Learning outcomes were designed based on the guideline provided by the ABET for Engineering Programs 2017-2018 as follows:
b) An ability to design and conduct experiments, as well as to analyze and interpret data.
c) An ability to design a system, component, or process to meet desired needs within realistic constraints such as economic, environmental, social, political, ethical, health and safety, manufacturability, and sustainability.
g) An ability to communicate effectively.
i) A recognition of the need for, and an ability to engage in life-long learning.
k) An ability to use the techniques, skills, and modern engineering tools necessary for engineering practice
To let students understand the relationship between physical phenomena and acquired data, MATLAB Mobile eases how movement data can be gathered and imported into MATLAB computing environment. Then, MATLAB provides many tools to assist students to work on their collected data.

This 3rd-year course is taken by more than 30 students as the required laboratory course of the Electrical Engineering curriculum. Due to the campus closure policy regarding to the COVID-19, all laboratory practices must be carried out as online education. At first, MATLAB programming tutorials with MATLAB grader assignments are provided to facilitate required MATLAB skills. Then, students will learn how to use MATLAB, MATLAB Mobile and smartphone to practice modern engineering skills including data acquisition, data visualization, data analysis and application development.

There are 3 learning activities in the course. First activity is to learn MATLAB programming based on data analysis problems. MATLAB grader assignments are provided to evaluate their understandings. The second activity is to practice data acquisition and analysis using MATLAB, MATLAB Mobile, and smartphone. The third activity is to assess students' knowledge and skills by asking them to implement their own project using sensors and methods not used in the laboratory practice.

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Electricity consumption as real-world data is used as the topic for students to practice data importing, processing and analysis.

Provenance: Supachai Vorapojpisut, Thammasat University
Reuse: This item is offered under a Creative Commons Attribution-NonCommercial-ShareAlike license http://creativecommons.org/licenses/by-nc-sa/3.0/ You may reuse this item for non-commercial purposes as long as you provide attribution and offer any derivative works under a similar license.

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MATLAB Grader provides a convenient way for students to test their works and also teacher to handle a programming class with a lot of students.

Provenance: Supachai Vorapojpisut, Thammasat University
Reuse: This item is offered under a Creative Commons Attribution-NonCommercial-ShareAlike license http://creativecommons.org/licenses/by-nc-sa/3.0/ You may reuse this item for non-commercial purposes as long as you provide attribution and offer any derivative works under a similar license.

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Labsheet is given to students that start with objective of learning and also scope of problems.

Provenance: Supachai Vorapojpisut, Thammasat University
Reuse: This item is offered under a Creative Commons Attribution-NonCommercial-ShareAlike license http://creativecommons.org/licenses/by-nc-sa/3.0/ You may reuse this item for non-commercial purposes as long as you provide attribution and offer any derivative works under a similar license.

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MATLAB code is provided for students to practice data acquisition from physical phenomena.

Provenance: Supachai Vorapojpisut, Thammasat University
Reuse: This item is offered under a Creative Commons Attribution-NonCommercial-ShareAlike license http://creativecommons.org/licenses/by-nc-sa/3.0/ You may reuse this item for non-commercial purposes as long as you provide attribution and offer any derivative works under a similar license.

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Students will practice AppDesigner to build a GUI application to ease their data-related works.

Provenance: Supachai Vorapojpisut, Thammasat University
Reuse: This item is offered under a Creative Commons Attribution-NonCommercial-ShareAlike license http://creativecommons.org/licenses/by-nc-sa/3.0/ You may reuse this item for non-commercial purposes as long as you provide attribution and offer any derivative works under a similar license.

Doing experiments with MATLAB Mobile and smartphone is efficient since sensor data is acquired in real time. Further data processing and visualization are also smooth since sensor data is updated to MATLAB variables seamlessly. Compared to microcontroller-based courses with environmental sensors, students were better to explain experiments based on environmental data compared to movement data from smartphone-based experiments. This issue is caused by the dimensions of each motion sensor (3 axes) and the number of converted views (absolute, gravity removal).

The assessment of learning outcomes were performed both during and after class. The in-class assessment considered the time spent to complete the data acquisition experiment and their explanation after completion. The post-assessment considered the submitted report whether the experiment was performed according to the given problem or not.

Online resources for motion data processing
1. Accelerometer calibration
https://www.st.com/resource/en/application_note/dm00119044-parameters-and-calibration-of-a-lowg-3axis-accelerometer-stmicroelectronics.pdf
2. Sensor Data Collection with MATLAB Mobile or MATLAB Online
https://www.mathworks.com/help/matlabmobile_android/ug/sensor-data-collection-with-matlab-mobile.html
3. Using accelerometer
https://developer.android.com/guide/topics/sensors/sensors_motion#sensors-motion-accel

Links to some student final projects
1. jumping burn calculator
https://www.youtube.com/watch?v=J-JXh48iuP0&list=PLRFmzqwcJPyXuxYTZrWcasiAAQ2X2pngj&index=6
2. activity classifier
https://www.youtube.com/watch?v=lsa4Nw13iZY&list=PLRFmzqwcJPyXuxYTZrWcasiAAQ2X2pngj&index=4