Sunday, 9 August 2015

Data representation unplugged - continued

This week I had an email around last weeks Data Representation work. In the email there were a few comments that I found rather interesting. I include part of it below. The whole entire focus is one around assessment, at the junior level. I must say I read this 5 times trying to understand why? Why the subject requiring 32 credits per semester? Why the assessment driven curriculum?
To be clear, the following is not the school that I work at, we work towards Learning Objectives based on our Learning Design Model and NZC 2007, we report on curriculum level and progression, based upon rubrics.
We have a junior diploma which is all about credits, each subject does 32 credits per semester.  If an assessment is worth say 12 credits, they'll get 12 credits for getting excellence, 9 for merit and 6 for achieved or something like that.  Then students get A/M/E for their junior diploma overall based on how many credits they got out of credits available.
IMHO it's awful because our junior curriculum is assessment driven.  Sure we get to decide on the topics and how the assessments work, but once that has been done we still get stuck having to balance covering what's needed for the assessment, and trying to make it catered to their interests.  See, we decide on the topics before we meet our classes and then we're locked in, there's not much room for "Hey you guys are fully interested in binary, let's spend a week on data representation (and make some movies like Gerard's class did" because we have to give them a decent shot at their assessments.
To be clear, a week in my classroom for this module, is one and a half hours on a Thursday. As part of our SPIN, Special Interest Module. I include the following on what is being covered.

The work I am developing towards is Technological Systems under the Technology Curriculum, The work you saw as part of the videos and page was on part of the Computer Science module that runs over 13.5 hours

I am using the basis of the computer science badges that the University of Canterbury, Computer Science Education Department developed. 
Students will then work through algorithms and finish off with HCI.

Data Representation

The core concept of this topic is the binary digit, which is the basis of all data storage and transmission on digital computers. Students should be familiar with the role of a bit, combinations of bits (such as a byte), and their use to represent numbers, characters and images. This work does not include compressed representations (e.g. mp3, jpeg).

For a student to be successful they need to :

Demonstrate the ability to work with binary and hexadecmimal numbers by showing how to:
  • manually convert between binary and decimal for numbers up to 8 bits.
  • Demonstrate the ability to manually convert between hexadecimal and binary for arbitrary numbers, and to convert between hexadecimal and decimal for numbers up to 255.
  • Demonstrate how to count and add in binary.
  • Explain how an 8-bit characters are typically stored on a computer.
  • Explain a system for representing colours with numbers. This might be one of:
    • Web page colour specification (6-digit hex values)
    • Colour picker in publishing software that allows RGB or HSV values to be chosen as three numbers
    • Photo processing software that gives the RGB or HSV value of chosen pixels
Demonstrate a data representation that has a choice of bit sizes, and explain the significance of the different representations. Examples that could be used include:
  • 8-bit and 16-bit characters
  • 24-bit and 8-bit colour
  • Other Examples could include:
    • 16-bit and 8-bit sound files
    • 56-bit and 128-bit encryption
    • IPv4 and IPv6 addresses
    • MAC addresses using MAC-48, EUI-48, and EUI-64
    • MIDI representation of notes, patch numbers and channels
Convey the concepts of data representation to someone who doesn't know about the topic. This might be:
  • A short video suitable for non-experts explaining a key aspect of the topic
  • Introducing it effectively to someone who is considering doing the module themselves
  • Creating effective quiz questions (e.g. in Peerwise)
The work they did last week in their second class was conveying a concept of data representation suitable for a non expert.

No comments: