Answering questions or solving problems – require data to justify. Require to interpret the data. By doing so it allows the development of critical, analytical thinking.
Sometimes in analysing and perform comparative studies.
Ask questions:
- What is the reliability? Reliability of the data, reliability of the source
- How general is it? Generalizability
- What is the validity?
Need to always be critical of each piece of research to see if it is valid.
1. Intuition
“Act or process of coming to direct knowledge or certainty without reasoning or inferring”
Own gut feeling - not systematic way in acquiring information and is inaccurate method.
Intuition basis to formulate a hypothesis.
2. Authority
High respected people of power or source providing information that the community will accept. Helps with one’s hypothesis providing feedback.
3. Rationalism
Uses reasoning to arrive at knowledge.
4. Empiricism (observation)
Using observation to acquire knowledge.
- Naive – if I experienced something it must be true. Only believe in what you experienced.
Must perform rigorous observations to avoid naive problem. Controlled conditions (testing done in a lab), us systematic strategies, participant selection.
What we see is subjected to limited view.
5. Scientific Methods
Drawing conclusions via induction (general reasoning process).
Also from deduction (general to specific).
Hypothesis testing – 2 methods
Method 1: Generate hypthesis testing
Conduct experiments, observe then derive whether true or false
Compare whether facts match hypothesis.
Method 2: Collected data to see if it disproves the hypothesis.
When we do research we assume it has regularity and predictable.
In reality of nature (for observations), things we hear, feel, see, smell, taste are real and able to obtain evidence to back the claims.
In discovering data, you need appropriate research data collection methods and able to group them to explain a phenomena.
In having control, one is able to eliminate influences.
6. Have to decide on what you want to measure (operationalization). Each concept is defined well. Sometimes it has strict demands and hard to specify because it is objective.
How does one define usability? Is it the same for everyone? (http://www.usability.gov/)
7. Replication
Able to reproduce the results obtained from one study to other studies. If unable to replicate, there must be something wrong.
(http://www.pewinternet.org)
8. So once you identify characteristics of a phenomenon, you need to be able to explain the cause and existence.
9. There needs to be empirical evidences and should be quoted. Explanations must be logical and rational. Must have consistent facts. It should be testable through direct observation, parsimonious whereby there is as few assumptions as possible and it has to be general. Can never prove a hypothesis but it can be confirmed.
10. Theories allow the prediction of future data. It allows the categorization of results. Diff level of operation: descriptive theories, analogical theories (analogy description), fundamental theories (IT usefulness and ease of use)
Quantitative: Fitt’s Law
Qualitative: Uncanny Valley
What is a good theory?
Should be account for “most” data.
Testability – capable of failing some empirical test (fail under certain conditions).
Parsimony – simplest possible terms and fewest assumptions.
Research Process
Ideas and hypothesis – must be precise as possible. Makes it easy to test.
Decide on what to observe, what are the questions you want to observe.
Report your results.
Start the whole process over again (results may raise more Questions than Answers)