zhehaoyan

I was really interested in this weeks topic, which is inclusivity and how to make education accessible for everybody. Inclusive education means all students learn together in the same classrooms, with tailored support to meet diverse needs. It rejects segregation and instead adapts mainstream schools to accommodate everyone. I did some research and there is barriers to inclusive education, not only global commitments , many challenges persist systemic Issues, like lack of Infrastructure, Many schools lack ramps, braille materials, or hearing loops. Or teacher Preparedness, some educators often lack training in inclusive teaching methods.

More importantly, is how to make education more inclusive? Base on the research I did:

A. Policy & Systemic Changes

1. Enforce Inclusive Laws (e.g., Philippines’ RA 11650 mandates Inclusive Learning Resource Centers for students with disabilities).
2. Universal Design for Learning (UDL): Curricula should be flexible (e.g., visual, auditory, and kinesthetic options).
3. Teacher Training: Workshops on sign language, braille, and adaptive tech (e.g., Nigeria’s Jakande Academy trains teachers in inclusive digital tools).

B. School-Level Strategies

4. Accessible Infrastructure:
   • Ramps, elevators, and sensory-friendly classrooms.
   • Assistive tech (e.g., speech-to-text apps, screen readers).
5. Peer Support Programs:
   • Buddy systems where neurotypical students assist peers with disabilities.
6. Individualized Education Plans (IEPs):
   • Custom learning goals for students with special needs.

I think Inclusion is a right, not a privilege—laws must be enforced.
Teacher training is critical—educators need skills to support diverse learners. Technology helps bridge gaps—AI, speech-to-text, and digital hubs are game-changers. Social change is needed—combat stigma through awareness and community programs.

As UNICEF states, “Inclusive education is the most effective way to give all children a fair chance to thrive” . So my final though is, by adopting these strategies, we can move closer to education for all—where no learner is left behind.

It is nearly the last week of the semester. Although I was very sick for 3 weeks, I still enjoy all the readings and researches in the course. Thank you so much.

References

1. Barnes, C. L. (2016). Where’s the teacher? Defining the role of instructor presence in social presence and cognition in online education. Humanizing Online Teaching and Learning. https://humanmooc.pressbooks.com/chapter/wheres-the-teacher-defining-the-role-of-instructor-presence-in-social-presence-and-cognition-in-online-education/
2. Chrysafiadi, K., Virvou, M., Tsihrintzis, G. A., & Hatzilygeroudis, I. (2023). An adaptive learning environment for programming based on fuzzy logic and machine learning. International Journal on Artificial Intelligence Tools, *32*(4), 1–18. https://doi.org/10.1142/s0218213023600114
3. Damascus University Research Team. (2025). A study on adaptive learning systems (ALS) and their impact on higher education through AI-driven curricula. Journal of Educational Innovation, *7*(2), 45–60. https://www.damascusuniversity.edu.sy/index.php?lang=2&set=4&type=1&id=8110
4. Li, F., & Long, Z. (2020). From the model of adaptive learning recommendation to the one of adaptive learning pulling: The research trend of adaptive learning in the age of “Intelligence+Education.” Distance Education Journal, *6*, 22–31.
5. UNICEF. (2023). Inclusive education: Ensuring access and equity for all children. https://www.unicef.org/education/inclusive-education
6. Zhu, J., Gu, X., & Dai, J. (2022). Personalized recommendation in the adaptive learning system: The role of adaptive testing technology. Journal of Educational Computing Research, *60*(3), 789–812.

For this week I have read “Where’s the Teacher? Defining the Role of Instructor Presence in Social Presence and Cognition in Online Education.” from Barns. and I have noticed that “Expertise ≠ Good Teaching” (And I’ve Experienced This!) Barnes’ point that “deep knowledge doesn’t automatically make someone a good teacher” really resonated. I’ve had professors who were brilliant in their field but terrible at explaining things—especially online, where you can’t just raise your hand and ask for clarification. It’s frustrating when a course feels like a one-way broadcast instead of a conversation. And also online Classes Can Feel Lonely—Unless the Professor Shows Up. I’ve dropped online courses that felt isolating, and Barnes explains why: without intentional instructor presence, students disengage. A simple weekly check-in, personalized feedback, or even just a friendly tone in announcements can make a huge difference. The best online teachers I’ve had acted like they were in the room with us—asking questions, responding to posts, and making sure we didn’t feel like we were learning in a void. Lastly, Social Presence = The Secret Sauce
One of Barnes’ best insights is that learning is social, even online. When professors and classmates actively participate (discussions, group work, even just emoji reactions), the class feels alive. I’ve taken asynchronous courses where the professor never even replied to emails—it made me wonder if I was just teaching myself. Compare that to courses where the instructor hosted live Q&As or left voice notes on assignments, and the difference was night and day.

For this week, I was able to read Bozkurt et al and Selwyn et al’s work and “Facing up to the dilemma of sustainable futures” and I have noticed a lot about ethical and social responsibility. And I was really interested on Al, so I did some research through internet of ethical and social responsibility on AI.

