Fu-Yin Cherng

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Assistant Professor in Human-Computer Interaction at National Chung Cheng University.

Hello!

I am Fu-Yin Cherng (程芙茵), currently a tenure-track assistant professor in the Department of Computer Science and Information Engineering at National Chung Cheng University since 2021. My research interests include Human-Computer Interaction (HCI), Human-Centered AI (HCAI)/Human-AI Interaction (HAI), Neuroergonomics, Brain-Computer Interface, Technology-Supported Learning, Data-Driven Design.

My research vision is to uncover how contemporary information formats, such as online comments and short-form videos, shape cognitive processes, behaviors, and decision-making. I achieve this vision by integrating physiological data from brain-sensing and eye-tracking. Guided by these physiological insights, my ultimate goal is to provide design recommendations that augment user cognition while preserving autonomy. My work applies this unique approach to crucial domains, including collective and peer commentary, online and programming education, and notification design.

Education & Professional Experience

Research Project Highlight

Short-form Video and Sustained Attention

project_esl 2023 - 2024, National Chung Cheng University

This study explored the relationship between short-form video consumption and sustained attention. Through an online survey using a psychological test, we found that consuming more short-form videos is associated with poorer sustained attention. However, a follow-up long-term field experiment with regular sustained attention tests showed that changing the amount of time spent watching short-form videos did not significantly alter performance on these tests. These findings offer a preliminary look into the effects of short-form videos on sustained attention.

Keywords: Short Video, Sustained Attention

Resource: [Paper - CHI 2024 LBW] [Presentation Video - CHI 2024 LBW]

ESL Learning and Video Speed

project_esl 2023 - 2024, National Chung Cheng University

We studied how different methods of adjusting video playback speed—direct versus gradual—affect English-as-a-Second-Language (ESL) learners. Using both objective metrics like pupil diameter and subjective survey feedback from 32 participants, we found that gradual adjustments were superior. This method enhanced the learners’ flow state and video comprehension while being less distracting.

Keywords: Educational Technology, Extensive Viewing, Cognitive Load, Flow State

Resource: [Paper - CHI 2024] [Presentation Video - CHI 2024]

Social Preference Effect in E-Commerce Context

project_vreeg 2019 - 2022, UC Davis

We studied how displaying collective information, such as social ratings and reviews, influences users’ decision-making. We used EEG signals to assess the cognitive responses of participants in a laboratory study. The results indicated that social information can alter user preferences and affect their attention, working memory, and emotions. Our predictive analysis also found that EEG-based measures are more powerful than behavioral measures at determining how this collective information is presented. The findings offer design implications for systems that use collective ratings.

Keywords: Social Computing, Neuromarketing, Virtual Reality

Resource: [Paper - CHI 2022] [Presentation Video - CHI 2022]

Course and Teaching Statement

As a student who struggles with traditional assessments like exams, I advocate for project-based learning and believe collaborative learning is essential. To support this, I design various in-class activities and open discussions, along with semester-long group projects that showcase diverse competencies. Also, I have taught several English as a Medium of Instruction (EMI) courses, which I believe are crucial for helping students connect with the international community.

Programming Design I & II

Human-Computer Interaction and Method of User Research

Grants

Principal Investigator

Co-Principal Investigator