Abstract
Students’ real-time feedback is acknowledged as an important source of information for teachers/lecturers to improve their teaching and address issues students may have, such as going deeper in some of the materials covered or providing more examples to understand an abstract concept. Previous
applications collecting real-time feedback from students through clickers and mobiles typically collect limited information with predefined questions, while more recent applications using social media collect such a large volume of information that a lecturer cannot manually process it in real time. We developed the SA-E system for analysing students’ real-time feedback provided via social media, and, in this paper, we present the evaluation of this system in real settings with lecturers and students. The results show that lecturers are highly satisfied with the proposed system. In contrast, although the participation of students in providing feedback was high, the students’ opinions of the system were between neutral and dislike.
applications collecting real-time feedback from students through clickers and mobiles typically collect limited information with predefined questions, while more recent applications using social media collect such a large volume of information that a lecturer cannot manually process it in real time. We developed the SA-E system for analysing students’ real-time feedback provided via social media, and, in this paper, we present the evaluation of this system in real settings with lecturers and students. The results show that lecturers are highly satisfied with the proposed system. In contrast, although the participation of students in providing feedback was high, the students’ opinions of the system were between neutral and dislike.
Original language | English |
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Title of host publication | Proceedings of the 17th IEEE International Conference on Advanced Learning Technologies |
Publisher | Institute of Electrical and Electronics Engineers Inc. |
Pages | 60-61 |
Number of pages | 2 |
ISBN (Electronic) | 978-1538638705 |
ISBN (Print) | 978-1538638712 |
DOIs | |
Publication status | Published - 8 Aug 2017 |
Event | 17th IEEE International Conference on Advanced Learning Technologies - Timisoara, Romania Duration: 3 Jul 2017 → 7 Jul 2017 |
Publication series
Name | IEEE ICALT Proceedings Series |
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Publisher | IEEE |
ISSN (Electronic) | 2161-377X |
Conference
Conference | 17th IEEE International Conference on Advanced Learning Technologies |
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Country/Territory | Romania |
City | Timisoara |
Period | 3/07/17 → 7/07/17 |
Keywords
- sentiment analysis
- technology enhanced learning
- students’ feedback
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Sentiment analysis on students’ real-time feedback
Altrabsheh, N. (Author), Cocea, M. (Supervisor), Fallahkhair, S. (Supervisor) & Gegov, A. (Supervisor), Feb 2016Student thesis: Doctoral Thesis
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