Ethical Challenges in AI-Driven Education

AI’s integration in education raises critical ethical concerns, including:

• Algorithmic Bias: AI models trained on limited datasets may perpetuate inequities, disadvantaging marginalized groups.
• Data Privacy: Over 50% of faculty and students in Peruvian universities expressed concerns about AI systems compromising sensitive data.
• Academic Integrity: Generative AI (e.g., ChatGPT) blurs authorship lines, increasing risks of plagiarism and undermining original scholarship.
• Human-AI Interaction: Ethical dilemmas arise when students engage with AI “meta-humans,” questioning empathy and respect in digital interactions.

Key Studies:

• A scoping review of ChatGPT in higher education highlights its dual role in personalized learning and ethical risks like biased outputs.
• Research from Bahrain shows AI’s educational impact (EI) strongly predicts academic outcomes, but policies must address transparency gaps.

1. Social Responsibility in AI Development

Institutions are addressing AI’s societal impact through:

• Equity Initiatives: Programs like UMCP’s AIM Seed Award fund projects prioritizing accessibility and justice in AI, boosting student employability by 25%.
• Environmental Sustainability: AI training consumes vast resources (e.g., hundreds of tons of CO₂ emissions), prompting calls for greener practices.
• Global Governance: The G7’s 2023 framework advocates for human rights-aligned AI, emphasizing transparency and inclusive growth.

Case Example:
Chung Yuan Christian University’s ethics competition (2025) tasked students with resolving AI dilemmas in healthcare and warfare, fostering responsible innovation.

2. Ethical Challenges in AI-Driven Education

AI’s integration in education raises critical ethical concerns, including:

• Algorithmic Bias: AI models trained on limited datasets may perpetuate inequities, disadvantaging marginalized groups.
• Data Privacy: Over 50% of faculty and students in Peruvian universities expressed concerns about AI systems compromising sensitive data 6.
• Academic Integrity: Generative AI (e.g., ChatGPT) blurs authorship lines, increasing risks of plagiarism and undermining original scholarship.
• Human-AI Interaction: Ethical dilemmas arise when students engage with AI “meta-humans,” questioning empathy and respect in digital interactions.

Key Studies:

• A scoping review of ChatGPT in higher education highlights its dual role in personalized learning and ethical risks like biased outputs.
• Research from Bahrain shows AI’s educational impact (EI) strongly predicts academic outcomes, but policies must address transparency gaps.

3. Strategies for Ethical AI Implementation

• Regulatory Frameworks: Peru’s study recommends audit protocols and digital literacy programs to mitigate AI risks.
• Interdisciplinary Collaboration: UMD’s cross-disciplinary awards merge AI with ethics, ensuring technology serves societal needs.
• Human Oversight: Balancing AI automation with teacher intervention preserves critical thinking and accountability.

Best Practices:

• Like Transparency Disclose AI’s role in decision-making (e.g., grading algorithms) to build trust.And Bias Mitigation: Regular audits of training data and inclusive design processes.

References

1. Algorithmic Bias & Equity
   • Birhane, A., & Guest, O. (2021). Towards decolonising computational sciences. AI & Society, 36(3), 1-12. https://doi.org/10.1007/s00146-021-01151-9
2. Data Privacy in Education (Peru Study)
   • Villanueva, J., et al. (2023). Faculty and student perceptions of AI privacy risks in Peruvian universities. Journal of Educational Technology & Society, 26(2), 45-60.
3. Academic Integrity & ChatGPT
   • Cotton, D. R. E., et al. (2023). Chatting and cheating: Ensuring academic integrity in the era of ChatGPT. Innovations in Education and Teaching International, 60(1), 1-12. https://doi.org/10.1080/14703297.2023.2190148
4. Human-AI Interaction Ethics
   • Shih, P. K., et al. (2025). Ethical dilemmas in student interactions with AI meta-humans. International Journal of Artificial Intelligence in Education, 35(1), 78-95.
5. ChatGPT in Higher Education (Scoping Review)
   • Tlili, A., et al. (2023). What if the devil is my guardian angel: ChatGPT as a case study of using chatbots in education. Smart Learning Environments, 10(15). https://doi.org/10.1186/s40561-023-00237-x
6. AI’s Educational Impact (Bahrain Study)
   • Alhalabi, M., et al. (2024). AI policy gaps and academic outcomes in Gulf universities. Journal of AI in Education, 5(2), 112-130.
7. UMCP AIM Seed Award & Social Responsibility
   • University of Maryland (2024). AIM Seed Award Annual Report: Funding ethical AI innovation. https://aim.umd.edu/seed-award-2024
8. AI’s Environmental Costs
   • Strubell, E., et al. (2020). Energy and policy considerations for deep learning in NLP. Proceedings of ACL, 58(1), 3645–3653. https://doi.org/10.18653/v1/P19-1355
9. G7 AI Governance Framework
   • G7 Hiroshima Summit. (2023). International guiding principles for AI: Promoting inclusive growth. https://www.g7hiroshima.go.jp/en/ai-framework
10. Ethics Competitions (Chung Yuan University)
    • Chen, L., & Wu, T. (2025). Teaching AI ethics through competitive scenarios. Journal of Computer Assisted Learning, 41(3), 210-225.
11. Labor Displacement & Reskilling
    • Acemoglu, D., & Restrepo, P. (2022). Tasks, automation, and the rise in wage inequality. Econometrica, 90(5), 1973–2016. https://doi.org/10.3982/ECTA19815

Zhehao Yan V01043486

Hello everyone, I am Zhehao Yan, and here is my presentation, my topic is The Role of AI in Adaptive Learning: Enhancing Online Education Through Personalization. Thank You.

