A guide to critical thinking

I do believe the value of asking questions, actually that applies to all kinds of critics, art critics, film critics, etc. the critical thinking is not only applied to evaluate the quality of other studies (literature critics), but also valuable for my own work. The main way is to identify the questions, evidence and conclusions, then question over the reasoning links that connect them into a logical and consistent text.

I. First, we need to identify the core questions and conclusions

Issues (core questions): 

a) Descriptive issues are those that raise questions about the accuracy of descriptions of the past, present, or future.

b) Prescriptive issues are those that raise questions about what we should do or what is right or wrong, good or bad. (normative/judgment)

II. Between the issue and conclusion lies the evidence and reasons which constitute the argument/reasoning.

III. Thus, we need first look at the question and conclusion itself: the ambiguity of the key terms used.

Define the main concepts: synonyms, examples, and what we will call "definition by specific criteria." synonyms and examples are inadequate.

IV. Evidence

The main difference between claims that are opinions/assertions and those are facts is the present state of the relevant evidence.

Sources:

a) intuition

b) personal experience

c) testimonials

d) appeals to authorities  

e) personal observations: The most reliable reports will be based on recent observations made by several people observing under optimal conditions who have no apparent, strong expectations or biases related to the event being observed.

f) case examples: We can generalize only to people and events that are like those that we have studied in the research!

g) research studies

h) analogies: The important analogies are the framing ons, which are used to not only explain a point, but also to influence the direction a discussion will take. Strong analogies will be ones in which the two things we compare possess relevant similarities and lack relevant differences. All analogies try to illustrate underlying principles. Relevant similarities and differences are ones that directly relate to the underlying principle illustrated by the analogy. even the best analogies are only suggestive. Thus can not directly support the conclusion.

PS: Statistics Traps

V. Reasoning

VI. Assumption

In all arguments, there will be certain ideas taken for granted as assumptions. Assumptions are needed for the reason to support the conclusion (as the base for logical reasoning), or just make the reason to be true.

Descriptive assumption: In the first case, we recall the typical model for scientific reasoning which needs a general theory, the specific description, the former is the assumption sometimes unstated, the second constitute the evidence. based on the assumption, we can make deductive reasoning from the evidence to the conclusion. Thus, we can identify the assumption and question its validity.

Prescriptive assumption: For some normative (prescriptive) conclusion, there exists also value assumptions, which indicates a value priority within typical value conflicts: Loyalty-honesty; competition-cooperation; freedom of press-national security; equality-individualism; order-freedom of speech; security-excitement; generosity-material success; rationality-spontaneity; tradition-novelty.

VII. Reasoning fallacies

a) Ad Hominem: against the person instead of his reasons.

b) Slippery Slope: Making the assumption that a proposed step will set off an uncontrollable chain of undesirable events, when procedures exist to prevent such a chain of events.

c) Searching for Perfect Solution: Falsely assuming that because part of a problem (which may not be the main objective of the solution) would remain after a solution is tried, the solution should not be adopted.

d) Equivocation: A key word is used with two or more meanings in an argument such that the argument fails to make sense once the shifts in meaning are recognized.

e) Appeal to Popularity (Ad populum): An attempt to justify a claim by appealing to sentiments that large groups of people have in common; falsely assumes that anything favored by a large group is desirable.

f) Appeal to questionable authority: Supporting a conclusion by citing an authority who lacks special expertise on the issue at hand. 

g) Appeals to Emotions: The use of emotionally charged language to distract readers and listeners from relevant reasons and evidence.

h) Straw Person: Distorting our opponent's point of view so that it is easy to attack; thus we attack a point of view that does not truly exist. 

i) Either-Or (Or False Dilemma): Assuming only two alternatives when there are more than two.

j) Wishful Thinking: Making the faulty assumption that because we wish X were true or false, then X is indeed true or false.

k) Explaining by Naming: Falsely assuming that because you have provided a name for some event or behavior that you have also adequately explained the event.

 l) Glittering Generality: The use of vague emotionally appealing virtue words that dispose us to approve something without closely examining the reasons.

