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Record W4403423380 · doi:10.1145/3677071

Flipping into the Future: Exploring Player Experience and Task Demand in Physical, VR, and PC Pinball

2024· article· en· W4403423380 on OpenAlexaff
Daniel Johnson, Nicholas O’Donnell, Julian Frommel, Regan L. Mandryk

Bibliographic record

VenueProceedings of the ACM on Human-Computer Interaction · 2024
Typearticle
Languageen
FieldPsychology
TopicEducational Games and Gamification
Canadian institutionsUniversity of Victoria
Fundersnot available
KeywordsHuman–computer interactionTask (project management)On demandPsychologyComputer scienceMultimediaEngineering

Abstract

fetched live from OpenAlex

Attempts to digitize pinball have been met with skepticism; however, VR presents a new opportunity to access and enjoy this popular game. In a controlled study (N=60), we investigated how physical pinball, VR pinball, and PC pinball differ in terms of player experience (pX) and task demand using both quantitative and qualitative data. Participants mainly preferred physical pinball, followed by VR pinball; only two participants preferred pinball on the PC. With the exception of immersion, results showed no pX differences between physical and VR pinball; although PC pinball was rated as inferior on multiple dimensions. Furthermore, enjoyment of physical pinball was associated with curiosity, control, and challenge, whereas in VR and PC pinball, immersion and audiovisual appeal mattered. Interestingly, preference and pX did not depend on existing familiarity with pinball. Our findings suggest that VR can offer an accessible, enjoyable pinball experience, regardless of familiarity.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.672
Threshold uncertainty score0.322

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.070
GPT teacher head0.372
Teacher spread0.302 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
Domainnot available
GenreEmpirical

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

Citations0
Published2024
Admission routes1
Has abstractyes

Explore more

Same venueProceedings of the ACM on Human-Computer InteractionSame topicEducational Games and GamificationFrench-language works237,207