·It answers the question, "What do you see?"
·The various elements that constitute a description include:
a. Form of art whether architecture, sculpture, painting or one of the minor arts
b. Medium of work whether clay, stone, steel, paint, etc., and technique (tools used)
c. Size and scale of work (relationship to person and/or frame and/or context)
d. Elements or general shapes (architectural structural system) within the composition, including building of post-lintel construction or painting with several figures lined up in a row; identification of objects
e. Description of axis whether vertical, diagonal, horizontal, etc.
f. Description of line, including contour as soft, planar, jagged, etc.
g. Description of how line describes shape and space (volume); distinguish between lines of objects and lines of composition, e.g., thick, thin, variable, irregular, intermittent, indistinct, etc.
h. Relationships between shapes, e.g., large and small, overlapping, etc.
i. Description of color and color scheme = palette
j. Texture of surface or other comments about execution of work
k. Context of object: original location and date
2. Analysis = determining what the features suggest and deciding why the artist used such features to convey specific ideas.
·It answers the question, "How did the artist do it?"
·The various elements that constitute analysis include:
a. Determination of subject matter through naming iconographic elements, e.g., historical event, allegory, mythology, etc.
b. Selection of most distinctive features or characteristics whether line, shape, color, texture, etc.
c. Analysis of the principles of design or composition, e.g., stable,
repetitious, rhythmic, unified, symmetrical, harmonious, geometric, varied, chaotic, horizontal or vertically oriented, etc.
d. Discussion of how elements or structural system contribute to appearance of image or function
e. Analysis of use of light and role of color, e.g., contrasty, shadowy,
illogical, warm, cool, symbolic, etc.
f. Treatment of space and landscape, both real and illusionary (including use of perspective), e.g., compact, deep, shallow, naturalistic, random
g. Portrayal of movement and how it is achieved
h. Effect of particular medium(s) used
i. Your perceptions of balance, proportion and scale (relationships of each part of the composition to the whole and to each other part) and your emotional
j. Reaction to object or monument
Part of becoming a successful critical reader is being able to translate the thoughts you had whilst reading into your writing. Below are some written examples of the observations a critical reader may make whilst commenting on various issues in text.
NOTE: The critical analysis component of each example below is highlighted in blue.
Further examples of critical writing can be found on the UniLearning Website.
Overgeneralisations and assumptions
Researchers often make simplifying assumptions when tackling a complex problem. While the results might provide some insight, these answers will also likely have some limitations.
Researchers may simplify the conditions under which an experiment occurs, compared to the real world, in order to be able to more easily investigate what is going on.
Objectivity of research
Some research may be biased in its structure.
Limitations due to sample group
Limitations can arise due to participant numbers. Example:
Limitations can also arise if there is a limited range of participants.
Limits to applicability
There can be concerns with studies’ applicability, for a number of reasons.
Results not replicated
One such reason could be that the study results have not been replicated in any other study. If results have not been replicated, it indicates that the results are suggestive, rather than conclusive.
Long term effects unknown
There would be limits to applicability if long term effects have not been tested.
It is important to look for things that have not been discussed within studies to ascertain whether this would limit the applicability of the results.
Correlation vs. causation
It is important to be aware that just because one variable is correlated with another, it doesn’t necessarily mean that one variable is the cause of another.