Chatbot per Moodle: un assistente virtuale per i corsi universitari ad alto numero di studenti

Conference paper

Nalli, G. and Amendola, D. 2020. Chatbot per Moodle: un assistente virtuale per i corsi universitari ad alto numero di studenti. MoodleMoot Italia 2020. Online 26 - 28 Nov 2020 MediaTouch 2000. pp. 64-67
TypeConference paper
TitleChatbot per Moodle: un assistente virtuale per i corsi universitari ad alto numero di studenti
AuthorsNalli, G. and Amendola, D.
Abstract

Negli ultimi anni, molte Università hanno iniziato ad utilizzare piattaforme e-learning, ad es. Moodle, come supporto alla didattica d’aula, attraverso la costruzione di corsi online dedicati che favoriscano un miglior processo di apprendimento per gli studenti universitari. In questi corsi online, in particolare nel caso di migliaia di studenti iscritti, per il docente risulta complicato gestire manualmente tutte le richieste personali degli utenti pervenute tramite i tool online come Chat e Forum. Questo è dovuto anche alla mancanza in piattaforme come Moodle di un sistema che permetta un supporto tecnologico dinamico e intelligente alle necessità individuali degli utenti. A tal fine abbiamo sviluppato un software intelligente in python, implementando un prototipo di Chatbot che riconosca le domande degli studenti e automaticamente, grazie all'uso di tecniche di Machine Learning, fornisca loro le risposte corrette in tempo reale. Questo software verrà quindi integrato nella piattaforma Moodle.

Sustainable Development Goals4 Quality education
Middlesex University ThemeCreativity, Culture & Enterprise
ConferenceMoodleMoot Italia 2020
Page range64-67
Proceedings TitleAtti del MoodleMoot Italia 2020
ISBN9788890749360
PublisherMediaTouch 2000
Publication dates
Print28 Nov 2020
Publication process dates
Accepted2020
Deposited14 Jun 2024
Output statusPublished
LanguageItalian
Permalink -

https://repository.mdx.ac.uk/item/wx65q

Log in to edit
  • 39
    total views
  • 0
    total downloads
  • 1
    views this month
  • 0
    downloads this month

Export as

Related outputs

Online application for the early detection of students at risk of failing through Artificial Intelligence
Nalli, G., Marconi, A., Karakatič, S., Brezočnik, L., Montagna, A., Amendola, D. and De Leone, R. 2024. Online application for the early detection of students at risk of failing through Artificial Intelligence. Minerva, T. and De Santis, A. (ed.) 2023 Italian Symposium on Digital Education. Reggio Emilia, Italy 13 - 15 Sep 2023 Pearson. pp. 56-62
Blockchain in e-learning platform to enhance trustworthy and sharing of micro-credentials
Bigiotti, A., Bottoni, M. and Nalli, G. 2024. Blockchain in e-learning platform to enhance trustworthy and sharing of micro-credentials. 36th International Conference on Advanced Information Systems Engineering Workshops. Limassol, Cyprus 03 - 07 Jun 2024 Cham, Switzerland. Springer. https://doi.org/10.1007/978-3-031-61003-5_1
Hybrid educational environments – using IoT to detect emotion changes during student interactions
Nalli, G., Dafoulas, G., Tsiakara, A., Langari, B., Mistry, K. and Tahmasebi Aria, F. 2023. Hybrid educational environments – using IoT to detect emotion changes during student interactions. Interaction Design and Architecture(s). 58 (1), pp. 39-52. https://doi.org/10.55612/s-5002-058-001
Online tutoring system for programming courses to improve exam pass rate
Nalli, G., Culmone, R., Perali, A. and Amendola, D. 2023. Online tutoring system for programming courses to improve exam pass rate. Journal of E-Learning and Knowledge Society. 19 (1), pp. 27-35. https://doi.org/10.20368/1971-8829/1135704
Machine Learning model for student drop-out prediction based on student engagement
Brezočnik, L., Nalli, G., De Leone, R., Val, S., Podgorelec, V. and Karakatič, S. 2023. Machine Learning model for student drop-out prediction based on student engagement. Karabegovic, I., Kovačević, A. and Mandzuka, S. (ed.) 9th International Conference on New Technologies, Development and Application. Sarajevo, Bosnia and Herzegovina 22 - 24 Jun 2023 Cham Springer. pp. 486–496 https://doi.org/10.1007/978-3-031-31066-9_54
Comparison of the effectiveness and performance of student workgroups in online wiki activities with and without AI
Nalli, G. and Smith, S. 2023. Comparison of the effectiveness and performance of student workgroups in online wiki activities with and without AI. 4th International Electronic Conference on Applied Sciences. Online 27 Oct - 10 Nov 2023 MDPI AG. https://doi.org/10.3390/ASEC2023-16273
Machine-learning-based software to group heterogeneous students for online peer assessment activities
Amendola, D., Nalli, G. and Miceli, C. 2023. Machine-learning-based software to group heterogeneous students for online peer assessment activities. Fulantelli, G., Burgos, D., Casalino, G., Cimitile, M., Lo Bosco, G. and Taibi, D. (ed.) 4th International Conference on Higher Education Learning Methodologies and Technologies Online. Palermo, Italy 21 - 23 Sep 2022 Cham Springer. https://doi.org/10.1007/978-3-031-29800-4_2
Artificial Intelligence to improve learning outcomes through online collaborative activities
Nalli, G., Amendola, D. and Smith, S. 2022. Artificial Intelligence to improve learning outcomes through online collaborative activities. Fotaris, P. and Blake, A. (ed.) 21st European Conference on e-Learning. Brighton, UK 27 - 28 Oct 2022 Academic Conferences and Publishing International (ACPI). pp. 475-479 https://doi.org/10.34190/ecel.21.1.661
Comparative analysis of clustering algorithms and moodle plugin for creation of student heterogeneous groups in online university courses
Nalli, G., Amendola, D., Perali, A. and Mostarda, L. 2021. Comparative analysis of clustering algorithms and moodle plugin for creation of student heterogeneous groups in online university courses. Applied Sciences. 11. https://doi.org/10.3390/app11135800
Application of machine learning to the learning analytics of the Moodle platform to create heterogeneous groups in on-line courses
Nalli, G., Mostarda, L., Perali, A., Pilati, S. and Amendola, A. 2019. Application of machine learning to the learning analytics of the Moodle platform to create heterogeneous groups in on-line courses. Italian Journal of Educational Research. p. 156–173.
Tool per la classificazione dei sentimenti degli studenti Implicati in moduli didattici universitari in modalità e-learning
Nalli, G., Amendola, D., Schettini, C. and Galassi, R. 2019. Tool per la classificazione dei sentimenti degli studenti Implicati in moduli didattici universitari in modalità e-learning. MoodleMoot Italia 2019. Verona, Italy 05 - 07 Dec 2019 MediaTouch 2000. pp. 29-32
Il Blended Learning per migliorare l’efficacia della didattica universitaria: il corso di Computer Ethics
Amendola, D., Nalli, G. and De Vivo, M. 2017. Il Blended Learning per migliorare l’efficacia della didattica universitaria: il corso di Computer Ethics. EMEMITALIA 2017. Bolzano, Italy 30 Aug - 01 Sep 2017