DIY Ecological Momentary Assessment

Sydney R Charitos; Amberly L C Brigden; Jon Bird

doi:10.1145/3544549.3574184

DIY Ecological Momentary Assessment

Sydney R Charitos, Amberly L C Brigden, Jon Bird

Research output: Chapter in Book/Report/Conference proceeding › Conference Contribution (Conference Proceeding)

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Abstract

Ecological Momentary Assessment (EMA) is an increasingly used methodology in HCI which captures an individual’s experiences, typically digitally. The benefits of EMA include: reducing recall bias with ‘in-the-moment’ measurement; improving ecological validity with ‘in-the-context’ measurement and enabling exploration of the dynamic interplay of variables from repeated measurement. This course will teach participants about EMA by providing hands-on practical skill development in how to use off-the-shelf software to develop their own EMA system. At the end of the course, participants will be able to rapidly prototype and run custom EMA studies securely and at scale without the usual associated costs.

Original language	English
Title of host publication	CHI EA '23: Extended Abstracts of the 2023 CHI Conference on Human Factors in Computing Systems
Publisher	Association for Computing Machinery
Number of pages	4
ISBN (Electronic)	9781450394222
DOIs	https://doi.org/10.1145/3544549.3574184
Publication status	Published - 19 Apr 2023

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Bristol Interaction Group

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@inproceedings{eda283da90f9472bb56bedd4809c8bf3,

title = "DIY Ecological Momentary Assessment",

abstract = "Ecological Momentary Assessment (EMA) is an increasingly used methodology in HCI which captures an individual{\textquoteright}s experiences, typically digitally. The benefits of EMA include: reducing recall bias with {\textquoteleft}in-the-moment{\textquoteright} measurement; improving ecological validity with {\textquoteleft}in-the-context{\textquoteright} measurement and enabling exploration of the dynamic interplay of variables from repeated measurement. This course will teach participants about EMA by providing hands-on practical skill development in how to use off-the-shelf software to develop their own EMA system. At the end of the course, participants will be able to rapidly prototype and run custom EMA studies securely and at scale without the usual associated costs.",

author = "Charitos, \{Sydney R\} and Brigden, \{Amberly L C\} and Jon Bird",

year = "2023",

month = apr,

day = "19",

doi = "10.1145/3544549.3574184",

language = "English",

booktitle = "CHI EA '23: Extended Abstracts of the 2023 CHI Conference on Human Factors in Computing Systems",

publisher = "Association for Computing Machinery",

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AU - Charitos, Sydney R

AU - Brigden, Amberly L C

AU - Bird, Jon

PY - 2023/4/19

Y1 - 2023/4/19

N2 - Ecological Momentary Assessment (EMA) is an increasingly used methodology in HCI which captures an individual’s experiences, typically digitally. The benefits of EMA include: reducing recall bias with ‘in-the-moment’ measurement; improving ecological validity with ‘in-the-context’ measurement and enabling exploration of the dynamic interplay of variables from repeated measurement. This course will teach participants about EMA by providing hands-on practical skill development in how to use off-the-shelf software to develop their own EMA system. At the end of the course, participants will be able to rapidly prototype and run custom EMA studies securely and at scale without the usual associated costs.

AB - Ecological Momentary Assessment (EMA) is an increasingly used methodology in HCI which captures an individual’s experiences, typically digitally. The benefits of EMA include: reducing recall bias with ‘in-the-moment’ measurement; improving ecological validity with ‘in-the-context’ measurement and enabling exploration of the dynamic interplay of variables from repeated measurement. This course will teach participants about EMA by providing hands-on practical skill development in how to use off-the-shelf software to develop their own EMA system. At the end of the course, participants will be able to rapidly prototype and run custom EMA studies securely and at scale without the usual associated costs.

U2 - 10.1145/3544549.3574184

DO - 10.1145/3544549.3574184

M3 - Conference Contribution (Conference Proceeding)

BT - CHI EA '23: Extended Abstracts of the 2023 CHI Conference on Human Factors in Computing Systems

PB - Association for Computing Machinery

ER -

DIY Ecological Momentary Assessment

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