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Laura Davies

Assistant Director, Senior Lecturer of EAP at Duke Kunshan University

Duke Kunshan University

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Integrating Generative AI within EAP Pedagogy: Strategies to Reduce the Cognitive Load

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Overview

  • The Context

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  • Opportunities: How GenAI was used

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  • Implementation challenges and suggestions for improvement

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  • Final thought

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Context

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Context

  • Sino-US JVU, access to internal ChatGPT tool
  • 2.5 hours p/w, 12 students, Chinese L2 English users
  • EAP course – first year students, 17 professors
  • 7-week schedule, session 3
  • Community-Based Learning (CBL) project
  • Team research project (assignment)
    • NOT a research methods class.

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Key Points

Important!

NOT the first encounter with GenAI

Essential:

Raise awareness of ethics & self-directed learning

Need:

Promote the efficiency of using GenAI

    • offset the cognitive load
    • 7-week course

Understand:

Promote the effectiveness of using GenAI – Bloom’s Taxonomy

Support:

Provide appropriate scaffolding/ guidance

Choice:

Create space for autonomy

    • Not used by all instructors (17 total)
    • Student-experimentation with input
    • Student-driven critique and enhancement

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OPPORTUNITIES

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What and Why

The Problem

  • Time: 7-week schedule
  • Timeline: National holiday conflict
  • Need to develop an ethical understanding of using such tools

Learning Objective

  • Primary data collection – survey development
  • Community-based learning –
    • Engaging the local community partner
    • High School students
    • English L2
  • Ethics of using AI

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Two Examples of Ethics

The Garbage Bin

The Internal Platform

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What we did and why

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Task Example:

Understanding and analyzing

Examining prompts, experimenting with AI

Application

Experiment and generate example survey questions (practice)

Evaluation and Creation

Critique generated survey questions, enhance them

“offsetting the cognitive load” – not starting from the beginning

Analyze

Pilot survey

Creation

Enhance and finalize survey questions

Understand

Additional resources

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Task Example:

  • Select the ‘right’ tool: accessible, safe
  • APPLY: Give the AI clear instructions
  • ANALYZE: Compare input prompts and results – enhance cognition
  • EVALUATE: Critique generated results, make recommendations for change, discuss, pilot
  • CREATE: The final survey

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Task Example:

  • Ask DKU’s Local Chat GPT tool (assessable through the intranet) to create survey questions for your research question.

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  • Ask the AI tool to create survey questions for you by typing in your instructions. See the template below:

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  • [Please create survey questions to gather data about [your research question)]

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Task Example:

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CHALLENGES

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Implementation Challenges and Suggestions for Improvement

  • “Allow” use much earlier and with more frequency

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  • Further scaffolding:
    • Enhance AI instructions (following a framework)

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  • (Possibly) create, generate, compare and enhance survey questions (time dependent)

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  • Potential to examine greater range of AI tools

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CONCLUSION

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Final Thought

We need to be experimental and teachable

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Bibliography

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Bearman, M., Dawson, P., Ajjawi, R., Tai, J., and Bowd D. Eds. Re-imagining University Assessment in a Digital World. Springer. https://doi.org/10.1007/978-3-030-41956-1

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Bloxham, S., & Campbell, L. (2010). Generating dialogue in assessment feedback: exploring the use of interactive cover sheets. Assessment & Evaluation in Higher Education, 35(3), 291-300. https://doi.org/10.1080/02602931003650045

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Speicher, S. (2022, December). AI Assignments: 10 best practices for higher Ed instructors. ACUE. https://acue.org/blog/unlocking-human-ai-potential-10-best-practices-for-ai-assignments-in-higher-ed/

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Thank you for Listening

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Are there any questions?

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Laura Davies

Assistant Director, Senior Lecturer of EAP at Duke Kunshan University

Laura.davies@dukekunshan.edu.cn

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