Building an Application to Track Psychomotor Skills with Wearable Sensors

Building an Application to Track Psychomotor Skills with Wearable Sensors

Tuesday 06/06 14:00-15:30h

Workshop Space B

Abstract

The participants can expect to learn at the workshop how to build a scalable mobile application that uses wearable sensors to collect data for a psychomotor skill. They will especially learn about the architecture of the application. More specifically how tasks are distributed between frontend and backend such as the collection and analysis of data with e.g. Machine Learning. Further the participants can expect to learn about sensor data and how it can be analyzed with e.g. Machine Learning. As a consequence, the participants will also experience how feedback can be visualized. Ultimately, participants have the chance to try out the prototype and discuss in groups what is good about the prototype and how it could be improved for psychomotor skill learning.

Needs Analysis

The workshop should be run because it is about building a scalable mobile application that uses wearable sensors to collect data for a psychomotor skill. The collected data is analyzed with e.g. Machine Learning Algorithms to provide the learner with feedback. Displaying feedback to the user is also part of the workshop. The workshop will satisfy the needs of PhD candidates in TEL who are interested in building scalable mobile applications, using wearable sensors, applying Machine Learning, or giving feedback for psychomotor skill learning. The topic of the workshop is relevant and fits TEL/ EdTech because it covers topics such as Artificial Intelligence in Education, Wearable Enhanced Learning, Smart/ Intelligent Learning Environments, Intelligent Tutoring, and Sensors/ Multimodal Learning Analytics. The content can help PhD candidates in their own projects.

Learning Objectives

The participants will learn how to build a scalable mobile application, how wearable sensors can be used to collect data for a psychomotor skill, how to analyze the data and how to get feedback for the learner. Further, participants will learn how machine learning can be used for data analysis. The participants can experience a prototype of the application, wear wearable sensors, and get insights on a specific psychomotor skill. Outcomes are experiencing a prototype application and learning about the aforementioned elements to build a mobile application that uses wearable sensors to collect data and give feedback to the learner.

Pre-activities

None.

Session Description

30 min presentation: Building Scalable Mobile Application, Pros/Cons using Wearable Sensors, How can Human Action Recognition help understanding psychomotor skills?
30 min testing: participants can test the prototype
30 min group work: group discussion about the prototype and what can be improved