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Michele Della Ventura

 

Michele Della Ventura, si è diplomato brillantemente in pianoforte sotto la guida di Francesco Bencivenga.
Parallelamente agli studi musicali, si è laureato in Discipline Tecnologiche con il massimo dei voti e la lode, ottenendo una borsa di studio, e successivamente ha conseguito un Master di II livello in Scienze e Tecnologie Didattiche presso l’Università Tor Vergata di Roma, risultando primo del corso con la Tesi “Apprendimento e nuove tecnologie”.
I suoi interessi nella ricerca riguardano:
- i rapporti tra musica e matematica con particolare riferimento agli studi sull’intelligenza artificiale nel campo dell’analisi computerizzata della musica tonale;
- l’utilizzo delle tecnologie web per la didattica.
È autore di articoli pubblicati su riviste scientifiche internazionali e di libri per la didattica nelle scuole superiori (presenti anche al Salone Internazionale del Libro di Torino 2012 e Torino 2018).
È il revisore di articoli e membro di comitati scientifici di Conferenze Internazionali.
È stato invitato come relatore in Conferenze Internazionali: Italia, Austria, Canada, Cina, Estonia, Francia, Germania, Grecia, Giappone, Inghilterra, Norvegia, Polonia, Portogallo, Repubblica Ceca, Romania, Singapore, Spagna, Stati Uniti (Baltimora, Boston, Las Vegas, New York, Washington), Ungheria.
È insegnante d’informatica nei corsi Universitari presso Accademie e Conservatori di Musica e di Tecnologie Musicali nei Licei ad Indirizzo Musicale.

 

Michele Della Ventura, professor of Music Technology, is a learning expert, researcher and instructional designer. His research interests include correlation between music and mathematics with a particular emphasis on artificial intelligence research in the field of computer-aided analysis of tonal music; intelligent systems; enhancing teaching and learning with technology; assessment for learning and strategies and models for the effective integration of technology into the curriculum at all academic levels.
He is the author of several articles presented at many conferences and published in international science magazines and high school textbooks (also featured at the International Book Salon of Turin in 2012 and 2018).
He proofreads articles and is a member of scientific committees in International Conferences.
He was invited as keynote speaker to International Conferences in Italy, Austria, Canada, China, Czech Republic, Estonia, France, Germany, Greece, Hong Kong, Hungary, Ireland, Japan, Norway, Poland, Portugal, Romania, Singapore, Spain, UK, US (Baltimora, Boston, Las Vegas, New York, Washington).
Michele Della Ventura has also consulted on Big Data and Semantic Technology projects in Italy. Some of the projects include indexation of the symbolic level of musical text.
He is currently involved in several researches related to technology supported learning for dyslexic students, learning through the use of social media and  technology supported student’s music analysis and composition.
He teaches Music Informatics in University courses at Music Academies and Conservatories and Musical Technologies in Music High Schools.

 


Pubblicazioni/ Publications

Journals and Books

M. Della Ventura, I. Bordignon (2022). Towards an Ecocritical Norwegian Folklore and Music: Water, Love and Death. IJMSTA. 2022 April 18; 3 (2): 17-31. ISSN: 2612-2146, DOI: https://doi.org/10.48293/IJMSTA-83

M. Della Ventura (2021), From the Music Learning Process to Its Effective Design, International Journal of Emerging Technologies in Learning (iJET), Vol. 16 No. 21, pp. 13-25, November 2021. ISSN: 1863-0383, DOI: https://doi.org/10.3991/ijet.v16i21.24273

M. Della Ventura, I. Bordignon (2021). Ecocritical Musicology as a Key to Understanding Grieg's Music. IJMSTA. 2021 November 19; 3 (2): 32-43. ISSN: 2612-2146, DOI: https://doi.org/10.48293/IJMSTA-79

M. Della Ventura (2018), DNA Musicale: matematicamente suono, ABEditore, Milano. ISBN: 978-88-6551-281-4

E.E. Mahmut, M. Della Ventura, V. Stoicutivadar (2018), An Entropy-Based Computer Model for the Measurement of Phonetic Similarity: Dyslalia Screening in Early School-Age Children, Applied Medical Informatics, Vol. 40, No. 1-2 /2018, pp. 15-23.

