Thematic Issues: Three Design Models to Address The Challenge of a New Interdisciplinary Course
Bibliographic record
Abstract
The increasing complexity of societal challenges requires interdisciplinary approaches in education to cultivate critical thinking, adaptability, and a holistic understanding of global issues.In response, the Quebec college system's Social Science program introduced the Thematic Issues course (TI), a single-instructor course designed to engage students in interdisciplinary inquiry through instructor-selected themes and three prescribed social science disciplines.To navigate the challenges of teaching across disciplines in an unstructured framework, instructors formed a Faculty Learning Community (FLC) to collaboratively refine course design and instructional strategies.This paper examines three TI course models: the serial model, offering compartmentalized insights; the spiral model, promoting cumulative, integrated learning; and the jigsaw model emphasizes collaborative synthesis by combining specialized disciplinary perspectives into a cohesive understanding.By analyzing these models, this practice-centered study highlights the pedagogical affordances and constraints of single-teacher interdisciplinary instruction. ContextAs societal issues grow more complex, interdisciplinary education is increasingly recognized as a way to help learners make sense of them.Curricula must prepare students for real-world challenges by fostering critical thinking, adaptability, and transferable skills (Peiqi & Xionghu, 2003).This paper presents a practitioner-centered perspective on the development of a multidiscipline course aimed at fostering interdisciplinary thinking.The course was collaboratively designed through the efforts of nine instructors (practitioners) at a large urban college in Quebec, part of the province's unique 2-year post-secondary CEPEP system (1).These individuals were tasked with developing and teaching the first cohort of a 45-hour, third semester Social Science course called Thematic Issues (TI), which prepares students for a self-directed interdisciplinary project in their final (fourth) semester.As a core course within the program, the TI is offered in 20 sections annually, serving approximately 500 students.Operating as a Faculty Learning Community (FLC; to be defined shortly), the nine instructors brought expertise from six disciplines: psychology, anthropology, philosophy, religious studies, sociology, and business administration.These instructors had no experience working within an explicit theoretical framework to prepare for the design of the interdisciplinary course.Beginning in late May 2024, the instructors held initial meetings of the FLC before pausing for the summer, during which independent course planning took place.Bi-weekly meetings resumed in Fall 2024, leading to the course's first large scale offering that semester.This piloting phase is currently ongoing (Winter 2025) and will extend into Fall 2025.Early design decisions were driven by pragmatic reasoning and practitioner insights.However, one FLC member--the first author-was simultaneously involved in a research-practice partnership focused on interdisciplinary instruction, allowing for the integration of research-informed insights of this process.Inasmuch, her role is characterized as that of boundary spanner (Akkerman & Bakker, 2011), bridging theory to practice and enriching the FLC's pedagogical approach to interdisciplinary course design. The faculty learning communityDrawing on the Cox model of Faculty Learning Community (Cox, 2004), an FLC is a structured, collaborative group of educators who engage in an ongoing, scholarly, and collegial process to enhance teaching, learning and professional development (Richlin & Essington, 2004).This participatory approach offers several advantages including fostering interdisciplinary collaboration, enhancing teaching practices and building a supportive
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.014 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.003 | 0.006 |
| Scholarly communication | 0.007 | 0.005 |
| Open science | 0.003 | 0.004 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".