Branch Campus Classroom Expectations: An Ethnographic Study of Transnational Faculty and Students in Qatar
Bibliographic record
Abstract
Few studies have deeply and empirically described and analyzed the teaching and learning dynamic in branch campus classrooms in the Middle East, and fewer still have focused on educational technology. The purpose of this ethnographic study is to examine whether any gaps in expectations between transnational Canadian faculty and students in Qatar might be present because teacher and student participants come from different cultural backgrounds. The three research questions guiding this study pertain to a priori expectations, gaps in expectations and acculturation of expectations. Current literature on globalization, internationalization, branch campuses, transnational education, Orientalism, Cosmopolitanism, culture, fundamental attribution error, and teaching and learning and educational technology in Arab Gulf nations is critically reviewed for this study. The study had four phases of data collection: (1) an initial online questionnaire about cultural differences in teaching and learning based on Hofstede’s (1986) work (faculty n = 20, students n = 20), (2) classroom observations of six faculty members over a semester, (3) semi-structured interviews (faculty n = 6, students n = 15) and, (4) a final online summary-feedback questionnaire (faculty n = 13, students n = 17). Findings suggest that Holliday’s (1999) proposition of a small culture approach specific to classrooms is more relevant to research in this context than Hofstede’s (1986) large, national/ethnic culture approach. Classroom activities and participant comments mostly concerned the fundamentals of teaching and learning and not large national/ethnic cultural concerns and issues. Large culture appeared more relevant to participants’ confidence than to the quality of teaching. Classrooms at the research site tend to have an oversupply of instructional technology for which faculty have received little or no training. This readily available technology was also not well supported. Classrooms on this campus are largely set up for lecture style instruction and do not easily accommodate constructivist approaches. Analyses of study findings suggest that the notions of heterogeneity, homogeneity, small culture and large culture are an apt framework for describing and analyzing transnational classrooms. Based on study findings, it is recommended that appropriate educational technology can be determined for the site by following a normal, systematic instructional design process.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".