DEC Scan Journal : Volume 36 Issue 1
2017 Volume 36, Issue 1 38 Contents Editorial Learning & teaching Research Share this Resource reviews Extended abstract The learner now generalises the structures to take in new and more abstract features, representing a new and higher mode of operation (Biggs & Collis, 1991, p. 65). Implicit in the SOLO model is a set of criteria for evaluating the quality of a response to (or outcome of) a task. The quality (or richness or complexity) of a response to a complex task varies with the relevance of the considerations brought to bear on the task, the range or plurality of those considerations, and the extent to which these considerations are integrated into a whole, and extended into broader contexts to create something new. An alternative taxonomy or framework to SOLO was developed by Benjamin Bloom and colleagues in 1956 (Bloom & Krathwohl, 1956). Bloom’s original taxonomy was organised around six broad Levels: Knowledge; Comprehension; Application; Analysis; Synthesis and Evaluation. Bloom’s revised taxonomy is also organised around six levels: Remember; Understand; Apply; Analyse; Evaluate and Create (Anderson, 2001). The SOLO framework can be used to assess the quality of a performance in a task involving computational thinking. It can be used to assess the quality of an individual performance, the performance of a group working collaboratively on a task, and the contribution of an individual to a group performance. SOLO can be used to design learning and assessment tasks and sequencing of learning tasks from simpler to more complex. Most crucially, SOLO can be used to document a learning journey – identifying where a learner has been, where they are now, and where they might go next, as the examples below illustrate. Examples of learning/assessment task design We now consider a number of task designs to cultivate and assess computational thinking. TangibleK Bers (2010) notes that robotics provides opportunities for young children to learn about mechanics, sensors, motors, programming, and the digital domain. The approach invites young children to build their own robotic projects, such as cars that follow a light, or puppets that can play music (Bers, 2010, pp.1-2). TangibleK involves children making robotic artefacts and programming their behaviours. Children are required to keep design journals while creating robots. This helps make visible to the children, their teachers and parents their own thinking and their learning over time (Bers, 2010, p. 6). TangibleK consists of seven sessions. 1. What Is a Robot? After an introduction to robotics by looking at different robots and talking about the functions they serve, children build their own robotic vehicles and explore the parts and instructions they can use to program them. 2. Sturdy building: Children build a nonrobotic vehicle to take small toy people from home to school. The vehicle needs to be sturdy and able to perform its intended functions. Design journals: Children will use the design journals to learn the engineering design process. 3. The Hokey-Pokey: Choose the appropriate commands and put them in order to program a robot to dance the Hokey-Pokey. 4. Again and Again until I Say When: Students use a pair of loop blocks (‘repeat’/’end repeat’) to make the robot go forward again and again, infinitely, and then just the right number of times to arrive at a fixed location. 5. Through the Tunnel: Children use light sensors and commands to program a robot to turn its lights on when its surroundings are dark and vice versa. 6. The Robot Decides: Students program their robots to travel to one of two destinations based on light or touch sensor information.
Volume 35 Issue 4
Volume 36 Issue 2