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Titel: Towards Integrating Conversational Agents and Learning Analytics in MOOCs
VerfasserIn: Demetriadis, Stavros
Karakostas, Anastasios
Tsiatsos, Thrasyvoulos
Caballé, Santi
Dimitriadis, Yannis
Weinberger, Armin
Papadopoulos, Pantelis M.
Palaigeorgiou, George
Tsimpanis, Costas
Hodges, Matthew
HerausgeberIn: Barolli, Leonard
Xhafa, Fatos
Javaid, Nadeem
Spaho, Evjola
Kolici, Vladi
Sprache: Englisch
Titel: Advances in Internet, Data & Web Technologies : The 6th International Conference on Emerging Internet, Data & Web Technologies (EIDWT-2018)
Startseite: 1061
Endseite: 1072
Verlag/Plattform: Springer
Erscheinungsjahr: 2018
Erscheinungsort: Cham
Titel der Konferenz: EIDWT 2018
Konferenzort: Tirana, Albania
Dokumenttyp: Konferenzbeitrag (in einem Konferenzband / InProceedings erschienener Beitrag)
Abstract: Higher Education Massive Open Online Courses (MOOCs) introduce a way of transcending formal higher education by realizing technology-enhanced formats of learning and instruction and by granting access to an audience way beyond students enrolled in any one Higher Education Institution. However, although MOOCs have been reported as an efficient and important educational tool, there is a number of issues and problems related to their educational impact. More specifically, there is an important number of drop outs during a course, little participation, and lack of students’ motivation and engagement overall. This may be due to one-size-fits-all instructional approaches and very limited commitment to student-student and teacher-student collaboration. This paper introduces the development agenda of a newly started European project called “colMOOC” that aims to enhance the MOOCs experience by integrating collaborative settings based on Conversational Agents and screening methods based on Learning Analytics, to support both students and teachers during a MOOC course. Conversational pedagogical agents guide and support student dialogue using natural language both in individual and collaborative settings. Integrating this type of conversational agents into MOOCs to trigger peer interaction in discussion groups can considerably increase the engagement and the commitment of online students and, consequently, reduce MOOCs dropout rate. Moreover, Learning Analytics techniques can support teachers’ orchestration and students’ learning during MOOCs by evaluating students’ interaction and participation. The research reported in this paper is currently undertaken within the research project colMOOC funded by the European Commission.
DOI der Erstveröffentlichung: 10.1007/978-3-319-75928-9_98
URL der Erstveröffentlichung: https://link.springer.com/chapter/10.1007/978-3-319-75928-9_98
Link zu diesem Datensatz: hdl:20.500.11880/32710
http://dx.doi.org/10.22028/D291-35884
ISBN: 978-3-319-75928-9
978-3-319-75927-2
Datum des Eintrags: 4-Apr-2022
Bemerkung/Hinweis: Lecture Notes on Data Engineering and Communications Technologies ; 17
Fakultät: HW - Fakultät für Empirische Humanwissenschaften und Wirtschaftswissenschaft
Fachrichtung: HW - Bildungswissenschaften
Professur: HW - Prof. Dr. Armin Weinberger
Sammlung:SciDok - Der Wissenschaftsserver der Universität des Saarlandes

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