m) Red Herring: An irrelevant topic is presented to divert attention from the original issue and help to "win" an argument by shifting attention away from the argument and to another issue.

n) Begging the Question: An argument in which the conclusion is assumed in the reasoning. (cyclic reasoning)

o) Hasty Generalization Fallacy: A person draws a conclusion about a large group based on experiences with only a few members of the group.

p) Faulty Analogy: Occurs when an analogy is proposed in which there are important relevant dissimilarities. 

q) Causal Oversimplification: Explaining an event by relying on causal factors that are insufficient to account for the event or by overemphasizing the role of one or more of these factors.

r) Confusion of Cause and Effect: Confusing the cause with the effect of an event or failing to recognize that the two events may be influencing each other.

s) Neglect of a Common Cause: Failure to recognize that two events may be related because of the effects of a common third factor.

t) Post hoc Fallacy: Assuming that a particular event, B, is caused by another event, A, simply because B follows A in time. 

PS: If the conclusion supports an action, determine whether the reason states a specific and/or concrete advantage or a disadvantage; if not, be wary!

Effective Research Proposals

The proposal for a piece of research is a document which deals basically with

1. what the proposed research is about; what it is trying to find out or achieve;

2. how it will go about doing that;

3. what we will learn from it and why that is worth learning.

the proposal needs to be a stand alone document. That means it should by itself be like an independent article to answer the three questions above, and convince the judges a) on a general level, which are concerned with the overall viability of the proposed study as a dissertation; b) on a more detailed and technical level – such as, for example, those concerned with the appropriateness of the design, or quality control issues in data collection, or the proposed methods of data analysis.

WHAT

1. Research area; Research topic;

Research areas are usually stated in a few words, and sometimes just one word. Topics similarly are a few words, but usually more than those describing the research area. It defines a body of literature as relevant to this piece of research.

Research topic can be viewed as the title of the final research product. To deduce a topic form an area one can pose the questions on who, when, where, etc.

2. General research question(s); Specific research question(s):

General research questions are more general, more abstract, and (usually) are not themselves directly answerable, because they are too general. Specific research questions are more specific, detailed and concrete. They are directly answerable because they point directly at the data needed to answer them.

To develop a general question into specific researchable questions is the process of making a general concept more specific by showing its dimensions, aspects, factors, components, or indicators. (Here can refer to different types of data: for example, concept and indicator)

To sum up, as you develop your research questions, ask, for each question ‘What data are needed to answer this question?’.

The formulation of specific questions is done on the basis of hypothesis, or on the review of pertinent literature.

3. Data collection question(s):

A research question is a question the research itself is trying to answer. A data collection question is a question which is asked in order to collect data in order to help answer the research question.

research questions identify what you want to understand; interview questions, as data collection questions, provide the data you need to understand these things. The same is true of survey questions. Being the most specific level of questions, the actual data collection questions may well not be shown in the proposal.

* Do we need literature?

(a) What literature is relevant to this project?: Identification of the body of literature

(b) What is the relationship of the proposed study to its relevant literature?: verification, falsification. The answer will lead us to the research questions, and the signification of proposed study.

(c) How will the proposed study deal with the literature and how will the argument in the proposal use the literature? The proposal writer should place the research question(s) – or hypotheses – in the context of previous work in such a way as to explain and justify the decisions made for the proposed study, especially with respect to (i) how and why the research question or hypothesis was formulated in the present form, and (ii) why the proposed research strategy was selected. They see no other role for the literature in the research proposal, and regard the heading ‘review of the literature’ as inappropriate in a proposal.

(d) For some topics, the volume of related literature is so great that a dissertation literature review cannot be comprehensive, covering everything. In these cases, the researcher is forced to be selective. When that occurs, the writer should indicate why it is being done, and the basis on which the selection is made. Here is where previous reviews of the literature, if available and relatively contemporary, can be extremely valuable.

