Social Learning Platform Analysis

Your goal is to evaluate and analyze a social learning platform of your choice, considering how it enables people to create, share, discover, and learn from content.

The Task

Choose a Platform: Select a social learning platform that interests you. Consider how people use the platform to create, share, discuss, and learn from content.

Develop Your Framework: Develop a set of criteria for evaluating the platform as a social learning environment. Your criteria should draw on relevant theories and concepts from the course. Briefly explain your criteria and how they connect to course concepts.

Evaluate & Analyze: Apply your framework to the platform. Consider both its strengths and limitations as a social learning environment. Use specific examples or evidence (i.e., screenshots, timestamps) from the platform to support your analysis and explicitly connect your observations to relevant course concepts.

Consider the Learner: Reflect on who benefits from the platform, who might be excluded or disadvantaged, and how the platform’s design influences what and how people learn. Consider the roles of learners, content creators, communities, algorithms, and other features of the platform.

Possible Platforms

Wikipedia	collaborative knowledge creation and content development (a focus on social content development)
TikTok	informal learning and knowledge sharing
LinkedIn	professional learning and networking
YouTube	content creation, tutorials, and learning communities
Reddit	community-based knowledge sharing and discussion
GitHub	collaborative learning through software development
Discord	community learning and peer interaction
Stack Overflow	community Q&A for coding
Your Choice	you may choose any platform as long as there is a social and educational component. if you want to double check your platform choice, do not hesitate to reach out

Assessment Rubric

	0 – 2 (Needs Additional Work)	3 (Marginally Meets Expectations)	4 (Fully Meets Expectations)	5 (Exceeds Expectations)
Theoretical Foundation	Framework are based on personal preference. Fails to reference course theories.	Mentions course theories but criteria are surface-level or do not accurately reflect the depth of the concepts.	Framework is explicitly built upon the course theories. Criteria reflect a solid understanding of these principles.	Criteria are sophisticated and demonstrate a high-level understanding of why specific design choices impact the educational experience in the social learning platform.
Critical Application & Analysis	Evaluation of social learning platform is missing or anecdotal. Does not appear to actually use the developed framework to generate scores.	Justifications in the evaluation are brief and lack specific evidence from the social learning platform.	Provides a logical justification for the evaluation, citing specific features in the social learning platform as evidence.	Uses the developed framework to “deconstruct” the social learning platform, linking specific evidence (timestamps/screenshots) to the theoretical foundations.
Reflection & Insight	Provides little consideration of what the analysis reveals about social learning.	Identifies some implications for learning but remains largely descriptive.	Clearly discusses what the analysis reveals about the platform’s strengths, limitations, and potential as a social learning environment.	Offers nuanced insights into who the platform enables or constrains as a learner, and considers broader issues such as agency, participation, accessibility, community, algorithms, or power.

Generative AI Guideline

This assignment allows for structured and defined support from AI tools at the planning and post-draft stages. You may use AI to deepen your understand of theory and, after drafting, for tasks such as clarifying your approach or engaging in meaningful revision, while preserving the integrity of the core writing process.

If you have any questions about permitted AI use, please contact me before you use the AI tools.

Stage	Permitted AI Use	Not Permitted
Research/obtaining data for the analysis, and before/during your draft	Understanding of theory, clarifying concepts, and exploring different perspectives	Generating thesis statements, arguments, outlining, paraphrasing, or full paragraphs
After your draft	Receiving feedback on structure, coherence, and alignment with the rubric	Rewriting content via AI suggestions

Here are sample prompts you can use with an LLM of your choice (e.g., Gemini, ChatGPT) to get the most out of AI while adhering to permitted AI use.

Before/during draft

I am a student in an undergraduate-level Educational Technology course. I want to understand [INSERT THEORY NAME HERE] deeply enough to write a critical reflection. Please use professional but accessible language. 

Your Role: Act as an expert academic mentor in Educational Technology.

