1.2 Tuning In Sessions

1.2.1 Reflecting through Relationships: A Grounded Theory of Professional Identity Development in Work-Integrated Learning
Ainsley Goldman, Experiential Learning & Professional Development, Experiential Learning Educational Developer, FAS

Amplifying the Signal: Connection, Engagement, and Civil Discourse

Work-integrated learning (WIL) is regarded as a panacea for incorporating students into the workforce, but scholars have called for more explicit curriculum and reflection related to professional identity development. Reflection is well-established in WIL curriculum, predominantly through graded written reflection assignments, but there is preliminary evidence that assessed reflections can become performative.

Using a constructivist grounded theory approach, this research project explored the question: how is professional identity developed through reflection in WIL curriculum? Data was collected from 20 undergraduate WIL students and three instructors at a large urban university using a combination of semi-structured interviews and discourse analysis of students’ reflection assignments and course syllabi.

Many students discussed the value of reflection through relationships (signals), as they had the opportunity to share ideas with one another while being disconnected from a permanent record they were handing in (noise). Patterns emerged related to their relationships in WIL, including relationships with classmates, student colleagues, co-workers, supervisors, and the school and workplace communities at large.

This research makes a significant contribution by emphasizing the importance of relationships in WIL. Relationships themselves are crucial, and it is often through relationships that WIL students are engaging in dialogical reflection. Furthermore, this research offers a theory of professional identity development through reflection and relationships in WIL that is not linear but contextual.  This theory is very accessible to WIL educators and practitioners, and specific approaches to theory application will be shared with all participants.

Research Track

1.2.2 Signal over Stress: Designing Flexible Deadlines and Intentional GenAI Use in Large Statistics Courses
Samantha-Jo Caetano, Assistant Professor, Teaching Stream, Statistical Sciences, FAS 
Emily Somerset, Assistant Professor, Teaching Stream, Statistical Sciences, FAS   

Filtering the Noise: Tools, Trends, and Tensions

 

In an era shaped by increasing student stress and the rapid uptake of generative AI, instructors face growing pressures around assessment design, academic integrity, and workload sustainability. This session shares the redesign of a large (n≈600) third-year XX course - Surveys, Sampling and Observational Data - built around structured flexibility in deadlines, grading-schemes, and generative-AI policy. Rather than adding more rules in response to complexity, the redesign amplified learning goals while reducing administrative and policy “noise”.

 

Flexible course design can be understood as a form of kind pedagogy: it supports student autonomy, acknowledges that students balance learning with complex lives, and reduces reactive administrative burden. Across the term, 97% of students used at least one flexible deadline and 95% appreciated the availability of flexible policies. Self-perceived skill development outcomes were comparable between students who did and did not use flexibility; while those who did not use extended deadlines earned marginally higher grades (differences were not statistically significant).

 

The course also incorporated a flexible generative-AI policy allowing use on take-home assessments. Students were required to disclose and reflect on their AI use as part of the rubric. Survey data indicated that 75% used AI tools, 82% supported the AI policy, and 98% viewed it as fair. Median assessment grades differed by less than 1% between AI users and non-users.

 

This session will explore how structured flexibility and intentional AI integration can sustain academic rigor while reducing stress and focusing attention on what matters most: meaningful student learning.

 

Research Track