{"title":"Pratiche basate sui dati nella valutazione e l’analisi della qualità didattica: il caso dell’Università di Padova","authors":"J. Raffaghelli, V. Grion, M. Rossi","doi":"10.30557/QW000036","DOIUrl":"https://doi.org/10.30557/QW000036","url":null,"abstract":"","PeriodicalId":41384,"journal":{"name":"Qwerty","volume":"14 1","pages":""},"PeriodicalIF":1.3,"publicationDate":"2021-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"87762965","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
M. Sofwan, R. Pratama, M. Muhaimin, Y. Yusnaidar, A. Mukminin, Akhmad Habibi
{"title":"Contribution of technology innovation acceptance and organizational innovation climate on innovative teaching behavior with ICT in indonesian education","authors":"M. Sofwan, R. Pratama, M. Muhaimin, Y. Yusnaidar, A. Mukminin, Akhmad Habibi","doi":"10.30557/QW000035","DOIUrl":"https://doi.org/10.30557/QW000035","url":null,"abstract":"","PeriodicalId":41384,"journal":{"name":"Qwerty","volume":"28 1","pages":""},"PeriodicalIF":1.3,"publicationDate":"2021-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"72654010","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Diari di apprendimento e learning analytics, strumenti integrabili per capire i processi di studio? Giudizi di difficoltà e tracciamento delle attività online","authors":"Riccardo Fattorini, G. Paoletti","doi":"10.30557/QW000038","DOIUrl":"https://doi.org/10.30557/QW000038","url":null,"abstract":"","PeriodicalId":41384,"journal":{"name":"Qwerty","volume":"68 1","pages":""},"PeriodicalIF":1.3,"publicationDate":"2021-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"80050432","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Giovanni Guarguaglini, Cristina Miceli, Daniela Amendola
{"title":"Sviluppo di una OER per l’insegnamento delle biotecnologie: risultati di una sperimentazione eseguita nell’ultimo anno dei Licei","authors":"Giovanni Guarguaglini, Cristina Miceli, Daniela Amendola","doi":"10.30557/QW000034","DOIUrl":"https://doi.org/10.30557/QW000034","url":null,"abstract":"","PeriodicalId":41384,"journal":{"name":"Qwerty","volume":"38 1","pages":""},"PeriodicalIF":1.3,"publicationDate":"2021-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"74805845","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Quali competenze e quali strategie formative per l’industria 4.0? Lo stato dell’arte","authors":"Marco Perini, F. Tommasi, R. Sartori","doi":"10.30557/QW000039","DOIUrl":"https://doi.org/10.30557/QW000039","url":null,"abstract":"","PeriodicalId":41384,"journal":{"name":"Qwerty","volume":"111 1","pages":""},"PeriodicalIF":1.3,"publicationDate":"2021-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"80696456","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
If AI is to have a positive transforming effect on education, it will be through the community norms, collective practices, and solidarity that emerge around it. In Knowledge Building, this means fuller realization of such principles as collective responsibility for idea improvement, idea diversity, and knowledge building as a way of life. AI can aid the development of this kind of community by providing powerful tools students themselves can use to strengthen their knowledgebuilding efforts and eventually by making intelligent machines active collaborators in these efforts. This paper describes advances currently taking place in Knowledge Building technology. Although full collaboration between humans and machines in knowledge creation may be years away, education can start preparing students for their role in it by emphasizing those capabilities that arise from the multifarious personal and social lives they lead.
{"title":"Will knowledge building remain uniquely human?","authors":"M. Scardamalia, C. Bereiter","doi":"10.30557/QW000028","DOIUrl":"https://doi.org/10.30557/QW000028","url":null,"abstract":"If AI is to have a positive transforming effect on education, it will be \u0000through the community norms, collective practices, and solidarity \u0000that emerge around it. In Knowledge Building, this means fuller realization of such principles as collective responsibility for idea improvement, idea diversity, and knowledge building as a way of life. AI can aid the development of this kind of community by providing powerful \u0000tools students themselves can use to strengthen their knowledgebuilding \u0000efforts and eventually by making intelligent machines active \u0000collaborators in these efforts. This paper describes advances currently \u0000taking place in Knowledge Building technology. Although full collaboration \u0000between humans and machines in knowledge creation may \u0000be years away, education can start preparing students for their role in \u0000it by emphasizing those capabilities that arise from the multifarious \u0000personal and social lives they lead.","PeriodicalId":41384,"journal":{"name":"Qwerty","volume":"28 1","pages":"12-26"},"PeriodicalIF":1.3,"publicationDate":"2020-12-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"85515016","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Teachers’ professional expertise cannot ignore anymore a technological component to it. Technology is nowadays accessible more and more widely, but it does not automatically translate into learning improvement. It is crucial to understand how educators give meaning to technology integration in their practices, i.e. investigate teachers’ professional reasoning. The paper reports on part of a wider study on Initial Teacher Education (ITE) institutions’ capability to engage student- teachers’ reasoning. Within the broader multiple case study across Europe, the paper reports on data emerging from document analysis and focused interviews with pre-service teachers (Ntot 36). The findings suggest an activation of reasoning whose roots might find place outside ITE influence, encouraging further research.
