Dr. William Allan Kritsonis, PhD Dissertation Chair for Dr. Michelle Annette Cloud, PhD Program in Educational Leadership, PVAMU, Member of the Texas A&M University System.
80 ĐỀ THI THỬ TUYỂN SINH TIẾNG ANH VÀO 10 SỞ GD – ĐT THÀNH PHỐ HỒ CHÍ MINH NĂ...
Dr. Michelle Annette Cloud, PhD Dissertation Defense, Dr. William Allan Kritsonis, Dissertation Chair
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14. Conceptual Framework Students often learn a great deal simply by observing other people Teachers and parents must model appropriate behaviors and take care that they do not model inappropriate behaviors Students must believe that they are capable of accomplishing school tasks Describing the consequences of behavior can effectively increase the appropriate behaviors and decrease in appropriate ones Factors Impacting Student Success During “School of Choice” Transition Teachers should help students set realistic expectations for their academic accomplishments Modeling provides an alternative to shaping for teaching new behaviors Teachers should expose students to a variety of other models Self-regulation techniques provide an effective method for improving student behavior Diagrammatic format of Ormrod’s (1999) findings developed from Albert Bandura’s Social Learning Theory
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23. Extant data from the 2005/2006 and 2006/2007 Mathematics and Reading TAKS Test were used to determine if differences existed between the 2005/2006 Mathematics and Reading TAKS scores and the 2006/2007 Mathematics and Reading TAKS scores of transfer students and non-transfer students in grades 6-8. Instrumentation
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60. References Bandura, A. (1993). Perceived self-efficacy in cognitive development and functioning. Educational Psychologist, 28 , 117-148. Bandura, A. (1997). Self-efficacy: The exercise of control. New York: W.H. Freeman. Bandura, A. (1986). Social foundations of thought and action . Englewood Cliffs, NJ: Prentice-Hall . Crain, W. (2000). Theories of development: Concepts and applications . Upper Saddle River, NJ: Prentice Hall. Fowler-Finn, T. (2001). Student stability vs. mobility. School Administrator , 58 (7), 36-40. Fraenkel, J., & Wallen, N. (2006). How to design and evaluate research in education. 6th ed. New York: McGraw Hill. Isaac, S. & Michael, W. (1997). Handbook in Research and Evaluation for Education and the Behavioral Sciences (3rd ed.) San Diego, CA: EdiTs/Educational and Industrial Testing Services. Kerbow, D. (1996). Patterns of urban student mobility and local school reform. Journal of Education for Students Placed At Risk , 1 (2). Kretchmar, J. (2008). Social Learning Theory . (pp. 1-1). Great Neck Publishing. Retrieved March 1, 2009, from the Research Starters - Education database. Ormrod , J. E. (1999). Human learning (3rd ed) Upper Saddle River, NJ: Prentice-Hall. Public Agenda, 1999).
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Notes de l'éditeur
A.Y.P. - “Under the accountability provisions in the No Child Left Behind (NCLB) Act, all public school campuses, school districts, and the state are evaluated for Adequate Yearly Progress (AYP). Districts, campuses, and the state are required to meet AYP criteria on three measures: Reading/Language Arts, Mathematics, and either Graduation Rate (for high schools and districts) or Attendance Rate (for elementary and middle/junior high schools).”
Research Methods This study is a mixed-method design. Triangulation - when two different methods are used in an attempt to confirm, cross-validate, or corroborate findings within a single study (Creswell, 1998).
T-tests are “ . . . used to compare means scores of two different, or independent, groups” (Fraenkel & Wallen, 2006, p. 233).
Structured interviews “. . . consist of a series of questions designed to elicit specific answers from respondents” (Fraenkel & Wallen, 2006, p. 455). Demographic information will include: gender, age, ethnicity, years of experience in education and years of experience in counseling and total years in current position. Semistructured interviews (see Appendix I) assist the researcher in “. . . (obtaining) information that can later be compared and contrasted” (Fraenkel & Wallen, 2006, p. 455). Fraenkel & Wallen (2006) explain that semistructured interviews “. . . are often best conducted toward the end of a study . . . (and) are most helpful for obtaining information to test a specific hypothesis that the researcher has in mind” (p. 455) “Feeling questions concern how respondents feel about things” (Fraenkel & Wallen, 2006, p. 458). “Sensory questions focus on what a respondent has seen, heard, tasted, smelled or touched” (Fraenkel & Wallen, p. 458).
