scholarly journals Advanced Sensors Technology in Education

Sensors ◽  
2019 ◽  
Vol 19 (19) ◽  
pp. 4155
Author(s):  
González Crespo ◽  
Burgos
Keyword(s):  
Learning Environments ◽  
Secondary Students ◽  
Low Cost ◽  
Multimodal Learning ◽  
Depth Cameras ◽  
Martial Art ◽  
Multimodal Learning Analytics ◽  
Soccer Kick ◽  
The Mind ◽  
Oral Presentations

The topic presented will show how different kinds of sensors can help to improve our skills in learning environments. When we open the mind and let it take the control to be creative, we can think how a martial art would be improved with registered sensors, or how a person may dance with machines to improve their technique, or how you may improve your soccer kick for a penalties round. The use of sensors seems easy to imagine in these examples, but their use is not limited to these types of learning environments. Using depth cameras to detect patterns in oral presentations, or improving the assessment of agility through low cost-sensors with multimodal learning analytics, or using computing devices as sensors to measure their impact on primary and secondary students’ performances are the focus of this study as well. We hope readers will find original ideas that allow them to improve and advance in their own researches.

scholarly journals Introducing Low-Cost Sensors into the Classroom Settings: Improving the Assessment in Agile Practices with Multimodal Learning Analytics

Sensors ◽  
2019 ◽  
Vol 19 (15) ◽  
pp. 3291 ◽  
Author(s):  
Hector Cornide-Reyes ◽  
René Noël ◽  
Fabián Riquelme ◽  
Matías Gajardo ◽  
Cristian Cechinel ◽  
...  
Keyword(s):  
Low Cost ◽  
Learning Activity ◽  
Attractive Alternative ◽  
Multimodal Learning ◽  
Analysis Techniques ◽  
Core Skills ◽  
Educational Challenges ◽  
Collaboration And Communication ◽  
Multimodal Learning Analytics ◽  
Learning Analysis

Currently, the improvement of core skills appears as one of the most significant educational challenges of this century. However, assessing the development of such skills is still a challenge in real classroom environments. In this context, Multimodal Learning Analysis techniques appear as an attractive alternative to complement the development and evaluation of core skills. This article presents an exploratory study that analyzes the collaboration and communication of students in a Software Engineering course, who perform a learning activity simulating Scrum with Lego® bricks. Data from the Scrum process was captured, and multidirectional microphones were used in the retrospective ceremonies. Social network analysis techniques were applied, and a correlational analysis was carried out with all the registered information. The results obtained allowed the detection of important relationships and characteristics of the collaborative and Non-Collaborative groups, with productivity, effort, and predominant personality styles in the groups. From all the above, we can conclude that the Multimodal Learning Analysis techniques offer considerable feasibilities to support the process of skills development in students.

scholarly journals Detecting Drowsy Learners at the Wheel of e-Learning Platforms with Multimodal Learning Analytics

IEEE Access ◽  
2021 ◽  
pp. 1-1
Author(s):  
Ryosuke Kawamura ◽  
Shizuka Shirai ◽  
Noriko Takemura ◽  
Mehrasa Alizadeh ◽  
Mutlu Cukurova ◽  
...  
Keyword(s):  
Learning Analytics ◽  
Multimodal Learning ◽  
E Learning ◽  
Learning Platforms ◽  
Multimodal Learning Analytics

scholarly journals Multimodal Learning Analytics and Education Data Mining: using computational technologies to measure complex learning tasks

2016 ◽  
Vol 3 (2) ◽  
pp. 220-238 ◽  
Author(s):  
Paulo Blikstein ◽  
Marcelo Worsley
Keyword(s):  
Data Mining ◽  
Learning Analytics ◽  
Online Courses ◽  
Educational Data Mining ◽  
Multimodal Learning ◽  
Learning Tasks ◽  
Education Data ◽  
Multimodal Learning Analytics ◽  
High Degree ◽  
Learning Analysis

New high-frequency multimodal data collection technologies and machine learning analysis techniques could offer new insights into learning, especially when students have the opportunity to generate unique, personalized artifacts, such as computer programs, robots, and solutions engineering challenges. To date most of the work on learning analytics and educational data mining has been focused on online courses and cognitive tutors, both of which provide a high degree of structure to the tasks, and are restricted to interactions that occur in front of a computer screen. In this paper, we argue that multimodal learning analytics can offer new insights into students’ learning trajectories in more complex and open-ended learning environments. We present several examples of this work and its educational application.

scholarly journals Designing Analytics for Collaboration Literacy and Student Empowerment

