Smart learning environment: Teacher’s role in assessing classroom attention
The main purpose of this article is to investigate the impact of teacher’s position on students’ performance in higher education. A new pedagogical approach based on collaborative learning is used due to the design of a smart learning environment (SLE). This workspace uses, respectively, information and communication technologies (ICT) and radio frequency identification (RFID)-based indoor positioning system in order to examine students’ perceptions and the involvement of groups into this smart classroom. The merge of interactive multimedia system, ubiquitous computing and several handheld devices should lead to a successful active learning process. Firstly, we provide a detailed description of the proposed collaborative environment using mainly new technologies and indoor location system serving as a platform for evaluating attention. The research provides an obvious consensus on the teacher’s role in assessing classroom attention. We discuss our preliminary results on how teacher’s position influences essentially students’ participation. Our first experiments show that the integration of novel technologies in the area of higher education is extremely promoting the traditional way of teaching. The smart classroom model has been recommended to support this evolution. As a result, the found results indicate that the teacher’s position increases the learner’s motivation, engagement and effective learning.
Bobescu, B. & Alexandru, M. (2015) ‘Mobile indoor positioning using WI-FI localization’, Proceedings of Review of the Air Force Academy, vol. 1, no. 28, pp. 119–122. Available at: http://www.afahc.ro/ro/revista/2015_1/119.pdf
Chin, K. & Chen, Y. (2013) ‘A mobile learning support system for ubiquitous learning environments’, in The 2nd International Conference on Integrated Information, vol. 73, pp. 14–21. doi: 10.1016/j.sbspro.2013.02.013.
Ciezkowski, M. (2017) ‘Triangulation positioning system based on a static IR beacon-receiver system’, in 22nd International Conference on Methods and Models in Automation and Robotics (MMAR), Miedzyzdroje, Poland, pp. 84–88. doi: 10.1109/MMAR.2017.8046803.
Cope, B. & Kalantzis, M. (2013) ‘Towards a new learning: The scholar social knowledge workspace, in theory and practice’, E–Learning and Digital Media, vol. 10, no. 4, pp. 332–356. doi: 10.2304/elea.2013.10.4.332.
Dari, Y., Suyoto, S. & Pranowo, P. (2018) ‘CAPTURE: A Mobile based indoor positioning system using wireless indoor positioning system’, International Journal of Interactive Mobile Technologies (iJIM), vol. 12, no. 1, pp. 61–72. doi: 10.3991/ijim.v12i1.7632.
Dong, S., Li, H. & Yin, Q. (2018) ‘Building information modeling in combination with real time location systems and sensors for safety performance’, Safety Science, vol. 102, pp. 226–237. doi: 10.1016/j.ssci.2017.10.011.
Elhoseny, H., et al., (2018) ‘Evaluating learners’ progress in smart learning environment’, in International Conference on Advanced Intelligent Systems and Informatics, Cairo, Egypt, pp. 734–744. doi: 10.1007/978-3-319-64861-3_69.
Gharat, V., et al., (2017) ‘Indoor performance analysis of LF-RFID based positioning system: Comparison with UHF-RFID and UWB’, in International Conference on Indoor Positioning and Indoor Navigation (IPIN), Sapporo, Japan, pp. 1–8. doi: 10.1109/IPIN.2017.8115901.
Gharat, V., et al., (2018) ‘Low Frequency RFID system for identification and localization in smart cities – Comparison with UHF RFID’, International Journal of RF Technologies Research and Applications, vol. 8, no. 4, pp. 191–211. doi: 10.3233/RFT-181781.
Gillies, R. (2008) ‘Teachers’ and students’ verbal behaviours during cooperative learning’, Journal Computer-Supported Collaborative Learning, vol. 8, pp. 238–257. doi: 10.1007/978-0-387-70892-8_12.
Guo, J., Liu, X. & Wang, Z. (2015) ‘Optimized indoor positioning based on WIFI in mobile classroom project’, in 11th International Conference on Natural Computation (ICNC), Zhangjiajie, China, pp. 1208–1212. doi: 10.1109/ICNC.2015.7378163.
Kakanejadi Fard, H., Chen, Y. & Kook Son, K. (2015) ‘Indoor Positioning of mobile devices with agile iBeacon deployment’, in 28th Canadian Conference on Electrical and Computer Engineering (CCECE), Halifax, NS, pp. 275–279. doi: 10.1109/CCECE.2015.7129199.
Kun, A. (2017) ‘Textbooks for pervasive computing training and education’, IEEE Pervasive Computing, vol. 16, no. 3, pp. 59–61. doi: 10.1109/MPRV.2017.2940951.
Laru, J., Naykki, P. & Jarvela, S. (2015) ‘Four stages of research on the educational use of ubiquitous computing’, IEEE Transactions on Learning Technologies, vol. 8, no. 1, pp. 69–82. doi: 10.1109/TLT.2014.2360862.
Makahinda, T. (2018) ‘The effect of learning based on technology model and assessment technique toward thermodynamic learning achievement’, IOP Conference Series: Materials Science and Engineering, vol. 306, pp. 1–6. doi: 10.1088/1757-899X/306/1/012125.
Moyne, M., et al., (2018) ‘The development and evaluation of DEFT, a web-based tool for engineering design education’, IEEE Transactions on Learning Technologies , vol. 11, no. 4, pp. 545–550. doi: 10.1109/TLT.2018.2810197.
Nakao, S., et al., (2011) ‘UHF RFID mobile reader for passive- and active-tag communication’, in IEEE Radio and Wireless Symposium (RWS), Phoenix, AZ, pp. 311–314. doi: 10.1109/RWS.2011.5725441.
Omae, Y., et al., (2017) ‘Machine learning-based collaborative learning optimizer toward intelligent CSCL’, in IEEE/SICE International Symposium on System Integration (SII), Taipei, Taiwan. doi: 10.1109/SII.2017.8279283.
Potgantwar, A., Kohli, J. K. & Shirke, P. (2015) ‘Adaptive RSS based indoor positioning system using RFID and wireless technology’, Global Journal of Advanced Engineering Technologies, vol. 4, no. 4, pp. 436–446. ISSN (Online): 2277-6370 & ISSN (Print): 2394-0921
Raca, M. & Dillenbourg, P. (2013) ‘System for assessing classroom attention’, in International Conference on Learning Analytics and Knowledge LAK '13’, Leuven, Belgium, pp. 265–269. doi: 10.1145/2460296.2460351.
Santerre, R. & Geiger, A. (2018) ‘Geometry of GPS relative positioning’, GPS Solutions, vol. 22, no. 2, p. 1. doi: 10.1007/s10291-018-0713-2.
Tesavrita, C., et al., (2017) ‘Intra-organizational and inter-organizational knowledge sharing in collaborative learning process: A conceptual framework for SME’, in 4th International Conference on Industrial Engineering and Applications (ICIEA), Nagoya, Japan, pp. 187–191. doi: 10.1109/IEA.2017.7939204.
Zhu, Z., Sun, Y. & Riezebos, P. (2016) ‘Introducing the smart education framework: Core elements for successful learning in a digital world’, International Journal of Smart Technology and Learning, vol. 1, no. 1, pp. 53–66. doi: 10.1504/IJSMARTTL.2016.078159.
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