Social Reader Perusall -- a Highly Effective Tool and Source of Formative Assessment Data
Project Overview
The document highlights the integration of generative AI in education, specifically through the use of Perusall, an advanced social annotation tool implemented at P.J. Šafárik University over three years. Targeted primarily at STEM disciplines, Perusall enhances blended and flipped learning environments by enabling collaborative annotations, which facilitate higher-order cognitive processes and prepare students for in-person discussions. The tool's capabilities were particularly beneficial during the Covid-19 pandemic, allowing for continued engagement and learning despite physical distancing. By leveraging AI and data science, Perusall effectively monitors student progress and fosters social learning, contributing to improved student engagement and overall learning outcomes. The findings underscore the potential of generative AI to transform educational practices, enhance collaborative learning, and provide valuable formative assessment data, ultimately leading to a more interactive and effective learning experience.
Key Applications
Perusall
Context: Used in blended and flipped learning environments for STEM disciplines at P.J. Šafárik University.
Implementation: Integrated into courses as a social annotation tool for collaborative learning and assessment, with data analytics features.
Outcomes: Enhanced student engagement, improved reading comprehension, and facilitated higher-order cognitive processes during face-to-face sessions.
Challenges: Requires continuous data processing and management, which can be time-consuming without automation.
Implementation Barriers
Technical Barrier
Manipulating and processing data reports from Perusall can be tedious and error-prone.
Proposed Solutions: Application of Open Data Science Tools like Jupyter for automating data processing and visualization.
Project Team
Jozef Hanč
Researcher
Martina Hančová
Researcher
Dominik Borovský
Researcher
Contact Information
For information about the paper, please contact the authors.
Authors: Jozef Hanč, Martina Hančová, Dominik Borovský
Source Publication: View Original PaperLink opens in a new window
Project Contact: Dr. Jianhua Yang
LLM Model Version: gpt-4o-mini-2024-07-18
Analysis Provider: Openai