LAFe: Learning Analytics Solutions to Support On-Time Feedback

Mello, Rafael Ferreira; Alves, Gabriel; Harada, Elaine; Felix, Esther; Chounta, IA; Santos, OC; Bittencourt, II; Olney, AM

Abstract

Feedback given to students by instructors is essential to guide students and help them improve from their mistakes. However, in higher education, instructors feel unable to give quality and timely feedback due to work overload and lack of time. In this context, this tutorial intends to discuss possible data-based and AI solutions for supporting students and instructors in the feedback process. It will include: a panel discussion about the importance of automating the feedback process, a demo of tools for this goal, and a card sorting activity to understand important aspects of developing tools to support on-time feedback.

Más información

Título según WOS: LAFe: Learning Analytics Solutions to Support On-Time Feedback
Título de la Revista: INTELLIGENT COMPUTING SYSTEMS (ISICS 2022)
Volumen: 2151
Editorial: SPRINGER INTERNATIONAL PUBLISHING AG
Fecha de publicación: 2024
Página de inicio: 478
Página final: 485
DOI:

10.1007/978-3-031-64312-5_61

Notas: ISI