Dynamic Genre-Specific Automated Online Feedback Tool

• Project/Area Number: 23K00656
• Research Category: Grant-in-Aid for Scientific Research (C)
• Allocation Type: Multi-year Fund
• Section: 一般
• Review Section: Basic Section 02100:Foreign language education-related
• Research Institution: The University of Aizu
• Principal Investigator: CARR Nicholas 会津大学, コンピュータ理工学部, 准教授 (70965699)
• Co-Investigator(Kenkyū-buntansha): Julian Villegas 会津大学, コンピュータ理工学部, 上級准教授 (50706281) ; BLAKE John 会津大学, コンピュータ理工学部, 上級准教授 (80635954)
• Project Period (FY): 2023-04-01 – 2026-03-31
• Project Status: Granted (Fiscal Year 2023)
• Budget Amount: ¥3,640,000 (Direct Cost: ¥2,800,000、Indirect Cost: ¥840,000); Fiscal Year 2025: ¥1,560,000 (Direct Cost: ¥1,200,000、Indirect Cost: ¥360,000); Fiscal Year 2024: ¥1,040,000 (Direct Cost: ¥800,000、Indirect Cost: ¥240,000); Fiscal Year 2023: ¥1,040,000 (Direct Cost: ¥800,000、Indirect Cost: ¥240,000)
• Keywords: Automated feedback / Sociocultural theory / Dynamic feedback / Computer-science writing / iCALL

Outline of Research at the Start

This project develops an online tool which identifies genre specific errors in computer-science academic writing; errors which are not detected in generic grammar checking tools. The tool then provides dynamic feedback to users. The learning benefits of the tool are investigated longitudinally.