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Utilizing Electroencephalography Measurements for Comparison of Task-Specific Neural Efficiencies: Spatial Intelligence Tasks
Published on: August 9, 2016
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Effects of generative artificial intelligence on cognitive effort and task performance: study protocol for a
Youjie Chen1,2, Yingying Wang3, Torsten Wüstenberg4
1Department of Information Science, Cornell University, Ithaca, USA. yc2669@cornell.edu.
Trials
|July 11, 2025
Summary
Generative artificial intelligence (AI) may impact cognitive effort and writing skills in college students. This study investigates AI
Area of Science:
- Cognitive Science
- Human-Computer Interaction
- Educational Technology
Background:
- Generative artificial intelligence (AI) presents dual possibilities: enhancing productivity or eroding human cognition through over-reliance.
- Understanding AI's role in cognition is crucial, particularly in educational settings.
- This study examines generative AI's impact on college students' analytical writing.
Purpose of the Study:
- To investigate the causal effects of generative AI on cognitive effort during analytical writing.
- To evaluate the impact of generative AI on writing performance in a collaborative human-AI context.
- To provide insights for responsible AI design and policy.
Main Methods:
- A randomized controlled laboratory experiment comparing AI use (intervention) versus non-use (control).
- Utilizing eye-tracking and functional near-infrared spectroscopy (fNIRS) to measure cognitive effort.
- Employing surveys to assess participants' perceptions and attitudes towards generative AI.
Main Results:
- The study aims to establish causal links between generative AI use, cognitive effort, and writing outcomes.
- Data collection includes physiological measures (eye-tracking, fNIRS) and self-reported perceptions.
- Findings will quantify the impact of AI on mental resource allocation and task performance.
Conclusions:
- This research will clarify generative AI's influence on cognitive processes in academic writing.
- Results will inform policymakers on regulating AI and guide the development of responsible AI tools.
- The study contributes empirical evidence to the ongoing debate on AI's augmentation versus erosion of human cognition.
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