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Teaching Inference, Interpretation and Analysis with New (and Old) Technologies By Jamie McKenzie About the Author Most new state curriculum standards stress three verbs . . . interpret infer analyze Given a set of numbers, a collection of diary entries, a poem, an essay or a photograph, the student is expected to read between the lines, crunch the numbers and find meaning. Once they have interpreted and inferred, they are then expected to come up with new meanings - synthesis.

© 2002, J.McKenzie The first Thinker? Perched atop Notre Dame, just what has he been pondering all these years? And just why do you suppose his tongue is protruding?

© 2002, J.McKenzie

Australian children digging in the sand. Inference is much like digging below the surface to find meaning.

Inference is detective work - seeking clues, resolving mysteries, figuring out whodunit.

The Internet is a great source of certain kinds of data and primary sources - images, diaries, text files of various kinds. Meanings are implicit rather than explicit. The student must develop insight rather than uncover it.

But teaching this skill requires more than repeated practice. It is not enough to send students to an online museum and ask them to come up with new titles for paintings.

Teaching such skills requires the introduction of the thinking strategies that combine to enable students to extract meanings and to construct meanings when the raw ingredients are present but the actual meaning is not self evident, followed by modeling and guided practice.

The following page lists ten types of inference drawn from Johnson and Johnson (1986)

http://www.d46.k12.il.us/curriculum/literacylearningi.htm#inference

1. LOCATION

2. AGENT

3. TIME

4. ACTION

5. INSTRUMENT

6. CAUSE-EFFECT

7. OBJECT

8. CATEGORY

9. PROBLEM-SOLUTION:

10. FEELING-ATTITUDE

The Exploratorium in San Francisco has collected excellent resources to assist with this kind of learning:

http://www.exploratorium.edu/IFI/resources/workshops/artofquestioning.html

http://www.exploratorium.edu/IFI/resources/index.html

The Net provides many rich data sources to support this kind of thinking and learning as is amply described in "No Free Lunch on the Internet" - an article published in the January issue of FNO.

http://fno.org/jan2000/freelunch.html