A cost-effective IoT learning environment for the training and assessment of surgical technical skills with visual learning analytics

2021 ◽  
pp. 103952
Author(s):  
Pablo Castillo-Segura ◽  
Carmen Fernández-Panadero ◽  
Carlos Alario-Hoyos ◽  
Pedro J. Muñoz-Merino ◽  
Carlos Delgado Kloos
2021 ◽  
Vol 13 (15) ◽  
pp. 8610
Author(s):  
Chung Kwan Lo ◽  
Gaowei Chen

The professional development of experienced teachers has received considerably less attention than that of novice teachers. This study focuses on four experienced secondary mathematics teachers in Shanghai, China, with two participating in a year-long professional development program (treatment teachers) and the other two received conventional knowledge-based professional development (comparison teachers). The program introduced productive classroom talk skills which can facilitate teachers’ formative assessment of student learning during class. To encourage teachers to reflect on their classroom discourse when reviewing recordings of their teaching, we used visual learning analytics with the treatment teachers and theorized the use of this technology with activity theory. After completing the program, the treatment teachers were better able to use productive talk moves to elicit student responses and to provide timely formative feedback accordingly. Specifically, the percentage of word contributions in lessons from students and the length of their responses increased noticeably. Qualitative findings suggest that the use of visual learning analytics mediated the treatment teachers and improved classroom discourse. Based on these findings and activity theory, we provide recommendations for future use of visual learning analytics to improve teachers’ classroom talk and designing professional development activities for experienced teachers.


2016 ◽  
Vol 3 (3) ◽  
pp. 5-8 ◽  
Author(s):  
Dragan Gasevic ◽  
Mykola Pechenizkiy

This paper is a guest editorial into a special section that offers a collection of tutorials on methods that can be used in learning analytics. The special section is prepared as a response to the growing need of learning analytics practitioners and researchers to learn and use novel methods. In spite of this need, papers that systematically introduce some of the methods have been underrepresented in the literature. Specifically, the special section features papers that introduce epistemic network analysis, automated content and network analysis of social media, text coherence analysis with Coh-Metrix, microgenetic analysis with sequence pattern mining, and design of visual learning analytics guided by educational theory informed goals.


2015 ◽  
Vol 10 (4) ◽  
pp. 242-252 ◽  
Author(s):  
Miguel A. Conde ◽  
Francisco J. Garcia-Penalvo ◽  
Diego-Alonso Gomez-Aguilar ◽  
Roberto Theron

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