Teaching Online and Auto-grading with MATLAB

Are you having difficulty in learning and teaching MATLAB according to the current situation?

We provide you distance learning solutions.

As many universities are moving to distance learning due to the ongoing COVID-19 situation, it is vital for educators to think carefully about how to adapt their approach to still deliver key learning outcomes for students in an online setting. Ascendas Systems is at the forefront of supporting universities as we are transiting to distance learning. We are more than glad to partner with educators to support them in achieving their goals for teaching and learning.

 

Session #1: Online Teaching & Auto-Grading with MATLAB for Engineering & Science Faculty

20 May 21 | 09:00-12:00 (GMT+7) | Via Zoom

Agenda

09.00 – 09.30 AM E-Learning with MATLAB, How does it work?
09.30 – 10.00 AM What's MATLAB Grader?
10.00 – 10.15 AM
Break
10.15 – 11.00 AM
[Engineering] Online Teaching & Auto-Grading with MATLAB
11.00 – 11.45 AM
[Science] Online Teaching & Auto-Grading with MATLAB
11.45 – 12.00 PM Q&A

 

In this live webinar, we will address some of the frequently asked questions that educators have been asking us and discuss resources as well as approaches to support them.

  • How to keep my students engaged and introduce projects in an online setting?
  • How to provide individualized student feedback in a scalable way?
  • How to ensure that my students can remotely access course material?
  • How to ensure that my students, co-instructors, and I have access to MATLAB?
  • What other resources does MathWorks provide to support online teaching. 

Session #2: Online Teaching & Auto-Grading with MATLAB for Medical & Finance Faculty

21 May 21 | 09:00-12:00 | Via Zoom

Agenda

09.00 – 09.30 AM E-Learning with MATLAB, How does it work?
09.30 – 10.00AM What's MATLAB Grader?
10.00– 10.15 AM
Break
10.15 – 11.00 AM
[Medical] Online Teaching & Auto-Grading with MATLAB
11.00 – 11.45 AM
[Finance] Online Teaching & Auto-Grading with MATLAB
11.45 – 12.00 PM Q & A

 

Create auto-graded MATLAB® assignments using MATLAB Grader. Build MATLAB coding problems and store them in collections. Host courses for students on MATLAB Grader, or include MATLAB based assignments in your Learning Management System based course.

  • Auto-graded student solutions with custom scoring rubrics
    • Options for both pass/fail and weighted grading.
    • See details about concepts where students are struggling.
    • Students receive real-time, contextual feedback on their solutions.
  • Individual and aggregate student performance analytics
    • Solution maps show size, time of arrival, and distance from the reference solution.
    • Includes a complete history of students’ attempts to find the correct solution.
    • Student outcomes are available to both instructors and authorized teaching assistants.
  • A library of reusable example courses and assignments
    • Templates of common assessment types for both script and function-based problems
    • Examples include advanced assessment scenarios such as randomized input parameters and creating custom assessments.
    • Ability to add examples to your existing course with a single click and modify them to match your topic.

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Presenters

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Supamith Sutharojana

Application Engineer Team

Lead at Ascendas Systems

 

He specializes in the areas of Model-Based Design and Auto Code Generation with MATLAB/Simulink. He holds a bachelor’s degree from Chulalongkorn University major in Automotive Engineering. Before joining Ascendas Systems, he was an Engine Software Designer at Toyota Daihatsu Engineering & Manufacturing working in Engine Calibration and Engine software development field.

Kantika-AE-TH

 

Kantika Wongkasem

Application Engineer

Ascendas Systems

 

She specializes in the areas of Image processing and Convolution neural network are a subset of machine learning, and they are at the heart of deep learning algorithms. Kantika received her a bachelor’s degree from King Mongkut’s Institute of Technology Ladkrabang with senior project Sign Language Detection use webcam camera to study image processing and learning algorithms with MATLAB. and now studying Master degree in Engineering Technology at Thai-Nichi Institute of Technology with research image processing analysis application in the animal industry