Frontiers in Software Engineering Education : Second International Workshop, FISEE 2023, Villebrumier, France, January 23-25, 2023, Invited Papers / / Alfredo Capozucca [and three others], editors
Lecture Notes in Computer Science Series ; ; Volume 14387
Disciplina
005.1071
Soggetti
Software engineering - Study and teaching
Lingua di pubblicazione
Inglese
Formato
Materiale a stampa
Livello bibliografico
Monografia
Nota di bibliografia
Includes bibliographical references and index.
Nota di contenuto
Intro -- Preface -- Organization -- Keynotes -- SING: Greatly Expanding Software Engineering Education -- Do Software Engineers Need to Know About Social Sciences and Humanities? -- Contents -- Specializations in Software Engineering Education -- 1 Background -- 1.1 Computer Science Education -- 1.2 The Origins of Software Engineering -- 1.3 Origins of Software Engineering Education -- 2 Modern Challenges in Software Engineering -- 2.1 The Internet Changes Everything -- 2.2 Mobile Applications Change Everything Again -- 2.3 The Internet of Things and "Smart" Devices Add to Complexity -- 2.4 Artificial Intelligence Changes Everything Yet Again -- 2.5 Changes in Software Engineering Processes and Tools -- 3 The Need for Specialization in Software Engineering Education -- 3.1 Specialization in Other Professions -- 3.2 Software Engineering Specialization -- 3.3 Possible Specialization Areas -- 4 Conclusion: Future Directions in Software Engineering Education -- References -- Co-design of Modern Technology Modules with Industry and Students as Partners -- 1 Introduction -- 2 Related Work -- 3 Our Approach -- 3.1 Access to Cloud Environments -- 3.2 Solution Design of the Private Cloud -- 3.3 Implementation Details of the Private Cloud -- 3.4 Iteration and Refinement -- 4 Cloud Computing Module -- 4.1 Assessment -- 5 Discussion -- 5.1 Student Experience and Evaluation -- 5.2 Industry Experience and Feedback -- 5.3 Academic Reflection --
6 Conclusion and Future Work -- References -- Tribal Capstone Project Course -- 1 Introduction -- 2 High-Level View -- 3 Teaching Sequences -- 4 Further Considerations -- 5 Related Work -- 6 Conclusions -- References -- Analyzing Scrum Team Impediments Using NLP -- 1 Introduction -- 2 Background -- 2.1 Agile in the Classroom -- 2.2 AI and Software Engineering -- 3 Educational Context -- 3.1 Capstone Course.
3.2 Process and Tooling -- 4 Classifying Scrum Impediments -- 4.1 Scrum Impediments Dataset -- 4.2 Scrum Impediments Categories -- 4.3 Findings -- 5 Automated Classification of Impediments with NLP -- 5.1 Overall Classification Process -- 5.2 Building a LLM -- 6 Validation by Subject Matter Experts -- 6.1 Subject Matter Expert 1 -- 6.2 Subject Matter Expert 2 -- 7 Conclusion and Future Work -- References -- Finding Behavioral Indicators from Contextualized Commits in Software Engineering Courses with Process Mining -- 1 Introduction -- 2 Related Work -- 2.1 Process Mining in Education -- 2.2 Process Mining in Software Engineering -- 2.3 Process Mining in Software Engineering Education -- 3 Empirical Study -- 3.1 Datasets Description -- 3.2 Pre-processing -- 3.3 Process Mining Analysis with BupaR -- 3.4 Results -- 4 Discussion -- 4.1 Interpretation -- 4.2 Limits -- 4.3 Script: G4S-Automation -- 5 Conclusion -- A Description of the Datasets -- References -- Education to Agile: Fostering Team Awareness with Essence -- 1 Introduction -- 2 Literature Review -- 3 Extreme Development -- 3.1 Our Motivation -- 3.2 Fostering Extreme Development -- 4 The Role of Essence -- 4.1 Monitoring the Status of a Project -- 4.2 Retrospectives with Essence -- 4.3 Process Organization -- 5 Outcomes -- 6 Conclusions and Further Work -- References -- The Physical and Human Dimension of Communication in Distance Education -- 1 Introduction -- 2 Definitions and Theoretical Framework -- 2.1 Definitions -- 2.2 Collaborative Learning -- 3 The Proposed Approach -- 3.1 Overview -- 3.2 The Collaborative Distance Learning Meta-model -- 3.3 The Functional Architecture of the Learning Environment -- 4 Exploring Feasibility: Java Programming Lab Project -- 4.1 Instantiation of the Meta-model and the Functional Architecture -- 4.2 Results -- 5 Conclusion and Future Works -- References.
Is ChatGPT 3 Safe for Students? -- 1 Introduction -- 2 Experiment -- 3 Results -- 4 Limitations and Threats to Validity -- 5 Related Work -- 6 Conclusions and Future Work -- References -- Author Index.