Exploring Lived Experience: A Phenomenological Inquiry into the Perspectives of Marginalized Students and Their Instructors with Hybrid Problem-Based Learning (PBL) in STEM Education through a Critical Digital Pedagogy Lens
Bibliographic record
Abstract
Despite the potential of hybrid Problem-Based Learning (PBL) to enhance accessibility and engagement in science, technology, engineering and mathematics (STEM) education, few studies have specifically investigated its effectiveness in promoting Equity, Diversity, and Inclusion (EDI) for marginalized students. This phenomenological study explores how its blended learning format shapes the experiences and perceptions of both underrepresented minority students and their instructors. Grounded in critical digital pedagogy, the study examined 40 semi-structured interviews and two focus group discussions with 29 STEM students and 11 STEM instructors at a large Canadian university. Through thematic analysis, the data yielded ten key themes that highlight the various complexities of implementing and experiencing hybrid PBL. On the one hand, there is the increased flexibility that goes along with hybrid PBL in so many ways; on the other, there is another digital divide that limits full participation from students of lower socioeconomic backgrounds cohesively. These barriers make them entirely dependent on school resources, while others struggle to keep up with coursework. The critical but complex role of the teacher in creating an inclusive atmosphere in hybrid PBL is also pointed out in the research. On one hand, the teachers are valued as “Cultural Guide” responsible for breaking biases and facilitating inclusion for diverse learners, but on the other hand, the integration of technology adds many layers of complexity to EDI. Technology acts as a “double-edged sword”: both empowerment and marginalization of students entrench socio-economic polarities. Further on the complexity, the socioeconomic inequalities persist in hybrid PBL and influence the problem-solving approaches of students, the access to resources, and even their sense of belonging. What the difference shows is that instructors really have to be aware of these socioeconomic factors as they design PBL activities and work in groups. The study also shows that, even in the context of hybrid PBL, the gender stereotype persists: female students report that they are being pushed to non-technical roles and experiencing microaggressions. While students enjoy hybrid learning for its flexibility and accessibility, especially those with very diverse commitments, the level of digital literacy among both instructors and students is still very important to fully maximize its potential and avoid creating a situation of digital exclusion. These findings therefore suggest that while hybrid PBL has the potential to advance EDI within STEM education, its success involves a holistic approach that includes several key factors, from digital equity and culturally responsive training of instructors to support of individual students and critical consideration of technology use as part of power dynamics. The recent pandemic has further shown its applicability beyond emergency remote teaching, indicating that PBL could still remain a useful method in physical classrooms post-pandemic. By recognizing the interplay among pedagogy, technology, instructor awareness, and socioeconomic dynamics, educators can take meaningful steps toward fostering inclusive and equitable learning opportunities in STEM for all students.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.010 | 0.015 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.018 | 0.034 |
| Scholarly communication | 0.012 | 0.011 |
| Open science | 0.004 | 0.014 |
| Research integrity | 0.004 | 0.006 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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".