (2025) highlights this balance between technological potential and ethical responsibility in digital learning ecosystems.

Open Access Week Conferences and Global Awareness (Mary)

Mary highlighted the global conversation around open access through initiatives like Open Access Week, whose 2025 theme, “Who Owns Our Knowledge?”, continues the dialogue from 2023–2024’s “Community Over Commercialization”. These annual events, supported by organizations like SPARC and UNESCO, promote transparency, collaboration, and fair access to scholarly knowledge.

Conferences such as Behind the Scenes: Open Scholarship (Concordia University, 2025) explore how openness can bridge “third spaces” between academia and the public. Similarly, the SUNY OER Summit (2022–2025) and the University of Calgary’s presentation “Fear of the Unknown: What Really Happens When You Make Your Work Open?” reflect ongoing debates about intellectual ownership, cultural differences in copyright interpretation, and the ethics of sharing across contexts (Adams, 2025).

These initiatives demonstrate that openness is not only a technical or legal question but also a cultural and epistemological one—asking who benefits from open knowledge, and whose voices are represented in it.

Selecting Ways to Share

Selecting how to share educational resources openly depends on the purpose, audience, and level of openness intended. I found several ways to share online: through institutional repositories (like OpenUCT or UFRJ’s Pantheon), dedicated OER platforms (MIT OpenCourseWare, OER Commons, MERLOT), or open media sites (Wikimedia Commons, Openverse, Pixabay). Educators can also share via MOOCs or academic networks such as ResearchGate and Academia.edu, depending on whether the goal is open education, scholarly dissemination, or collaboration (Cox & Trotter, 2017; Hilton, 2020).

1. How Many Ways Are There to Share?

There are multiple modes of sharing educational materials depending on purpose, audience, and licensing preferences:

• Institutional Repositories:
  Many universities maintain open repositories (e.g., OpenUCT, Pantheon at UFRJ, Open Access Scholarly Information Sourcebook) where educators can deposit publications, datasets, and teaching materials under open licenses (Cox & Trotter, 2017).
• Open Educational Resource Platforms:
  Sites such as OER Commons, MERLOT, OpenLearn, MIT OpenCourseWare, Coursera, and edX enable public access to teaching content globally.
• Creative Commons and Open Licensing:
  Sharing can be structured through Creative Commons (CC) licenses, which provide clarity on reuse, remixing, and redistribution rights (Hilton, 2020).
• Wikimedia and Open Media Platforms:
  Wikimedia Commons, Openverse, Pixabay, and similar media repositories allow sharing of images, videos, and music that can complement OERs.
• Academic Social Networks:
  Platforms like ResearchGate or Academia.edu allow semi-open sharing, though often outside the fully open-access ecosystem (Piwowar et al., 2018).

Example: UNESCO’s Recommendation on Open Educational Resources (2019) encourages governments and institutions to support diverse dissemination channels that promote “equitable and inclusive access to quality education.”

2. Who Do I Want to Share With?

Deciding on audience and purpose determines the right channel and license:

• Students: Learning platforms, MOOCs, LMS-integrated OERs (Salmon, 2013).
• Educators/Peers: Institutional repositories, OER Commons, professional networks.
• General Public: Open platforms (YouTube, Wikimedia, blogs) under CC licenses.
• Researchers: Preprint servers (e.g., arXiv, SSRN) or open-access journals for scholarly outputs.

Choosing the audience shapes how openly the material is licensed (for reuse, remix, or adaptation).

3. How Can I Do This?

Practical steps for open sharing include:

• Select a License: Use creativecommons.org/choose to determine the appropriate license (e.g., CC BY, CC BY-SA, CC BY-NC).
• Upload Strategically: Post on trusted OER or institutional repositories rather than only on personal websites for discoverability and credibility.
• Ensure Accessibility: Provide materials in editable and accessible formats (e.g., .docx, .rtf, subtitles on videos) to align with inclusive education goals (UNESCO, 2019).
• Cite and Attribute Properly: Always credit the original creator, and if you remix or adapt materials, clearly indicate your contributions (Hilton, 2020).
• Monitor Use and Impact: Platforms like Zenodo and Figshare provide metrics for downloads and citations to track the reach of shared materials.