Please provide the following:
 - Core Essence: A clear, concise explanation of the theory's main argument.
 - Clarifying Nuances: What are 2–3 specific concepts within this theory that are often misunderstood? Explain them simply but accurately.
 - Diverse Perspectives: How might different educators or researchers view this differently? Provide one "pro" (supportive) perspective and one "critical" (skeptical) perspective.
 - Practical Tension: What is one way this theory is difficult to apply in a real-world classroom or digital environment?

Tips for Theory-Based AI Engagemen

• Challenge the Theory: Ask for common critiques or “skeptical” perspectives of the concept
• Request Analogies: If a concept feels too dense, ask for a non-educational analogy (e.g., “What would this theory look like in soccer?”) or to “explain like I am five years old”. This makes the theory simpler, intuitive and/or easier to connect to.
• Dive Deeper: Explore the nuances by identifying “unintended consequences” or “hidden assumptions” within the theory; how might the concept evolve in the future or where might it break down.

After draft

I am a student in an undergraduate-level Educational Technology course. I am developing an educational multimedia assessment rubric that can be used to evaluate educational resources (videos, interactive websites, simulations, or digital modules).

My goal is to translate course theory into a practical, evaluative tool. I aim to design a robust multimedia assessment rubric grounded in course concepts and be able to use it to critically evaluate the quality of existing educational resources. Through this process, I am working to bridge abstract learning theory and concrete design decisions.

Your Role: Act as my academic writing and design coach. Support me in strengthening the theoretical grounding, clarity, and critical rigor of my rubric and analyze compared to the Multimedia Assessment Rubric. Your feedback should help me refine my thinking, not replace it.

Your Tasks. Please review my work and provide targeted, actionable feedback on the following:
 - Rubric Design & Theory Translation: Assess whether my rubric meaningfully operationalizes the course’s core pillars: Theories of Multimedia Learning, Models of Active Learning, and Accessibility and Universal Design for Learning
 - Clarity & Usability: Identify areas where rubric criteria may be vague, subjective, or difficult for another evaluator to apply consistently.
 - Critical Evaluation: Evaluate whether I apply the rubric rigorously when assessing educational resources, using evidence rather than impressions.
 - Theory–Practice Alignment: Highlight opportunities to strengthen the connection between specific design features in the resources and the underlying theoretical principles that justify their evaluation.

Important Constraint: Please do not rewrite the text for me. Instead, give me specific, actionable suggestions or ask me clarifying questions that will help me improve the draft myself.

Multimedia Assessment Rubric
1. Theoretical Foundation
0–2 (Needs Additional Work): Criteria are based on personal preference and fail to reference or meaningfully engage with course theories.
3 (Marginally Meets Expectations): Mentions course theories, but criteria are surface-level or do not accurately reflect the depth of the concepts.
4 (Fully Meets Expectations): Rubric is explicitly built upon course theories. Criteria reflect a solid understanding of the theoretical principles.
5 (Exceeds Expectations): Criteria are sophisticated and demonstrate a high-level understanding of why specific design choices impact the educational experience.
2. Tool Actionability & Design
0–2 (Needs Additional Work): Rubric is vague, unformatted, or relies on binary (Yes/No) judgments. It would be difficult for another person to use it reliably.
3 (Marginally Meets Expectations): Criteria are broad or subjective, with repetitive language across score levels that makes distinctions unclear.
4 (Fully Meets Expectations): Rubric is a functional, professional tool. It uses a clear scale with observable indicators, and the layout is organized and easy for a third party to read and apply.
5 (Exceeds Expectations): Rubric uses precise, objective language that minimizes ambiguity and would likely yield consistent results across different evaluators.

Current Draft
[PASTE YOUR DRAFT RUBRIC HERE]

Tips for Using AI for Feedback

• Be Specific: If you are worried about a specific section, ask the AI to focus specifically on that part of the rubric.
• The “Why” Matters: If the AI suggests a change, ask it why that change would improve the score. This helps you learn the underlying principles of design and communication.
• Iterate: Don’t just take the first set of feedback. If the AI says your goals are “vague,” ask it: “Can you give me an example of what a ‘highly specific’ goal looks like in the context of EdTech?”
• Maintain Your Voice: Remember that the AI doesn’t know your personal “voice” or your specific project as well as you do. If its suggestions feel too robotic, disregard them.