Experiencer: An Open-Source Context-Sensitive Wearable Experience Sampling Tool-Reference-Cited by-同舟云学术

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Experiencer: An Open-Source Context-Sensitive Wearable Experience Sampling Tool

Published:2023 Issue: Volume: Page:315-331
ISSN:1867-8211
Container-title:Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering
language:
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Author:

Khanshan Alireza^ORCID,Van Gorp Pieter^ORCID,Markopoulos Panos^ORCID

Publisher

Springer Nature Switzerland

Link

https://link.springer.com/content/pdf/10.1007/978-3-031-34586-9_21

Reference56 articles.

1. Aharony, N., Gardner, A., Sumter, C.: funf | open sensing framework (2021). http://www.funf.org/

2. Arslan, R.C., Walther, M.P., Tata, C.S.: formr: A study framework allowing for automated feedback generation and complex longitudinal experience-sampling studies using R. Behav. Res. Methods 52(1), 376–387 (2020). https://doi.org/10.3758/s13428-019-01236-y

3. Barrett, L.F., Barrett, D.J.: An introduction to computerized experience sampling in psychology. Soc. Sci. Comput. Rev. 19(2), 175–185 (2001). https://doi.org/10.1177/089443930101900204

4. Batalas, N., Markopoulos, P.: Introducing tempest, a modular platform for in situ data collection. In: Proceedings of the 7th Nordic Conference on Human-Computer Interaction: Making Sense Through Design, pp. 781–782 (2012)

5. Batalas, N., aan het Rot, M., Khan, V.J., Markopoulos, P.: Using tempest: End-user programming of web-based ecological momentary assessment protocols. Proceedings ACM Hum. Comput. Interact. 2(EICS), 1–24 (2018)

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