2021 ◽  
Vol 8 (1) ◽  
pp. 30-48
Author(s):  
Marcelo Worsley ◽  
Khalil Anderson ◽  
Natalie Melo ◽  
JooYoung Jang
Keyword(s):  
Student Perceptions ◽  
21St Century ◽  
Learning Analytics ◽  
Student Empowerment ◽  
Multimodal Learning ◽  
Theoretical Understanding ◽  
Student Collaboration ◽  
Communication Conflict ◽  
Multimodal Learning Analytics ◽  
The Moment

Collaboration has garnered global attention as an important skill for the 21st century. While researchers have been doing work on collaboration for nearly a century, many of the questions that the field is investigating overlook the need for students to learn how to read and respond to different collaborative settings. Existing research focuses on chronicling the various factors that predict the effectiveness of a collaborative experience, or on changing user behaviour in the moment. These are worthwhile research endeavours for developing our theoretical understanding of collaboration. However, there is also a need to centre student perceptions and experiences with collaboration as an important area of inquiry. Based on a survey of 131 university students, we find that student collaboration-related concerns can be represented across seven different categories or dimensions: Climate, Compatibility, Communication, Conflict, Context, Contribution, and Constructive. These categories extend prior research on collaboration and can help the field ensure that future collaboration analytics tools are designed to support the ways that students think about and utilize collaboration. Finally, we describe our instantiation of many of these dimensions in our collaborative analytics tool, BLINC, and suggest that these seven dimensions can be instructive for re-orienting the Multimodal Learning Analytics (MMLA) and collaboration analytics communities.

scholarly journals Preface

2021 ◽  
Vol 2125 (1) ◽  
pp. 011001
Keyword(s):  
High Performance ◽  
Direct Reduction ◽  
Low Cost ◽  
Committee Member ◽  
Scientific Information ◽  
Main Research ◽  
University Of Technology ◽  
The World ◽  
Oral Presentations ◽  
The Impact

We are glad to introduce you that the 2021 4th International Conference on Mechanical, Electrical and Material Application (MEMA 2021) was successfully held on October 29-31, 2021. In light of worldwide travel restriction and the impact of COVID-19, MEMA 2021 was carried out in the form of virtual conference to avoid personnel gatherings. Because most participants were still highly enthusiastic about participating in this conference, we chose to carry out MEMA 2021 via online platform according to the original schedule instead of postponing it. MEMA 2021 is to bring together innovative academics and industrial experts in the field of Mechanical, Electrical and Material Application to a common forum. The primary goal of the conference is to promote research and developmental activities in Mechanical, Electrical and Material Application and another goal is to promote scientific information interchange between researchers, developers, engineers, students, and practitioners working all around the world. The conference will be held every year to make it an ideal platform for people to share views and experiences in Mechanical, Electrical and Material Application and related areas. We were greatly honored to invited Prof. Kun Li, from Chongqing University, China and Assoc. Prof. Wei Wei, from Xi’an University of Technology, China as our Conference Chairmen. This scientific event brings together more than 100 national and international researchers in mechanical, electrical and material application. During the conference, the conference model was divided into three sessions, including oral presentations, keynote speeches, and online Q&A discussion. In the first part, some scholars, whose submissions were selected as the excellent papers, were given about 5-10 minutes to perform their oral presentations one by one. Then in the second part, keynote speakers were each allocated 30-45 minutes to hold their speeches. We were pleased to invite four distinguished experts to present their insightful speeches. Our first keynote speaker, Prof. Shahid Hussain, Jiangsu University, China. His research interests include MOS-MOF-MXene Nanomaterials, Gas-Sensors, Electrochemical Supercapacitors, Li-S batteries. And then we had Prof. Jie Huang, from Southwest University, China. His research includes RF/Microwave circuits and sensors. Prof. Qiyan Xu, Anhui University of Technology, China. His main research directions are: New process and technology of low cost steel making, Direct reduction and melting reduction, Development of new metallurgical technology - comprehensive utilization of waste resources. Lastly, we were glad to invite Prof. Kun Li, Chongqing University, China. He mainly engaged in additive manufacturing, intelligent 3D net forming, high performance materials and phase transformation, material computing and other research. In the last part of the conference, all participants were invited to join in a WeChat group to discuss and explore the academic issues after the presentations. The online discussion was lasted for about 30-60 minutes. We are glad to share with you that we still received lots of submissions from the conference during this special period. Hence, we selected a bunch of high-quality papers and compiled them into the proceedings after rigorously reviewed them. These papers feature following topics but are not limited to: Mechanical Dynamics and its Applications, Material Physics, Electrical and Electronic Systems and other related topics. All the papers have been through rigorous review and process to meet the requirements of International publication standard. Lastly, we would like to express our sincere gratitude to the Chairman, the distinguished keynote speakers, as well as all the participants. We also want to thank the publisher for publishing the proceedings. May the readers could enjoy the gain some valuable knowledge from the proceedings. We are expecting more and more experts and scholars from all over the world to join this international event next year. The Committee of MEMA 2021 List of Committee member is available in this pdf.

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