M. Della Ventura (2017), Creating Inspiring Learning Environments by means of Digital Technologies: A Case Study of the Effectiveness of WhatsApp in Music Education, EAI Endorsed Transactions on e-Learning (Journal), Vol. 4, pp. 1-9, July 2017. ISSN: 2032-9253, DOI: http://dx.doi.org/10.4108/eai.26-7-2017.152906

M. Della Ventura (2017), Digital Technologies and Digital Strategies to Enhance Musical Knowledge: A Qualitative Case Study , The International Journal of E-Learning and Educational Technologies in the Digital Media (IJEETDM), Vol. 3(2), pp. 75-82, June 2017. ISSN: 2410-0439, DOI: http://dx.doi.org/10.17781/P002329

M. Della Ventura (2017), Dai numeri al suono, ABEditore, Milano, ISBN: 978-88-6551-252-4

M. Della Ventura (2014), Discovering Hidden Themes in Symbolic Music Text, International Journal on Lecture Notes on Software Engineering, Vol. 3(3), pp. 210-213, August 2015. ISSN: 2301-3559, DOI: 10.7763/LNSE.2015.V3.192

M. Della Ventura (2014), The Social Network as a Filter for Internet Research , International Journal of Information and Education Technology, IPEDR Vol. 70(1), pp. 1-6. ISSN: 2010-4626, DOI: 10.7763/IPEDR.2014.V70.1

M. Della Ventura (2014), Problem-Based Learning and e-Learning in Sound Recording, International Journal of Information and Education Technology, Vol. 4(5), pp. 426-429. ISSN: 2010-3689, DOI: 10.7763/IJIET.2014.V4.443

M. Della Ventura (2014), Detection of Historical Period in Symbolic Music Text, International Journal of e-Education, e-Business, e-Management and e-Learning, Vol.4(1), pp. 32-36, February 2014. ISSN: 2010-3654, DOI: 10.7763/IJEEEE.2014.V4.297

M. Della Ventura (2013), Detection of Historical Period in Symbolic Music Text, International Journal of e-Education, e-Business, e-Management and e-Learning, Vol. 4(1), pp. 32-36. ISSN: 2010-3654, DOI: 10.7763/IJEEEE.2014.V4.297

M. Della Ventura (2013), Relations between melody and rhythm on music analysis: representations and algorithms for Symbolic Musical Data, International Journal of Applied Physics and Mathematics, Vol. 3(2), pp. 87-91. ISSN: 2010-362X, DOI: 10.7763/IJAPM.2013.V3.181

M. Della Ventura (2012), Teoria e pratica della ripresa stereofonica, ABEditore, Milano. ISBN: 978-88-6551-111-4


Conferences

Della Ventura, M. (2024). A Statistical Approach for Modeling the Expressiveness of Symbolic Musical Text. In: Younas, M., Awan, I., Petcu, D., Feng, B. (eds) Mobile Web and Intelligent Information Systems. MobiWIS 2024. Lecture Notes in Computer Science, vol 14792. Springer, Cham.
ISBN: 978-3-031-68004-5, DOI: https://doi.org/10.1007/978-3-031-68005-2_17

Della Ventura, M. (2024). Artificial Intelligence Literacy to Enhance Teacher Critical Thinking. In: Cheng, YP., Pedaste, M., Bardone, E., Huang, YM. (eds) Innovative Technologies and Learning. ICITL 2024. Lecture Notes in Computer Science, vol 14785. Springer, Cham.
ISBN: 978-3-031-65880-8, DOI: https://doi.org/10.1007/978-3-031-65881-5_19

Della Ventura, M. (2024). ICT: Inclusive Competences for Teaching. In: Daimi, K., Al Sadoon, A. (eds) Proceedings of the Third International Conference on Innovations in Computing Research (ICR’24). ICR 2024. Lecture Notes in Networks and Systems, vol 1058. Springer, Cham.
ISBN: 978-3-031-65521-0, DOI: https://doi.org/10.1007/978-3-031-65522-7_34

Della Ventura, M. (2024). A Deep Learning Algorithm for the Development of Meaningful Learning in the Harmonization of a Musical Melody. In: Lopata, A., Gudonienė, D., Butkienė, R. (eds) Information and Software Technologies. ICIST 2023. Communications in Computer and Information Science, vol 1979. Springer, Cham.
ISBN: 978-3-031-48980-8, DOI: https://doi.org/10.1007/978-3-031-48981-5_1

