Future Skills Case Study: SOCI 355
AI Literacy and Digital Literacy modules were used.
Teaching team
- Dr. Jenny Godley, PhD
- Josh DeGuglielmo, student partner
Cohort
Second- and third-year sociology students (>150 students)
Module
Digital literacy and AI literacy are enabling skills that support students’ ability to critically engage with demographic data and emerging technologies. The modules were selected to align with the increasingly digital and AI-mediated nature of social demography, where research and analysis rely on data systems, computational tools, and AI-supported outputs.
The instructor aimed to ensure that students could critically interpret AI-generated information, identify bias and hallucinations, and understand how emerging technologies shape the study of populations and societies. FUSION was selected for its emphasis on transferable skills development and its alignment with student demand for practical competencies beyond theoretical knowledge.
Focus
Developing students’ digital and AI literacy skills, with a focus on critically evaluating AI-generated outputs, identifying bias and limitations, and understanding the implications of emerging technologies for demographic research.
Applied learning
Students participated in an in-class AI lab activity focused on applied analysis and discussion.
Assessment
Student learning was assessed through participation-based evaluation consistent with other SOCI 355 lab components. Assessment focused on engagement with module materials rather than mastery of technical expertise.
Students were evaluated based on:
- Completion of the explore phase workbook
- Participation in the in-lab apply phase activity
- Submission of a custom lab worksheet aligned with AI literacy competencies
Grading
2% of final grade
Pacing
- Explore phase completed independently prior to the lab session
- Apply phase conducted during a 45-minute in-lab activity
- Reflect phase assigned post-lab as an ungraded component
Due to time constraints and class size, the module was delivered as a focused, single-lab intervention rather than a multi-week experience.
In-class integration
- A custom-designed lab worksheet aligned with AI literacy competencies and course content.
- Group-based activities generating and critically examining AI-generated statistical data and policy recommendations.
- In-class reflection on AI bias, hallucinations, and limitations when working with demographic data.
Rather than implementing the full FUSION workbook, the Apply phase was adapted to provide an opportunity to apply AI skills in the context of the course and prioritize group reflection.
Observed impact
Students demonstrated increased awareness of their digital practices and a more critical approach to AI-generated demographic information. Several students also reported reconsidering academic and career pathways in relation to technology- and data-focused fields.
Insights
- Students responded positively to applied, in-class activities, and critical reflection. The module felt integrated and relevant to the subject matter.
- The modules are adaptable to scale down to meet different course needs effectively, shortening the overall experience to the Explore phase plus in-class application and reflection works.
- Large class size limited opportunities for extended reflection, contributing to the decision not to assess the full student workbook.
- Adaptability was essential given rapid changes in AI tools during the semester, the lab assignment had to modified due to AI updates.
The Future Skills Innovation Network (FUSION) is a collaborative network of Canadian universities focused on exploring inclusive and innovative learning approaches to foster skill development and prepare university students across the country for the future economy. Future Skills modules created by FUSION are available to the UCalgary community.