* Do we need hypotheses to develop research questions?

whether hypotheses are appropriate in a particular study:

for each specific research question, can I predict (in advance of the empirical research – that is, in advance of getting and analysing the data) what I am likely to find? 

if so, is the basis for that prediction a rationale, some set of propositions, a ‘theory’ from which the hypotheses follow, and which ‘explains’ the hypotheses?

If so, I should by all means formulate and test hypotheses in the research, and, in so doing, test the theory. If not, I suggest we leave the matter at the level of research questions. I can see no logical difference between answering research questions and testing hypotheses, when it comes to what data we will get and how we will analyse them. The same operations are required.

* Do we need theory? 

does the description–explanation distinction apply in the proposed project?

does the theory-generation–theory-verification distinction apply? it is historically true that theory verification studies in social science research have more often been quantitative, and theory generation studies have more often been qualitative.

Theory must be mentioned when the study is theory verification one.

* Do we need paradigm?

There might be a particular paradigm or metatheory or philosophical position behind the research. it there are various perspectives in the research area, it s an important clarifying task for the researcher, and an important safeguard against mistaken expectations on the part of the reader.

HOW

DATA

Data decides methods. Quantitative data are produced by quantitative methods; qualitative data are produced by qualitative methods.

Quantitative or qualitative data:

Re-examine the research questions and the way they are phrased – what implications for data are there?

Are we interested in making standardized comparisons, sketching contours and dimensions, quantifying relationships between variables and accounting for variance? - QUANTITATIVE

Or are we more interested in studying a phenomenon or situation in detail, holistically and in context, focusing on interpretations and/or processes? - QUALITATIVE

What guidance do we find from the literature about this topic on this methodological question?

What are the practical consequences of each alternative (including resources)?

Which way would we learn more?

Which sort of research is more ‘my style’?

To measure or not to measure:

(a) get the research questions clear;

(b) as far as possible, let questions dictate the nature of the data;

(c) measure if it is feasible and helpful to do so;

(d) use both types of data, if appropriate.

DESIGN

The data will be collected and analysed:

a) following what strategy? and within what framework? - General and procedural description of research method (analyze)

b) from whom? and how? - Sampling and data collection procedure (collection)

Research strategies

Quantitative research strategies:

the experiment, the quasi experiment and the (correlational) survey. But there are others, most of which are more specialized. Examples are: normative surveys, longitudinal studies, time series analysis, panel studies, causal path studies, structural equation modeling, hierarchical linear modeling, event history analysis, facet design and analysis, Q methodology, cluster analysis, cohort analysis, mobility analysis, unidimensional scaling and

multidimensional scaling, operations research and multiattribute evaluation.

Qualitative research strategies:

the case study, ethnography and participant observation, phenomenology, ethnomethodology and interpretive practice, grounded theory, the biographical method, the historical method, applied and action research, and clinical models, life history, oral history, field research or field study, naturalistic study, ecological descriptive study, descriptive study, symbolic interactionist study, microethnography, interpretive research, action research, narrative research, historiography, and literary criticism, discourse analysis and participant observation, qualitative ethology and ethnoscience.

However, the general description of the research method, such as ethnography, participant observation, grounded theory, and fieldwork are not useful to a reviewer unless they are described procedurally, in relation to the specific proposal.

Data collection

From who? - Sampling

For the proposal, the researcher needs to see sampling as part of the planning process for the research, to select among sampling possibilities in line with the logic of the study, and to indicate the sampling plan in the proposal.

If the study is quantitative, the proposal should indicate:

the sampling strategy, especially whether it is purposive, representative or both, and what claims will be made for the generalizability of findings; how big the sample will be; how it will be selected.

This description of the sampling plan should include justification of the sample size, since there are established methods for determining appropriate sample size in quantitative research. This is a technical matter, which essentially involves balancing cost and access against the level of precision required in relation to the variability of the population on the characteristics being measured. Also, the power of the statistical test to be used needs to be considered (Moser and Kalton, 1979; Lipsey, 1990) and many computer packages now include this (Schofield, 1996).

If the study is qualitative, the proposal should similarly indicate:

the sampling strategy, including what intention (if any) there is for the generalizability of findings; the extent of the proposed sample; how sample units will be chosen.