Della Ventura, M. (2023). Intelligent Tutoring System and Learning: Complexity and Resilience.  In: Dascalu, M., Mealha, O., Virkus, S. (eds) Smart Learning Ecosystems as Engines of the Green and Digital Transition. SLERD 2023. Advances in Sustainability Science and Technology. Springer, Singapore. ISBN: 978-981-99-5790-3, DOI: https://doi.org/10.1007/978-981-99-5540-4_3

Della Ventura, M. (2023). Intelligent (Musical) Tutoring System: The Strategic Sense for Deep Learning? In: Huang, YM., Rocha, T. (eds) Innovative Technologies and Learning. ICITL 2023. Lecture Notes in Computer Science, vol 14099. Springer, Cham. ISBN: 978-3-031-40112-1, DOI: https://doi.org/10.1007/978-3-031-40113-8_1

Della Ventura, M. (2023). Human-Centred Artificial Intelligence in Sound Perception and Music Composition. In: Abraham, A., Pllana, S., Casalino, G., Ma, K., Bajaj, A. (eds) Intelligent Systems Design and Applications. ISDA 2022. Lecture Notes in Networks and Systems, vol 646. Springer, Cham. ISBN: 978-3-031-27439-8, DOI: https://doi.org/10.1007/978-3-031-27440-4_21

Della Ventura, M. (2022). A Self-learning Musical Tool to Support the Educational Activity. In: Arai, K. (eds) Intelligent Systems and Applications. IntelliSys 2022. Lecture Notes in Networks and Systems, vol 543. Springer, Cham. ISBN: 978-3-031-16077-6, DOI: https://doi.org/10.1007/978-3-031-16078-3_3

Della Ventura, M. (2022). Compensatory Skill: The Dyslexia’s Key to Functionally Integrate Strategies and Technologies. In: Uden, L., Liberona, D. (eds) Learning Technology for Education Challenges. LTEC 2022. Communications in Computer and Information Science, vol 1595. Springer, Cham. ISBN: 978-3-031-08889-6, DOI: https://doi.org/10.1007/978-3-031-08890-2_12

Della Ventura, M. (2022). A Self-adaptive Learning Music Composition Algorithm as Virtual Tutor. In: Maglogiannis, I., Iliadis, L., Macintyre, J., Cortez, P. (eds) Artificial Intelligence Applications and Innovations. AIAI 2022. IFIP Advances in Information and Communication Technology, vol 646. Springer, Cham. ISBN: 978-3-031-08332-7, DOI: https://doi.org/10.1007/978-3-031-08333-4_2

M. Della Ventura (2021). Automatic Recognition of Key Modulations in Symbolic Musical Pieces Using Information Theory. In: Arai K. (eds) Intelligent Systems and Applications. IntelliSys 2021. Lecture Notes in Networks and Systems, vol 294. Springer, Cham. ISBN: 978-3-030-82192-0, DOI: https://doi.org/10.1007/978-3-030-82193-7_56

Lariccia, S., Lariccia, G., Gabrieli, M., Della Ventura, M., Toffoli, G., Montanari, M.(2021). Museup: how virtual choirs may help students learning to learn. In: International Technology, Education and Development Conference INTED 2021 Proceedings. ISBN: 978-84-09-27666-0, ISSN: 2340-1079, DOI: http://dx.doi.org/10.21125/inted.2021.1360

M. Della Ventura (2021). Implementation of an Automatic Musical Scores Recognition System. In: Haber P., Lampoltshammer T., Mayr M., Plankensteiner K. (eds) Data Science – Analytics and Applications. Springer Vieweg, Wiesbaden. ISBN: 978-3-658-32181-9, DOI: https://doi.org/10.1007/978-3-658-32182-6_8

M. Della Ventura (2020). Removing Digital Natives from Technological Illiteracy with the Weblog. In: Huang TC., Wu TT., Barroso J., Sandnes F.E., Martins P., Huang YM. (eds) Innovative Technologies and Learning. ICITL 2020. Lecture Notes in Computer Science, vol 12555. Springer, Cham. ISBN: 978-3-030-63884-9, DOI: https://doi.org/10.1007/978-3-030-63885-6_65

