Сравнение методов
Просматривайте выбранные методы рядом; строки с различиями подсвечены.
| Сбор данных с помощью мобильных датчиков× | Мобильный отбор проб опыта× | |
|---|---|---|
| Область | Методология опросов | Методология опросов |
| Семейство | Process / pipeline | Process / pipeline |
| Год появления≠ | Mid-2000s (smartphone-era formalization ~2006–2010) | 1983 |
| Автор метода≠ | Andrew Campbell, Tanzeem Choudhury, and colleagues (early smartphone sensing research); broader field of ubiquitous computing | Mihaly Csikszentmihalyi & Reed Larson |
| Тип≠ | Passive and active quantitative data collection technique | Intensive longitudinal data collection technique |
| Основополагающий источник≠ | Lane, N. D., Miluzzo, E., Lu, H., Peebles, D., Choudhury, T., & Campbell, A. T. (2010). A survey of mobile phone sensing. IEEE Communications Magazine, 48(9), 140–150. DOI ↗ | Csikszentmihalyi, M., & Larson, R. (1987). Validity and reliability of the Experience-Sampling Method. Journal of Nervous and Mental Disease, 175(9), 526–536. DOI ↗ |
| Другие названия | mobile sensing, smartphone sensor data collection, wearable sensor data collection, passive mobile data collection | ESM, Experience Sampling Method, Ecological Momentary Assessment, EMA |
| Связанные≠ | 4 | 5 |
| Сводка≠ | Mobile sensor data collection uses the built-in sensors of smartphones, tablets, or wearable devices to capture behavioral, physiological, and environmental data in real-world settings. Sensors such as accelerometers, GPS, heart rate monitors, ambient light detectors, and microphones record data passively or on demand, enabling researchers to study human behavior with high temporal resolution outside the laboratory. | Mobile Experience Sampling (ESM) is an intensive longitudinal data-collection technique in which participants respond to brief, repeated questionnaires delivered to their smartphones at random or scheduled intervals throughout the day. By capturing thoughts, feelings, behaviors, and context at or near the moment they occur, ESM minimises retrospective recall bias and provides a high-resolution picture of psychological and behavioral fluctuations in everyday life. |
| ScholarGateНабор данных ↗ |
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