1. Seminar in Applied Theory and Research II By: Peta-Gaye Grey
I’ve Got Style…What’s Your Style? Matching Students With Their Learning Style
Seminar in Applied Theory and Research II
By: Peta-Gaye Grey

2. Table of Contents Method Introduction Results Discussion Implications
Statement of the Problem
Review of Related Literature
Statement of the Hypothesis
Method
Participants (N)
Instrument (s)
Experimental Design
Procedure
Results
Discussion
Implications
References
Appendix (ces)
Consent Forms
Student Surveys
Pre-test
Posttest
Correlation Charts/Tables

3. Statement of the Problem
Educators, Practitioners and Researchers agree that all children can learn, but not all children learn in the same way. Even though we believe this, many of us are not embracing the idea or implementing a change.

4. Theorist Howard Gardner Rita & Kenneth Dunn
According to multiple intelligence theory, there are nine basic types of intelligence.
Rita & Kenneth Dunn
Identification of key learning styles of each student and matching instruction and learning activities with each student's styles.

5. Review of Related Literature (Pros)
We know teaching to the students’ learning style will improve scores (Dunn & Dunn, 1992; Searson & Dunn, 2001)
Teachers deliver content in ways that better match students’ strengths. This leads to increase academic performance and improved attitudes towards school (Beglane, 2001; Dunn et al. 2009; )

6. Review of Related Literature (Cons)
Ivie (2009) states “most of the supporting research cited by the Dunns comes from their own in-house studies of faculty who finished their doctoral work at St. John’s University. Few of this studies meet the standard of having been published in peer-reviewed journals.
The application of learning style theory encompasses three pervasive problems: confusion in definitions, weakness in measurement reliability and validity and identification of relevant learner characteristics (Curry, 1990).

7. Dunn and Dunn Learning Style Model

8. Statement of the Hypothesis
HR1: Integrating preferred learning styles over a six week period to 21 kindergarten students at PS X during math times will increase on-task behavior and increase content knowledge.

9. Method
Participants (N)-The sample for this action research paper was conducted with twenty-one kindergarten students in Brooklyn, New York. The students are from an intact class from a school with middle-to-high income families. The class of consists of 11 boys and 10 girls. Of all the students 50%- White, 10%- Black and 40%- Bi-Racial.

10. Method Instruments Consent forms administered to: Principal Parents
Likert Scale Survey administered to:
Students prior to intervention
Math Assessment
1 Pretest (TERC math program)
1 Posttest (created by the research)

11. Research Design
Pre-Experiment Design: One Group Pretest- Posttest Design
Single Group: Single group is Pre-tested (O), exposed to a treatment (X), and Posttested (O).
Symbolic Design: OX1O

12. Method Procedure
The research was conducted over a four month period from September 2010 to December 2010:
Consent forms were administered to the principal and 21 parents in September 2010.
Pretest was administered to the single group of 21 students in October 2010
Survey was administered to the 21 students in October 2010.
Students were group according to learning preference in November 2010.
Posttest was administered to the 21 students according to the learning preferences.

13. Threats to Internal and External Validity
History: Attendance, poor weather conditions, assemblies, fire drills, school tours and students misbehavior.
Maturation: May not be valid, however one student is older due to the fact that he repeated pre-school.
Testing: The pre-test and posttest is very similar, familiarity could improve scores.
Instrumentation: Researcher created student surveys based on the Dunn and Dunn Learning Style Inventory which was presented by the teacher.
Selection: Non-random student group.
Mortality: Failure to pay tuition, school/parent decision that the school is not the right fit or relocation for a family.
Selection: Students vary in age and gender.
Generalizable Conditions: Same instructor for multiple subjects allows students to adjust to instructors teaching style.
Pre-Test Treatment: The exposure to pre-test questions are likely to have an impact on post-test scores.
Selection-Treatment Interaction: The teacher and student participants were chosen, rather than selected randomly.
Experimenter Effects: The actions of the researcher through observation, whether conscious or unconscious, may affect the performance and responses of the participants.

14. Data of Pretest without Learning Preference
Students
Scores without Preference 1
100% 2
80% 3
90% 4 5 6 7
30% 8
60% 9 10
40% 11 12 13
70% 14 15 16 17 18 19 20 21
Class Average- 76%

15. Results Averages Analytical Learners Global Learners Pretest Posttest
Student
Pretest
Posttest 1
100%
90% 5 8
60%
70% 9 10
40% 11 12 13 20
Student
Pretest
Posttest 2
80%
90% 3 4 6 7
30%
50% 14
100% 15 16
60% 17
70% 18 19 21
Averages
Pretest
Posttest
Global
75%
83%
Analytical
78%
84%

16. Correlation
Correlation of students on-task behavior in mathematics when paired with their learning preferences.
Correlation between students you prefer to work on the floor and test scores.
Question 7- I like to lay on the floor when I am learning new things.
There was a negative correlation between laying on the floor and test scores
Correlation between students who like to sit at a desk and test scores.
Question 8- I like to sit at a desk when I am learning new things.
There was a weak correlation between sitting at a table and test scores 0.125

17. Implications Further research needs to be done
More participants are needed
A longer study needs to be done
A different population needs to be studied

18. Discussions The findings supports previous research
Test scores improved
Correlation was weak and negative
Class average increased
Researchers uncertainty