M. Della Ventura (2020). Analytical Techniques for the Identification of a Musical Score: The Musical DNA. In: Krzhizhanovskaya V. et al. (eds) Computational Science – ICCS 2020. ICCS 2020. Lecture Notes in Computer Science, vol 12141. Springer, Cham. ISBN: 978-3-030-50425-0, DOI: https://doi.org/10.1007/978-3-030-50426-7_3

M. Della Ventura (2020). Symbolic Music Text Fingerprinting: Automatic Identification of Musical Scores. In: Czarnowski I., Howlett R., Jain L. (eds) Intelligent Decision Technologies. IDT 2020. Smart Innovation, Systems and Technologies, vol 193. Springer, Singapore. ISBN: 978-981-15-5924-2, DOI: https://doi.org/10.1007/978-981-15-5925-9_22

M. Della Ventura (2019). Speech Assessment Based on Entropy and Similarity Measures. In: Le Thi H., Le H., Pham Dinh T., Nguyen N. (eds) Advanced Computational Methods for Knowledge Engineering. ICCSAMA 2019. Advances in Intelligent Systems and Computing, vol 1121. Springer, Cham. ISBN: 978-3-030-38363-3, DOI: https://doi.org/10.1007/978-3-030-38364-0_20

M. Della Ventura (2019) Between Research and Action: The Generative Sense of Technology. In: Rønningsbakk L., Wu TT., Sandnes F., Huang YM. (eds) Innovative Technologies and Learning. ICITL 2019. Lecture Notes in Computer Science, vol 11937, pp. 754-763. Springer, Cham. ISBN: 978-3-030-35342-1, DOI: https://doi.org/10.1007/978-3-030-35343-8_78

M. Della Ventura (2019) Exploring the Impact of Artificial Intelligence in Music Education to Enhance the Dyslexic Student’s Skills. In: Uden L., Liberona D., Sanchez G., Rodríguez-González S. (eds) Learning Technology for Education Challenges. LTEC 2019. Communications in Computer and Information Science, vol 1011. Springer, Cham, ISBN: 978-3-030-20797-7, DOI: https://doi.org/10.1007/978-3-030-20798-4_2

E.E. Mahmut, M. Della Ventura, D. Berian, V. Stoicutivadar (2019), Entropy-Based Dyslalia Screening, In proceeding of the 17th International Conference on Informatics, Management and Technology in Healthcare, 2019 Jul 4;262:252-255, Athens, Greece, ISBN: 978-1-61499-986-7, DOI:10.3233/SHTI190066

M. Della Ventura (2019) Monitoring the Learning Process to Enhance Motivation by Means of Learning by Discovery Using Facebook. In: Ma W., Chan W., Cheng C. (eds) Shaping the Future of Education, Communication and Technology. Educational Communications and Technology Yearbook. Springer, Singapore, ISBN: 978-981-13-6680-2, DOI: https://doi.org/10.1007/978-981-13-6681-9_9

M. Della Ventura (2018), Shaping the Music Perception of an Automatic Music Composition: An Empirical Approach for Modelling Music Expressiveness, In Proceedings of the Tenth International Conference on Soft Computing and Pattern Recognition (SoCPaR 2018), Porto, Portugal, Springer vol 942, ISBN: 978-3-030-17064-6, DOI: https://doi.org/10.1007/978-3-030-17065-3_1

M. Della Ventura (2018), Computer System for Designing Musical Expressiveness in an Automatic Music Composition Process, In Proceedings of the International Conference on Bio-inspired Computing: Theories and Applications (BIC-TA 2018), Hong Kongi, People's Republic of China, Springer, ISBN: 978-981-13-2825-1, DOI: https://doi.org/10.1007/978-981-13-2826-8_38

M. Della Ventura (2018), Twitter As A Music Education Tool To Enhance The Learning Process: Conversation Analysis, In Proceedings of the International Conference on New Media for Educational Change: Effect on Learning and Reflection on Practice (HKAECT 2018), Hong Kong, People's Republic of China, Springer, ISBN: 978-981-10-8895-7, DOI: https://doi.org/10.1007/978-981-10-8896-4_7

