Concept Identification Visualizer (CIV) using Knowledge Tracing

Hui Jun Huang; I. Wei Lai

doi:10.1109/ICCE-Taiwan58799.2023.10226995

Concept Identification Visualizer (CIV) using Knowledge Tracing

Hui Jun Huang, I. Wei Lai

National Taiwan Normal University

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

Abstract

The COVID-19 pandemic has resulted in an escalation in the demand for online learning, leading to the need for experts, such as experienced math teachers, to classify exercises. However, achieving accurate and effective classification may present challenges due to differing expert opinions and complex exercise concepts. To address this challenge, we propose the use of the Concept Identification Visualizer (CIV). The CIV tool assists experts who lack engineering programming knowledge in comprehending the exercises and evaluating student responses. The tool leverages Knowledge Tracing to extract relevant information from students' answers and presents this data in a visual format. By providing a more comprehensive understanding of the exercises, the experts enable more informed exercise classification based on student feedback and improve the overall effectiveness of online learning.

Original language	English
Title of host publication	2023 International Conference on Consumer Electronics - Taiwan, ICCE-Taiwan 2023 - Proceedings
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	41-42
Number of pages	2
ISBN (Electronic)	9798350324174
DOIs	https://doi.org/10.1109/ICCE-Taiwan58799.2023.10226995
State	Published - 2023
Externally published	Yes
Event	2023 International Conference on Consumer Electronics - Taiwan, ICCE-Taiwan 2023 - Pingtung, Taiwan Duration: 17 07 2023 → 19 07 2023

Publication series

Name	2023 International Conference on Consumer Electronics - Taiwan, ICCE-Taiwan 2023 - Proceedings

Conference

Conference	2023 International Conference on Consumer Electronics - Taiwan, ICCE-Taiwan 2023
Country/Territory	Taiwan
City	Pingtung
Period	17/07/23 → 19/07/23

Bibliographical note

Publisher Copyright:
© 2023 IEEE.

Keywords

Data Analysis
Embedding Visualization
Knowledge Tracing

Access to Document

10.1109/ICCE-Taiwan58799.2023.10226995

Cite this

Huang, H. J., & Lai, I. W. (2023). Concept Identification Visualizer (CIV) using Knowledge Tracing. In 2023 International Conference on Consumer Electronics - Taiwan, ICCE-Taiwan 2023 - Proceedings (pp. 41-42). (2023 International Conference on Consumer Electronics - Taiwan, ICCE-Taiwan 2023 - Proceedings). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ICCE-Taiwan58799.2023.10226995

@inproceedings{d5322b2e6acb44d6bd590bef5edba161,

title = "Concept Identification Visualizer (CIV) using Knowledge Tracing",

abstract = "The COVID-19 pandemic has resulted in an escalation in the demand for online learning, leading to the need for experts, such as experienced math teachers, to classify exercises. However, achieving accurate and effective classification may present challenges due to differing expert opinions and complex exercise concepts. To address this challenge, we propose the use of the Concept Identification Visualizer (CIV). The CIV tool assists experts who lack engineering programming knowledge in comprehending the exercises and evaluating student responses. The tool leverages Knowledge Tracing to extract relevant information from students' answers and presents this data in a visual format. By providing a more comprehensive understanding of the exercises, the experts enable more informed exercise classification based on student feedback and improve the overall effectiveness of online learning.",

keywords = "Data Analysis, Embedding Visualization, Knowledge Tracing",

author = "Huang, {Hui Jun} and Lai, {I. Wei}",

note = "Publisher Copyright: {\textcopyright} 2023 IEEE.; 2023 International Conference on Consumer Electronics - Taiwan, ICCE-Taiwan 2023 ; Conference date: 17-07-2023 Through 19-07-2023",

year = "2023",

doi = "10.1109/ICCE-Taiwan58799.2023.10226995",

language = "英语",

series = "2023 International Conference on Consumer Electronics - Taiwan, ICCE-Taiwan 2023 - Proceedings",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

pages = "41--42",

booktitle = "2023 International Conference on Consumer Electronics - Taiwan, ICCE-Taiwan 2023 - Proceedings",

