The robot Tangy facilitating Trivia games: A team-based user-study with long-term care residents
Bibliographic record
Abstract
Robot facilitated cognitive interventions for older adults have mainly focused on one-on-one interactions or with groups of people each individually playing. In this paper, we present the design of the socially assistive robot, Tangy, for autonomously facilitating the team-based cognitively stimulating activity of Trivia with older adults which encourages users to interact with each other. A pilot study at a local long-term care facility with older adult residents demonstrated that Tangy could successfully facilitate Trivia games. In general, the participants were engaged in the activity, complied with the robot's requests, and had positive attitudes towards Tangy during the games. The Trivia game scenario also promoted cooperation and interactions between teammates. Furthermore, we compared the results in this study with the results of our previous study on the individually played game of Bingo. The comparison results showed that participants complied with the robot and were engaged during both activities, however, the team-based Trivia had higher levels of engagement and player interaction.
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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 | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".