M. Della Ventura (2018), Mobile Teaching: Remodel Music Technology Education to Engage Students, In Proceedings of the International Conference on Education and E-Learning (ICEEL 2018), Budapest, Hungary, ISBN: 978-93-87954-62-5, DOI: http://dx.doionline.org/dx/ISERD.25052018.8065

M. Della Ventura (2018), Voice Separation in Polyphonic Music: Information Theory Approach, In Proceedings of the 14th International Conference on Artificial Intelligence Applications and Innovations (AIAI 2018), Rhodes, Greece, Springer, ISBN: 978-3-319-92006-1, DOI: https://doi.org/10.1007/978-3-319-92007-8_54

M. Della Ventura (2018), Using Twitter to Enhance the Students Skills: Motivation a Disregarded Factor in Educational Design, In Proceedings of the 4th International Conference on e-Learning e-Education and Online Training (eLEOT 2018), Shanghai, People's Republic of China, Springer, ISBN 978-3-319-93719-9, DOI: http://dx.doi.org/10.1007/978-3-319-93719-9_46

M. Della Ventura (2017), Smart On-Line Technologies to Enhance Musical Kmowledge: A Qualitative Case Study, In Proceedings of the 6th International Conference on E-Learning and E-technology in Education (ICEEE 2017), Lodz, Poland, ISBN: 978-1-941968-44-4

M. Della Ventura (2017), Technology-Enhanced CLIL: Quality Indicators for the Analysis of an On-Line CLIL Course, In Proceedings of the 4th International Conference on Smart Innovation, Systems and Technologies (SEEL 2017), Vilamoura, Portugal, Springer, ISBN: 978-3-319-59450-7, DOI: https://doi.org/10.1007/978-3-319-59451-4_34

M. Della Ventura (2017), Similarity Measures for Music Information Retrieval, In Proceedings of the 5th International Conference on Computer Science, Apllied Mathematics and Applications (ICCSAMA 2017), Berlin, Germany, Springer, ISBN: 978-3-319-61910-1, DOI: https://doi.org/10.1007/978-3-319-61911-8_15

M. Della Ventura (2017), Peer Music Education For Social Sounds in a CLIL Classroom, In Proceedings of the 14th International Conference on Information Technology: New Generation (ITNG 2017), Las Vegas, USA, Springer, ISBN: 978-3-319-54978-1, DOI: https://doi.org/10.1007/978-3-319-54978-1_47

M. Della Ventura (2016), Automatic Music Composition from a Self-learning Algorithm. In: Ravulakollu K., Khan M., Abraham A. (eds) Trends in Ambient Intelligent Systems. Studies in Computational Intelligence, vol 633. Springer, Cham. ISBN: 978-3-319-30182-2, DOI: https://doi.org/10.1007/978-3-319-30184-6_9

M. Della Ventura (2016), A Learning Approach to Hierarchical Features for Automatic Music Composition, In Proceedings of the 3rd Euro-China Conference on Intelligent Data Analysis and Applications (ECC 2016), Fuzhou, China, Springer, ISBN: 978-3-319-48499-0, DOI: https://doi.org/10.1007/978-3-319-48499-0_24

M. Della Ventura (2016), Creating Inspiring Learning Environments by Means of Digital Technologies: A Case Study of the Effectiveness of WhatsApp in Music Education, In Proceedings of the 3rd International Conference on E-Learning, E-Education, and Online Training, Dublin, Ireland, Springer, pp. 36-45, ISBN: 978-3-319-49624-5, DOI: https://doi.org/10.1007/978-3-319-49625-2_5

M. Della Ventura (2016), A Bayesian Approach to Classify the Music Scores on the basis of the Music Style, In Proceedings of the 8th 8th International KES Conference on Intelligent Decision Technologies, Puerto de la Cruz, Tenerife, Spain, Springer, ISBN: 978-3-319-39627-9, DOI: https://doi.org/10.1007/978-3-319-39627-9_15

M. Della Ventura (2016), Using Mathematical Tools to Reduce the Combinatorial Explosion During the Automatic Segmentation of the Symbolic Musical Text, In Proceedings of the 4th International Conference on Computer Science, Applied Mathematics and Applications, Vienna, Austria, Springer, ISBN: 978-3-319-38883-0, DOI: https://doi.org/10.1007/978-3-319-38884-7_20

