Mathis ARP Fall 2008

Action Research Project : 

Action Research Project Casey Mathis SCE 5340 Fall 2008 Dr. Davis

Background information : 

Background information Cooperative learning enhances student learning and assists in preparing them to be productive members of society. In Cooperative Learning, Dr. Spencer Kagan (1994) states that “It is hard to imagine a job today which does not involve some cooperative interaction with others. The most frequent reason individuals are fired from a job is not lack of job related skills, but rather lack of interpersonal skills.”

Slide 3: 

I found many articles in my review of literature that supported the use of cooperative learning. Students learn as much from each other, or possibly more, as they do from their teacher. Cooperative learning capitalizes on the students’ natural propensity for interaction. I wondered if there were additional ways to select my groups and if that would impact student learning in my classroom.

Slide 4: 

Research question: How do alternative methods of grouping affect student learning?

Purpose of this study : 

Purpose of this study To determine the effect of group selection on student learning gains. This will be a pretest-posttest control group design that collects quantitative data.

Fall 2007 Action Research Project: : 

Fall 2007 Action Research Project: Four classes were used: First class: Control group randomly selected Second class: Heterogeneously grouped by GRADE (Group Reading Assessment and Diagnostic Evaluation) scores Third class: Heterogeneously grouped by FCAT reading scores Fourth class: Randomly grouped by gender. All boys or all girls in each group.

Results of Fall 2007AR project: : 

Results of Fall 2007AR project:

Mean scores on pretest and posttest : 

Mean scores on pretest and posttest

Mean scores on learning gains between pretest and posttest : 

Mean scores on learning gains between pretest and posttest

Descriptive statistics for the mean scores on the differences between the pretest and posttest : 

Descriptive statistics for the mean scores on the differences between the pretest and posttest

Conclusion from Fall 07 Action Research Project: : 

Conclusion from Fall 07 Action Research Project: Comparing the mean scores of gains between the pre- and posttests seemed to indicate that the class that was randomly grouped, as the control group, had the greatest learning gains.

Slide 13: 

I was surprised to find that the class with the randomly selected groups showed the most gain between the pre-and posttest. I had hypothesized that the heterogeneously grouped classes (using FCAT or GRADE scores) would show more gains. I decided to repeat this study applying statistical analyses acquired from my Statistics for Science Teaching course from the summer of 2008.

Fall 2008Action Research Project: : 

Fall 2008Action Research Project:

Methodology employed : 

Methodology employed The study was conducted using all six of my 7th grade Life Science classes. A total of 148 students were included in this study. A unit pretest and posttest were administered.

Three classes were heterogeneously grouped by FCAT reading levels. : 

Three classes were heterogeneously grouped by FCAT reading levels. These subjects served as my experimental group.

Three classes were randomly grouped. : 

Three classes were randomly grouped. These subjects served as my control group.

Null hypothesis: : 

Null hypothesis: The mean learning gain between the pre- and posttest for the randomly grouped classes will be the same as the mean learning gain for the classes grouped by FCAT reading levels.

Alternative hypothesis: : 

Alternative hypothesis: The mean learning gain between the pre- and posttest for the classes heterogeneously grouped by FCAT reading levels will be greater than the mean learning gain for the randomly grouped classes.

Summary of data: : 

Summary of data: Two-sample problem Group 2 CONTROL GROUP 3 classes Randomly grouped Group 1 EXPERIMENTAL GROUP 3 classes Heterogeneously grouped by FCAT reading levels

Slide 21: 

Goal of inference: comparison of the mean responses in the two populations. Conditions: Samples are independent (3 classes vs. 3 classes) Measuring the same variable for each sample (mean difference between pre- and posttest) Both populations are normally distributed Means and standard deviations are unknown.

Slide 22: 

Variables measured: X1 = first population = FCAT (experimental) group X2 = second population = Random (control) group Four unknown parameters: Mean for X1 Standard deviation for X1 Mean for X2 Standard deviation for X2 Means and standard deviations were calculated using Excel.

DATA ANALYSIS: : 

DATA ANALYSIS:

Test statistic (t) and p-value: : 

Test statistic (t) and p-value: X1 = 49.91 S1 = 18.71 n1 = 70 X2 = 47.22 S2 = 17.56 n2 = 78 t = 0.90 d.f. = 70 – 1 = 69 p = .15 - .20

Slide 25: 

P-value measures strength of evidence against the null hypothesis. Common rule of thumb: a p-value less than 0.05 is statistically significant. This means that it would be rare that the results happened by chance. The p-value of 0.15- 0.20 is high. This indicates a higher likelihood that the difference in mean learning gains occurred by chance. The null hypothesis cannot be rejected.

Discussion: : 

Discussion: What if the same statistics were applied to my results from the Fall of 2007? I had not taken the statistics class before I conducted that action research project.

Slide 27: 

Examining the two classes that were grouped by FCAT reading levels and random grouping (t-test): FCAT mean learning gain = 49 Random mean learning gain = 62 Calculation of p-value = 0.01 to 0.02 Results in this case did not seem to occur by chance. This is evidence contradicting the null hypothesis which stated that there would be no difference in learning gain.

Conclusion: : 

Conclusion: Analysis of data from the Fall 2007 action research project indicated that the random group had greater learning gains than the FCAT group. Analysis of data from the Fall 2008 action research project indicated that there was no difference in learning gains between the two groups.

Slide 29: 

The analysis of data indicated that the method for selecting groups may not affect learning gains as much as the expected outcome of this study. Intentional group selection encourages group members to learn and socialize in different ways. Students who normally do not socialize are encouraged to interact.

Slide 30: 

Heterogeneous grouping increases tolerance and gives students ways to deal with diversity. This mirrors what students will face in the real world. My action plan will be to continue to utilize cooperative learning as one, but not the only, classroom strategy to increase student learning. Further data will be conducted throughout the school year to validate results from the previous two studies.

Resources necessary: : 

Resources necessary: Collier County Public Schools Data Warehouse: http://test.collier.k12.fl.us/welcome.aspx Glencoe Science Professional Series (2008). Cooperative Learning in the Science Classroom.Columbus, Ohio: Glencoe McGraw-Hill.

Slide 32: 

Johnson, D. and Johnson, R (1997) Cooperative Learning: Two heads learn better than one. Retrieved on November 18, 2007 from http://www.context.org/ICLIB/IC18/Johnson.htm Kagan, S. (1994) Cooperative learning. Chapter one. California: Kagan

Slide 33: 

Marzano, R., Pickering, D., & Pollock, J. (2001) Classroom instruction that works: Research-based strategies for increasing student achievement. Chapter seven. pp.86-101. Alexandria, Virginia: Association for Supervision and Curriculum Development

Slide 34: 

Mertler, C. (2006) Action research: Teachers as researchers in the classroom. Chapter four. Thousand Oaks: Sage Publications Yates, D., Moore, D., & Starnes, D. (2003) The practice of statistics: TI-83/89 Graphing calculator enhanced. Second edition. Chapter eleven. pp. 648-672. New York: W.H. Freeman and Company