GRASPED Social Media Algorithms and AI

Strategies, Insights, and Engagement Dynamics

This course's structure is designed to foster an immersive learning experience, where students are encouraged to engage actively, think critically, and assess their understanding continuously. The intersection of AI and social media algorithms is a dynamic field, and this course aims to equip learners with the insight and confidence to navigate it proficiently.

Module 1: Introduction to AI and Social Media Algorithms

• Primary Learning Prompt:

  How do AI and machine learning intertwine with social media algorithms, and why is understanding this relationship crucial for content visibility and user engagement?
• Immediate Knowledge Check: List one way in which AI influences social media algorithms and subsequently affects content visibility.
• Self-rating Question: On a scale from 1 to 10, how would you rate your current understanding of the interaction between AI and social media algorithms?

Module 2: Historical Context of Social Media Algorithms

• Primary Learning Prompt:

  Trace the evolution of social media platforms and their use of algorithms. How has the integration of AI evolved over time to shape user experiences and content prioritization?
• Immediate Knowledge Check: Describe a significant shift in the social media landscape that resulted from the implementation of AI-driven algorithms.
• Self-rating Question: On a scale from 1 to 10, how confident are you in your grasp of the history of social media algorithms and AI's role in their evolution?

Module 3: Understanding AI and Algorithm Mechanics

• Primary Learning Prompt:

  What are the critical AI concepts, theories, or technologies that play a pivotal role in the way modern social media algorithms function?
• Immediate Knowledge Check: Explain how a specific AI technology or concept is utilized in the mechanics of social media algorithms.
• Self-rating Question: How do you rate your comprehension of the AI technologies that power social media algorithms, on a scale from 1 to 10?

Module 4: Real-World Applications of AI in Social Media

• Primary Learning Prompt:

  Can you identify practical instances where AI's influence on social media algorithms has had a noticeable impact on content strategy and audience engagement?
• Immediate Knowledge Check: Give an example of a brand or individual who successfully adapted their content strategy in response to AI-driven changes in social media algorithms, and describe the outcome.
• Self-rating Question: How confident are you in identifying and explaining real-world applications of AI's impact on social media strategies, on a scale from 1 to 10?

Module 5: Innovations and Trends in AI-Driven Social Media

• Primary Learning Prompt:

  What current trends and innovations in AI are poised to further transform social media algorithms and content distribution strategies?
• Immediate Knowledge Check: Identify one current AI innovation and discuss how it might influence social media algorithms in the future.
• Self-rating Question: On a scale from 1 to 10, how well do you understand the emerging AI trends impacting social media?

Module 6: Debates and Challenges in AI and Social Media

• Primary Learning Prompt:

  What are the major challenges or debates associated with the increasing influence of AI on social media algorithms, especially concerning content visibility and user engagement?
• Immediate Knowledge Check: Detail a prominent challenge or debate related to AI-driven social media algorithms and propose a potential way forward.
• Self-rating Question: How comfortable are you in discussing the complex challenges and debates surrounding AI's role in social media, on a scale from 1 to 10?

Module 7: Case Study - AI in Social Media in Action

• Primary Learning Prompt:

  Analyze a case study where a change in social media algorithms, driven by AI, significantly affected a business or influencer's content strategy and visibility.
• Immediate Knowledge Check: Summarize the case study, emphasizing the specific AI-induced algorithm change, the response strategy employed, and the results achieved.
• Self-rating Question: How proficient are you in analyzing case studies and extracting actionable insights regarding AI's role in social media, on a scale from 1 to 10?

Module 8: Ethical Considerations in AI-Powered Social Media

• Primary Learning Prompt:

  What ethical considerations arise with the use of AI in shaping social media algorithms, especially in terms of content bias, visibility, and user data?
• Immediate Knowledge Check: Present an ethical issue related to AI's influence on social media algorithms and suggest how platforms or content creators can address it responsibly.
• Self-rating Question: How would you rate your understanding of the ethical dimensions of AI's influence on social media, on a scale from 1 to 10?

Module 9: Global Perspectives on AI and Social Media Algorithms

• Primary Learning Prompt:

  How do AI-driven social media algorithms function across different global markets and cultures, and what implications do these variations have for content creators and brands?
• Immediate Knowledge Check: Compare the application or impact of AI-driven social media algorithms in two different cultural or geographic contexts.
• Self-rating Question: On a scale from 1 to 10, how confident are you in your comprehension of the global dynamics of AI in social media?

Module 10: Reflective Insights and Future Learning Paths

• Primary Learning Prompt:

  Reflect on your learning journey: what insights have you gained about AI and social media algorithms, and what areas are you keen to explore further?
• Immediate Knowledge Check: Write a reflective piece that captures your learning milestones and outlines your future learning objectives in the realm of AI and social media.
• Self-rating Question: How confident are you in your cumulative understanding of the AI-social media landscape, and what areas do you identify as opportunities for deeper exploration, on a scale from 1 to 10?