This paper proposes an Artificial Intelligence-based architecture for the selection and management of groupworks. The COVID era has taught us that future schooling systems will be based on both face to face lessons and remote ones. Groupwork can bring strong motivation to students and help them fight loneliness and discouragement, especially in case groups are handled with properly, in terms of membership and skills at disposal.

KEEPING STUDENTS ENGAGED AND MOTIVATED THROUGH WORKGROUP AND NEURAL NETWORKS-BASED GROUPS MANAGEMENT DURING AND AFTER THE COVID ERA

C De Castro
2021

Abstract

This paper proposes an Artificial Intelligence-based architecture for the selection and management of groupworks. The COVID era has taught us that future schooling systems will be based on both face to face lessons and remote ones. Groupwork can bring strong motivation to students and help them fight loneliness and discouragement, especially in case groups are handled with properly, in terms of membership and skills at disposal.
2021
Istituto di Elettronica e di Ingegneria dell'Informazione e delle Telecomunicazioni - IEIIT
COVID-19
e/m-learning
groupwork
neural networks
deep networks
groups management
blended learning.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.14243/398898
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