TY - JOUR
T1 - Development of a software that supports multimodal learning analytics
T2 - A case study on oral presentations
AU - Munoz, Roberto
AU - Villarroel, Rodolfo
AU - Barcelos, Thiago S.
AU - Souza, Alexandra
AU - Merino, Erick
AU - Guiñez, Rodolfo
AU - Silva, Leandro A.
N1 - Funding Information:
Roberto Munoz, is partially funded by INF-PUCV 2015 doctoral grant. Rodolfo Villarroel is funded by PUCV 2017 039.440/2017 grant. Finally, the authors would like to thank Travis Jones for his valuable contributions to the elaboration of this paper.
Publisher Copyright:
© J.UCS.
PY - 2018
Y1 - 2018
N2 - Learning Analytics is the intelligent use of data generated from students with the objective of understanding and improving the teaching and learning process. Currently, there is a lack of tools to measure the development of complex skills in real classroom environments that are flexible enough to add and process data from different sensors and oriented towards a massive public. Based on this finding, we developed a free software system that permits to capture and to visualize a set of 10 body postures using the Microsoft Kinect sensor, along with the ability to track custom body postures and data from other sensors. The developed tool was validated by means of precision and usability tests. Furthermore, with the goal of demonstrating the potential of incorporating this type of software into the classroom, the software was used as a tool to give feedback to the teacher and to the students at the moment of giving and evaluating oral presentations. Also, a clustering analysis of data gathered from 45 student presentations indicate that presentations on similar topics with also similar complexity levels can be successfully discriminated.
AB - Learning Analytics is the intelligent use of data generated from students with the objective of understanding and improving the teaching and learning process. Currently, there is a lack of tools to measure the development of complex skills in real classroom environments that are flexible enough to add and process data from different sensors and oriented towards a massive public. Based on this finding, we developed a free software system that permits to capture and to visualize a set of 10 body postures using the Microsoft Kinect sensor, along with the ability to track custom body postures and data from other sensors. The developed tool was validated by means of precision and usability tests. Furthermore, with the goal of demonstrating the potential of incorporating this type of software into the classroom, the software was used as a tool to give feedback to the teacher and to the students at the moment of giving and evaluating oral presentations. Also, a clustering analysis of data gathered from 45 student presentations indicate that presentations on similar topics with also similar complexity levels can be successfully discriminated.
KW - Microsoft kinect
KW - Multimodal learning analytics
KW - Oral presentations
KW - Self- organizing maps
UR - http://www.scopus.com/inward/record.url?scp=85048891089&partnerID=8YFLogxK
M3 - Article
AN - SCOPUS:85048891089
VL - 24
SP - 149
EP - 170
JO - Journal of Universal Computer Science
JF - Journal of Universal Computer Science
SN - 0948-695X
IS - 2
ER -