1. What inspired you to explore AI and chatbot-assisted learning for logic development in English argumentative writing?
My research was motivated by the growing need for AI-enhanced educational tools that support critical thinking and writing skills. Many English as a Foreign Language (EFL) learners struggle with logical reasoning in argumentative writing, often producing fallacies that weaken their arguments. AI-driven chatbots offer a scalable and interactive way to train students in logic and reasoning, providing instant feedback and personalised learning experiences.
2. How do chatbots improve students’ ability to identify and avoid logical fallacies in argumentative writing?
Chatbots provide structured, interactive learning experiences that help students recognise and correct logical fallacies. Through real-time dialogues, chatbots can:
- Present examples of logical fallacies in different argumentative contexts.
- Offer immediate feedback when students make reasoning errors.
- Simulate Socratic questioning to guide learners toward logical reasoning.
- Encourage self-reflection by prompting learners to revise their arguments.
Our research found that chatbot-assisted training significantly improved students’ fallacy identification skills, though some learners initially struggled with adapting to the AI-driven approach.
3. What are the key advantages of chatbot-based learning compared to traditional methods?
Chatbot-based learning offers several advantages:
- High interactivity: Learners can engage in simulated debates and reasoning exercises.
- Personalised learning paths: AI adapts to the learner’s pace and progress.
- Instant feedback: Unlike traditional classroom instruction, chatbots provide immediate corrections and explanations.
- Reduced cognitive load: Learners receive guidance in digestible segments, making complex concepts more approachable.
However, chatbots should complement rather than replace human instruction, as nuanced reasoning and debate still require human expertise.
4. What challenges do students face when using chatbots for logic learning?
Some students find AI-driven learning intimidating at first, especially when dealing with abstract concepts. Common challenges include:
- Over-reliance on AI: Some learners expect the chatbot to generate answers rather than engaging critically.
- Lack of human interaction: While chatbots provide structured learning, they cannot replicate the depth of teacher-led discussions.
- Varying engagement levels: Students who enter a “flow state”—a deep focus on learning—tend to perform better, but achieving this state varies across individuals.
Our research suggests that skill-challenge balance and interactive feedback are crucial for maintaining engagement.
5. How does AI-based logic training impact students’ confidence in writing?
Interestingly, while chatbot-based training improves logical accuracy, it may reduce students’ writing self-efficacy in the short term. This happens because as students become more aware of their reasoning errors, they may feel less confident in their writing ability. However, over time, continuous practice with chatbots enhances both logical proficiency and confidence, especially when integrated with traditional writing instruction.
6. How do you see the role of AI evolving in writing instruction?
AI is shifting writing instruction from grammar-focused correction to critical thinking and logical structuring. In the future, AI-driven tools will likely:
- Provide adaptive writing prompts based on learners’ proficiency.
- Offer real-time argumentative feedback that goes beyond grammar.
- Integrate multi-modal learning, combining text, speech, and visuals for deeper engagement.
AI should empower learners, helping them refine their reasoning while preserving their authentic writing voice.
7. How do you ensure that chatbot-assisted learning remains engaging and effective?
To maximise engagement, chatbot-based learning should incorporate:
- Game-based elements: Encouraging competition and achievement.
- Conversational interactions: Mimicking real-life debates to promote deeper thinking.
- Personalisation: Adapting learning content to students’ needs.
Our research proposes the RAISE model—Repetitiveness, Authenticity, Interactivity, Student-centeredness, and Enjoyment—to guide chatbot-assisted learning design.
8. What are the future directions for AI in language learning and the humanities?
Future advancements will likely include:
- AI-driven argument analysis: Detecting logical strengths and weaknesses in real time.
- Emotion-aware AI tutors: Adjusting responses based on students’ engagement and frustration levels.
- Cross-disciplinary applications: Using AI to enhance critical thinking not only in writing but also in social sciences and philosophy.
Ultimately, AI should be seen as a collaborator rather than a replacement—enhancing, rather than diminishing, human creativity and critical reasoning.
