Herrmanny, Katja; Löppenberg, Simone; Schwarz, Michael:
Investigating mechanisms for user integration in the activity goal recommendation process by interface design
In: Interfaces and Human Decision Making for Recommender Systems 2019 : Proceedings of the 6th Joint Workshop on Interfaces and Human Decision Making for Recommender Systems / Brusilovsky, Peter; de Gemmis, Marco; Felfernig, Alexander; Lops, Pasquale; O’Donovan, John; Semeraro, Giovanni; Willemsen, Martijn C. (Eds.). - 6th Joint Workshop on Interfaces and Human Decision Making for Recommender Systems (IntRS2019), 19.09.2019, Copenhagen - Aachen: RWTH Aachen, 2019 - (CEUR Workshop Proceedings ; 2450), pp. 46 - 54
2019book article/chapter in ProceedingsOA Gold
Computer ScienceFaculty of Engineering » Computer Science and Applied Cognitive Science » Computer Science » Interactive Systems
Title in English:
Investigating mechanisms for user integration in the activity goal recommendation process by interface design
Author:
Herrmanny, KatjaUDE
LSF ID
54788
Other
connected with university
;
Löppenberg, Simone
;
Schwarz, MichaelUDE
LSF ID
57816
Other
connected with university
Open Access?:
OA Gold
Scopus ID
Note:
OA platinum
Language of text:
English
Keyword, Topic:
Activity tracking ; Goal setting ; Recommendation ; User empowerment ; User integration ; User interface

Abstract in English:

In the field of physical activity recommendation, we have to deal with many confounding variables that lead to high result uncertainty. Assuming that users’ competence is an essential factor for reduction of the problem of inaccurate recommendations, we present and evaluate an approach on how to integrate users in the recommendation process. We investigate if and how interface element design can contribute to understanding, reflection and modification of the recommendation result. In the work described here, we use interface elements that allow for planning of physical activity goal striving. Results show that such interface elements can principally empower users, support recommendation reflection and stimulate user interaction with the recommendation.