4. Balancing Openness and Control

Concerns about quality, misuse, and attribution are common (as in the scenario).

• Educators can mitigate these by using licenses that restrict commercial use or modification (e.g., CC BY-NC-ND).
• Open sharing increases visibility and collaboration opportunities, which can enhance academic reputation rather than diminish it (Wiley & Hilton, 2018).
• Quality assurance can also be community-driven — through peer feedback and adaptation tracking (Cronin, 2017).

Ethics, Sustainability, and the Future of Openness

Openness should be viewed through an ethical and sustainable lens. Open education must ensure data privacy, authorship recognition, and the protection of indigenous and community knowledge. Sustainable openness requires shared governance and equitable funding models so that open access does not rely solely on individual or institutional goodwill (Hess & Ostrom, 2022).

In this light, open education becomes not just a pedagogical innovation but a social contract that commits institutions to inclusivity, accountability, and justice in the digital age. It asks: how can we sustain open practices in a way that values diversity, ensures representation, and supports long-term global collaboration?

References

Adams, S. (2025). Fear of the unknown: What really happens when you make your work open? University of Calgary. Retrieved October 23, 2025, from https://yuja.ucalgary.ca/V/Video?v=1110604&a=32129370

Concordia University. (2025). Behind the scenes: Open scholarship | Fourth Space events. Retrieved October 23, 2025, from https://www.concordia.ca/cuevents/offices/provost/fourth-space/2025/10/24/behind-the-scenes.html

Cox, G., & Trotter, H. (2017). Factors shaping lecturers’ adoption of OER at three South African universities. Open Praxis, 9(1), 103–121. https://doi.org/10.5944/openpraxis.9.1.473

Cronin, C. (2017). Openness and praxis: Exploring the use of open educational practices in higher education. International Review of Research in Open and Distributed Learning, 18(5), 15–34. https://doi.org/10.19173/irrodl.v18i5.3096

Hess, C., & Ostrom, E. (2022). Understanding knowledge as a commons: From theory to practice. MIT Press.

Hilton, J. (2020). Open educational resources, student efficacy, and user perceptions: A synthesis of research. Educational Technology Research and Development, 68, 853–876. https://doi.org/10.1007/s11423-019-09700-4

Piwowar, H., Priem, J., Larivière, V., Alperin, J. P., Matthias, L., Norlander, B., … & Haustein, S. (2018). The state of OA: A large-scale analysis of the prevalence and impact of Open Access articles. PeerJ, 6, e4375. https://doi.org/10.7717/peerj.4375

Salmon, G. (2013). E-tivities: The key to active online learning. Routledge.

UNESCO. (2019). Recommendation on Open Educational Resources (OER). Paris: UNESCO. https://unesdoc.unesco.org/ark:/48223/pf0000370936

UNESCO. (2023). Dubai Declaration on AI and OER. UNESCO Open Education Global Forum. https://www.unesco.org/en/open-educational-resources

Wiley, D., & Hilton, J. (2018). Defining OER-enabled pedagogy. International Review of Research in Open and Distributed Learning, 19(4), 133–147. https://doi.org/10.19173/irrodl.v19i4.3601

Introduction: Navigating the Digital Age as Learners and Educators

In an era where learning increasingly unfolds through screens, networks, and shared digital spaces, online participation and digital literacy have become indispensable for educators and learners alike. The Open Networked Learning (ONL) course’s first topic, Online Participation and Digital Literacies, invited participants to explore how we communicate, collaborate, and construct meaning in virtual environments. Beyond mastering tools and platforms, this topic illuminated the social, ethical, and affective dimensions of digital engagement. As our group, Roots & Routes, discussed, thriving in this environment requires confidence, critical thinking, and a reflective approach to our own digital identities.

Digital Participation and Engagement (Rotich)

Rotich emphasized that successful online participation depends on both student and faculty engagement. Students are expected to manage time effectively, maintain digital etiquette, and cultivate responsibility for their learning, while instructors must provide clear communication, accessible materials, and meaningful feedback. These practices are consistent with research showing that engagement in online education depends on the quality of digital interaction and the presence of “social immediacy” (Henry, 2020; Stancin et al., 2025).

