Application of Interactive Classification System in University Study Course Comparison

Autor/inn/en	Birzniece, Ilze; Rudzajs, Peteris; Kalibatiene, Diana; Vasilecas, Olegas; Rencis, Edgars
Titel	Application of Interactive Classification System in University Study Course Comparison
Quelle	In: Informatics in Education, 14 (2015) 1, S.13-34 (22 Seiten)Infoseite zur Zeitschrift PDF als Volltext kostenfreie Datei Verfügbarkeit
Sprache	englisch
Dokumenttyp	gedruckt; online; Zeitschriftenaufsatz
ISSN	1648-5831
Schlagwörter	Classification; Accuracy; Higher Education; Exchange Programs; Information Systems; Management Systems; Curriculum Development; Computer Assisted Instruction; Knowledge Management; Computer Software; Foreign Countries; Universities; Course Descriptions; International Cooperation; Business Administration Education; Information Science Education; Comparative Education; Student Mobility; Austria; Latvia; Russia + Suchen Sie Ihr Suchwort? Classification system; Klassifikation; Klassifikationssystem; Hochschulbildung; Hochschulsystem; Hochschulwesen; Exchange programme; Exchange program; Exchange programmes; Austauschprogramm; Curriculum; Development; Curriculumentwicklung; Lehrplan; Entwicklung; Computer based training; Computerunterstützter Unterricht; Wissensmanagement; Ausland; University; Universität; Kursstrukturplan; Internationale Kooperation; Internationale Zusammenarbeit; Informationstechnologische Bildung; Vergleichende Erziehungswissenschaft; Student; Students; Mobility; Schüler; Schülerin; Studentin; Mobilität; Österreich; Lettland; Russland
Abstract	The growing amount of information in the world has increased the need for computerized classification of different objects. This situation is present in higher education as well where the possibility of effortless detection of similarity between different study courses would give the opportunity to organize student exchange programmes effectively and facilitate curriculum management and development. This area which currently relies on manual time-consuming expert activities could benefit from application of smartly adapted machine learning technologies. Data in this problem domain is complex leading to inability for automatic classification approaches to always reach the desired result in terms of classification accuracy. Therefore, our approach suggests an automated/semi-automated classification solution, which incorporates both machine learning facilities and interactive involvement of a domain expert for improving classification results. The system's prototype has been implemented and experiments are carried out. This interactive classification system allows to classify educational data, which often comes in unstructured or semi-structured, incomplete and/or insufficient form, thus reducing the number of misclassified instances significantly in comparison with the automatic machine learning approach. [A bibliography is included.] (As Provided).
Anmerkungen	Vilnius University Institute of Mathematics and Informatics, Lithuanian Academy of Sciences. Akademjos str. 4, Vilnius LT 08663 Lithuania. Tel: +37-5-21-09300; Fax: +37-5-27-29209; e-mail: info@mii.vu.lt; Web site: http://www.mii.lt/informatics_in_education/
Erfasst von	ERIC (Education Resources Information Center), Washington, DC
Update	2020/1/01