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Can log files analysis estimate learners' level of motivation?

Research output: Chapter in Book/Report/Conference proceedingChapter (peer-reviewed)peer-review

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Can log files analysis estimate learners' level of motivation? / Cocea, Mihaela; Weibelzahl, Stephan.

LWA 2006: Lernen - Wissensentdeckung - Adaptivitat, 14th Workshop on Adaptivity and User Modeling in Interactive Systems (ABIS 2006). Hildesheim : University of Hildesheim, Institute of Computer Science, 2006. p. 32-35 (Hildesheimer Informatik-Berichte; No. 1/2006).

Research output: Chapter in Book/Report/Conference proceedingChapter (peer-reviewed)peer-review

Harvard

Cocea, M & Weibelzahl, S 2006, Can log files analysis estimate learners' level of motivation? in LWA 2006: Lernen - Wissensentdeckung - Adaptivitat, 14th Workshop on Adaptivity and User Modeling in Interactive Systems (ABIS 2006). Hildesheimer Informatik-Berichte, no. 1/2006, University of Hildesheim, Institute of Computer Science, Hildesheim, pp. 32-35, LWA, 1/05/11. <http://web1.bib.uni-hildesheim.de/edocs/2007/522048412/meta/>

APA

Cocea, M., & Weibelzahl, S. (2006). Can log files analysis estimate learners' level of motivation? In LWA 2006: Lernen - Wissensentdeckung - Adaptivitat, 14th Workshop on Adaptivity and User Modeling in Interactive Systems (ABIS 2006) (pp. 32-35). (Hildesheimer Informatik-Berichte; No. 1/2006). University of Hildesheim, Institute of Computer Science. http://web1.bib.uni-hildesheim.de/edocs/2007/522048412/meta/

Vancouver

Cocea M, Weibelzahl S. Can log files analysis estimate learners' level of motivation? In LWA 2006: Lernen - Wissensentdeckung - Adaptivitat, 14th Workshop on Adaptivity and User Modeling in Interactive Systems (ABIS 2006). Hildesheim: University of Hildesheim, Institute of Computer Science. 2006. p. 32-35. (Hildesheimer Informatik-Berichte; 1/2006).

Author

Cocea, Mihaela ; Weibelzahl, Stephan. / Can log files analysis estimate learners' level of motivation?. LWA 2006: Lernen - Wissensentdeckung - Adaptivitat, 14th Workshop on Adaptivity and User Modeling in Interactive Systems (ABIS 2006). Hildesheim : University of Hildesheim, Institute of Computer Science, 2006. pp. 32-35 (Hildesheimer Informatik-Berichte; 1/2006).

Bibtex

@inbook{2f1bc4a631c44e0e9704c52683be1e7e,
title = "Can log files analysis estimate learners' level of motivation?",
abstract = "The learners{\textquoteright} motivation has an impact on the quality of learning, especially in e-Learning environments. Most of these environments store data about the learner{\textquoteright}s actions in log files. Logging the users{\textquoteright} interactions in educational systems gives the possibility to track their actions at a refined level of detail. Data mining and machine learning techniques can “give meaning” to these data and provide valuable information for learning improvement. An area where improvement is absolutely necessary and of great importance is motivation, known to be an essential factor for preventing attrition in e-Learning. In this paper we investigate if the log files data analysis can be used to estimate the motivational level of the learner. A decision tree is build from a limited number of log files from a web-based learning environment. The results suggest that time spent reading is an important factor for predicting motivation; also, performance in tests was found to be a relevant indicator of the motivational level.",
author = "Mihaela Cocea and Stephan Weibelzahl",
year = "2006",
language = "English",
series = "Hildesheimer Informatik-Berichte",
publisher = "University of Hildesheim, Institute of Computer Science",
number = "1/2006",
pages = "32--35",
booktitle = "LWA 2006: Lernen - Wissensentdeckung - Adaptivitat, 14th Workshop on Adaptivity and User Modeling in Interactive Systems (ABIS 2006)",
note = "LWA ; Conference date: 01-05-2011",

}

RIS

TY - CHAP

T1 - Can log files analysis estimate learners' level of motivation?

AU - Cocea, Mihaela

AU - Weibelzahl, Stephan

PY - 2006

Y1 - 2006

N2 - The learners’ motivation has an impact on the quality of learning, especially in e-Learning environments. Most of these environments store data about the learner’s actions in log files. Logging the users’ interactions in educational systems gives the possibility to track their actions at a refined level of detail. Data mining and machine learning techniques can “give meaning” to these data and provide valuable information for learning improvement. An area where improvement is absolutely necessary and of great importance is motivation, known to be an essential factor for preventing attrition in e-Learning. In this paper we investigate if the log files data analysis can be used to estimate the motivational level of the learner. A decision tree is build from a limited number of log files from a web-based learning environment. The results suggest that time spent reading is an important factor for predicting motivation; also, performance in tests was found to be a relevant indicator of the motivational level.

AB - The learners’ motivation has an impact on the quality of learning, especially in e-Learning environments. Most of these environments store data about the learner’s actions in log files. Logging the users’ interactions in educational systems gives the possibility to track their actions at a refined level of detail. Data mining and machine learning techniques can “give meaning” to these data and provide valuable information for learning improvement. An area where improvement is absolutely necessary and of great importance is motivation, known to be an essential factor for preventing attrition in e-Learning. In this paper we investigate if the log files data analysis can be used to estimate the motivational level of the learner. A decision tree is build from a limited number of log files from a web-based learning environment. The results suggest that time spent reading is an important factor for predicting motivation; also, performance in tests was found to be a relevant indicator of the motivational level.

M3 - Chapter (peer-reviewed)

T3 - Hildesheimer Informatik-Berichte

SP - 32

EP - 35

BT - LWA 2006: Lernen - Wissensentdeckung - Adaptivitat, 14th Workshop on Adaptivity and User Modeling in Interactive Systems (ABIS 2006)

PB - University of Hildesheim, Institute of Computer Science

CY - Hildesheim

T2 - LWA

Y2 - 1 May 2011

ER -

ID: 223405