Mining users' preferences in an interactive multimedia learning system: A human factor perspective

Kyriacos A. Chrysostomou; Sherry Y. Chen; Xiaohui Liu

Mining users' preferences in an interactive multimedia learning system: A human factor perspective

Kyriacos A. Chrysostomou, Sherry Y. Chen, Xiaohui Liu

Graduate Institute of Network Learning Technology

Research output: Contribution to conference › Paper › peer-review

Abstract

With the increasing popularity of the Internet, interactive multimedia learning systems are widely used in both educational and industrial settings. However, as human factors vary across users, they may prefer the design of interactive multimedia learning systems differently. To have a deep understanding of the influence of human factors, we apply a data mining approach to the assessment of users' preferences in using interactive multimedia learning systems. More specifically, the K-modes algorithm is used to group users' preferences. The results indicate that users' preferences could be divided into four groups where computer experience significantly influences their preferences. Implications for the development of interactive multimedia learning systems are also discussed.

Original language	English
Pages	118-122
Number of pages	5
State	Published - 2020
Event	20th British Computer Society Conference on Human-Computer Interaction: Engage, HCI 2006 - London, United Kingdom Duration: 11 Sep 2006 → 15 Sep 2006

Conference

Conference	20th British Computer Society Conference on Human-Computer Interaction: Engage, HCI 2006
Country/Territory	United Kingdom
City	London
Period	11/09/06 → 15/09/06

Keywords

Data mining
E-Learning
Human factors
Interface
K-modes
Vlustering

Cite this

@conference{db577c4ccf28469b8cb638c482888f0a,

title = "Mining users' preferences in an interactive multimedia learning system: A human factor perspective",

abstract = "With the increasing popularity of the Internet, interactive multimedia learning systems are widely used in both educational and industrial settings. However, as human factors vary across users, they may prefer the design of interactive multimedia learning systems differently. To have a deep understanding of the influence of human factors, we apply a data mining approach to the assessment of users' preferences in using interactive multimedia learning systems. More specifically, the K-modes algorithm is used to group users' preferences. The results indicate that users' preferences could be divided into four groups where computer experience significantly influences their preferences. Implications for the development of interactive multimedia learning systems are also discussed.",

keywords = "Data mining, E-Learning, Human factors, Interface, K-modes, Vlustering",

author = "Chrysostomou, {Kyriacos A.} and Chen, {Sherry Y.} and Xiaohui Liu",

note = "Publisher Copyright: {\textcopyright} BCS HCI Group Conference: Engage, HCI 2006.All right reserved.; 20th British Computer Society Conference on Human-Computer Interaction: Engage, HCI 2006 ; Conference date: 11-09-2006 Through 15-09-2006",

year = "2020",

language = "???core.languages.en_GB???",

pages = "118--122",

}

Mining users' preferences in an interactive multimedia learning system: A human factor perspective. / Chrysostomou, Kyriacos A.; Chen, Sherry Y.; Liu, Xiaohui.
2020. 118-122 Paper presented at 20th British Computer Society Conference on Human-Computer Interaction: Engage, HCI 2006, London, United Kingdom.

Research output: Contribution to conference › Paper › peer-review

TY - CONF

T1 - Mining users' preferences in an interactive multimedia learning system

T2 - 20th British Computer Society Conference on Human-Computer Interaction: Engage, HCI 2006

AU - Chrysostomou, Kyriacos A.

AU - Chen, Sherry Y.

AU - Liu, Xiaohui

PY - 2020

Y1 - 2020

N2 - With the increasing popularity of the Internet, interactive multimedia learning systems are widely used in both educational and industrial settings. However, as human factors vary across users, they may prefer the design of interactive multimedia learning systems differently. To have a deep understanding of the influence of human factors, we apply a data mining approach to the assessment of users' preferences in using interactive multimedia learning systems. More specifically, the K-modes algorithm is used to group users' preferences. The results indicate that users' preferences could be divided into four groups where computer experience significantly influences their preferences. Implications for the development of interactive multimedia learning systems are also discussed.

AB - With the increasing popularity of the Internet, interactive multimedia learning systems are widely used in both educational and industrial settings. However, as human factors vary across users, they may prefer the design of interactive multimedia learning systems differently. To have a deep understanding of the influence of human factors, we apply a data mining approach to the assessment of users' preferences in using interactive multimedia learning systems. More specifically, the K-modes algorithm is used to group users' preferences. The results indicate that users' preferences could be divided into four groups where computer experience significantly influences their preferences. Implications for the development of interactive multimedia learning systems are also discussed.

KW - Data mining

KW - E-Learning

KW - Human factors

KW - Interface

KW - K-modes

KW - Vlustering

UR - http://www.scopus.com/inward/record.url?scp=84860523659&partnerID=8YFLogxK

M3 - 會議論文

AN - SCOPUS:84860523659

SP - 118

EP - 122

Y2 - 11 September 2006 through 15 September 2006

ER -

Mining users' preferences in an interactive multimedia learning system: A human factor perspective

Abstract

Conference

Keywords

Fingerprint

Cite this