Pre- and posttest data comparisons from control groups and a treatment group.
This will be given at the beginning of a physical science unit and highlight students’ prior knowledge of ten specific content vocabulary words. After the intervention period, a posttest will be given that has the same ten content-specific vocabulary words as the pretest; however, the questions will be in a different order. This allows the posttest to be reliable but not identical to the pre-test. An analysis of t-test results from the control and treatment group will be made. This quantitative measure allows me to study the big picture effects of the Frayer model, and to compare student growth during the intervention period.
Analysis of student journals from the treatment group
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During the study period, students will be asked to keep a journal recording their understanding of the ten specific vocabulary words. I am still in the process of finalizing this idea, but I imagine it to be something along the lines of showing their thought process in completing their Frayer models. Upon every instance when a student completes a model for a given vocabulary word, they will complete a journal entry that explains their thinking for each of the four components: definition, characteristics, examples, and non-examples. I will assess these entries and have an unbiased, third-party teacher look at them to compare common themes. This would mean a significant undertaking by both myself and colleague; however, I work in a very supportive science department, and I think this would be a feasible—though time-consuming—option.
Analysis of student Frayer models via rubric for the treatment group
This proposed data collection model involves taking qualitative information from student-generated Frayer models, and quantifying them based on a rubric from 1 to 3 for each of the four Frayer model components. Students will need to write the definition in their own words, list characteristics of the vocabulary word, and give both examples and non-examples. Each category is scored based on accuracy. Granted, this will involve some subjectivity; however, I plan to counter this similar to evaluating student journals via a third-party assessor. The results of this data collection method can show parallels to any words that students missed on either the pre- or posttest, and provide better insight into how the intervention of the Frayer model can be improved for future use.
Using these data collection methods, I believe I will become better informed in relation to vocabulary acquisition of content-specific science vocabulary words, and how the Frayer model can affect such learning. Some possible storylines for the data would be either an increase in content knowledge due to the intervention, a decrease, or stagnation. I believe that by using a mixed-method approach, I will gain a better understanding of how to explain these issues.
Some themes that I might encounter could be how the Frayer model impacts student learning of vocabulary words, how direct instruction through the Frayer model could affect students’ vocabulary knowledge, and how a change in frequency of vocabulary study could potentially benefit student language acquisition. When studying the data, I believe that it is important to look both big picture and on a student-by-student basis to determine which theme best fits. Not every student is the same, and therefore, what works for one might not for another. I believe the same might be true about this potential action research study, but I will have to look at the data to be sure.
