Francene Leonce & Pamela Ledbetter Education 703.22- Spring 2009 Professor O’Connor-Petruso.

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Presentation transcript:

Francene Leonce & Pamela Ledbetter Education Spring 2009 Professor O’Connor-Petruso

 Research Design  Threats to Internal Validity  Threats to External Validity  Proposed Data  Correlational Graphs  References

*Quasi-Experimental-Two Groups *Two groups (or more) are exposed to a treatment (X), and post tested (O). Groups (not individuals) are randomly assigned. one designated treatment for both groups (X¹) & (X²).  *Symbolic Design:  O X 1 O  O X 2 O

 History * There are many factors within the lives of our students that may sway the results of the research. Some of these may be lateness, absences, and illnesses. Also due to the fact that the students may have not eaten breakfast, or may have had a fight with their caregiver. Within the classroom, distractions can have an effect on the outcome of the surveys as well, especially in an inclusive population. For example, telephone calls, fire drills, shelter drills, announcements, outbursts, snow, rain, a piece of flying lint etc.  Maturation * Maturity may pose as a threat to the validity of our research in that some of the improvement in their achievement may simply be a result of the students’ inner maturity making them more apt to tackle specific tasks. Especially in a kindergarten classroom where the ages range from 4 through 6, maturation must be taken into consideration.  I nstrumentation * Students may respond to different personalities differently.

 Mortality * Students may be transferred or discharged to other schools thus altering the data.  Differential Selection of Subjects Two different groups: a second grade gifted class and an inclusion kindergarten class. Testing Pre and post testing may affect results due to familiarity of the directions and expectations the second time. Selection- Maturation Interaction  Children develop at different rates and in their own time. Boys and girls have different maturity schedules, culture and home-life may play a part in the maturity levels of our students

 Pretest Treatment * Familiarity with directions and format.  Selection-Treatment Interaction *Not a random selection of students/parents.  Treatment Diffusion *Interaction during the survey may allow for imitation of answers.  Experimenter Effects *The administrator’s mood, enthusiasm or lack thereof may encourage or discourage the student’s answers during the research.

4 Strongly Agree 3 Somewhat Agree 2 Somewhat Disagree 1 Strongly Disagree I really want to learn. I like to learn. I love to read. I read books often. I spend lots of time reading with my mom or dad. I get help at home with homework and school projects. I am doing well in reading and writing. I would do better at school if my mom or dad would help me more often. My parents read a lot. I prefer to read alone.

AttitudesMid Year Kindergarten TowardsReading Participant #Reading (X) Levels (Y) 1252 rxy =

AttitudesMid Year 2nd Grade TowardsReading Participant #Reading (X) Levels (Y) rxy = nd Grade Correlation Data

 In our research, we have been analyzing the effects of single parenting on the academic achievement of our students. One of the variables that we have considered was the impact that the children’s attitude may have on the effects of their learning. Each student was given a survey to determine how they felt about reading, being read to and school as a whole. We correlated the cumulative scores for each student survey to their mid-year reading levels and found an extremely strong relationship. The correlations for both samples of students, kindergarten and 2 nd graders, revealed that students who have a good attitude towards school and reading had better reading scores than students who did not. The scores were (.870rxy) for the second grade which is a very good positive correlation and (.911rxy) for the kindergartners which shows an even higher positive correlation. Both of these correlations show the better student’s attitudes are, the better their reading scores tend to be.

O’Connor-Petruso, Sharon. A. (2009, February 5). Descriptive & Inferential Stats, Analyses, Threats, & Designs. Presented at an Ed lecture at Brooklyn College.