Qualitative sample sizes tend to be small, with no statistical grounds for guidance. The sample size here is usually a function of the purpose of the study in the light of its sampling frames and of practical constraints.

The proposal for the research may be to work (in whole or in part) with data which already exist. This is known as secondary analysis – the term used for the reanalysis of previously collected and analyzed data. In such a case, the proposal should discuss instruments, procedures and sample as appropriate, in describing how the initial data were collected.

How? - Instruments and procedure

Quantitative data collection instruments are questionnaires, standardized measuring instruments, ad hoc rating scales or observation schedules. 

If the decision is to use existing data collection instruments, a brief description of their history, use in research and their psychometric characteristics should be included; If the decision is to construct an instrument(s) specifically for this study, an outline of the steps involved in doing that should be given, showing what pre-testing is involved.

Qualitative data may be mediated by the researcher as the primary instrument for data collection and analysis, or by other instruments such as questionnaires, documents, diaries and journals, other written materials, and non-written qualitative data such as audio-visual materials or artefacts.

If interviews are involved, what type of interviews, and especially what degree of structure and standardization is proposed? If standardized interview schedules are to be used, how will they be developed and pre-tested?

Similarly, if qualitative questionnaires are proposed, what will be the degree of structure and standardization? How would they be developed and (if appropriate) pre-tested?

The same considerations apply for observational data – what degree of structure and standardization is proposed, and how would proposed schedules be developed and pre-tested?

If documents are to be used, which ones and why? Are there sampling or access considerations?

If diaries, journals, critical incident reports, or other qualitative materials are involved, how would the collection of these, including any sampling aspects, be organized?

Procedures refer to the actual process of data collection, over and above any instruments proposed. If instruments are involved, the question here is how the instruments will be used or administered? In other words, what will be the actual data collection procedures? If fieldwork is involved, how would it be carried out?

For the proposal, data collection procedures raise three main questions:

quality of data – how will the proposed data collection and recording procedures ensure that data of the best quality will be obtained?

access – how will the researcher obtain access to the people, situations, and/or information required for the research?

ethics – what ethical issues are involved in the proposed data collection procedures and how will they be handled?

Data analyse needs to demonstrate the methodological mastery of a technique. Quantitative proposals should indicate the statistical procedures proposed. Similarly, the qualitative proposal needs to show how its data will be analysed, and how the proposed analysis fits with the other components of the study. If applicable, both types of proposal should indicate what computer use is planned in the analysis of the data.

STRUCTURE OF A PROPOSAL

i. Title and title page

ii. Abstract

iii. Introduction 

– Area and topic

– Background and context

– Statement of purpose (or aims)

iv.Research questions

– General

– Specific

v. Conceptual framework, theory, hypotheses (if appropriate)

vi.The literature

vii.Methods

– Design 

– Strategy and framework

– Sample

– Data collection 

– Instruments and procedures

– Data analysis

viii.Significance

ix. Limitations and delimitations (if appropriate)

x. Consent, access and participants' protection

xi. References

xii. Appendices

QUALITATIVE UNFOLDING RESEARCH

Maxwell (1996: 59–60) defines five categories of understanding in qualitative research – description, interpretation, theory (explanation), generalization and evaluation. The first three categories include most types of questions that qualitative researchers develop.

The function of proposals is not to provide a watertight blueprint or formula the researcher is to follow, but to

develop a cogent case that makes it plain to a knowledgeable reader that the writer has the necessary background to do the study and has thought clearly about the resources that are likely to be used in doing the study, and that the topic, problem, or issue being addressed is educationally significant.

The writer should indicate early in the document the unfolding nature of the proposed research and why such an approach is appropriate for this study on this topic in this context at this time. The need to preserve flexibility, the unfolding nature of the study, and the ways in which this research will follow a path of discovery can be strongly stated. Against that background, it is good advice to develop likely research questions and issues of design and methods as far as possible in the proposal, indicating what methodological choices will be involved and the basis on which they will be made.

