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Social and Collaborative Interactions for Educational Content Enrichment in ULEs.

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Title: Social and Collaborative Interactions for Educational Content Enrichment in ULEs.
Authors: Araújo, Rafael D.1 rafael.araujo@ufu.br, Brant-Ribeiro, Taffarel1,2 brant.ribeiro@ifsuldeminas.edu.br, Mendonça, Igor E. S.1 igoremendonca@gmail.com, Mendes, Miller M.1 m3iller@gmail.com, Dorça, Fabiano A.1 fabianodor@ufu.br, Cattelan, Renan G.1 renan@ufu.br
Source: Educational Technology & Society. Jul2017, Vol. 20 Issue 3, p133-144. 12p.
Subject Terms: *Classroom environment, *Multimedia systems in education, *Collaborative learning, *Performance, *Semester system in education
Abstract: This article presents a social and collaborative model for content enrichment in Ubiquitous Learning Environments. Designed as a loosely coupled software architecture, the proposed model was implemented and integrated into the Classroom eXperience, a multimedia capture platform for educational environments. After automatically recording a lecture in instrumented classrooms, students and instructors can enrich its content with comments and rating features. The platform usage was monitored for three school semesters to analyze the receptivity and the impact of the proposed features over 121 undergraduate students. As a result, we observed that both system's access rate and students' performance increased, suggesting that interactive features leverage collaborative learning interactions and promote the teaching/learning process. [ABSTRACT FROM AUTHOR]
Copyright of Educational Technology & Society is the property of International Forum of Educational Technology & Society (IFETS) and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
Database: Education Research Complete
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  Data: <searchLink fieldCode="JN" term="%22Educational+Technology+%26+Society%22">Educational Technology & Society</searchLink>. Jul2017, Vol. 20 Issue 3, p133-144. 12p.
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  Data: *<searchLink fieldCode="DE" term="%22Classroom+environment%22">Classroom environment</searchLink><br />*<searchLink fieldCode="DE" term="%22Multimedia+systems+in+education%22">Multimedia systems in education</searchLink><br />*<searchLink fieldCode="DE" term="%22Collaborative+learning%22">Collaborative learning</searchLink><br />*<searchLink fieldCode="DE" term="%22Performance%22">Performance</searchLink><br />*<searchLink fieldCode="DE" term="%22Semester+system+in+education%22">Semester system in education</searchLink>
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  Data: This article presents a social and collaborative model for content enrichment in Ubiquitous Learning Environments. Designed as a loosely coupled software architecture, the proposed model was implemented and integrated into the Classroom eXperience, a multimedia capture platform for educational environments. After automatically recording a lecture in instrumented classrooms, students and instructors can enrich its content with comments and rating features. The platform usage was monitored for three school semesters to analyze the receptivity and the impact of the proposed features over 121 undergraduate students. As a result, we observed that both system's access rate and students' performance increased, suggesting that interactive features leverage collaborative learning interactions and promote the teaching/learning process. [ABSTRACT FROM AUTHOR]
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  Data: <i>Copyright of Educational Technology & Society is the property of International Forum of Educational Technology & Society (IFETS) and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
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