Formative Assessment with Artificial Intelligence: Strategies for Generating Descriptive, Personalized, and Sustainable Feedback to Address Teacher Burnout
DOI:
https://doi.org/10.5281/zenodo.21712844Keywords:
Ethical Automation, Teacher Bureaucratic Workload, Generative Artificial Intelligence, Data Privacy, Teacher Burnout, School Management, Digital Humanism, Formative Assessment.Abstract
Teacher burnout has established itself over the past decade as one of the most acute structural crises in global educational systems. Empirical research demonstrates that a disproportionate share of educators' working hours is allocated not to direct pedagogical mediation or socio-emotional support for students, but to a hypertrophied network of routine and bureaucratic administrative tasks (writing qualitative reports, manual grade entry, designing assessment instruments, adapting lesson plans, and managing institutional correspondence). The emergence of Generative Artificial Intelligence (GAI) offers an unprecedented historical opportunity to automate and optimize these operational workloads.
However, the hasty and uncritical adoption of algorithmic tools within the school ecosystem raises profound ethical dilemmas: the risk of violating minors' personal data privacy, the loss of contextual sensitivity in assessment, the amplification of systemic biases, and the potential dehumanization of the educational act. This research paper proposes a comprehensive theoretical-practical framework for the ethical automation of administrative tasks in the classroom, grounded in the "Human-in-the-Loop" principle. The socio-educational impact of teacher exhaustion is analyzed, an Ethical Administrative Automation Matrix (EAAM) is established, anonymized implementation protocols are provided, and indispensable regulatory safeguards are discussed to protect the teacher's pedagogical sovereignty.
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