M. Della Ventura (2016), iPAD in Music Education: a Case Study of Collaborative Learning With Dyslexic Learners, In Proceedings of the International Conference on Interdisciplinary Social Science Studies , Oxford, UK, IOS Press, ISBN 978-1-911185- 02-4

M. Della Ventura (2015), Automatic Tonal Music Composition Using Functional Harmony, Social Computing, Behavioral- Cultural Modeling and Prediction, Springer. ISBN: 978-3-319-16267-6, DOI: https://doi.org/10.1007/978-3-319-16268-3_32

G. Fiocchetta, M. Della Ventura (2015), Motivational Influences in a Transnational Music Virtual Studio: A Qualitative Case Study, Workshop Proceedings of the 11th International Conference on Intelligent Environments, Prague, Czech Republic, ISBN 978-1-61499-529-6

M. Della Ventura (2015), The Influence of the Rhythm with the Pitch on Melodic Segmentation, In Proceedings of the Second Euro-China Conference on Intelligent Data Analysis and Applications (ECC 2015), Ostrava, Czech Republic, Springer, ISBN 978-3-419-21205-0, DOi: https://doi.org/10.1007/978-3-319-21206-7_17

M. Della Ventura (2015), E-Learning Indicators to Improve the Effectiveness of the Learning Process, In Proceedings of the International Conference on E-Learning in The Workplace (ICELW 2015), New York, USA, ISBN 978-0-9827670-5-4

M. Della Ventura (2014), Process, Project and Problem Based Learning as a Strategy for Knowledge Building in Music Technology, In Proceedings of the Multidisciplinay Academic Conference on Education, Teaching and e-Learning (MAC-EteL 2014), Prague, Czech Republic, ISBN: 978-80-905442-7-7

M. Della Ventura (2014), Music Technology: The Social Network as a Learning Resource, In the Proceedings of the 2nd International Conference on Computer Supported Education (COSUE 2014), Cambridge, Massachusetts, USA, ISBN: 978-960-474-363-6

M. Della Ventura (2013), Blended Learning and Sustainability in Music Education: Motivation to Learn, In Proceedings of the 11th WSEAS International Conference on E-Activities (EACTIVITIES 2013), Nanjing, China, ISBN: 978-960-474-356-8

M. Della Ventura (2013), Detection of Historical Period in Symbolic Music Data: Revisited Version, In Proceedings of the 12th International Conference on Telecommunications and Informatics (TELE-INFO 2013), Baltimora, USA, ISBN: 978-960-474-330-8

M. Della Ventura (2013), Evaluation of musical similarity on the symbolic level of the musical text, In Proceedings of the 15th International Conference on Artificial Intelligence (ICAI 2013), Las Vegas, USA, ISBN: 1-60132-246-1

M. Della Ventura (2013), Toward an Analysis of Polyphonic Music in The Textual Symbolic Segmentation, In Proceedings of the 2nd International Conference on Computer, Digital Comunications and Computing (ICDCC 2013), Brasov, Romania, ISBN: 978-1-61804-194-4

M. Della Ventura (2013), The "Concealed" Motif: Analysis and Identification, In Proceedings of the 12th International Conference on Artificial Intelligence, Knowledge Engineering and Data Bases (AIKED 2013), Cambridge, UK, ISBN: 978-1-61804-162-3

M. Della Ventura (2012), Influence of the harmonic/functional analysis on the musical execution: representation and algorithm, In Proceedings of the 3rd International Conference on Applied Informatics and Computing Theory (AICT 2012), Barcellona, Spain, ISBN: 978-1-61804-130-2

M. Della Ventura (2012), Rhythm analysis of the "Sonorous Continuum" and conjoint evaluation of the musical entropy, In Proceedings of the 13th International Conference on Acoustics & Music: Theory & Applications (AMTA 2012), Iasi (Romania), ISBN: 978-1-61804-096-1

M. Della Ventura (2011), Analysis of algorithms’ implementation for melodical operators in symbolical textual segmentation and connected evaluation of musical entropy, In Proceedings of the 2nd International Conference on Environment, Economics, Energy, Devices, Systems, Comunications, Computer, Mathematics, Drobeta Turnu Severin, Romania, ISBN: 978-1-61804-044-2

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