This module helps you develop essential critical reading skills for analyzing AI-generated content. You will also learn to use GenAI tools for text analysis, summarization, and comprehension enhancement. The module emphasizes practice, encouraging you to evaluate both the strengths and limitations of these tools in academic and professional contexts. You will end the module with a self-assessed written reflection where you'll critically analyze an AI-generated text using the techniques you have learned.

This module will help you identify and analyze different types of biases in AI-generated content. Through interactive videos, you'll learn to recognize explicit and implicit biases, including common cognitive biases like confirmation bias. The module uses real-world examples to demonstrate how algorithmic bias perpetuates societal inequalities and expert insights to explain how GenAI biases occur. Your learning will be assessed through a quiz that tests your understanding of different types of biases.

This module equips you with the skills to construct and evaluate logical arguments while mastering effective AI prompt design. Through interactive videos, you'll explore five core argument types (deductive, inductive, abductive, analogical, and causal) and learn to spot logical fallacies that undermine reasoning. The module also delves into advanced prompt techniques-from zero-shot to tree-of-thought prompting, highlighting how clarity and context shape AI outputs. Real-world examples and ethical dilemmas illustrate the interplay between human reasoning and AI decision-making, emphasizing transparency and bias mitigation. Your learning will be assessed through a peer-reviewed prompt-engineering task, where you’ll demonstrate systematic reasoning by refining AI outputs.

This module will help you effectively integrate GenAI tools into your critical writing process while maintaining rigorous standards. Through annotated examples and practical workflows, you'll learn to use AI for argument structuring, evidence verification, and cautious language refinement while preserving human judgment. The module demonstrates how to combine reasoning-focused LLMs with research assistants and editing tools, using techniques like evidence matrices and adversarial prompting to reduce hallucinations. At the end of this module, you will use AI tools to write a short critical introduction on a chosen topic, along with an explanation about the way you used these tools.