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Record W4283588888 · doi:10.1017/s2058631022000277

Building a virtual Roman city: teaching history through video game design

2022· article· en· W4283588888 on OpenAlexaffabout
Harrison Forsyth

Bibliographic record

Venue˜The œjournal of classics teaching · 2022
Typearticle
Languageen
FieldComputer Science
TopicVirtual Reality Applications and Impacts
Canadian institutionsYork University
Fundersnot available
KeywordsVirtual realityArchitectureVariety (cybernetics)Immersion (mathematics)MultimediaComputer scienceStrict constructionismClass (philosophy)Video gameSoftwareGame designMathematics educationHuman–computer interactionVisual artsPsychologyArtificial intelligenceMathematics

Abstract

fetched live from OpenAlex

Abstract In October of 2018, a pedagogical experiment was conducted at York University, Toronto, Canada, in which students were given an assignment. For this assignment they were to conduct research on a variety of Roman public buildings in groups, build digital reconstructions of them using the Unity 3D game engine, and present them to the class in the form of a virtual reality (VR) simulation. In doing so, students were able to create a virtual built environment based on their research, navigate it, and discuss the space with a sense of immersion and scale. Using this experiment as a case study, the goal of this article is twofold: firstly, to assess the pedagogical efficacy of constructionist approaches to teaching students about Roman architecture, specifically using VR and video game design technology. The second goal is to address the technical and pedagogical challenges of using game design software in the classroom and to propose ways in which this assignment can be improved in the future.

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.007
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesResearch integrity
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.889
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0070.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.001
Open science0.0030.001
Research integrity0.0000.003
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.055
GPT teacher head0.293
Teacher spread0.238 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designNot applicable
Domainnot available
GenreMethods

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".

Quick stats

Citations3
Published2022
Admission routes2
Has abstractyes

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