Artificial Intelligence methodologies to early predict student outcome and enrich learning material
Year: 2022
Type: dissertation
Abstract: From the emergence of the Web onward new learning modes such as distance learning and blended learning have developed.At the same time, Artificial Intelligence (AI) has taken hold in most areas including education.This dissertation focuses on the application of AI (i) to predict the student's exam outcome and (ii) to enrich learning resources.List of Tables xiii 3.3 Example of overlapped n-grams . . . . . . . . . . . . . . . . . . .3.4 VISA Named Entity Linking performance on DMBS-LARGE dataset 3.5 VISA Named Entity Linking performance on DMBS-FOCUS dataset 3.6 VISA Recommendation performance in a Database course . . . . . .4.1 Analysis on available datasets for Cross-media Retrieval . . . . . .4.2 Features characterizing the hts,vi pair in TVREM . . . . . . . . . .4.3 Hyper-parameters for grid search in TVREM . . . . . . . . . . . .4.4 Statistics on new datasets defined for Cross-Media Retrieval in education: BookToYout and EDUCA . . . . . . . . .
Source: PORTO@Iris
Author: CANALE, LORENZO
Language: English
Subfield: Computer Science Applications
Field: Computer Science
Domain: Physical Sciences
SDG: Quality education
Open Access status: green
OpenAlex ID: W7217209652