Cohabitant: The Design, Implementation, and Evaluation of a Virtual Reality Application for Interfaith Learning and Empathy Building
Bibliographic record
Abstract
Lack of interfaith communication often gives rise to prejudice and group-based conflict in multi-faith societies. Nurturing this communication via interfaith learning may reduce this conflict by fostering interfaith empathy. HCI has a dearth of knowledge on interfaith coexistence and empathy building. To address this gap, we present the design, implementation, and usability of Cohabitant: a virtual reality (VR) application that promotes interfaith learning and empathy. Cohabitant’s design is theoretically underpinned by Allport’s intergroup contact theory and informed by insights from a participatory workshop we ran with members of three religious groups: Christians, Hindus, and Muslims. Our evaluation study, combining quantitative and qualitative data from 30 participants, suggests that Cohabitant may enhance general interpersonal empathy, but falls short for ethnocultural empathy. We discuss the possible design and policy implications of using this kind of VR technology for interfaith learning and empathy building.
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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 | 0.005 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 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".