DT Hub releases new AI Course

In time for the new school year, the Digital Technologies Hub released a brand-new free AI course for teachers. We are pleased to disclose that the Digital Technologies Institute played a significant role in the design and creation of this course, and we want to share the news about this fantastic new resource.

Martin Richards, content manager at the DT Hub, is the driving force behind this course; working with him was an absolute joy and pleasure. Martin started creating AI resources, lesson plans and webinars about five years ago, long before AI rose to prominence in the education community. Now that is foresight!

The DT Hub has a dedicated page on AI, which illustrates AI's increasing importance and prominence in education. Head over to https://www.digitaltechnologieshub.edu.au/ai/, and you will see the DT Hub's AI Classroom resources and the professional learning section:

Under Professional learning, click on 'AI course'.

The course consists of seven modules, which span AI introduction, the AI learning process, AI and programming (primary and secondary), AI applications, ethical aspects, and how an AI learns and functions inside.

The modules are bite-sized and designed to be easily and quickly consumed by teachers in preparation for their own AI teaching in the classroom. It isn't necessary to do all the modules to teach AI, so the modules stand independently. However, I would recommend doing the first module, 'Artificial intelligence: What’s it about?' first. It gives a great overview of the field and introduces the related terminology. It also touches on Generative AI and explains that the underlying technology of Artificial Neural Networks is so important to know about.

What I like about the course is that it has just about the right length of instructions, interleaved with videos, short callbacks, and reflection activities. There are also unplugged resources that teachers can download, such as an AI card activity.

The course interweaves with our MyComputerBrain AI, which provides several animations and deep dives, particularly in the final module about the Inner workings of AI.

It has never been easier to get started teaching AI in the classroom, so don't wait to head over to https://www.digitaltechnologieshub.edu.au/ai/professional-learning/ai-course/ and https://mycomputerbrain.net

Yours,

Dr. Karsten Schulz

CreativITy 2022 – Gateways to the Future – Register Now

Kelvin Grove State College in Brisbane is hosting the 2022 Queensland Society for IT in Education State Conference this year. The event runs during the upcoming school holidays on Sept 19+20. Check out this website, which contains all the details of the two days Digital Tech + Digital Literacy conference, including keynote speakers, workshops, presentations, and the conference dinner.

With many tried and tested classroom activities, the Digital Technologies Institute will hold a two-hour workshop to get teachers started with Artificial Intelligence In the classroom. AI is easier than you think, so come and give it a go. In addition, there will be many more workshops on topics such as: Robotics programming using Python;

• eSports - Creating an eSports curriculum plan;

• Demystifying Arduinos: Simple Classroom Activities;

• Robotics programming usingBlocks;

• PHP / MySQL for Digital Solutions IA2 and IA3;

• Taking your classroom robotics to international RoboRave robot competition;

• Python game design on PyGamer for DigitalTechnologies V9 curriculum;

• Robotics programming using Blocks

Visit the website for all the details, or contact the fantastic Lyn Allsop at office@qsite.edu.au for further information.

Artificial Intelligence Science Lab

The collection, representation and interpretation of data are everyday tasks for students of all ages. The science subjects are a rich source of data, whether students measure plant growth in biology, the time it takes for a chemical reaction to occur in Chemistry, or how far a projectile will fly in physics.

Common to these and many other experiments is that we want students to understand the data based on their interpretation of input-output relations and whether these relations are simply linear or more complex.

Those of us with experience in the matter can often tell by just looking at the charts how these relations are. But learners who take their first steps in data science often struggle. This is particularly true when multiple variables affect the outcome.

Artificial Intelligence is particularly suitable for looking at datasets and learning the relations between input variables and outputs. Because programming can get in the way when dealing with AI libraries, we have made a simple toolkit that students can use without writing code. We call it the AI Science Lab. The code-freeness makes the lab suitable for all students who understand what a table is.

Let's take a look:

Students enter the data from their science experiments in the table on the left-hand side. As they enter it, the data gets plotted in the charts. At the top of the screen is a simple deep-learning artificial neural network. Students scroll through the data with the input sliders. The instructions on the right-hand side menu help students to navigate.

The input table allows students to enter records, rename the columns, de-select them if their experiment has fewer than three input variables, etc. In addition, students can store their data on the server to avoid losing it between lessons.

Training the AI:

When the data has been entered, the real fun begins. By clicking on the Start learning button at the bottom of the screen, the AI starts to learn about the data.

First, it tries to recreate the relations between inputs and output. Red lines on the chart appear to inform the trends that the AI sees in the data.

Is the output growing with the input? Is it shrinking? How much growth is there? The red curves provide important cues concerning the nature of the relationship between input and output.

Using the AI Model

Students use the input sliders to test their model once the training process is complete (or stopped manually). Then, they compare the calculated output from the AI against the results they would expect. The AI Science Lab supports both interpolation and extrapolation to explore data areas between our outside the records students collected previously.

In Summary

You find the AI Science Lab directly here of by navigating from the My Computer Brain Website to the Artificial Intelligence (Secondary+Tertiary) course. Look out for the yellow robot. Teacher accounts are free and student accounts are very reasonably priced. Check out the getting started blog post.

The AI Science Lab is the last activity in the AI course.

We hope you and your students like the new Lab. Please ping us if we can be of any help !