Teaching Human Trafficking Awareness and Action: Interdisciplinary Approaches and AI-Supported Learning for Social Justice
Iuliia Hoban, PhD (she/her) & Alex Rister, PhD (she/her) | September 23 | 1:45-2:45 pm EDT
Topic: Programming | Knowledge Level: Beginner
This presentation shares the design and implementation of a 9-week asynchronous online general education course aimed at raising awareness of human trafficking. This 100-level course was designed to equip undergraduate learners with foundational knowledge and actionable skills to address human trafficking within broader social justice contexts. The presenters argue that an “Explore–Engage–Apply” instructional framework, enhanced by responsible use of generative AI, can effectively scaffold student learning from foundational understanding to real-world action in anti-human trafficking efforts. Students begin by defining human trafficking, examining its global prevalence, root causes, indicators, and recruitment methods, and then progress to survivor-informed perspectives, technology’s role, and industry-specific prevention strategies. Learning culminates in a scaffolded final project in which students propose prevention or intervention strategies in their local communities. In this session, the presenters will also share insights on how they integrated Generative AI tools to support real world scenario development, personalized feedback, and iterative learning while maintaining ethical guidelines. This course model demonstrates how early undergraduate education can move beyond awareness to cultivate actionable social justice competencies. They recommend adopting scaffolded, AI-enhanced pedagogies to prepare students as informed advocates and practitioners. Beyond undergraduate settings, this approach can be adapted for professional development, continuing education, and workplace training programs. Attendees will gain a replicable framework for developing interdisciplinary, impact-driven curricula that strengthen global anti-trafficking and social justice efforts.
Presentation Objectives:
• Describe the design and structure of a human trafficking awareness course, including its learning outcomes, scaffolded assessments, and the “Explore–Engage–Apply” framework
• Demonstrate how generative AI can be responsibly integrated to enhance scenario-based learning, provide personalized feedback, and support iterative skill development
• Discuss strategies for applying course content and pedagogical approaches beyond undergraduate education
• Explain a replicable framework for developing interdisciplinary, impact-driven curricula that cultivate actionable social justice competencies and strengthen anti-trafficking initiatives