The proposal should indicate:

that the study (or some part of it) is of the unfolding, emerging type; why this is appropriate for the area, topic and approach; in general terms, how structure and specificity will emerge during the research – how research questions will be identified, how the design will be developed and how the analysis will uncover structure in the data. In other words, an unfolding type of study does not imply an ‘anything goes’ sort of proposal.

TACTICS

Two pages on the research questions and methods

Another simultaneous paper on literature and background/context

Persuasive writing (They say I say)

What I view this book is about the art of quoting. May need to refer it later for any templates needed in writing.

Background. To keep an audience engaged, a writer needs to explain what he is responding to either before offering that response or very early in the discussion. even when presenting your own claims, you should keep returning to the motivating "they say".

Quotation often needs summarization in stead of direct quoting or paraphrasing of short texts. A good summary requires balancing what the original author is saying with the writer's own focus. Use more precise verbs to summarize the views of author:
Making a claim: argue, insist, assert, observe, believe, remind us, claim, report, emphasize, suggest
Agreement: acknowledge, endorse, admire, praise, agree, extol, concur, reaffirm, corroborate, support, do not deny, verify
Disagreement: complain, disavow, complicate, question, contend, refute, contradict, reject, deny, renounce, deplore, repudiate
Recommendation: advocate, implore, call for, plead, demand, recommend, encourage, urge, exhort, warn

A wise quotation integrated into your own text should be done: 1) by choosing quotations wisely, with an eye on how well they support a particular part of your text; 2) by surrounding every major quotation with a frame explaining whose words they are, what the quotation means, and how the quotation relates to your text. To adequately frame a quotation, you need to insert it into what called "quotation sandwich", with the statement introducing it and the explanation following it.

Give your opinion early in the text. Three main forms of your opinion relative to others
Disagreement often follows the critical reviewing of other arguments, by pointing out the argument fails to take relevant factors into account, based on incomplete evidence, on questionable assumptions, uses flawed logic (Check Critical Thinking for more info.). You can also agree on the evidence that someone has presented, but through a twist of logic, use it to support you position.
Agreement but contributing to the argument by pointing out unnoticed implications or explaining something that needs to be better understood. you agree while always disagreeing something else.
Yes...but. No...but

Respond to imaginary objections. to be sure that any counter argument you address is not more convincing than your own claims. the best way to overcome an objection is not to try to refute it completely, but to agree with certain parts while challenging only those you dispute.

If you take it for granted that readers will somehow intuit the answer to "so what?" and "who cares?" on their own, you may make your work seem less interesting and exciting than it actually is.

Four ways to connect sentences:
1) Transition terms: also, and, besides, furthermore, in addition, indeed, in fact, moreover, so too; after all, as an illustration, for example, for instance, specifically, to take a case in point; actually, by extension, that is, in other words, to put it another way; along the same lines, in the same way, likewise, similarly; although, but, by contrast, conversely, despite, even though, however, in contrast, nevertheless, nonetheless, on the contrary, on the other hand, regardless, whereas, while, yet; consequently, as a result, because, accordingly, hence, in effect, since, so ,then, therefore, thus; admittedly, although, granted, naturally, of course, to be sure.
2) Pointing words: THIS/THAT (account, advice, answer, argument, area, assertion, assumption, claim, comment, conclusion, criticism, description, difficulty, discussion, distinction, emphasis, estimate, example, explanation, finding, idea, improvement, increase, observation, proof, proposal, reference, rejection, report, rise, situation, suggestion, view, warning)
3) Key terms
4) Repeating with difference
Paraphrase with difference with aim to clarify possible confusion and misunderstanding.

