#EL30 Two tasks

This week’s task is to install IPFS

and to create a content addressed resource. Here it is:

https://ipfs.io/ipfs/QmcJC9phgw2kkNuEmtBYHgvByAAZrP3wnGDkppm2KjuRZA

This week’s topic is resources, and this fits well to Jenny’s task for us, about Jupyter.

There are so many discussions and efforts about the logistical and legal frameworks of educational resources and the technological changes of these frameworks. So one might be frustrated that there is so little about new technological affordances of the resources themselves. Dominant theory, for example “Split Attention Effect” (from Cognitive Load Theory) is still mainly drawing upon the paper age where interactive resources were unknown. So it is refreshing that this course covered an interactive resource called Jupyter notebooks.

And Jenny’s task wants us to

“Explain your understanding of the Jupyter Notebook for four different people, none of whom have heard of Jupyter Notebooks before:

• A 10 year old child
• A 15 year old secondary school pupil
• An undergraduate trainee teacher, specialising in Art
• A University Lecturer working in the Educational Research Department”

So here is my attempt. (Disclaimer: I am not an educator!)

10 year old: Suppose you have a new cooking robot. And you have alien ingredients that you have never tasted before, and you don’t know any recipe about them. The robot understands written orders and it will quickly execute each step for you. If the result is not tasty, you can start over and modify your orders; the robot will patiently execute each step again if you tell it to do so. A Jupyter notebook contains all these orders, and a “Run” button for each step. Just too sad that the result is only on the screen and not edible.

15 year old: Same as above, but with data for a diagram instead of ingredients for a meal. If the pupil’s basic IT training has already covered databases (? I hope so), the ingredients are ‘JOINed’ rather than just mixed, and the orders to be modified will particularly be about ‘parameters’ to be varied.

The arts teacher-to-be: Same as above, but with a sculpture instead of a meal. And with additional explaining: Why does the robot have a command line interface, rather than visual user controls where I immediately see the effects (‘what you see is what you get’)? Well, some people want and prefer this linear style, and it is important for you to also understand those of your pupils who might not have chosen arts as elective subject. Furthermore, graphical interfaces don’t yet lend themselves well to such ‘scripting’. And finally, machine learning works very similarly, by such parameters that you have to tweak.

The educational researcher: Same as above, but perhaps more help is needed to overcome their traditional understanding about tweaking and fiddling: While such practical, quantitative bricolage may seem much less noble than theory, facts, and abstractions, the latter may soon fall prey to cognitive automation, and a skill of the former is also desirable, to cope with unknown futures.