{"title":"Student teachers’ pedagogical reasoning in TPCK-based design tasks. A multiple case study","authors":"Ottavia Trevisan, M. Rossi","doi":"10.30557/QW000031","DOIUrl":"https://doi.org/10.30557/QW000031","url":null,"abstract":"Teachers’ professional expertise cannot ignore anymore a technological \u0000component to it. Technology is nowadays accessible more and \u0000more widely, but it does not automatically translate into learning improvement. \u0000It is crucial to understand how educators give meaning to \u0000technology integration in their practices, i.e. investigate teachers’ professional reasoning. The paper reports on part of a wider study on \u0000Initial Teacher Education (ITE) institutions’ capability to engage student- \u0000teachers’ reasoning. Within the broader multiple case study \u0000across Europe, the paper reports on data emerging from document \u0000analysis and focused interviews with pre-service teachers (Ntot 36). \u0000The findings suggest an activation of reasoning whose roots might \u0000find place outside ITE influence, encouraging further research.","PeriodicalId":41384,"journal":{"name":"Qwerty","volume":"28 1","pages":"68-84"},"PeriodicalIF":1.3,"publicationDate":"2020-12-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"77984643","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
This paper presents the learning-teaching innovation process of a University course. The traditional elements of the teaching-learning process (lecture, study, exam) involving students in ongoing activities have changed. The paper focuses on the learning changes introduced by social annotation activities carried out through the Perusall web environment. In particular, Perusall functionalities that assess students’ participation were examined. These rely on multiple indicators set by the teacher, and a Machine Learning algorithm, which assesses the quality of annotations. A study was carried out to examine the validity of this process by analysing the relationship between Perusall algorithm’s scores and teacher’s scores, and how students perceive the automated scoring. The relationship was investigated through the Spearman correlation coefficient and Kendall’s coefficient of concordance. Thematic analysis was used to analyse the qualitative data concerning students’ perceptions. The results indicate that the Perusall algorithm provided scores quite similar to those of the teacher, and that students positively perceived the automated scoring.
{"title":"Perusall: University learning-teaching innovation employing social annotation and machine learning","authors":"G. Cecchinato, L. Foschi","doi":"10.30557/QW000030","DOIUrl":"https://doi.org/10.30557/QW000030","url":null,"abstract":"This paper presents the learning-teaching innovation process of a \u0000University course. The traditional elements of the teaching-learning \u0000process (lecture, study, exam) involving students in ongoing activities \u0000have changed. The paper focuses on the learning changes introduced \u0000by social annotation activities carried out through the Perusall web \u0000environment. In particular, Perusall functionalities that assess students’ participation were examined. These rely on multiple indicators set by the teacher, and a Machine Learning algorithm, which assesses the quality of annotations. A study was carried out to examine the validity of this process by analysing the relationship between Perusall algorithm’s scores and teacher’s scores, and how students perceive the automated scoring. The relationship was investigated through the Spearman correlation coefficient and Kendall’s coefficient of concordance. \u0000Thematic analysis was used to analyse the qualitative data \u0000concerning students’ perceptions. The results indicate that the Perusall algorithm provided scores quite similar to those of the teacher, and \u0000that students positively perceived the automated scoring.","PeriodicalId":41384,"journal":{"name":"Qwerty","volume":"107 1","pages":"45-67"},"PeriodicalIF":1.3,"publicationDate":"2020-12-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"80506732","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"From the Teaching machines to the Machine learning. Opportunities and challenges for Artificial Intelligence in education","authors":"V. Grion, G. Cecchinato","doi":"10.30557/QW000027","DOIUrl":"https://doi.org/10.30557/QW000027","url":null,"abstract":"","PeriodicalId":41384,"journal":{"name":"Qwerty","volume":"14 1","pages":""},"PeriodicalIF":1.3,"publicationDate":"2020-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"84232364","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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