Literaturnachweis - Detailanzeige
| Autor/inn/en | Jiang, Han; Iandoli, Matthew; Van Dessel, Steven; Liu, Shichao; Whitehill, Jacob |
|---|---|
| Titel | Measuring Students' Thermal Comfort and Its Impact on Learning [Konferenzbericht] Paper presented at the International Conference on Educational Data Mining (EDM) (12th, Montreal, Canada, Jul 2-5, 2019). |
| Quelle | (2019), (10 Seiten)
PDF als Volltext kostenfreie Datei |
| Sprache | englisch |
| Dokumenttyp | gedruckt; online; Monographie |
| Schlagwörter | Climate; Heat; Environmental Influences; Climate Control; Measurement Techniques; Predictor Variables; Nonverbal Communication; Measurement Equipment; Learning; Learner Engagement; Foreign Countries; College Students; Romania |
| Abstract | "Thermal comfort" (TC) -- how comfortable or satisfied a person is with the temperature of her/his surroundings -- is one of the key factors influencing the "indoor environmental quality" of schools, libraries, and offices. We conducted an experiment to explore how TC can impact students' learning. University students (n = 25) were randomly assigned to different temperature conditions in an office environment (25[degrees]C [right arrow] 30[degrees]C, or 30[degrees]C [right arrow] 25[degrees]C) that were implemented using a combination of heaters and air conditioners over a 1.25 hour session. The task of the participants was to learn from tutorial videos on three different topics, and a test was given after each tutorial. The results suggest that (1) changing the room temperature by a few degrees Celsius can stat. sig. impact students' self-reported TC; (2) the relationship between TC and learning exhibited an inverted U-curve, i.e., should be neither too uncomfortable nor too comfortable. We also explored different computer vision and sensor-based approaches to measure students' thermal comfort automatically. We found that (3) TC can be predicted automatically either from the room temperature or from an infra-red (IR) camera of the face; however, (4) TC prediction from a normal (visible-light) web camera is highly challenging, and only limited predictive power was found in the facial expression features to predict thermal comfort. [For the full proceedings, see ED599096.] (As Provided). |
| Anmerkungen | International Educational Data Mining Society. e-mail: admin@educationaldatamining.org; Web site: http://www.educationaldatamining.org |
| Erfasst von | ERIC (Education Resources Information Center), Washington, DC |
| Update | 2020/1/01 |
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