Paolo Casari;Sabrina Maniero;Andrea Rosani;Federica Picasso;Anna Serbati
{"title":"Experimenting Team-Based Learning in a Large Computer Networks Class","authors":"Paolo Casari;Sabrina Maniero;Andrea Rosani;Federica Picasso;Anna Serbati","doi":"10.1109/TE.2025.3549688","DOIUrl":null,"url":null,"abstract":"Contribution: An innovative teaching experience carried out at the University of Trento using team-based learning (TBL) in a large computer networks class. The impact of TBL on the students’ learning and satisfaction was investigated.Background: Active learning pedagogies, including TBL, play an important role in enhancing higher-order cognitive skills among the student community. Reports on the implementation of TBL in engineering education are still scarce, despite its potential as an effective strategy for teaching problem solving skills in large classes.Intended Outcomes: Improved learning and student engagement via structured groupwork and challenging activities. A structure that makes it possible to scale TBL up to large classes with measurable learning improvements.Application Design: Laboratory classes were structured so that they became instrumental to TBL sessions, which in turn provided a stimulating environment to improve learning of key computer networks concepts. Grouping students with different backgrounds and previous knowledge enabled a more effective group work.Findings: The application of TBL fostered a deeper understanding of the topics covered in the course, resulting in higher scores on final exams and fewer failures. Interviewed students found the experience very satisfactory in terms of learning, group work, and involvement.","PeriodicalId":55011,"journal":{"name":"IEEE Transactions on Education","volume":"68 2","pages":"248-257"},"PeriodicalIF":2.1000,"publicationDate":"2025-03-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"IEEE Transactions on Education","FirstCategoryId":"5","ListUrlMain":"https://ieeexplore.ieee.org/document/10938973/","RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"EDUCATION, SCIENTIFIC DISCIPLINES","Score":null,"Total":0}
引用次数: 0
Abstract
Contribution: An innovative teaching experience carried out at the University of Trento using team-based learning (TBL) in a large computer networks class. The impact of TBL on the students’ learning and satisfaction was investigated.Background: Active learning pedagogies, including TBL, play an important role in enhancing higher-order cognitive skills among the student community. Reports on the implementation of TBL in engineering education are still scarce, despite its potential as an effective strategy for teaching problem solving skills in large classes.Intended Outcomes: Improved learning and student engagement via structured groupwork and challenging activities. A structure that makes it possible to scale TBL up to large classes with measurable learning improvements.Application Design: Laboratory classes were structured so that they became instrumental to TBL sessions, which in turn provided a stimulating environment to improve learning of key computer networks concepts. Grouping students with different backgrounds and previous knowledge enabled a more effective group work.Findings: The application of TBL fostered a deeper understanding of the topics covered in the course, resulting in higher scores on final exams and fewer failures. Interviewed students found the experience very satisfactory in terms of learning, group work, and involvement.
期刊介绍:
The IEEE Transactions on Education (ToE) publishes significant and original scholarly contributions to education in electrical and electronics engineering, computer engineering, computer science, and other fields within the scope of interest of IEEE. Contributions must address discovery, integration, and/or application of knowledge in education in these fields. Articles must support contributions and assertions with compelling evidence and provide explicit, transparent descriptions of the processes through which the evidence is collected, analyzed, and interpreted. While characteristics of compelling evidence cannot be described to address every conceivable situation, generally assessment of the work being reported must go beyond student self-report and attitudinal data.