XDesign: Integrating Interface Design into Explainable AI Education

Hyungyu Shin; Nabila Sindi; Yoonjoo Lee; Jaeryoung Ka; Jean Y. Song; Juho Kim

doi:10.1145/3478432.3499052

XDesign: Integrating Interface Design into Explainable AI Education

Hyungyu Shin
, Nabila Sindi
, Yoonjoo Lee
, Jaeryoung Ka
, Jean Y. Song
, Juho Kim

Department of Electrical Engineering and Computer Science

Korea Advanced Institute of Science and Technology

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

1 Scopus citations

Abstract

We introduce XDesign, a web-based interactive platform that guides learners through a multi-stage design process for creating user-centered explanations of AI models. Results from a course deployment show that students were able to identify concrete user needs in interacting with explanations, highlight user tasks to support the needs, and design a user interface that aids the tasks.

Original language	English
Title of host publication	SIGCSE 2022 - Proceedings of the 53rd ACM Technical Symposium on Computer Science Education V.2
Publisher	Association for Computing Machinery, Inc
Pages	1097
Number of pages	1
ISBN (Electronic)	9781450390712
DOIs	https://doi.org/10.1145/3478432.3499052
State	Published - 3 Mar 2022
Event	53rd Annual ACM Technical Symposium on Computer Science Education, SIGCSE 2022 - Virtual, Online, United States Duration: 3 Mar 2022 → 5 Mar 2022

Publication series

Name	SIGCSE 2022 - Proceedings of the 53rd ACM Technical Symposium on Computer Science Education V.2

Conference

Conference	53rd Annual ACM Technical Symposium on Computer Science Education, SIGCSE 2022
Country/Territory	United States
City	Virtual, Online
Period	3/03/22 → 5/03/22

Bibliographical note

Publisher Copyright:
© 2022 Owner/Author.

Keywords

design process
explainable ai
ui prototyping
usable explanation

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

Access to Document

10.1145/3478432.3499052

Cite this

Shin, H., Sindi, N., Lee, Y., Ka, J., Song, J. Y., & Kim, J. (2022). XDesign: Integrating Interface Design into Explainable AI Education. In SIGCSE 2022 - Proceedings of the 53rd ACM Technical Symposium on Computer Science Education V.2 (pp. 1097). (SIGCSE 2022 - Proceedings of the 53rd ACM Technical Symposium on Computer Science Education V.2). Association for Computing Machinery, Inc. https://doi.org/10.1145/3478432.3499052

Shin, Hyungyu ; Sindi, Nabila ; Lee, Yoonjoo et al. / XDesign : Integrating Interface Design into Explainable AI Education. SIGCSE 2022 - Proceedings of the 53rd ACM Technical Symposium on Computer Science Education V.2. Association for Computing Machinery, Inc, 2022. pp. 1097 (SIGCSE 2022 - Proceedings of the 53rd ACM Technical Symposium on Computer Science Education V.2).

@inproceedings{3252408fdc5f44c186ec68c2d4763e99,

title = "XDesign: Integrating Interface Design into Explainable AI Education",

abstract = "We introduce XDesign, a web-based interactive platform that guides learners through a multi-stage design process for creating user-centered explanations of AI models. Results from a course deployment show that students were able to identify concrete user needs in interacting with explanations, highlight user tasks to support the needs, and design a user interface that aids the tasks.",

keywords = "design process, explainable ai, ui prototyping, usable explanation",

author = "Hyungyu Shin and Nabila Sindi and Yoonjoo Lee and Jaeryoung Ka and Song, \{Jean Y.\} and Juho Kim",

note = "Publisher Copyright: {\textcopyright} 2022 Owner/Author.; 53rd Annual ACM Technical Symposium on Computer Science Education, SIGCSE 2022 ; Conference date: 03-03-2022 Through 05-03-2022",

year = "2022",

month = mar,

day = "3",

doi = "10.1145/3478432.3499052",

language = "English",

series = "SIGCSE 2022 - Proceedings of the 53rd ACM Technical Symposium on Computer Science Education V.2",

publisher = "Association for Computing Machinery, Inc",

pages = "1097",

booktitle = "SIGCSE 2022 - Proceedings of the 53rd ACM Technical Symposium on Computer Science Education V.2",

}

Shin, H, Sindi, N, Lee, Y, Ka, J, Song, JY & Kim, J 2022, XDesign: Integrating Interface Design into Explainable AI Education. in SIGCSE 2022 - Proceedings of the 53rd ACM Technical Symposium on Computer Science Education V.2. SIGCSE 2022 - Proceedings of the 53rd ACM Technical Symposium on Computer Science Education V.2, Association for Computing Machinery, Inc, pp. 1097, 53rd Annual ACM Technical Symposium on Computer Science Education, SIGCSE 2022, Virtual, Online, United States, 3/03/22. https://doi.org/10.1145/3478432.3499052

XDesign: Integrating Interface Design into Explainable AI Education. / Shin, Hyungyu; Sindi, Nabila; Lee, Yoonjoo et al.
SIGCSE 2022 - Proceedings of the 53rd ACM Technical Symposium on Computer Science Education V.2. Association for Computing Machinery, Inc, 2022. p. 1097 (SIGCSE 2022 - Proceedings of the 53rd ACM Technical Symposium on Computer Science Education V.2).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - XDesign

T2 - 53rd Annual ACM Technical Symposium on Computer Science Education, SIGCSE 2022

AU - Shin, Hyungyu

AU - Sindi, Nabila

AU - Lee, Yoonjoo

AU - Ka, Jaeryoung

AU - Song, Jean Y.

AU - Kim, Juho

PY - 2022/3/3

Y1 - 2022/3/3

N2 - We introduce XDesign, a web-based interactive platform that guides learners through a multi-stage design process for creating user-centered explanations of AI models. Results from a course deployment show that students were able to identify concrete user needs in interacting with explanations, highlight user tasks to support the needs, and design a user interface that aids the tasks.

AB - We introduce XDesign, a web-based interactive platform that guides learners through a multi-stage design process for creating user-centered explanations of AI models. Results from a course deployment show that students were able to identify concrete user needs in interacting with explanations, highlight user tasks to support the needs, and design a user interface that aids the tasks.

KW - design process

KW - explainable ai

KW - ui prototyping

KW - usable explanation

UR - https://www.scopus.com/pages/publications/85127431506

U2 - 10.1145/3478432.3499052

DO - 10.1145/3478432.3499052

M3 - Conference contribution

AN - SCOPUS:85127431506

T3 - SIGCSE 2022 - Proceedings of the 53rd ACM Technical Symposium on Computer Science Education V.2

SP - 1097

BT - SIGCSE 2022 - Proceedings of the 53rd ACM Technical Symposium on Computer Science Education V.2

PB - Association for Computing Machinery, Inc

Y2 - 3 March 2022 through 5 March 2022

ER -

Shin H, Sindi N, Lee Y, Ka J, Song JY, Kim J. XDesign: Integrating Interface Design into Explainable AI Education. In SIGCSE 2022 - Proceedings of the 53rd ACM Technical Symposium on Computer Science Education V.2. Association for Computing Machinery, Inc. 2022. p. 1097. (SIGCSE 2022 - Proceedings of the 53rd ACM Technical Symposium on Computer Science Education V.2). doi: 10.1145/3478432.3499052

XDesign: Integrating Interface Design into Explainable AI Education

Abstract

Publication series

Conference

Bibliographical note

Keywords

UN SDGs

Access to Document

Other files and links

Fingerprint

Cite this