SEEver

SEEver, short for Software Engineering Education and Evaluation Repository, is a proposed framework for collecting, standardizing, and sharing longitudinal evidence about software engineering education and professional practice outcomes. The aim is to enable comparability across programs and studies by providing a common schema for reporting interventions, metrics, and results over time.

Origins and development: The concept arose in discussions about fragmentation in SE education research and the need for reproducible, cross-study analyses. Proposals emphasize collaboration among universities, industry partners, and professional bodies to establish guidelines and a governed repository.

Structure and data model: SEEver envisions core entities such as Study, Program, Intervention, Participant, Measure, Outcome, and Timepoint. Metrics commonly referenced include skill retention, project performance, defect density in contributed software, employability indicators, and student or practitioner self-efficacy. The framework supports both quantitative data and qualitative evidence, with standardized reporting templates.

Governance and ethics: The model incorporates data privacy, informed consent, anonymization, and access controls. It also recommends data quality checks and versioning to maintain audit trails.

Current status and usage: As of now, SEEver remains a proposal with pilot efforts in a limited number of institutions. It has yet to achieve broad adoption or formal standards bodies, but is discussed in scholarly and practitioner forums as a roadmap for evidence-based SE education.

Limitations: Critics point to the difficulty of longitudinal data collection, variability of SE programs, and potential for data bias or misuse if governance is weak. See also: Education research, Software engineering education.