Hey,I'm Vincent Dörig.

CS student & Research Assistant @ ETH Zürich

I’m Vincent, a software engineer and research assistant based in Zurich, Switzerland. Currently, I’m completing my Bachelor's degree in Computer Science at ETH Zurich.

I am passionate about human-AI interaction, natural language processing and human-computer interaction, and I am eager to apply these disciplines across various interdisciplinary fields. With a sharp eye for design, I am committed to creating products that excel in both visual and functional appeal.

Outside of academia, I enjoy various sports and do analog photography.

Research

Harmonizing Assistance: Moderating Visual and Textual Aids in AI-Enhanced Textbook Reading with IRead

IRead is an interactive tool that transforms textbooks into engaging, visual, and AI-enhanced study experiences. Its effectiveness is evaluated based on educational models and user feedback.

  • Xiaoyu Zhang=, Vincent Dörig=,
  • researchsquare.com
  • iread.ethz.ch
  • Show Abstract
    Textbooks continue to be one of primary mediums of learning. Students often need additional support during the process of reading textbooks leading to several research efforts that aim to increase student engagement and provide tailored experiences in textbook reading. However, providing excessive information beyond the textbook can also distract students from the reading task. When enhancing the reading experience, one has to strike a delicate balance between providing sufficient informational support and maintaining students’ focus on textbook reading. Fusing together latest developments in large language models (LLMs), their applications in education and several pedagogical theories, we design a textbook reading guidance mechanism. We introduce IRead, an interactive tool for textbook reading which uses LLMs with visualization and interaction techniques, to enhance students’ reading and learning experiences. IRead incorporates conceptual visualizations that reflect the textbook’s content and features an AI-driven question bot that generates questions and offers hints in response to student reading and interaction history. We evaluate IRead with a between-subject user study and measure the effectiveness of our methodology in supporting the students’ reading experience based on the Bloom’s Taxonomy and the ARCS model. We collect feedback from participants ranging from undergraduate to doctorate students. The results highlight the effectiveness of simple yet intuitive visualizations, such as the concept tree in IRead. We also derive general insights for the development of tools that enhance educational reading experiences.

Featured Personal Projects

ETH Dashboard & Quicklinks

A collection of useful links and a customisable timetable for ETH students.

n.ethz.ch/~vdoerig/dashboard

LaTeX.css

A classless CSS framework that makes every website look like a LaTeX document.

latex.now.sh

chl.li

A simple, modern and privacy-friendly URL shortener.

chl.li

Gallery

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