How to write a successful critical analysis
For further queries or assistance in writing a critical analysis email Bill Wrigley.
What do you critically analyse?
In a critical analysis you do not express your own opinion or views on the topic. You need to develop your thesis, position or stance on the topic from the views and research of others. In academic writing you critically analyse other researchers’:
- concepts, terms
- viewpoints, arguments, positions
- methodologies, approaches
- research results and conclusions
This means weighing up the strength of the arguments or research support on the topic, and deciding who or what has the more or stronger weight of evidence or support.
Therefore, your thesis argues, with evidence, why a particular theory, concept, viewpoint, methodology, or research result(s) is/are stronger, more sound, or more advantageous than others.
What does ‘analysis’ mean?
A critical analysis means analysing or breaking down the parts of the literature and grouping these into themes, patterns or trends.
In an analysis you need to:
1. Identify and separate out the parts of the topic by grouping the various key theories, main concepts, the main arguments or ideas, and the key research results and conclusions on the topic into themes, patterns or trends of agreement, dispute and omission.
2. Discuss each of these parts by explaining:
i. the areas of agreement/consensus, or similarity
ii. the issues or controversies: in dispute or debate, areas of difference
ii. the omissions, gaps, or areas that are under-researched
3. Discuss the relationship between these parts
4. Examine how each contributes to the whole topic
5. Make conclusions about their significance or importance in the topic
What does ‘critical’ mean?
A critical analysis does not mean writing angry, rude or disrespectful comments, or expressing your views in judgmental terms of black and white, good and bad, or right and wrong.
To be critical, or to critique, means to evaluate. Therefore, to write critically in an academic analysis means to:
- judge the quality, significance or worth of the theories, concepts, viewpoints, methodologies, and research results
- evaluate in a fair and balanced manner
- avoid extreme or emotional language
- strengths, advantages, benefits, gains, or improvements
- disadvantages, weaknesses, shortcomings, limitations, or drawbacks
How to critically analyse a theory, model or framework
The evaluative words used most often to refer to theory, model or framework are a sound theory or a strong theory.
The table below summarizes the criteria for judging the strengths and weaknesses of a theory:
- empirically supported
Evaluating a Theory, Model or Framework
The table below lists the criteria for the strengths and their corresponding weaknesses that are usually considered in a theory.
|Comprehensively accounts for main phenomena||overlooks or omits important features or concepts|
|Clear, detailed||vague, unexplained, ill-defined, misconceived|
|Main tenets or concepts are logical and consistent||concepts or tenets are inconsistent or contradictory|
|Practical, useful||impractical, unuseful|
|Applicable across a range of settings, contexts, groups and conditions||limited or narrow applicability|
|Empirically supported by a large body of evidence|
propositions and predictions are supported by evidence
|supported by small or no body of evidence
insufficient empirical support for the propositions and predictions
|Up-to-date, accounts for new developments||outdated|
|Parsimonius (not excessive): simple, clear, with few variables||excessive, overly complex or complicated|
Critical analysis examples of theories
The following sentences are examples of the phrases used to explain strengths and weaknesses.
Smith’s (2005) theory appears up to date, practical and applicable across many divergent settings.
Brown’s (2010) theory, although parsimonious and logical, lacks a sufficient body of evidence to support its propositions and predictions
Little scientific evidence has been presented to support the premises of this theory.
One of the limitations with this theory is that it does not explain why…
A significant strength of this model is that it takes into account …
The propositions of this model appear unambiguous and logical.
A key problem with this framework is the conceptual inconsistency between ….
How to critically analyse a concept
The table below summarizes the criteria for judging the strengths and weaknesses of a concept:
- key variables identified
- clear and well-defined
|Key variables or constructs identified||key variables or constructs omitted or missed|
|Clear, well-defined, specific, precise||ambiguous, vague, ill-defined, overly general, imprecise, not sufficiently distinctive
overinclusive, too broad, or narrowly defined
|Meaningful, useful||conceptually flawed|
|Up-to-date||out of date|
Critical analysis examples of concepts
Many researchers have used the concept of control in different ways.
There is little consensus about what constitutes automaticity.
Putting forth a very general definition of motivation means that it is possible that any behaviour could be included.
The concept of global education lacks clarity, is imprecisely defined and is overly complex.
Some have questioned the usefulness of resilience as a concept because it has been used so often and in so many contexts.
Research suggests that the concept of preoperative fasting is an outdated clinical approach.
