To the Stars
Some key concepts relevant to TMA03 with referenced notes per course materials, and definitions restated in my own words…
KEY CONCEPTS (P3)
• appreciation
• appreciative systems
• boundary interactions [Read more…] about Key Concepts Relevant to TMA03
How We Find Out Things is important. Intelligence is the ability to find things out about a situation or subject, and to apply what we have previously found out to a new or novel situations or subjects.
Machine Learning does this through methods of Computational Statistics. It is powerful, but we still need to be there applying our own Intelligence & Sense-making abilities to ensure the results are logical & consistent with what we would expect.
As Ramon y Cajal, Spanish biologist and father of modern neuroscience, noted in his excellent book of advice for novice scientific researchers (1999), the key stages of a scientific investigation are (1) observation, (2) experimentation, (3) working hypotheses, and (4) proof. [Read more…] about How We Find Out Things
This post summarises learnings from Dr Oakley’s MOOC on learning How to Learn (see References below for link) together with my own thoughts and reflections on that course together with my Systems Theory post-grad course currently being studied with the Open University and other current studies. Related posts can be found under the tag Learning About Learning.
In particular, I have taken time out from that post-grad module due to feeling really confused, fed up, bored and generally utterly demoralised by my continually unsuccessful attempts to get on with studying that module. Rather than beat myself up about it, I decided to just give myself some time off to go and study a different (albeit, connected) subject. Hopefully it will free up some mind-space and sparks some useful ideas to go towards my next assignment.
Chunking as a Learning Method
Chunking is studying information in small, accessible packages. These chunks are more easily assimilated, since the mind is better able to unite and fit them together into a unified whole. Chunking has been described as a ‘mental leap’ – taking pieces of a jigsaw puzzle and fitting them together to make a whole picture. [Read more…] about Effective Study Skills
Some reading materials (highlighted = likely useful for TU812 TMA03):
Chapters 1-3 of A Mind for Numbers are especially helpful in providing helpful information and additional exercises related to the materials of Module 1.
A key theme of part three of the systems module TU812 is ‘learning about learning’, and this course on Coursera by Dr Barbara Oakley – which covers that from one angle – came highly recommended: http://www.coursera.org/learn/learning-how-to-learn. It’s subtitled ‘powerful tools to help you master tough subjects’, which is definitely the kind of help I need right now with this systems course. The MOOC course is, I believe, in the top 3 on Coursera, although it’s worth pointing out the focus is on helping you with mathematical or scientific subjects. Yet the ideas and study tips should be extendable across to more abstract and wordy subjects (the ones I struggle most with).
Two Types of Thinking: Focussed and Diffuse
If we understand something about how the brain works, we can develop and deploy strategies to help us learn more optimally. As humans we have two thinking modes – with Dr Oakley refers to as ‘focussed’ and ‘diffuse’. These are mental states where we’re, respectively, concentrating really hard on something (like reading & note-taking from a course text) or allowing our minds to wander and day-dream (which is, of course, my preferred mental state!). Another way to think of the two different states is that focussed is looking at the details (a church within the landscape), while diffuse is looking at the much bigger picture (drinking in the whole scene as far as the eye can see). [Read more…] about Learning About Learning
Thought on waking this morning:
Vector Spaces*
Had gone to bed asking: ‘OK so what should I do for our AI system? What’s next?’
Assume this answer means I should be studying Vector Spaces – and hence Linear Algebra – more fully for my delve into AI.
Makes sense given LA is such a strong math basis for all ML courses out there, also for AI generally.
But I can’t help wondering if this also relates somehow to my recent Systems Struggles. E.g. the vector space is an abstract mathematical way of representing a realworld physical geometric reality. Can this offer a parallel to Systems Modelling which might [Read more…] about Vector Spaces
The Over-arching idea in Part 2 of the TU812 module, Managing Systemic Change (inquiry, action and interaction), is of taking an inquiry process and turning it into a systemic inquiry.
As a part of this, there are two key questions to be answered in this section of the module (per the Study Guide, p. 51):
1. Why an inquiry process?
2. What is a systemic inquiry?
[Before proceeding, here are some of my reflections on this:
I think of a PROCESS as being a step-by-step and methodical action/activity – or set of actions/activities – and which causes something to change states (from a ‘before process’ state to an ‘after process’ state). Similarly, an INQUIRY PROCESS, I view as a step-by-step approach to gaining some knowledge about something, e.g. an event or a situation. So I as a practitioner (or we as a group of practitioners) undertake some actions or activities in a logical sequence which leads me/us to a better awareness and understanding of a given thing, event or situation. [Read more…] about P2 (1) Turning My Inquiry Process Into A Systemic Inquiry