How To Create Knowledge

I’m obsess­ively inter­ested in how to cre­ate knowledge.

I love to learn about learn­ing. And I love to know about knowledge.

Of course, not every­one will find this inter­est­ing, but not all know­ledge is cre­ated equally. Understanding how know­ledge is cre­ated makes it easi­er to under­stand the strengths and weak­nesses of dif­fer­ent types of reasoning.

At least I think so.

Here we go:

How To Create Knowledge

Spin Academy | Online PR Courses

How To Create Knowledge

“If you can­’t explain it simply, you don’t under­stand it well enough.”
— Albert Einstein

This list of how to cre­ate know­ledge presents aspects of reas­on­ing, meth­od­o­lo­gic­al approaches, data ana­lys­is per­spect­ives, and philo­soph­ic­al frame­works. It explains how know­ledge can be approached, ana­lysed, and interpreted.

Types of Reasoning and Logical Processes

• Inductive reas­on­ing. Generalising from spe­cif­ic obser­va­tions to broad­er generalizations.
• Deductive reas­on­ing. Starting with a gen­er­al state­ment or hypo­thes­is and reach­ing a spe­cif­ic conclusion.
• Abductive reas­on­ing. Starting with an obser­va­tion and seek­ing the simplest and most likely explanation.
• Probabilistic reas­on­ing. Making pre­dic­tions based on prob­ab­il­it­ies in uncer­tain situations.

Methodological Approaches

• Empirical vs logic­al. Empirical—Deriving know­ledge from obser­va­tion or exper­i­ment­a­tion. Logical—Using struc­tured reas­on­ing and val­id argu­ments inde­pend­ent of empir­ic­al evidence.
• Heuristic vs algorithmic. Heuristic—Applying prac­tic­al meth­ods or “rules of thumb” for imme­di­ate solu­tions. Algorithmic—Using sys­tem­at­ic pro­ced­ures for defin­it­ive, often optim­al solutions.

Data and Analysis Perspectives

• Analytical vs syn­thet­ic. Analytical—Breaking down com­plex prob­lems into smal­ler com­pon­ents. Synthetic—Combining ele­ments to form a coher­ent whole.
• Qualitative vs quant­it­at­ive. Qualitative—Focusing on non-stat­ist­ic­al aspects and qual­it­ies. Quantitative—Involving numer­ic­al data col­lec­tion and analysis.

Philosophical and Theoretical Frameworks

• Rationalism vs empir­i­cism. Rationalism—Emphasising reas­on as the primary source of know­ledge. Empiricism—Stressing the import­ance of sens­ory exper­i­ence and evidence.
• Positivism. Asserting that sci­entif­ic know­ledge is the true form of knowledge.
• Hermeneutics. Focusing on the inter­pret­a­tion of texts, lan­guage, and symbols.
• Phenomenology. Concentrating on the study of con­scious­ness and dir­ect experience.
• Pragmatism. Considering prac­tic­al con­sequences as vital in mean­ing and truth.
• Constructivism. Suggesting that know­ledge is con­struc­ted from exper­i­ences and ideas.
• Deconstruction. Analysing philo­soph­ic­al and lit­er­ary lan­guage to uncov­er impli­cit assumptions.

Learn more: How To Create Knowledge

💡 Subscribe and get a free ebook on how to get bet­ter PR ideas.

PR Resource: More Better Thinking

Spin Academy | Online PR Courses

Doctor Spin’s PR School: Be Clear-Minded

• Mental Models: How To Be Better a Better Thinker
• 10 Intelligence Types: Howard Gardner’s Theory
• How To Create Knowledge
• Types of Bad Thinking Habits
• Principles of Clear Thinking
• My Mind Palace (and How It Helps Me To Think Better)
• Image Streaming — Unleash Your Inner Genius

💡 Subscribe and get a free ebook on how to get bet­ter PR ideas.

PR Resource: List of Logical Fallacies and Biases

List of Logical Fallacies and Biases

We eas­ily fall prey to the tricks our psy­cho­logy plays on us. These “think­ing errors” exist because they’ve often aided our sur­viv­al. However, know­ing and under­stand­ing vari­ous types of com­mon fal­la­cies and biases is help­ful in every­day life.

Here are a few examples of logic­al fal­la­cies and biases that I’ve come across while study­ing pub­lic rela­tions and linguistics:

Learn more: 58 Logical Fallacies and Biases