Modules 7-9: Social Media, Information Literacy, and AI

Summary

This document covers modules on social media, information literacy, and artificial intelligence. It describes the fundamentals of each topic such as social media best practices, information literacy evaluation criteria, and AI applications.

Full Transcript

Module 7 -- Social media **Social Media Fundamentals:** - Digital platforms enabling content creation, sharing, and interaction - Connects people globally across geographical boundaries - Impacts marketing, branding, communication, and culture **Professional Development Strategies:**...

Module 7 -- Social media **Social Media Fundamentals:** - Digital platforms enabling content creation, sharing, and interaction - Connects people globally across geographical boundaries - Impacts marketing, branding, communication, and culture **Professional Development Strategies:** - Use LinkedIn for networking and professional profile - Personal branding through strategic content sharing - Showcase professional work and achievements - Follow industry experts and learning opportunities - Manage online reputation consistently **Online Presence Best Practices:** - Maintain consistent branding across platforms - Create professional profiles - Develop a content strategy - Engage authentically with audience - Consider personal website/blog - Optimize for search engines - Manage privacy settings **Communication Guidelines:** - Be clear and concise - Maintain professional tone - Post consistently - Use visual content - Utilize relevant hashtags - Handle criticism professionally **Social Media Security:** - Regularly review privacy settings - Use strong, unique passwords - Enable two-factor authentication - Limit personal information sharing - Be cautious with links and third-party apps - Monitor account activity **Current Social Media Trends:** - Short-form video content - Influencer marketing - Social commerce - Emphasis on authenticity - Niche community platforms - Social activism **Popular Platforms Overview:** - Facebook: Social connections - Twitter: Microblogging - Instagram: Visual content - LinkedIn: Professional networking - YouTube: Video sharing **Ethical Considerations:** - Respect privacy - Be authentic - Practice cultural sensitivity - Be aware of digital footprint - Respect intellectual property - Prevent cyberbullying - Maintain professional boundaries Module 8 -- Information Literacy Information Literacy Fundamentals: - **Definition:** Ability to locate, evaluate, and effectively use needed information - Core skills: Critical thinking, research skills, ethical information use - **Importance:** - Crucial in digital age - Supports academic and professional success - Enables lifelong learning - Empowers critical information consumption **Credibility Evaluation Criteria:** 1. Authority: Check author\'s credentials and expertise 2. Accuracy: Cross-reference with other credible sources 3. Currency: Verify publication dates and updates 4. Objectivity: Identify potential biases 5. Publisher reputation: Check institutional affiliations 6. Citations and references: Verify source documentation 7. Design and presentation: Assess professionalism 8. Audience and purpose: Understand context **Identifying Bias:** - Types of bias: - Confirmation bias - Selection bias - Implicit bias - **Evaluation methods:** - Analyze language and tone - Examine source origins - Check evidence representation - Assess fairness of perspectives **Misinformation Detection:** - Verification strategies: - Check source credibility - Cross-reference information - Use fact-checking websites - Assess evidence quality - Examine visual content - Watch for sensationalism - Analyse writing quality - Verify publication dates **Online Research Strategies:** - Keyword selection - Advanced search techniques - Subject-specific databases - URL evaluation - Metadata utilization - Checking cited references **Responsible Information Use:** - Respect intellectual property - Ensure accurate representation - Maintain transparency - Protect individual privacy - Ethical sourcing - Proper acknowledgment - Responsible sharing - Cultural sensitivity **Plagiarism Prevention:** - Understanding plagiarism types - Proper citation methods - Using citation management tools - Self-checking with plagiarism detection tools - Adhering to academic honesty policies **Current Trends in Information Literacy:** - Expanding digital literacy - Combating fake news - Media literacy integration - Data literacy development - AI and algorithmic bias awareness - Open access resources - Interdisciplinary approaches - Global collaboration Module 9 -- Artificial Intelligence (AI) **Definition of Intelligence:** - Ability to learn, understand, and adapt to new situations - Involves communication, problem-solving, and learning - ***LLM:*** AI system trained on massive amounts of text data to understand and generate human-like language. **AI Fundamentals:** - Computer science field designing software/hardware to imitate human cognitive abilities - Aims to replicate human-like problem solving, communication, and learning **Historical Milestones:** - Early conceptualizations: Leonardo\'s Robot Knight (15th century) - Turing Test (1950): Proposed method to determine machine intelligence - CAPTCHA: Modern application of Turing test principles **Key AI Applications:** 1. ***[Autonomous Vehicles]*** - Computer vision - Waymo self-driving taxis - Intelligent highway systems 2. ***[Image Recognition]*** - Facial recognition - Handwriting interpretation - Deep learning image classification 3. ***[Natural Language Processing]*** - Personal assistants (Siri, Alexa) - Large Language Models (ChatGPT) - Watson (IBM\'s question-answering system) 4. ***[Generative AI]*** - Text generation - Image creation (DALL-E, Stable Diffusion) - Music and video generation 5. ***[Industry-Specific Applications:]*** - Healthcare: Disease diagnosis - Finance: Fraud detection - Security: Biometric authentication - Education: Intelligent tutoring systems - Agriculture: Crop monitoring **Machine Learning Types:** 1. Supervised Learning: Uses labelled data 2. Unsupervised Learning: Identifies patterns in unlabelled data 3. Reinforcement Learning: Learning through rewards/penalties **Ethical Considerations:** - Bias and fairness - Transparency of algorithms - Privacy concerns - Job displacement - Need for human oversight **Emerging Trends:** - Autonomous robotic workers - More sophisticated generative AI - Continued development of **Large Language Models** Recommended Next Steps: - Explore AI learning resources - Test digital skills - Reflect on digital literacy journey

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