Measuring What Heteronormative Systems Erase in Education: Queer and Transgender Pedagogy, Context-Sensitive Evaluation, and Responsible AI in Pakistan and Afghanistan
Taller | En línea
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Organizado por:
Independent
Sobre el evento
This 60-minute hybrid interactive workshop examines how artificial intelligence can be critically and ethically integrated into the evaluation of queer and transgender inclusion within education systems in Pakistan and Afghanistan, where heteronormative and cisnormative structures shape access, participation, safety, and belonging. Through moderated panel discussion and facilitated group reflection, participants will explore how educational institutions, pedagogical practices, and evaluation systems often marginalize or erase gender-diverse learners, while critically assessing both the potential and limitations of AI in evidence generation and evaluation practice. The session will address how AI may strengthen evaluation through qualitative data analysis, pattern recognition, and cross-context synthesis, but also how it can hinder evaluation through embedded bias, misrepresentation, excessive data extraction, ethical harm, and the reproduction of exclusionary norms. Grounded in context-sensitive evaluation methodologies and global AI ethics principles, the workshop emphasizes methodological rigor, human oversight, and ethical responsibility in designing more inclusive and trustworthy education evaluation systems.
Presentador/a
| Nombre | Título | Biografía |
|---|---|---|
| Waqas Halim | Mr. | Waqas Halim is a queer pedagogist and M and E expert, whose work engages with questions of visibility, inclusion, and learning in constrained contexts. He brings critical insight into how heteronormative systems shape pedagogy and what remains unrecognized within education and evidence systems. |
Resumen
This workshop examined the Inclusion Measurement Gap, the difference between what educational institutions report and what learners actually experience. Using examples from Pakistan and Afghanistan, it explored practical approaches for generating ethical, context-sensitive evidence in environments where visibility, disclosure, and data collection may create risks. Participants engaged with tools including Inclusion Lenses, Risk-Benefit Matrices, Realist Evaluation, Contribution Analysis, Outcome Harvesting, and AI Evaluation Checklists. The workshop concluded with a practical framework for measuring belonging, dignity, safety, and agency alongside conventional indicators of access and participation.
Follow-up actions focused on translating workshop insights into practice. Participants identified opportunities to strengthen evaluation design, review existing data collection instruments, and incorporate more context-sensitive approaches to evidence generation. Several discussions highlighted the need for greater attention to participant safety, ethical decision-making, and the limitations of conventional indicators when assessing inclusion. The workshop also encouraged continued reflection on the role of AI in evaluation and the development of more responsive frameworks capable of capturing complex educational experiences across diverse contexts.