Introduction to AI Concepts

Defining AI

• AI refers to the development of intelligent systems that mimic human behavior and decision-making.
• AI simulates human intelligence through learning, reasoning, and self-correction.

Fundamentals of AI

• AI encompasses various stages of intelligence.
• Narrow AI/Weak AI: Performs specific tasks (e.g., voice recognition, recommendation systems).
• Artificial General Intelligence/Strong AI: Learns/adapts across various tasks like a human.
• Superintelligent AI: Outperforms human intelligence in all areas.

How AI Learns

• Supervised Learning: Uses labeled data for predictions (e.g., image classification).
• Unsupervised Learning: Identifies patterns in unlabeled data (e.g., grouping similar books).
• Reinforcement Learning: Learns through actions and rewards (e.g., game playing).
• Deep Learning: Uses neural networks for complex tasks on large amounts of unstructured data (e.g., image recognition).
• Transfer Learning: Reuses a pre-existing trained model for a related task.

Exploring Generative AI(GenAI)

• GenAI systems generate new content (text, images, music) based on learned patterns.
• GenAI uses machine learning, especially deep learning models (neural networks).
• Autoencoders: Compress and decompress input data.
• Generative Adversarial Networks (GANs): Two networks (generator and discriminator) compete.
• Transformers (e.g., GPT): Effective at generating text, trained on web data, process sentences differently.
• Large Language Models: Understand text input and generate human-like text.

AI and the Future of Teaching and Learning

• Human-like computers have capabilities different from early edtech tools.
• AI-powered systems offer homework assistance/lesson planning.
• Educational applications can converse with students/teachers, co-pilot classroom activities.
• "Intelligence Augmentation" recognizes that people benefit from assistive tools.

Educational Benefits of AI in ELT

• AI supports speaking, writing, and reading development.
• Enhances pedagogy and self-regulation in various ways.
• Notable exclusion that listening skills were not highlighted as a focus area in education.

AI in Speaking/Reading/Writing Skills

• AI enhances vocabulary, grammar, and reading comprehension.
• AI supports reading by assisting with vocabulary.
• AI aids in writing by helping with grammar and checking for patterns.

AI in Pedagogy

• AI facilitates ELT methods, strategies, and techniques.
• Some approaches use lectures/explanations/approaches for personalized learning.
• Challenges include technology breakdowns, limited capabilities, fear of the unknown.

Ethical Considerations

• Transparency(educators, students, and parents understand AI decision-making processes)
• Explainability(AI systems provide clear reasoning for their outputs/decisions).
• Diversity, Non-discrimination, Fairness (avoiding bias)
• Societal, Environmental Wellbeing(bridging social divides and ensuring equitable access).
• Privacy/Data Protection (AI systems comply with data privacy laws and handle student data responsibly).
• Technical Robustness and Safety(secure and resilient AI systems).
• Accountability (accountable AI development, deployment and outcomes).

AI and Data Usage Examples in Education

• Student teaching using AI (intelligent tutoring/dialogue-based tutoring).
• Supporting student learning (exploratory learning environments/formative writing assessments).
• Supporting teachers (summative writing assessment/pedagogical resource recommendation).
• Supporting systems (diagnostic systems/resource allocation).

Ethical Course of Action

• Rule Followers: Adhere to strict ethical guidelines.
• Outcome Seekers: Flexible approach that prioritizes beneficial outcomes.

Transparency and Explainability

• Transparency builds trust in AI systems, enabling user questioning and challenge of AI decisions.
• Explainable AI provides clear reasoning for AI systems' outputs/decisions.

Diversity, Non-Discrimination, Fairness

• AI systems must be designed/implemented ensuring fairness/avoiding bias affecting any student group.
• Regularly evaluating AI systems ensures that they don't perpetuate/introduce bias related to data or application of algorithms themselves.

Societal, Environmental Wellbeing

• AI in education promotes bridging social divides and ensuring equitable access.
• AI systems aim for social impact and social wellbeing.

Privacy and Data Protection

• AI systems must comply with data privacy laws and handle student data responsibly.
• Data should only be used for its intended purpose; students must have control over data usage.

Technical Robustness and Safety

• Protecting student data from cyberattacks is crucial.
• AI systems should be designed with built-in safeguards for data misuse/unauthorized access.

Accountability

• Establish clear accountability for AI system development, deployment, and outcomes.
• AI providers/educators involved should be accountable for their actions.

Emerging Competencies for Ethical Use of AI

• Area 1 (Professional Development): Utilize digital technology for communication, collaboration, and professional development.
• Area 2 (Digital Resources): Sourcing/creating/sharing digital learning resources/Data/AI governance.
• Area 3 (Teaching & Learning): Employ digital technologies for enhanced learning and assessment.
• Area 4 (Assessment): Utilize digital technologies for enhancing assessment.
• Area 5 (Empowering Learners/Area 6(Digital Competence for Learners): Employ digital technologies to enhance learning and personalization/learner inclusion.
• AI Foundation and Application in ELT: AI simulations of human intelligence support both teaching and learning. AI-driven tools that can be used for teaching/assessment.
• Natural Language Processing/Automated Writing Evaluation/Data-Driven Learning: Examples of AI in language learning/teaching.

Conclusions

• Educators should integrate AI effectively while fostering critical human skills.

Computerized Dynamic Assessment/Intelligent Tutoring Systems/Automatic Speech Recognition

• AI tools that aid learning of language, pronunciation and speaking.

Chatbots in Language Learning

• Tools to facilitate flexible/personalized learning.