Investigating the Well-Being Impacts of Educational Technologies Supported by Learning Analytics: An Application of the Initial Phase of IEEE P7010 Recommended Practice to a Set of Cases
E. Hakami, and D. Hernandez-Leo. LAK21: 11th International Learning Analytics and Knowledge Conference, page 269–279. New York, NY, USA, Association for Computing Machinery, (2021)
DOI: 10.1145/3448139.3448165
Abstract
The accelerated adoption of digital technologies by people and communities results
in a close relation between, on one hand, the state of individual and societal well-being
and, on the other hand, the state of the digital technologies that underpin our life
experiences. The ethical concerns and questions about the impact of such technologies
on human well-being become more crucial when data analytics and intelligent competences
are integrated. To investigate how learning technologies could impact human well-being
considering the promising and concerning roles of learning analytics, we apply the
initial phase of the recently produced IEEE P7010 Well-being Impact Assessment, a
methodology and a set of metrics, to allow the digital well-being of a set of educational
technologies to be more comprehensively tackled and evaluated. We posit that the use
of IEEE P7010 well-being metrics could help identify where educational technologies
supported by learning analytics would increase or decrease well-being, providing new
routes to future technological innovation in Learning Analytics research.
%0 Conference Paper
%1 10.1145/3448139.3448165
%A Hakami, Eyad
%A Hernandez-Leo, Davinia
%B LAK21: 11th International Learning Analytics and Knowledge Conference
%C New York, NY, USA
%D 2021
%I Association for Computing Machinery
%K Digital Ethics Learning Values analytics hlsforward well-being
%P 269–279
%R 10.1145/3448139.3448165
%T Investigating the Well-Being Impacts of Educational Technologies Supported by Learning Analytics: An Application of the Initial Phase of IEEE P7010 Recommended Practice to a Set of Cases
%U https://doi.org/10.1145/3448139.3448165
%X The accelerated adoption of digital technologies by people and communities results
in a close relation between, on one hand, the state of individual and societal well-being
and, on the other hand, the state of the digital technologies that underpin our life
experiences. The ethical concerns and questions about the impact of such technologies
on human well-being become more crucial when data analytics and intelligent competences
are integrated. To investigate how learning technologies could impact human well-being
considering the promising and concerning roles of learning analytics, we apply the
initial phase of the recently produced IEEE P7010 Well-being Impact Assessment, a
methodology and a set of metrics, to allow the digital well-being of a set of educational
technologies to be more comprehensively tackled and evaluated. We posit that the use
of IEEE P7010 well-being metrics could help identify where educational technologies
supported by learning analytics would increase or decrease well-being, providing new
routes to future technological innovation in Learning Analytics research.
%@ 9781450389358
@inproceedings{10.1145/3448139.3448165,
abstract = {The accelerated adoption of digital technologies by people and communities results
in a close relation between, on one hand, the state of individual and societal well-being
and, on the other hand, the state of the digital technologies that underpin our life
experiences. The ethical concerns and questions about the impact of such technologies
on human well-being become more crucial when data analytics and intelligent competences
are integrated. To investigate how learning technologies could impact human well-being
considering the promising and concerning roles of learning analytics, we apply the
initial phase of the recently produced IEEE P7010 Well-being Impact Assessment, a
methodology and a set of metrics, to allow the digital well-being of a set of educational
technologies to be more comprehensively tackled and evaluated. We posit that the use
of IEEE P7010 well-being metrics could help identify where educational technologies
supported by learning analytics would increase or decrease well-being, providing new
routes to future technological innovation in Learning Analytics research.},
added-at = {2021-11-02T00:10:37.000+0100},
address = {New York, NY, USA},
author = {Hakami, Eyad and Hernandez-Leo, Davinia},
biburl = {https://www.bibsonomy.org/bibtex/2c2e4186f16db42fd45783a37f43d713a/yish},
booktitle = {LAK21: 11th International Learning Analytics and Knowledge Conference},
doi = {10.1145/3448139.3448165},
interhash = {dd6276bc0a83b2d1d65546567e1d300a},
intrahash = {c2e4186f16db42fd45783a37f43d713a},
isbn = {9781450389358},
keywords = {Digital Ethics Learning Values analytics hlsforward well-being},
location = {Irvine, CA, USA},
numpages = {11},
pages = {269–279},
publisher = {Association for Computing Machinery},
series = {LAK21},
timestamp = {2021-11-02T00:10:37.000+0100},
title = {Investigating the Well-Being Impacts of Educational Technologies Supported by Learning Analytics: An Application of the Initial Phase of IEEE P7010 Recommended Practice to a Set of Cases},
url = {https://doi.org/10.1145/3448139.3448165},
year = 2021
}