Evidence Bundle from QTS initial teacher training course 2020-2021. The bundle is a computer science evidence bundle and focuses on the teaching of 6 lessons from a self made problem solving scheme of work.
This is the third lesson in the problem-solving module. Learners will continue to learn about the cornerstones of computational thinking and this week will focus on the concept of pattern recognition. Learners will learn that pattern recognition is the ability to use past experiences and patterns to predict solutions to problems. By the end of this lesson, learners will have had the chance the demonstrate patter recognition skills be solving mathematical sequences and sudoku puzzles. Through this, learners will use what they have learnt about in previous to decompose and abstract problems before applying the skill of pattern recognition to the problems.
This is the second lesson in the problem-solving module. This lesson learners will begin to delve into the term computational thinking. Learners will learn about two of the four cornerstones of computational thinking: abstraction and decomposition. Learners will learn about what the two terms mean and will also look at real life examples of where abstraction and decomposition have been used. Learners will practice solving problems through abstraction and decomposition. This lesson will lead onto the cornerstone of pattern recognition. Learners will complete tasks by ignoring irrelevant details and just focusing on important information and by breaking problems down into smaller more manageable steps.
This is the first lesson in the Problem Solving module. The module will enable learners to develop their problem-solving skills and logical thinking skills. Within this lesson, learners will begin to learn about what constitutes a problem, how we can solve problems, the characteristics of problems, and the different problem conditions. Learners will learn about the three states of a problem which include the initial state, intermediate state, and goal state. Learners will begin their journey of becoming effective problem solvers and will develop an understanding of how to recognise constraints which impede goals, creating the concept of a problem in the first place. Students will practice solving problems and will develop an understanding of key terms related to problem solving.
This scheme of work includes 6 lessons focusing on introducing students to the art of problem solving. Lessons offer the chance for students to move away from computers and learn important computational logic skills in real world situations which do not involve the use of computers. Students are introduced to concepts such as abstraction, decomposition, pattern recognition, memory, and problem characteristics. Lessons have proven to be engaging and innovative with several cross-curricular links. Lessons can also be easily adapted to suit your own classes and teaching style.
A resource workbook enabling students to create a car racing game in Scratch. The task is decomposed into individual steps with images and clear labels to enable students to successful work towards creating their own Scratch projects.
Car or Cup Program-
This workbook will teach you how to create an AI program is Scratch. The program will sort photos and you will train the computer to sort photos into a pile of cups and a pile of cars.
Can you drive yet?
We have now had an introduction into sequencing and how to practice sequencing in Scratch. We need to now introduce the concept of decision making!
Decision making is the process which involves choosing between multiple different solutions to solve a problem.
Today we are going to introduce comparison blocks to create a program which uses user input to decide whether you can drive or not yet! The program will ask the user their age, followed by if they can drive yet. If the user can drive, the sprite will drive away. If not, the sprite will not drive.
This is the sixth and final lesson within the problem-solving module. Throughout the module, students have developed an understanding of what problem solving is and how, as computer scientists, we can become effective problem solvers. Learners have developed a knowledge bank of key terms and have focused on some key aspects of the foundations of problem solving. Not only will this module prepare students for IT modules such as programming projects, but it will also aid students in developing as self-regulative learners within their future academic studies. This lesson will complete the series of six lessons, and will briefly focus on chunking, knowledge, and complex problems such as Einstein’s Riddle. Learners will learn about what knowledge is, how knowledge is useful, and what chunking is. Following this, I will model and demonstrate how we can use logic and the skills which we have learnt over the last six lessons to solve complex problems such as Einstein’s Riddle. After this, learners will have the opportunity to choose and complete one of three problems similar to Einstein’s Riddle. The riddles have been split into three relating to learning pathways (core, proficient, exceptional). Learners will choose one to suit their ability level.
This is the fifth lesson within the problem-solving module. Learners have so far covered the cornerstones of computational thinking and how the skills such as abstraction, decomposition, and pattern recognition can be used within the solving of problems. Learners have also looked at codebreaking and how problem solving can be used to encrypt and decrypt information. Within this lesson, learners will look at short-term and long-term memory. By the end of the lesson, learners will be able to identify the differences between short and long-term memory, as well as example of repeated exposure can be used to solidify information within their memory. Students will practice different brain training memory activities, to demonstrate how they use logic and problem-solving skills to transfer information from their working memory to their short-term and long-term memory. As an extension, students will link this to the three states of a problem. Learners will also continue to build up their knowledge of the key terms relating to problem-solving.
This is the fourth lesson in the problem-solving module. Learners have so far looked at the cornerstones of computational thinking and have practiced abstracting, decomposing, and using pattern recognition to solve problems. This lesson will enable learners’ practice to their codebreaking skills. Learners will learn about how codebreaking links in with the art of problem-solving. Learners will look at the history of codebreaking and how Julius Caesar exampled it. Learners will practice codebreaking using a shift key. Learners will demonstrate encryption and decryption of Caesar Ciphers before moving on to learn about how logic can be used to decrypt codes without a key. Learners will be demonstrated two methods of logical decryption- cipher wheels and relative letter frequency. Learners will have the opportunity to practice these codebreaking skills with the extension of creating their own ciphers for their peers to solve.