The subjects of the study were sixth through eighth grade students from two campuses from one large school district in Texas. The transfer students will be a criterion case, which entails criterion sampling. The criteria for selecting cases in this study will be all transfer students that elected to transfer. There will be a total of 100 transfer students from School A and a total of 68 transfer students from School B. The total number of transfer students will be 168. Stratified random sampling will be utilized to select the cases of non-transfer students. “Stratified random sampling is a process in which certain subgroups, or strata, are selected for the sample in the same proportion as they exist in the population” (Fraenkel & Wallen, 2006, p. 96). The number of non-transfer students will equal to the number of cases of transfer students and will be similar in certain demographics.
Criterion sampling entails selecting cases “. . . that meet some predetermined criterion of importance” (Isaac & Michael, 1997, p. 224). According to Isaac & Michael, these cases “. . . are likely to be information rich because they reveal major system weaknesses (or strengths) leading to program improvement” (Isaac & Michael, p. 224).
Descriptive statistics were analyzed and frequencies and percentages were presented in table format.
T-tests for independent means were used to compare means to answer the research questions for the quantitative portion of the study. The researcher applied the standard alpha level: 0.05. The rejection rule was applied. The null hypotheses was rejected if the 2-tailed significance level is less than 0.05.
Peer debriefing - strategy used to provide the researcher with insight and assist in reviewing the methods and findings (Spall, 1998). The researcher used peer debriefing to work collaboratively with a peer who had general knowledge of the study. Peer debriefing sessions provided feedback to the researcher and provided the research with insight. Peer debriefing also assisted the researcher in reviewing the researcher’s methods and findings. Triangulation - when two different methods are used in an attempt to confirm, cross- validate, or corroborate findings within a single study (Creswell, 1998).
Of the 168 transfer students, 52.4% were female and 47.6% were male. Of the 168 non-transfer students, 57.1% were female and 42.9% were male.
In regard to the total number of transfer students, 42.2% were African-American, 3% were Caucasian, 39.9% were Hispanic and 14.9% were other, not of the aforementioned races. Stratified random sampling was used and the percentages for non-transfer students were the same as for transfer students.
Of the 168 transfer students 66.7% were in grade 6, 16.1% of transfer students were in grade 7 and 17.3% of transfer students were in grade 8. Of the 168 non-transfer students 67.3% were in grade 6, 16.1% of non-transfer students were in grade 7 and 16.8% of non-transfer students were in grade 8.
Of the total number of transfer students, 54.8% were economically disadvantaged and 45.2% of transfer students were not economically disadvantaged. Stratified random sampling was used and the percentages for non-transfer students were the same as for transfer students
The t-test indicated that the difference of 62.65 was statistically significant since the significance level (2-tailed) was equal to .05. Therefore, the null hypothesis was rejected. There was a statistically significant difference between the 2006/2007 Mathematics Texas Assessment of Knowledge and Skills scores between transfer and non-transfer students in grade 6.
The mean difference between the 2005/2006 Mathematics Texas Assessment of Knowledge and Skills was 213.60. The t-test indicated that the difference of 213.60 was statistically significant since the significance level (2-tailed) was less than .05. Therefore, the null hypothesis was rejected. There was a statistically significant difference between the 2005/2006 Mathematics Texas Assessment of Knowledge and Skills scores between transfer and non-transfer students in grade 7. The mean difference between the 2006/2007 Mathematics Texas Assessment of Knowledge and Skills was 59.69. The t-test indicated that the difference of 59.69 was not statistically significant since the significance level (2-tailed) was more than .05. Therefore, the null hypothesis was accepted. There was no statistically significant difference between the 2006/2007 Mathematics Texas Assessment of Knowledge and Skills scores between transfer and non-transfer students in grade 7.
The mean difference between the 2005/2006 Mathematics Texas Assessment of Knowledge and Skills was 213.60. The t-test indicated that the difference of 213.60 was statistically significant since the significance level (2-tailed) was less than .05. Therefore, the null hypothesis was rejected. There was a statistically significant difference between the 2005/2006 Mathematics Texas Assessment of Knowledge and Skills scores between transfer and non-transfer students in grade 7. The mean difference between the 2006/2007 Mathematics Texas Assessment of Knowledge and Skills was 59.69. The t-test indicated that the difference of 59.69 was not statistically significant since the significance level (2-tailed) was more than .05. Therefore, the null hypothesis was accepted. There was no statistically significant difference between the 2006/2007 Mathematics Texas Assessment of Knowledge and Skills scores between transfer and non-transfer students in grade 7.
