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Comulang: towards a collaborative e-learning system that supports student group modeling.

Troussas C, Virvou M, Alepis E - Springerplus (2013)

Bottom Line: This paper describes an e-learning system that is expected to further enhance the educational process in computer-based tutoring systems by incorporating collaboration between students and work in groups.The resulting system is called "Comulang" while as a test bed for its effectiveness a multiple language learning system is used.One of the resulting system's basic aims is to provide efficient student groups whose limitations and capabilities are well balanced.

View Article: PubMed Central - PubMed

Affiliation: Department of Informatics, University of Piraeus, Piraeus, Greece.

ABSTRACT
This paper describes an e-learning system that is expected to further enhance the educational process in computer-based tutoring systems by incorporating collaboration between students and work in groups. The resulting system is called "Comulang" while as a test bed for its effectiveness a multiple language learning system is used. Collaboration is supported by a user modeling module that is responsible for the initial creation of student clusters, where, as a next step, working groups of students are created. A machine learning clustering algorithm works towards group formatting, so that co-operations between students from different clusters are attained. One of the resulting system's basic aims is to provide efficient student groups whose limitations and capabilities are well balanced.

No MeSH data available.


Student’s errors.
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Fig3: Student’s errors.

Mentions: Figure 3 illustrate a snapshot of the operating educational application, where a student is completing a “fill-in-the-gap” exercise and taking the system’s feedback. More specifically, it illustrates a categorization to a student’s specific errors. The student can be evaluated and check where s/he is wrong and what type of mistake s/he has made. The different colors indicate different type of errors, such as errors in articles or pronouns, verb mistake, spelling mistakes, confusion with the German or French language or unanswered questions. Finally, Figure 4 illustrates a report of k-means, the initial user data and the resulting k-mean vectors.Figure 3


Comulang: towards a collaborative e-learning system that supports student group modeling.

Troussas C, Virvou M, Alepis E - Springerplus (2013)

Student’s errors.
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC3755789&req=5

Fig3: Student’s errors.
Mentions: Figure 3 illustrate a snapshot of the operating educational application, where a student is completing a “fill-in-the-gap” exercise and taking the system’s feedback. More specifically, it illustrates a categorization to a student’s specific errors. The student can be evaluated and check where s/he is wrong and what type of mistake s/he has made. The different colors indicate different type of errors, such as errors in articles or pronouns, verb mistake, spelling mistakes, confusion with the German or French language or unanswered questions. Finally, Figure 4 illustrates a report of k-means, the initial user data and the resulting k-mean vectors.Figure 3

Bottom Line: This paper describes an e-learning system that is expected to further enhance the educational process in computer-based tutoring systems by incorporating collaboration between students and work in groups.The resulting system is called "Comulang" while as a test bed for its effectiveness a multiple language learning system is used.One of the resulting system's basic aims is to provide efficient student groups whose limitations and capabilities are well balanced.

View Article: PubMed Central - PubMed

Affiliation: Department of Informatics, University of Piraeus, Piraeus, Greece.

ABSTRACT
This paper describes an e-learning system that is expected to further enhance the educational process in computer-based tutoring systems by incorporating collaboration between students and work in groups. The resulting system is called "Comulang" while as a test bed for its effectiveness a multiple language learning system is used. Collaboration is supported by a user modeling module that is responsible for the initial creation of student clusters, where, as a next step, working groups of students are created. A machine learning clustering algorithm works towards group formatting, so that co-operations between students from different clusters are attained. One of the resulting system's basic aims is to provide efficient student groups whose limitations and capabilities are well balanced.

No MeSH data available.