Richard S. Croft

1. The Effect of Attribute Emphasis in Photographic Illustrations on Concept Attainment by Learners having Varying Degrees of Field Dependence Richard S. Croft

2. Overview • Introduction • Concept Learning • Illustrations for Instruction • Field Dependence • The Hypotheses • The Experiment • Results and Analyses • Conclusion

3. Introduction • Common learning task:Classification of things or ideas based on characteristics • AKA Concept Learning or Concept Attainment

4. Introduction • Learning concrete concepts is a very visual task • Best to use genuine instances to teach? • Lions, tigers and bears (oh, my!) • Illustrations are frequently more practical

5. Introduction • What kind of illustration is most effective? • Much-studied, frustrating issue

6. Introduction • Field dependence:individual’s ability to impose structure on a perceived field • Field dependent learners less successful at visual tasks

7. Introduction • How can we choose illustrations to help in concept learning? • Can we develop visual treatments to assist field dependent learners in concept learning?

8. Concept Learning: Terminology • Concept: “…a partitioning of a stimulus population.” (Bourne, 1970) • Concept attainment: “…the subject must learn a rule for classifying objects into mutually exclusive categories.” (Mayer, 1977)

9. Terminology • Rules for classification describe specific characteristics • Attributes (Bruner, Goodnow, & Austin, 1956) or cues (Trebasso, 1963) are characteristics • Attributes may be critical or non-critical

10. Terminology • Attributes represent values within a dimension (color may be red or green)

11. Strategies • Bruner, Goodnow, Austin (1956) • Selection strategies: Focusing & Scanning • Presentation strategies: Wholist & Partist • Focusing and Wholist more effective

12. Transfer • (Di Vesta & Peverly, 1984) • Learning from a wide variety of instances reduces the chance that non-critical attributes become bound in learner’s conceptualization • Wider application ==better transfer

13. Task Complexity • Increased number of dimensions increases difficulty of learning…even irrelevant dimensions (Bourne & Haygood, 1959, 61) • Subtle distinctions increase difficulty(Baum, 1954;Battig & Bourne,1961)

14. Apparent Familiarity of Domain • Bruner et al. (1956) • Concepts that seem to lie within a familiar domain are harder to learn than unfamiliar concepts with identical complexity

15. Assisting Concept Learning • Presentation ModeKoran, Koran, & Freeman (1976)Di Vesta & Peverly (1984):Defining important characteristics first facilitates concept learning

16. Assisting Concept Learning • Park (1984):Pointing out criteria is not enoughUnderstanding the definition in contextual form is important too

17. Assisting Concept Learning • Modifying ExamplesTrabasso (1963) and Turner (1983) • Emphasizing subtle attributes helps • Type of emphasis is significant

18. Instructional Illustration • Intrinsically visual tasks benefit from illustration…verbal tasks usually don’t • Types of images vary greatlyChoice of illustration depends on many factors • Recognition & Recall factors

19. Image selection Factors • Dwyer (1967, 1968, 1975), and many othersLesson PacingPrior KnowledgeGeneral IntelligenceSpecial Illustrations

20. Recognition Factors • Fleming & Sheikhan (1972):Amount of detail X Viewing timeinfluences recognition • Berry (1983):Color (realistic or not) increases recognition

21. Recall • Moore & Sasse (1971):Image detail X Age of viewer • Katzman & Nyenhuis (1972):Color vs. GrayscaleViewers liked color betterBut recall was no different except for peripheral information

22. Recall • Berry (1991):Realistic color, non-realistic color, and grayscaleRealistic color yielded best recall • Differences may be due to age of participants and nature of content

23. Field Dependence • Asch & Witkin (1948):Individuals’ determining “upright”Body Adjustment Test (BAT)Rod and Frame Test (RFT)Internal vs. External cues • Witkin, Dyk, Faterson, Goodenough, & Karp (1962): Disembedding figures

24. Field Dependence Individual scores on BAT, RFT and EFT (Embedded Figures Test) correlate. Individuals who rely heavily on external rather than internal cues tend to have difficulty with visual tasks.

25. FD Effects on Learning • Detecting subtle cues (Moore & Gross, 1973) • Slective attention (Avolio, Alexander, Barret, & Sterns, 1981) • Automatize simple sequences (Jolly & Reardon, 1985)

26. FD & Concept Learning • Kirschenbaum (1968):FI learners tend to use Wholist strategyFD learners tend to use Partist strategy • Park (1984):FD learners seem to rely on external examples rather than organizing their own

27. FD & Transfer • Frank (1983):Paired association taskFree recall: no difference between FD & FIAlternate context: FI outperform FD

28. FD & Illustrations • Canelos & Taylor (1981), Canelos, Taylor & Altschuld (1983).Wise (1984):No interaction between complexity and degree of FD using Dwyer’s material

29. FD & Illustrations • French (1984):Illustrating concept-learning task Color coded line drawings improve performance of FD learners

30. Conclusions • Increasing number of attribute dimensions increases difficulty of concept learning • Increased information requires more processing time • Reducing complexity speeds processing but may inhibit transfer • Emphasizing important attributes facilitates learning

31. Conclusions • Field dependent learners have more difficulty articulating complex images • FD learners have greater difficulty with transfer • Color coding images seems to help FD learners identify salient attributes

32. A Real World Problem University students learning a large number of plant or animal species in short time. Many dimensions, both relevant and irrelevant; limited time, limited feedback.Need to transfer to non-classroom settings.

33. Proposed Solution Use realistic illustrations to facilitate transfer Emphasize important attributesEmphasis should provide particular benefit to FD learners

34. Hypothesis One Learners presented a lesson on tree identification illustrated with photographs having emphasized criterial attributes will score higher on post-tests than learners presented a similar lesson that uses unmodified photographs.

35. Hypothesis Two Field independent learners will score higher on the post tests than field dependent learners, regardless of the type of illustration.

36. Hypothesis Three Field dependent participants in the treatment group will demonstrate a greater increase in performance than their field independent counterparts.(There will be a positive interaction between the treatment and degree of field dependence)

37. Methodolgy • Pretest (“Introductory Survey”) to rule out individuals with prior knowledge of dendrology. • Group Embedded Figures Test (GEFT) to determine degree of FD • Computer-based lesson on identifying red maple, sugar maple, norway maple, and silver maple by looking at leaves.

38. Methodology • Thirty second delay. • Computer-based post-test of fifteen randomly selected stimuli • Transfer test of 20 randomly chosen genuine leaves mounted on card stock • Random assignment to group • 115 voluntary participants

41. Results • 31 FD participants • 46 FI participants • 38 indeterminant (mean GEFT +/- 1/2 SD)

42. Analysis • Bartlett’s test for homogeneity of means failed, so assumptions for ANOVA were not satisfied • Use t tests for hypotheses one and two

43. T-test of Treatment Effect

44. Effect of FD

45. Interaction • No ANOVA • However, inspection shows that FD participants scores were almost identical in all conditions, so interaction is ruled out

46. Conclusions • Overall, treatment improved performance both in the computer-based test and in the transfer test. • FI learners performed better in all cases. • There was no evidence of interaction between the treatment and degree of field dependence.

47. Further Study • Pacing may be a variable to examine. • What about the nature of emphasis? • Combining the materials with some form of practice to encourage internalizing. • Correct possible flaws in instruments.

49. Treatment Effect