TY - GEN
T1 - Towards value-sensitive learning analytics design
AU - Chen, Bodong
AU - Zhu, Haiyi
N1 - Publisher Copyright:
© 2019 Copyright held by the owner/author(s). Publication rights licensed to ACM.
Copyright:
Copyright 2019 Elsevier B.V., All rights reserved.
PY - 2019/3/4
Y1 - 2019/3/4
N2 - To support ethical considerations and system integrity in learning analytics, this paper introduces two cases of applying the Value Sensitive Design methodology to learning analytics design. The first study applied two methods of Value Sensitive Design, namely stakeholder analysis and value analysis, to a conceptual investigation of an existing learning analytics tool. This investigation uncovered a number of values and value tensions, leading to design trade-offs to be considered in future tool refinements. The second study holistically applied Value Sensitive Design to the design of a recommendation system for the Wikipedia WikiProjects. To proactively consider values among stakeholders, we derived a multi-stage design process that included literature analysis, empirical investigations, prototype development, community engagement, iterative testing and refinement, and continuous evaluation. By reporting on these two cases, this paper responds to a need of practical means to support ethical considerations and human values in learning analytics systems. These two cases demonstrate that Value Sensitive Design could be a viable approach for balancing a wide range of human values, which tend to encompass and surpass ethical issues, in learning analytics design.
AB - To support ethical considerations and system integrity in learning analytics, this paper introduces two cases of applying the Value Sensitive Design methodology to learning analytics design. The first study applied two methods of Value Sensitive Design, namely stakeholder analysis and value analysis, to a conceptual investigation of an existing learning analytics tool. This investigation uncovered a number of values and value tensions, leading to design trade-offs to be considered in future tool refinements. The second study holistically applied Value Sensitive Design to the design of a recommendation system for the Wikipedia WikiProjects. To proactively consider values among stakeholders, we derived a multi-stage design process that included literature analysis, empirical investigations, prototype development, community engagement, iterative testing and refinement, and continuous evaluation. By reporting on these two cases, this paper responds to a need of practical means to support ethical considerations and human values in learning analytics systems. These two cases demonstrate that Value Sensitive Design could be a viable approach for balancing a wide range of human values, which tend to encompass and surpass ethical issues, in learning analytics design.
KW - Data ethics
KW - Learning analytics
KW - Social media
KW - Value sensitive design
KW - Values
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U2 - 10.1145/3303772.3303798
DO - 10.1145/3303772.3303798
M3 - Conference contribution
AN - SCOPUS:85062770735
T3 - ACM International Conference Proceeding Series
SP - 343
EP - 352
BT - Proceedings of the 9th International Conference on Learning Analytics and Knowledge
PB - Association for Computing Machinery
T2 - 9th International Conference on Learning Analytics and Knowledge, LAK 2019
Y2 - 4 March 2019 through 8 March 2019
ER -