address = "美国",

}

Huang, HJ & Lai, IW 2023, Concept Identification Visualizer (CIV) using Knowledge Tracing. in 2023 International Conference on Consumer Electronics - Taiwan, ICCE-Taiwan 2023 - Proceedings. 2023 International Conference on Consumer Electronics - Taiwan, ICCE-Taiwan 2023 - Proceedings, Institute of Electrical and Electronics Engineers Inc., pp. 41-42, 2023 International Conference on Consumer Electronics - Taiwan, ICCE-Taiwan 2023, Pingtung, Taiwan, 17/07/23. https://doi.org/10.1109/ICCE-Taiwan58799.2023.10226995

Concept Identification Visualizer (CIV) using Knowledge Tracing. / Huang, Hui Jun; Lai, I. Wei.
2023 International Conference on Consumer Electronics - Taiwan, ICCE-Taiwan 2023 - Proceedings. Institute of Electrical and Electronics Engineers Inc., 2023. p. 41-42 (2023 International Conference on Consumer Electronics - Taiwan, ICCE-Taiwan 2023 - Proceedings).

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

TY - GEN

T1 - Concept Identification Visualizer (CIV) using Knowledge Tracing

AU - Huang, Hui Jun

AU - Lai, I. Wei

PY - 2023

Y1 - 2023

N2 - The COVID-19 pandemic has resulted in an escalation in the demand for online learning, leading to the need for experts, such as experienced math teachers, to classify exercises. However, achieving accurate and effective classification may present challenges due to differing expert opinions and complex exercise concepts. To address this challenge, we propose the use of the Concept Identification Visualizer (CIV). The CIV tool assists experts who lack engineering programming knowledge in comprehending the exercises and evaluating student responses. The tool leverages Knowledge Tracing to extract relevant information from students' answers and presents this data in a visual format. By providing a more comprehensive understanding of the exercises, the experts enable more informed exercise classification based on student feedback and improve the overall effectiveness of online learning.

AB - The COVID-19 pandemic has resulted in an escalation in the demand for online learning, leading to the need for experts, such as experienced math teachers, to classify exercises. However, achieving accurate and effective classification may present challenges due to differing expert opinions and complex exercise concepts. To address this challenge, we propose the use of the Concept Identification Visualizer (CIV). The CIV tool assists experts who lack engineering programming knowledge in comprehending the exercises and evaluating student responses. The tool leverages Knowledge Tracing to extract relevant information from students' answers and presents this data in a visual format. By providing a more comprehensive understanding of the exercises, the experts enable more informed exercise classification based on student feedback and improve the overall effectiveness of online learning.

KW - Data Analysis

KW - Embedding Visualization

KW - Knowledge Tracing

UR - http://www.scopus.com/inward/record.url?scp=85174957755&partnerID=8YFLogxK

U2 - 10.1109/ICCE-Taiwan58799.2023.10226995

DO - 10.1109/ICCE-Taiwan58799.2023.10226995

M3 - 会议稿件

AN - SCOPUS:85174957755

T3 - 2023 International Conference on Consumer Electronics - Taiwan, ICCE-Taiwan 2023 - Proceedings

SP - 41

EP - 42

BT - 2023 International Conference on Consumer Electronics - Taiwan, ICCE-Taiwan 2023 - Proceedings

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 2023 International Conference on Consumer Electronics - Taiwan, ICCE-Taiwan 2023

Y2 - 17 July 2023 through 19 July 2023

ER -

Huang HJ, Lai IW. Concept Identification Visualizer (CIV) using Knowledge Tracing. In 2023 International Conference on Consumer Electronics - Taiwan, ICCE-Taiwan 2023 - Proceedings. Institute of Electrical and Electronics Engineers Inc. 2023. p. 41-42. (2023 International Conference on Consumer Electronics - Taiwan, ICCE-Taiwan 2023 - Proceedings). doi: 10.1109/ICCE-Taiwan58799.2023.10226995

Concept Identification Visualizer (CIV) using Knowledge Tracing

Abstract

Publication series

Conference

Bibliographical note

Keywords

Access to Document

Other files and links

Fingerprint

Cite this