Welcome to 2013EDN Technologies Education. This course has been designed to help you achieve the course aims and objectives:
Dr Jason Zagami
This week we are introducing the Technologies Learning Area and the nature of technologies education.
First and foremost, the Technologies Learning Area is about teaching students to think in ways they will not learn in other learning areas.
Students will learn how to think about problems as the interaction of systems, using Systems Thinking as a process for understanding how things, regarded as systems, influence one another within a whole. In nature, systems thinking examples include ecosystems in which various elements such as air, water, plants, and animals work together to survive or perish. In organisations, such as schools or classrooms, systems consist of people, structures, and processes that work together to make an organisation "healthy" or "unhealthy".
Students will learn how to think about problems from the perspective of a designer, using design thinking as strategies for understanding design needs and opportunities, visualising and generating creative and innovative ideas, planning, and analysing and evaluating those ideas that best meet the criteria for success.
Students will learn how to think about problems from the perspective of a computer scientists, using computational thinking as a problem-solving method to create solutions that can be implemented using digital technologies. This will involve integrating strategies, such as organising data logically, breaking down problems into parts, interpreting patterns and models and designing and implementing algorithms.
Within these contexts, there are specific content that you will need to teach, the Australian Curriculum website describes these in detail, but in summary you will teach students about:
Technologies contexts: technologies and design across a range of technologies contexts.
Digital systems: the components of digital systems: hardware, software and networks and their use.
Representation of data: how data are represented and structured symbolically.
In addition to specific content, you will also need to teach your students how to do things, and in particular how to use a project based approach to solving problems.
The Australian Curriculum website is your primary resource when planning how to teach and you will need to become very familiar with the Technologies section for this course. In particular you need to understand the Rationale, Aims, and Content Elaborations, these provide good examples for your own unit planning and activities to do with your students.
Details of assessment can be found on the Learning@Griffith website under Assessment.
Of particular note is that some assessment occurs during tutorials in Weeks 2, 4 and 6.
Discussion: What is technology? what is not technology? why is it important to study?
Discussion: What were your experiences of technology in primary school?
Discussion: What is Digital Technology Education? What is Design Technologies Education?
Demonstration: MakeyMakey video and demo
Discussion: What sort of projects could use the MakeyMakey to address the D&T and DT curriculum?
Discussion: What other sorts of activities could be included in Technology Education?
Discussion: What will be your challenges in learning how to teach the Technologies learning area
Discussion: What do you hope that will this course teach you?
Discussion: How will we assess your learning?
This activity builds off of the classic game of Rock/Paper/Scissors, known to most students and also related to a phenomenon seen in biology. In the off-line activity students play two rounds of the game with different rules in each round. After debriefing the game, the outcomes will be discussed in the context of computer modelling by viewing a model that uses the same rules. This is followed by a brief decoding of the computer program to learn computer science concepts.
Stickers or cards- 3 colours for all participants (to represent rocks, papers and scissors
Part 1 - (approx. 5 minutes) Assign each student a “breed” of rock, paper, or scissors, making the groups as equal as possible. Have each student choose a classmate at random and play one round of the game (paper covers rock, rock crushes scissors, scissors cut paper). Have each student who loses the first round sit down, and the remaining students continue to play until a single student is left standing. Play again (with students reassigned in equal groups), and encourage students to choose partners at random. If there are enough students and the groups are roughly equal, the “winner” should not be predictable. Change of rules: Have students play where the loser of each round changes to the winner’s breed for the next round. For example, in a match between paper and scissors, the student who was paper ‘loses’ and becomes a scissor (and the student who was scissors stays a scissor). Both play round 2 as scissors. To identify the breeds, you can have participants wear coloured hats, display a sticker or card. Continue to play until one breed wins (or is in a large majority) – again, with a large enough group, the winning breed should not be predictable.
Debriefing the Game:
• What did you observe while playing the game?
• Were you able to predict who would win the game? Why or why not?
• Who thinks someone in the group didn’t follow the rules during the game?
http://www.slnova.org/GUTS/projects/9434/ for the computer model. Click ‘View Code’ button on right side. Scroll down to see the green Spaceland where the action will happen. Show the model:
1. Click the Setup button
2. Click the Forever button to watch the action.
3. Take note of the data boxes counting the populations as well as the graph.
4. Run the model multiple times and have students take note of the outcomes.
5. Can students predict the winning group?
Discuss computer modelling with students -
• What are the benefits of creating a computer model of the game we just played? (Answers could include: all agents will follow the rules (i.e. no cheating), can play over and over again quickly, agents don’t only follow their friends the way students might.)
• What can we do with a model that is impossible in the real world? (Answers could include: larger number of agents, fast collection of data.)
• What are the limits or assumptions behind such a model? (Answers could include: agents all move the same way (step size, angle of turning), equal probability of interactions between agents (no clumping of breeds).)
Part 3 - Decoding the computer model (approx. 5 minutes). Have students work in small groups to look at the code and verbalise how the computer program works in StarLogo Nova. This can also be done as a large group with the code blocks projected on a screen. Below are the code blocks for the computer model made in the programming language StarLogo Nova.
This set of blocks gets executed when the user presses the Setup button in the Spaceland area. It create 30 of each of the rock, paper and scissor agents and gives them specific colors and scatters them to random positions on the green Spaceland. (click on the image to enlarge it)
These blocks define the movement procedure called ‘wiggle.’ The random blocks allows for the unpredictable movement of the agents (in this case, rock agents, paper agents and scissor agents)
Collision blocks are used for agent-to-agent interactions. In this case, when the rock agent collides with a scissor agent, the rock ‘wins.’ In this case it means that the scissor agent is deleted and a rock agent is created to replace it. The new rock agent is separated from where the scissor agent was by the command ‘forward 3.’
Rock-paper-scissors may be common in many ecosystems, such as coral reefs, where scientists first observed the dynamic. The strategy of producing toxins to kill or slow the growth of a competitor is called allelopathy. It occurs in many plants, marine invertebrates, fungi and essentially every major bacterial group. The toxins that one population of bacteria uses to poison others are exploited in medicine as antibiotics.