Rotich’s insights align with pedagogical frameworks emphasizing community, connection, and autonomy as drivers of motivation in virtual classrooms. Faculty can encourage deeper participation by using strategies such as peer review, open discussions, and negotiated expectations for camera use, approaches that create belonging while respecting learners’ diverse contexts (Acacia University, n.d.). This balance reflects the human side of digital learning: building trust and connection through intentional design.

Modes of Participation: Synchronous, Asynchronous, and In-Person (Lia)

Lia compared online synchronous, asynchronous, and in-person learning, emphasizing that no single modality is superior. Each offers distinct advantages and limitations. Synchronous learning enables real-time dialogue and shared presence but demands coordination across time zones. Asynchronous formats promote flexibility and reflection but can feel impersonal. In-person settings strengthen social bonds yet lack the global reach of online environments.

Lia’s contribution underscores the value of a blended approach that integrates all three modes to cultivate meaningful inquiry. This mirrors findings by Afonso et al. (2025), who argue that hybrid and flexible models empower students to engage through varied learning rhythms and cultural lenses. By blending modalities, educators not only accommodate learners’ individual needs but also sustain community across digital boundaries.

AI and Authentic Participation (Daniela)

Daniela explored how generative AI tools such as ChatGPT and Claude are transforming online class participation. She argued that discussion boards, once cornerstones of asynchronous interaction, risk losing their authenticity when students can generate responses instantly. This challenge calls for educators to rethink assessment and move toward authentic, reflective, and dialogic forms of engagement.

Daniela proposed alternatives such as oral assessments, reflective journals, and project-based learning, echoing Hertz’s (2025) call for assessment that fosters “genuine intellectual growth.” She also advocated for transparent institutional guidelines on AI use, framing it not as a threat but as a catalyst for redefining what constitutes meaningful participation. This approach positions AI as a partner in inquiry, not a shortcut to performance.

Developing Digital Literacies

I believe the essential role of faculty development is in building digital literacies. According to her synthesis, instructors who model consistent, creative technology use inspire students to develop their own competencies. Digital literacy, as Buchan et al. (2024) explain, extends beyond technical skills to include critical evaluation, adaptability, and ethical responsibility.

Supporting both students and faculty through professional development and mentorship enhances confidence and inclusivity in online learning spaces. This resonates with Zhang and Wu’s (2025) findings that faculty digital teaching skills directly influence teaching quality and student motivation. Ultimately, fostering digital literacy is not merely a technical endeavor; it is a human process of empowerment and connection.

Third Spaces and Brave Spaces

This topic also opened conversations around Third Spaces, a framework I explored deeply in my reflection. Drawing on Bhabha’s (1994) theory, the Third Space represents a hybrid zone where learners negotiate their personal and professional identities, merging what they know with who they are becoming. In online education, these spaces invite authenticity and intercultural dialogue, enabling students and educators to co-construct meaning beyond institutional boundaries (Zhang & Jian, 2020).

In my reflection, I emphasized that teaching in multilingual and multicultural environments requires co-creating Third Spaces where both teacher and learner bring their full selves into dialogue. As Fellows (2025) notes, digital third spaces foster “identity work and relational agency” that make learning personally significant.

While Third Spaces address identity and hybridity, Brave Spaces (Arao & Clemens, 2013) add the emotional and ethical dimension necessary for learning in the open. The Six Pillars of Brave Space: vulnerability, storytelling, respectful challenge, accountability, empathy, and acknowledgment of inequity (University of Maryland School of Social Work, 2021), remind educators that discomfort is not failure but growth. To best capture this spirit, we need to understand that learning in the open requires managing the fear of being seen. As Rountree (2025) argues, such spaces become “ritual grounds for voice and belonging” when difference and discomfort are welcomed rather than silenced.

Conclusion

Our ONL group’s exploration of Online Participation and Digital Literacies revealed that thriving in digital education requires much more than technical proficiency. It involves cultivating critical awareness, emotional courage, and relational sensitivity. Lia’s focus on flexible modalities, Rotich’s insights on engagement, Daniela’s call for authenticity amid AI, the emphasis on literacy-building, and my reflection on Third and Brave Spaces all point to a shared truth: online learning is a deeply human practice. As learners and educators, our task is not only to navigate networks but to create spaces, digital or otherwise, where knowledge and identity evolve together.

References

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