Teachers of Science in the middle school usually face a problem of balancing between theory and practice in their instructions and activities (Kelly, 2014). According to McDaniel, Thomas, Agarwal, McDermott, and Roediger (2013), educators need to pay much attention to integrating the laboratory work and practical activities into the Science curriculum in order to address the learning needs of students. Smart and Marshall (2013) support this idea, stating that practical tasks and the laboratory work contribute to understanding theoretical concepts related to the field of chemistry and physics. From this point, it is important to ask the question regarding the possible difference between the performance of those students who are good at their laboratory work and those students whose results are average or low (Mandler, Mamlok-Naaman, Blonder, Yayon, & Hofstein, 2012; Talanquer, 2013). The question to answer in the proposed research is the following one: Do the Science test results differ between the students who have high marks for their laboratory work, who have average marks, and those students who have poor marks? To examine the statistically important difference between the determined groups of students from the middle school, it is appropriate to use the one-way ANOVA.
Methods
Participants
The sample for this study will include 42 students recruited from three classes (grade 8) at Robert Frost Middle School, Rockville, Maryland. It is important to use the stratified random sampling because students from each class will be divided into such strata as students having high, average, and low marks for their laboratory work (Tipton, Hedges, Vaden-Kiernan, Borman, & Sullivan, 2014). Participants will be randomly selected from each stratum to reduce the possibility of errors. Students will be different in terms of their gender, age, and ethnicity, but these demographic characteristics will not be taken into account while analyzing the study results.
Procedures
In this study, the independent variable is the students’ performance regarding the laboratory work. The variable is nominal (categorical), and it will be measured in relation to receiving high, average, or poor marks for the laboratory work. The students’ performance regarding the Science test is the dependent variable that is ratio according to the scale, and it will be measured in 0-100 scores. Thus, the participants will be divided into three groups (having high, average, and poor marks for the laboratory work), and they will be proposed to conduct the Science test, the results of which will be measured using 0-100 scores.
Results
The one-way ANOVA will be used as the statistical test to analyze the collected data. The reason to use the one-way ANOVA is in the fact that the study’s independent variable is categorical, and it has three factors to influence one continuous dependent variable (Hsieh, Lee, & Chu, 2013). While using the ANOVA design, it will be possible to state whether differences between test scores of students are observable and statistically significant. Differences will be analyzed with reference to the F distribution (Ostertagova & Ostertag, 2013).
Discussion
The study results will allow for speaking about the role of practice and laboratory work in influencing the learning of Science in the middle school with reference to the experience of students from grade 8. However, the study will demonstrate only the possible difference between test scores of students having different results in relation to their laboratory work. The use of the ANOVA test will not allow for concluding regarding the cause-and-effect relationships, as well as regarding differences between concrete groups. To address these limitations, it will be necessary to conduct the post-hoc test to add to the discussion of differences in results or conduct the experiment to analyze the relationships between variables. The practical significance of the anticipated results is in attracting the educators’ attention to the integration of the laboratory work into studying Science in the middle school.
References
Hsieh, Y. C., Lee, C. I., & Chu, K. K. (2013). Effect of innovative ontology-based approach on learning performance of students with ANOVA method. International Journal of Applied Mathematics and Statistics, 38(8), 191-201.
Kelly, N. (2014). Teaching science in elementary and middle school: A project-based approach. Interdisciplinary Journal of Problem-Based Learning, 8(1), 8-16.
Mandler, D., Mamlok-Naaman, R., Blonder, R., Yayon, M., & Hofstein, A. (2012). High-school chemistry teaching through environmentally oriented curricula. Chemistry Education Research and Practice, 13(2), 80-92.
McDaniel, M. A., Thomas, R. C., Agarwal, P. K., McDermott, K. B., & Roediger, H. L. (2013). Quizzing in middle‐school science: Successful transfer performance on classroom exams. Applied Cognitive Psychology, 27(3), 360-372.
Ostertagova, E., & Ostertag, O. (2013). Methodology and application of one-way ANOVA. American Journal of Mechanical Engineering, 1(7), 256-261.
Smart, J. B., & Marshall, J. C. (2013). Interactions between classroom discourse, teacher questioning, and student cognitive engagement in middle school science. Journal of Science Teacher Education, 24(2), 249-267.
Talanquer, V. (2013). School chemistry: The need for transgression. Science & Education, 22(7), 1757-1773.
Tipton, E., Hedges, L., Vaden-Kiernan, M., Borman, G., & Sullivan, K. (2014). Sample selection in randomized experiments: A new method using propensity score stratified sampling. Journal of Research on Educational Effectiveness, 7(1), 114-135.