The mean difference between the 2006/2007 Reading Texas Assessment of Knowledge and Skills was 67.95. The t-test indicated that the difference of 67.95 was statistically significant since the significance level (2-tailed) was less than .05. Therefore, the null hypothesis was rejected. There was a statistically significant difference between the 2006/2007 Reading Texas Assessment of Knowledge and Skills scores between transfer and non-transfer students in grade 6.
The mean difference between the 2005/2006 Reading Texas Assessment of Knowledge and Skills was 200.53. The t-test indicated that the difference of 200.53 was statistically significant since the significance level (2-tailed) was less than .05. Therefore, the null hypothesis was rejected. There was a statistically significant difference between the 2005/2006 Reading Texas Assessment of Knowledge and Skills scores between transfer and non-transfer students in grade 7. The mean difference between the 2006/2007 Reading Texas Assessment of Knowledge and Skills was 150.42. The t-test indicated that the difference of 150.42 was statistically significant since the significance level (2-tailed) was less than .05. Therefore, the null hypothesis was rejected. There was a statistically significant difference between the 2006/2007 Reading Texas Assessment of Knowledge and Skills scores between transfer and non-transfer students in grade 7.
The mean difference between the 2005/2006 Reading Texas Assessment of Knowledge and Skills was 42.87. The t-test indicated that the difference of 42.87 was not statistically significant since the significance level (2-tailed) was more than .05. Therefore, the null hypothesis was accepted. There was not a statistically significant difference between the 2005/2006 Reading Texas Assessment of Knowledge and Skills scores between transfer and non-transfer students in grade 8. The mean difference between the 2006/2007 Reading Texas Assessment of Knowledge and Skills was -86.39. The t-test indicated that the difference of -86.39 was not statistically significant since the significance level (2-tailed) was more than .05. Therefore, the null hypothesis was accepted. There was not a statistically significant difference between the 2006/2007 Reading Texas Assessment of Knowledge and Skills scores between transfer and non-transfer students in grade 8.
The mean difference between the 2005/2006 Mathematics grade point averages was 8.0. The t-test indicated that the difference of the 8.0 was statistically significant since the significance level (2-tailed) was less than .05. Therefore, the null hypothesis was rejected. There was a statistically significant difference between the 2005/2006 Mathematics grade point averages between transfer and non-transfer students in grade 7. The mean difference between the 2006/2007 Mathematics grade point averages was 3.22. The t-test indicated that the difference of 3.22 was not statistically significant since the significance level (2-tailed) was more than .05. Therefore, the null hypothesis was accepted. There was not a statistically significant difference between the 2006/2007 Mathematics grade point averages between transfer and non-transfer students in grade 7.
The mean difference between the 2005/2006 Reading grade point averages was 4.40. The t-test indicated that the difference of 4.40 was not statistically significant since the significance level (2-tailed) was more than .05. Therefore, the null hypothesis was accepted. There was not a statistically significant difference between the 2005/2006 Reading grade point averages between transfer and non-transfer students in grade 7. The mean difference between the 2006/2007 Reading grade point averages was 2.44. The t-test indicated that the difference of 2.44 was not statistically significant since the significance level (2-tailed) was more than .05. Therefore, the null hypothesis was accepted. There was not a statistically significant difference between the 2006/2007 Reading grade point averages between transfer and non-transfer students in grade 7.
The mean difference between the 2005/2006 Mathematics grade point averages was -0.89. The t-test indicated that the difference of -0.89 was not statistically significant since the significance level (2-tailed) was more than .05. Therefore, the null hypothesis was accepted. There was not a statistically significant difference between the 2005/2006 Mathematics grade point averages between transfer and non-transfer students in grade 8. The mean difference between the 2006/2007 Mathematics grade point averages was -2.55. The t-test indicated that the difference of -2.55 was not statistically significant since the significance level (2-tailed) was more than .05. Therefore, the null hypothesis was accepted. There was not a statistically significant difference between the 2006/2007 Mathematics grade point averages between transfer and non-transfer students in grade 8.
The mean difference between the 2005/2006 Reading grade point averages was -3.66. The t-test indicated that the difference of -3.66 was not statistically significant since the significance level (2-tailed) was more than .05. Therefore, the null hypothesis was accepted. There was not a statistically significant difference between the 2005/2006 Reading grade point averages between transfer and non-transfer students in grade 8. The mean difference between the 2006/2007 Reading grade point averages was -0.95. The t-test indicated that the difference of the -0.95 was not statistically significant since the significance level (2-tailed) was more than .05. Therefore, the null hypothesis was accepted. There was not a statistically significant difference between the 2006/2007 Reading grade point averages between transfer and non-transfer students in grade 8.
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