Inside Track Successful Academic Writing

Basically it's a book for students to successfully conduct their assignments, bring very little insightful information for researchers. However there are still some thing worth noting down.
1. The title may contain certain "instruction word" and "keywords"
2. Style of writing: a) avoid multiple-word verbs; b) passive terms or not depends on whether the action or the result is more important than the person carrying it out.
3, Topic sentences+Supporting sentences+Concluding sentences. Connecting the sentences and then the paragraphs with lists of words.
4. Different types of papers: a) research proposal: TITLE what is the topic? what is the research problem? PURPOSE what is the purpose of your work? JUSTIFICATION why it is important? LITERATURE REVIEW what do you already know about the topic? METHOD how will the research be conducted? what resources will be needed?DISSEMINATION how the finding will be used? READING LIST a preliminary reading list; b) book review: INTRODUCTION what is the text about? who is it written for? what is the purpose of the book? BACKGROUND what has been written before? CONTENT what is the content of the text? EVALUATION is it any good?RECOMMENDATION

Philosophy of Science

Karl Popper thought that the fundamental feature of a scientific theory is that it should be falsifiable. to call a theory falsifiable is not to say that it is false.

Popper criticized Freudians and Marxists for explaining away any data that appeared to conflict with their theories, rather than accepting that the theories had been refuted.
In general, scientists do not just abandon their theories whenever they conflict with the observational data. Usually they look for ways of eliminating the conflict without having to give up their theory.
A simple criterion for demarcating science form pseudo-science is unlikely to be found.

To be falsifiable is no doubt true for any scientific theory, but the more important is what to do facing the conflicting facts. 

Deductive reasoning is a much safer activity than inductive reasoning. when we reason deductively, we can be certain that if we start with true premisses, we will end up with a true conclusion. But the same does not hold for inductive reasoning.
So for Karl Popper, if a scientist is only interested in demonstrating that a given theory is false, she may be able to accomplish her goal without the use of inductive inferences.

Without inductive there's no way to generate new knowledge.

Hume's "uniformity of nature" dilemma
Inductive inference is used to take us from the examined to unexamined, and to provide the best way of accounting for the available data.
A popular way to choose the best answer for the competing hypothesis is the simplest and the most parsimonious one.

That's why it is important to 大胆假设, for almost there's no way to justifiy one hypothesis is better than other alternatives. 

Probability could be a subjective estimation, or the objective measure of the strength of evidence in its favor.

The logic interpretatino of probability itself is a product of inductive inference, for example statistics is to generalize the observation on a sample to the whole population.

Hempel's Covering law model
Scientific explanation consists on 1) the premisses should entail the conclusion; 2) the premisses should all be true; 3) the premisses should include at least one general law.
General laws+particular facts=explanation of particular phenomenon
Hemple implies that every scientific explanation is potentiall a prediction.
Nevertheless Hemple's model has the symmetric problem (that means you can exchange the position of facts and phemoneon to be explained, and then use the phenomenon to explain the facts)

A good explanation should also contain information that is relevant to the phenomenon's occurrence.

Natural sicence or more specifically physics is not superior than other discplines, for the objects studies by other disciplines are multiply realized at the physical level (so diverse that it is impossible to define it in a single physics term).

Anti-realism is sometimes called "instrumentalism" for scientific theories are regarded as instruments for helping us predict observational phenomena, rather than as attempts to describe the underlying nature of reality.
The limits to scientific knowledge are set by our powers of observation.
Realism proponents use the empirical success of theories that posit unobservable entitites to argument for scientific realism even on unobserved world, but there existed in the scientific history the counter examples.
Unobservable vs. unobserved (the effects of techonolgy development)

The positivists argue that it makes no difference how a hypothesis is arrive at initially. what matters if how it is tested once it is already there, for it is this that makes science a rational activity.
Again, 大胆假设, 小心求证。
The disputes between rival theories could be solved in a perfectly objective way, by comparing the theories directly with the neutral observational facts, which all parties could accept.

Kuhn's contribution
Normal science is a paradigm, a constellation of shared assumptions, beliefs, and values tha tunite a scientific community and allow normal science to take place. The job of the normal scientist is to try to eliminate these minor puzzles while making as few changes as possible to the paradigm.
Adopting a new paradigm involves a certain act of faith on the part of scientist. He allowed that a scientist could have good reasons for abandoning an old paradigm for a new one, but reasons alone could never rationally compel a paradigm shift.
Concepts cannot be explained independently of the theories in which they are embedded, and the data are "theory ladenness", no such data that are neutral and can be accepted by all.