Difference between revisions of "Urbanicity"
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(Created page with "Ocumpaugh et al. (2014) https://bera-journals.onlinelibrary.wiley.com/doi/pdf/10.1111/bjet.12156 pdf * Models detecting student affective states (boredom, confusion, engaged concentration, frustration) from the interaction with ASSISTment system * Detectors generally performed the best for the same subpopulation that they were trained on (average kappa = 0.26, A′ = 0.67), and worse for other subpopulations (average kappa = 0.03 and A′ = 0.52) * Detectors trained...") |
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Ocumpaugh et al. (2014) | Ocumpaugh et al. (2014) [https://bera-journals.onlinelibrary.wiley.com/doi/pdf/10.1111/bjet.12156 pdf] | ||
* Models detecting student affective states (boredom, confusion, engaged concentration, frustration) from the interaction with ASSISTment system | * Models detecting student affective states (boredom, confusion, engaged concentration, frustration) from the interaction with ASSISTment system | ||
* Data set involved urban, rural, and suburban learners. | |||
* Detectors generally performed the best for the same subpopulation that they were trained on (average kappa = 0.26, A′ = 0.67), and worse for other subpopulations (average kappa = 0.03 and A′ = 0.52) | * Detectors generally performed the best for the same subpopulation that they were trained on (average kappa = 0.26, A′ = 0.67), and worse for other subpopulations (average kappa = 0.03 and A′ = 0.52) | ||
* Detectors trained on combined population generally performed better for urban and suburban population (kappa = 0.18, 0.16; A′ = 0.62, 0.66) and not as well for rural population (kappa = 0.06; A′ = 0.54) | * Detectors trained on combined population generally performed better for urban and suburban population (kappa = 0.18, 0.16; A′ = 0.62, 0.66) and not as well for rural population (kappa = 0.06; A′ = 0.54) | ||
Samei et al. (2015) [https://files.eric.ed.gov/fulltext/ED560879.pdf pdf] | |||
* Models predicting classroom discourse properties (e.g. authenticity and uptake) | |||
* Model trained on urban students (authenticity: 0.62, uptake: 0.60) performed with similar accuracy when tested on non-urban students (authenticity: 0.62, uptake: 0.62) | |||
* Model trained on non-urban students (authenticity: 0.61, uptake: 0.59) performed with similar accuracy when tested on urban students (authenticity: 0.60, uptake: 0.63) | |||
Latest revision as of 05:06, 10 June 2022
Ocumpaugh et al. (2014) pdf
- Models detecting student affective states (boredom, confusion, engaged concentration, frustration) from the interaction with ASSISTment system
- Data set involved urban, rural, and suburban learners.
- Detectors generally performed the best for the same subpopulation that they were trained on (average kappa = 0.26, A′ = 0.67), and worse for other subpopulations (average kappa = 0.03 and A′ = 0.52)
- Detectors trained on combined population generally performed better for urban and suburban population (kappa = 0.18, 0.16; A′ = 0.62, 0.66) and not as well for rural population (kappa = 0.06; A′ = 0.54)
Samei et al. (2015) pdf
- Models predicting classroom discourse properties (e.g. authenticity and uptake)
- Model trained on urban students (authenticity: 0.62, uptake: 0.60) performed with similar accuracy when tested on non-urban students (authenticity: 0.62, uptake: 0.62)
- Model trained on non-urban students (authenticity: 0.61, uptake: 0.59) performed with similar accuracy when tested on urban students (authenticity: 0.60, uptake: 0.63)