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Correlation of Reasoning Ability and Secondary Science Achievement

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Review of Related Literature

With the introduction of the No Child Left Behind (NCLB) act, increased emphasis has been placed on student achievement in mathematics and reading (Kinniburgh & Shaw, 2009). Science was later added to the assessment requirements (Kinniburg & Shaw). Schools who fail to make adequate yearly progress, or AYP, in the disciplines of mathematics, reading, and science will be penalized (No Child Left Behind revisited, 2008). Schools identified as needing improvement must provide transportation for students to other schools which don't fall under this classification and/or provide academic tutoring to students at no cost to the students or their families (Overview of No Child Left Behind, 2008).

Students with designated learning disabilities are provided with accommodations, but are nonetheless measured against the same standards under the No Child Left Behind Act (Hobart, 2008). NCLB evaluates a school's preparation of low socioeconomic status populations, but does nothing to help the school overcome the resultant challenges (Smyth, 2008). Kohen-Raz (1969) included a myriad of factors that might affect the development of formal thought when investigating a relationship between physical growth and mental development. The results included a strong correlation of the primary confounding variables, "socioeconomic status and parental education background" (Kohen-Raz, p. 91) with how quickly students develop more advanced reasoning skills.

In a study of twelfth-grade students, Valanides (97) discovered that less than half (49.7%) were operating at full formal reasoning and less than 17% were to be considered rigorous formal. When Yenilmez and Tekkaya (2006) studied the relationship between reasoning ability and master of the concepts of photosynthesis and respiration, they found a performance gap between students based on cognitive developmental stage. Students who scored low in formal reasoning perform poorly in relation to students who scored higher when asked to draw conclusions about the importance of photosynthesizing plants to other organisms (Yenilmez, Sungur, & Tekkaya, 2006).

Kuhn, Ho, and Adams (1979) conducted a study in which they compared the formal reasoning capabilities of college students with late elementary-age students. They found while some college students do not immediately display formal thinking when presented with a problem, they are more readily coached (Kuhn, Ho, & Adams, 1979). In a study which challenged students to conduct a single experiment to test three variables affecting microorganism growth, Huppert, Lomask, and Lazarowitz (2002) found that integration of technology, in the form of computer simulations, enabled students who otherwise operated at concrete or transitional reasoning level successfully perform task that require formal reasoning.

Problem Statement

The purpose of this study is to investigate for a correlation between an Eastern Kentucky high school students' capacity for formal reasoning and their achievement on science assessments.


There will be a positive correlation between students formal reasoning abilities and their achievement on science assessments correlated to the Kentucky Core Content for assessment.

Operational definitions

Formal (abstract) Reasoning (thought): The stage of cognitive development where an individual is capable of interpreting informational patterns of varying complexity and make reasonable judgments and predictions.

Science assessments: End of chapter and/or unit exams correlated to the state-mandated curriculum for instruction and assessment.

Significance of the study

High school students are mandated to learn about many concepts that relate to making predictions and generalizations about abstract ideas such as atomic structure, composition of stars, cell functions, genetics, and chemical reactions. If students who have not fully developed formal reasoning consistently struggle on science assessments, it stands to reason they are being tested over materials that are too advanced for their cognitive developmental stage. High schools would subsequently be held accountable for teaching students the content regardless of whether it is appropriate for their level of cognitive operation. If this study proves consistent with the previous research already referenced in the literature review it will further add to concerns about the suitability of the Kentucky Core Content for Assessment.


Research Design

This is a correlational study conducted in a population of mostly 11th graders with some 12th graders who, as vocational students, had not received the full science content prior to the end of their 11th grade year. The subjects were all enrolled in a science class where the chemistry and physics portion of the state science content was taught.


A convenience sample of all students in each of three classes was used. Students who were not present for the original date of the abstract reasoning exam were excluded from the study, since the answers were reviewed in the time immediately the test.


Two end of chapter assessments were used to measure science achievement. The exams were constructed using test generating software aligned to the state curriculum standards. The first was over changes in matter such as distinguishing between chemical and physical changes and behavior of confined gases. The second exam dealt specifically with chemical reactions and included tasks such as classifying types of reactions and balancing chemical equations. Formal reasoning was measured with a free practice test obtained from . All tests were multiple-choice. The science assessments were not timed, but the usual completion time is approximately 40 minutes for the entire class. Students were given only 30 minutes for the abstract reasoning test, but all of them finished in less time. The number of questions the students got correct on the abstract reasoning was compared for correlation to the percentage and average percentage scores for the classroom science assessments.

Data Analysis

The data was entered into spreadsheet software and a linear regression performed on scatter plot of the entire population and each class. The software was used to compute an R2 coefficient of determination. Correlation values were then determined from



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