R
Rafael Ferreira Mello
Researcher at Universidade Federal Rural de Pernambuco
Publications - 73
Citations - 391
Rafael Ferreira Mello is an academic researcher from Universidade Federal Rural de Pernambuco. The author has contributed to research in topics: Computer science & Learning analytics. The author has an hindex of 7, co-authored 37 publications receiving 121 citations.
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Journal ArticleDOI
Automatic feedback in online learning environments: A systematic literature review
Anderson Pinheiro Cavalcanti,Arthur Barbosa,Ruan Carvalho,Fred Freitas,Yi-Shan Tsai,Dragan Gašević,Dragan Gašević,Dragan Gašević,Rafael Ferreira Mello +8 more
TL;DR: In this article, a systematic literature review on automatic feedback generation in learning management systems is presented, showing that 65.07% of the studies demonstrate that automatic feedback increases student performance in activities.
Proceedings ArticleDOI
Towards automatic content analysis of social presence in transcripts of online discussions
Maverick Andre Dionisio Ferreira,Vitor Rolim,Rafael Ferreira Mello,Rafael Dueire Lins,Guanliang Chen,Dragan Gašević +5 more
TL;DR: This study adopted epistemic network analysis to investigate the structural construct validity of the automatic classification approach and showed that the epistemic networks produced based on messages manually and automatically coded produced nearly identical results.
Proceedings ArticleDOI
Towards automatic cross-language classification of cognitive presence in online discussions
Gian Barbosa,Raissa Camelo,Anderson Pinheiro Cavalcanti,Péricles B. C. de Miranda,Rafael Ferreira Mello,Vitomir Kovanović,Dragan Gašević +6 more
TL;DR: The findings suggest that certain aspects of cognitive presence construct are highly generalizable and transfer across different languages.
Proceedings ArticleDOI
How good is my feedback?: a content analysis of written feedback
Anderson Pinheiro Cavalcanti,Arthur Diego,Rafael Ferreira Mello,Katerina Mangaroska,André Luiz Borba do Nascimento,Fred Freitas,Dragan Gašević +6 more
TL;DR: A content analysis of feedback text provided by instructors based on different indicators of good feedback quality is proposed and insights into the most influential textual features of feedback that predict feedback quality are provided.
Proceedings ArticleDOI
Student appreciation of data-driven feedback: A pilot study on OnTask
TL;DR: In this paper, a pilot study that examined students' experience of LA-based feedback, offered with the OnTask system, took into consideration the factors of students' selfefficacy and self-regulation skills.