9. We think therefore we exist.

What is Thinking?

<NB> 9. To think: To employ any of the intellectual powers except that of simple perception through the senses; to exercise the higher intellectual faculties.[1913 Webster]; no entries in Lexitron for 'think', 'คิด'

Thinking is employed by Hamilton as "comprehending all our collective energies." It is defined by Mansel as "the act of knowing or judging by means of concepts", by Lotze as "the reaction of the mind on the material supplied by external influences." Synonym: to expect; guess; cogitate; reflect; ponder; contemplate; meditate; muse; imagine; suppose; believe; [to conceive, to imagine, to reckon/evaluate/assess/compare; to plan, design, focus/concentrate; to reflect, recall/recollect, to believe, to consider, to esteem], ...

<NB> 10. Learning and Thinking may be 'interdependent' (or co-arising and co-evolving). Both seem to convolute -- learning leads to (more) thinking and thinking leads to (more) learning. Which is closer to knowing - learning or thinking? In a sense we may define thinking as a 'general purpose' process but learning as 'specific purpose' or goal-directed process. Both result in knowing.

Thinking model:
    {challenge-->[info processing: id, map/link, what if/best-fit, review]-->KL+scheme+expectation}

Continuing with a simple system model extension of our earlier knowing and learning models, we look at thinking as information processing (an extension of 'data processing' when 'information' replaces 'data'). A thinking process produces possible knowledge pieces (knowing and learning: KL) with certain arrangement: scheme, and possible predictions or expectations. The subprocesses involved in thinking may be: identifying or establishing uniqueness of objects, ranking or ordering objects, mapping or linking (giving associations between) objects (in one area/space/domain to another domain), testing possible events, transforming or best-fitting or adapting and reviewing or validating (the links). We may see similarities with mathematical conceptualization such as: sets of objects, sorting or partial ordering, mapping (relatons), transforming (projecting) and so on. This may allow similar results in 'study of thinking' to be inferred from some other well-established areas.

By projecting 'thinking' from 'information processing' which is projected from 'data processing', we say that it is possible to make computers think!

A challenge today:
 
    If computers can think then computers are intelligent. At present, computers are not programmed to think but to process data. How human and animals think, no one really knows. There are research efforts to understand the working of sensory organs and the brain, communication among sensory organs and the brain, (electrical, chemical and neural) types of communication languages and brain activities. Some results have been achieved in 'control of mechanical devices by brain waves' (that is by 'thinking') but no explanation of how we think has come forth. How do we make computers think?
 
<NB> 11. Let function T denote a thinking function defined over a collection of (mental/thought) objects {m} in M. Let D be data processing (function) over a collection of known facts {f} in F. And similarly information processing function I over knowledge/information object {k} in K. We project information processing I from F by mapping information objects to facts, and define information processing operations as 'procedures' (algorithms) of data processing operations (e.g. get, move, put, add, change, ...). In computing applications, we input data into a process and receive information as output. Now if we map mental objects to informational items and use a certain symbolic representation - 'symbol=meaning' pairing (as in a dictionary!), we say

     T(m=I(i=D(f)) --> thinking-output={k} in K; for {f} in F; {i} in I; {m} in M

That is, we can look at 'a way' we receive data, grasp its information and 'think' about the consequences or the meaning conveyed by the information conveyed by the 'fact' or data. This model of thinking is a 'system of systems'. In general, thinking is a system (brain?) for processing outputs from sensory (eye, ear, ...) and neural systems. Each sense processes environmental and internal signals (data) into informational messages (perhaps, in a common language used by the brain).

<NB> 12. Teaching as commonly practiced goes like this.
    Learners sit, watch, listen, take notes or copy what written by the teacher, (sometimes) ask or answer questions, do homework, get feedback from the teacher as how well the object has been learned but there is little chance to amend/relearn.
    Teachers stand, talk, write or draw representations of the objects and relationships of knowledge topic in the lesson, ask or answer questions, give (hand out) homework exercises, 'mark' (handed in) homework exercises.

In some classes, there may be opportunities for learners to discuss, experiment or express their learning in interactive mode. But, in general, teaching and learning has become 'mundane' chore - no novelty, no discovery, no exciting interactions, no creative activities! In simple word -- very little 'thinking' in teaching and learning.

In extreme analogy, teachers become (tape) players and students become (tape) recorders.

<NB> 13. The need to assess and rank learners of their learned knowledge (as specified in the curricula) quickly and unbiasedly, lead to the current popular 'multiple choice' examinations. Combined with automation, multiple choice exam is now the standard assessment tool in Thailand. Students anticipate this assessment by memorizing possible questions and answers. Their education becomes 'rote learning' of exam papers. After some 12 years (of schooling and a few more years at university) experience of multiple choice examinations, students learn 'how to choose' - but not 'how to think'. Though, choosing may require thinking, evaluating and best-fitting -- choosing can be done on whims.

Already, there are concerns over the lack of creative thinking, innovation and deep understanding of knowledge arising from overuse of multiple choice exams. The argument that choices offered become the limiting box constraining exploration and innovation is gaining. Also, the emphasis on multiple choice denies learners the opportunity to learn the process of 'how to construct knowledge' - an important knowledge skill to extend knowledge.