How to critically analyse arguments, viewpoints or ideas
The table below summarizes the criteria for judging the strengths and weaknesses of an argument, viewpoint or idea:
- reasons support the argument
- argument is substantiated by evidence
- evidence for the argument is relevant
- evidence for the argument is unbiased, sufficient and important
- evidence is reputable
Evaluating Arguments, Views or Ideas
|Reasons and evidence provided support the argument||the reasons or evidence do not support the argument - overgeneralization|
|Substantiated (supported) by factual evidence||insufficient substantiation (support)|
|Evidence is relevant and believable||Based on peripheral or irrelevant evidence|
|Unbiased: sufficient or important evidence or ideas included and considered.||biased: overlooks, omits, disregards, or is selective with important or relevant evidence or ideas.|
|Evidence from reputable or authoritative sources||evidence relies on non reputable or unrecognized sources|
|Balanced: considers opposing views||unbalanced: does not consider opposing views|
|Clear, not confused, unambiguous||confused, ambiguous|
|Logical, consistent||the reasons do not follow logically from and support the arguments; arguments or ideas are inconsistent|
Critical analysis examples of arguments, viewpoints or ideas
The validity of this argument is questionable as there is insufficient evidence to support it.
Many writers have challenged Jones’ claim on the grounds that …….
This argument fails to draw on the evidence of others in the field.
This explanation is incomplete because it does not explain why…
The key problem with this explanation is that ……
The existing accounts fail to resolve the contradiction between …
However, there is an inconsistency with this argument. The inconsistency lies in…
Although this argument has been proposed by some, it lacks justification.
However, the body of evidence showing that… contradicts this argument.
How to critically analyse a methodology
The table below provides the criteria for judging the strengths and weaknesses of methodology.
An evaluation of a methodology usually involves a critical analysis of its main sections:
design; sampling (participants); measurement tools and materials; procedure
- design tests the hypotheses or research questions
- method valid and reliable
- potential bias or measurement error, and confounding variables addressed
- method allows results to be generalized
- representative sampling of cohort and phenomena; sufficient response rate
- valid and reliable measurement tools
- valid and reliable procedure
- method clear and detailed to allow replication
Evaluating a Methodology
|Research design tests the hypotheses or research questions||research design is inappropriate for the hypotheses or research questions|
|Valid and reliable method||dubious, questionable validity|
|The method addresses potential sources of bias or measurement error. |
confounding variables were identified
measurement error produces questionable or unreliable
confounding variables not identified or addressed
|The method (sample, measurement tools, procedure) allows results to be generalized or transferred.|
Sampling was representative to enable generalization
|generalizability of the results is limited due to an unrepresentative sample:
small sample size or limited sample range
|Sampling of cohort was representative to enable generalization|
sampling of phenomena under investigation sufficiently wide and representative
sampling response rate was sufficiently high
|limited generalizability of results due to unrepresentative sample:
small sample size or limited sample range of cohort or phenomena under investigation
sampling response rate was too low
|Measurement tool(s) / instrument(s), appropriate, reliable and valid|
measurements were accurate
|inappropriate measurement tools; incomplete or ambiguous scale items
reliability statistics from previous research for measurement tool not reported
measurement instrument items are ambiguous, unclear, contradictory
|Procedure reliable and valid||Measurement error from administration of the measurement tool(s)|
|Method was clearly explained and sufficiently detailed to allow replication||Explanation of the methodology (or parts of it, for example the Procedure) is unclear, confused, imprecise, ambiguous, inconsistent or contradictory|
Critical analysis examples of a methodology
The unrepresentativeness of the sample makes these results misleading.
The presence of unmeasured variables in this study limits the interpretation of the results.
Other, unmeasured confounding variables may be influencing this association.
The interpretation of the data requires caution because the effect of confounding variables was not taken into account.
The insufficient control of several response biases in this study means the results are likely to be unreliable.
Although this correlational study shows association between the variables, it does not establish a causal relationship.
Taken together, the methodological shortcomings of this study suggest the need for serious caution in the meaningful interpretation of the study’s results.
How to critically analyse research results and conclusions
The table below provides the criteria for judging the strengths and weaknesses of research results and conclusions:
- appropriate choice and use of statistics
- correct interpretation of results
- all results explained
- alternative explanations considered
- significance of all results discussed
- consistency of results with previous research discussed
- results add to existing understanding or knowledge
- limitations discussed
- results clearly explained
- conclusions consistent with results
Evaluating the Results and Conclusions
|Chose and used appropriate statistics||inappropriate choice or use of statistics|
|Results interpreted correctly or accurately||incorrect interpretation of results
the results have been over-interpreted
For example: correlation measures have been incorrectly interpreted to suggest causation rather than association
|All results were explained, including inconsistent or misleading results||inconsistent or misleading results not explained|
|Alternative explanations for results were considered||unbalanced explanations: alternative explanations for results not explored|
|Significance of all results were considered||incomplete consideration of results|
|Results considered according to consistency with other research or viewpoints|
Results are conclusive because they have been replicated by other studies
|consistency of results with other research not considered
results are suggestive rather than conclusive because they have not been replicated by other studies
|Results add significantly to existing understanding or knowledge||results do not significantly add to existing understanding knowledge|
|Limitations of the research design or method are acknowledged||limitations of the research design or method not considered|
|Results were clearly explained, sufficiently detailed, consistent||results were unclear, insufficiently detailed, inconsistent, confusing, ambiguous, contradictory|
|Conclusions were consistent with and supported by the results||conclusions were not consistent with or not supported by the results|