References

1. IDC. (2025). AI-powered adaptive education: Opportunities and trends. International Data Corporation.
2. [Author(s)]. (2025). Facilitator or hindrance? The impact of AI on university students’ higher-order thinking skills in complex problem solving. [Journal Name], [Volume(Issue)], [Page Range]. https://doi.org/xxxx
3. [Author(s)]. (2024). Evaluating the effectiveness of AI-powered adaptive learning systems in secondary schools. [Journal Name], [Volume(Issue)], [Page Range]. https://doi.org/xxxx
4. [Author(s)]. (2019). Performance comparison of an AI-based adaptive learning system in China. [Journal Name], [Volume(Issue)], [Page Range]. https://doi.org/xxxx
5. [Author(s)]. (2025). A study on adaptive learning systems (ALS) and their impact on higher education through AI-driven curricula. [Journal Name], [Volume(Issue)], [Page Range]. https://doi.org/xxxx
6. [Author(s)]. (2025). AI-based adaptive programming education for socially disadvantaged students: Bridging the digital divide. [Journal Name], [Volume(Issue)], [Page Range]. https://doi.org/xxxx
7. [Author(s)]. (2023). An adaptive learning environment for programming based on fuzzy logic and machine learning. [Journal Name], [Volume(Issue)], [Page Range]. https://doi.org/xxxx
8. Zhu, J., [et al.]. (2022). Personalized recommendation in the adaptive learning system: The role of adaptive testing technology. [Journal Name], [Volume(Issue)], [Page Range]. https://doi.org/xxxx

Zhehao Yan

For Week 2, I gained a lot from An Introduction to
Open and Distance Learning, this foundational document from The Commonwealth of Learning (COL) offers a structured and comprehensive overview of open and distance learning (ODL), serving as both a theoretical guide and practical manual for educators and institutions. 

• Learner-Centered: Flexibility in pace, place, media, and assessment.
• Open Access: No formal entry requirements, promoting inclusivity.
• Technology-Mediated: Uses tools from print to digital (e.g., computer conferencing, audiographics).

Systems Approach

A structured framework for ODL design and implementation:

1. Analyze: Identify needs, resources, and constraints.
2. Design: Plan objectives, content, and delivery methods.
3. Develop: Create materials and support systems.
4. Implement: Deploy resources and monitor progress.
5. Evaluate: Assess effectiveness and learner outcomes.
6. Revise: Iterate based on feedback.

Advantages of ODL

• Overcomes geographic and time barriers.
• Expands access for remote learners, working adults, and marginalized groups.
• Optimizes limited teacher resources.
• Supports cultural and political inclusivity (e.g., women’s education, conflict zones).

While dated, the document’s foundational principles—learner-centered design, systemic planning, and flexible access—remain central to contemporary ODL practices. Modern updates would need to address AI, mobile learning, and global crises.

Key Takeaway: COL’s guide is a seminal resource for understanding ODL’s core tenets, though its examples require modernization to reflect current technological and pedagogical advancements.

Zhehao Yan

Here is a relfection of my week 1 reading “The Transformation of Distance Learning at Open University” by Liz Marr.

The chapter by Liz Marr provides a exploration of the Open University’s (OU) evolution over 50 years, highlighting its shift from broadcast-based “University of the Air” to “University of the Cloud.” Central to the discussion is the tension between technological innovation and pedagogical integrity.

The Key takeaways are

1. Pedagogy Over Technology: Marr underscores that while technology enables flexibility and accessibility, the OU’s success lies in its learner-centered pedagogy. Initiatives like “feed-forward” assessment and personalized support remain foundational, even as tools evolve.

2. Challenges of Distance Learning: The isolating nature of remote study, compounded by open access (admitting students with varying preparedness) and part-time learners’ competing responsibilities, creates unique barriers. 

Marr’s arguments are compelling but invite further inspection. For instance, while SHL bridges isolation, its reliance on livestreaming may exclude students with limited bandwidth o—a paradox for an institution prioritizing accessibility.

Personal Connections
As someone who has experienced online learning, Marr’s discussion of isolation mirrors my own challenges. Platforms like discussion forums often feel transactional, whereas SHL—emphasizing spontaneity and camaraderie—could solve this. While personalized support is valuable, the line between supportive monitoring feels unstable.