This presentation is based on a US Department of Education grant entitled IMPACT.
The goals are to give teachers in Toledo Public Schools a MA degree in science, retain the teachers in TPS, and improve student achievement and interest in science.
Plan of Study: The program requires completion of a minimum of 30 graduate credit hours to earn a non-thesis Master of Science in Biology degree. All courses are offered at The University of Toledo campus.
The pedagogical focus of the grant is on Project-Based Science, which engages children in scientific inquiry much like a scientist would investigate a real world question.
The PBS course required the teachers to design their own PBS unit for their students. Here is one example.
Here is Mary Lynn taking her students out to the pond on the school’s property to investigate whether they would be willing to go swimming in it.
The IMPACT Student Science Attitudes Survey was based upon Leopold Klopher’s (1971) categories of affective behaviors in science education that cross behaviors with phenomena (elaborate a bit). Our hope was to discover to what extent students in urban high schools internalized positive aspects of science and whether teachers who study advanced content can affect this change. Internalization occurs when a value or phenomenon becomes a part of the individual’s identity. Our survey specifically targeted favorable attitudes towards science and scientists, enjoyment of science, the development of interests in science and science-related activities, and the development of an interest in pursuing a science-related career.
The resulting survey consisted of 19 items—8 on the “value of science” scale and 11 on the “personal perspective of science” scale. The value scale looked at science in the context of society and the perspective scale examined the role of science in the student’s life. The survey has been used in an NSF Gk-12 project for 4 years and the meaning of the scales was determined through a factor analysis. Each item in the survey made a statement about science. Students were asked to indicate their level of agreement with the statements using a four point scale with “agree” at one end of the continuum and “disagree” at the other end. An example of a value question is: Everyone should study science because it affects their lives. An interest/perception of science item: I do not mind if I have to work hard to understand scientific concepts.
256 high school students completed the surveys in Fall 2010 and Spring 2011. We targeted freshman/sophomore level science classes because those courses included a more general (and therefore more representative of the “typical”) student population than upper level science classes. As you can see, we still had over 20% upperclassmen in our study. The classes that were surveyed included general science, biology, life science, and physical science. Because the group sizes were slightly different, we checked for equal variances prior to conducting any statistical analyses.
We used Rasch modeling to analyze the data for several reasons. First, it provides us with reliability indices for both persons completing the survey and items within the survey. Second, it examines our response categories to determine whether our intervals are effectively separating responses. We found, in fact, that the four point scale was redundant with 2 and 3 overlapping. We recoded our scale to 3 responses by combining the 2’s and 3’s into one category. This changed our scale scores to a possible low score of 8/11 and high score of 24/33. Rasch also allows us to convert the ordinal scale into an interval scale so that we can conduct parametric analyses. The conversion also allows us to anchor our scores. Whenever a Rasch analysis is conducted, the results are unique to the specific scores entered. By anchoring scores to the pretest, our posttest scores will reflect the same scale thereby allowing us to make legitimate comparisons.
Scores for students in the treatment and control groups were not statistically significantly different indicating that the groups were equivalent on the variables we measured. Using Rasch, we were able to adjust the scores from both scales to an expected mean of 15. Students in both groups scored right about at the expected mean on both scales. Standard deviations are moderate indicating that the majority of scores hovered between 13 and 19.
Rasch analysis allows us to determine which items in the scale are the easiest and which are the most difficulty for students to agree with. Isolating these items provides a clearer picture of exactly how students perceive science. On the value of science scale, students most frequently agreed with these items:Most people can understand scienceScience is essential for the continued vitality of society.The items that were the most difficult for students to agree with were:Science is relevant to our society (odd--what makes this markedly different from “essential to continued vitality of society?”)I do not need to be a highly trained scientist to understand science. (indicating that much training is required)When we looked at the personal perception of science the items easiest to agree with were:Scientists have to study but not more than other professionalsPeople with good social skills tend to become scientists (that’s good !)The hardest to agree with are a bit more interesting:Science classes are interestingScience should be a required part of everyone’s education.
Posttest scores showed no statistically significant difference within groups (pretest to posttest) or between groups on the posttest. To get a different perspective of possible change, we also looked at effect sizes. As you can see, both groups experienced a small to medium effect size growth (based on Cohen’s d) for the value of science but actually became more negative in their perception of the role science does or may play in their own personal lives. It appears that between the pretest and posttest students actually become less likely to pursue a science career and have less interest in studying science in general.
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Impact what do urban student think about science
What do secondary school students in
high needs urban schools think of
science? A survey of student
perceptions of the value of science.
Charlene M. Czerniak, Professor
Gale A. Mentzer, Evaluator
Funded by the United States Department of Education
Goals of IMPACT
• Increase the number of high quality science teachers in
Toledo Public Schools and the Toledo area by adding 20
science teachers with a MS in Biology degree.
• Maintain a minimum of 90% retention of participants.
• 100% of program completers will remain as science teachers
in TPS or other high needs schools for at least two years after
• Improve student academic achievement in science in IMPACT
• Increase the number of secondary school students enrolled in
upper level science courses by 20% in the schools where
• Increase the number of secondary school students who plan
to pursue postsecondary education in a science-related field
by 15% in the classes taught by IMPACT teachers.
• EEES 6606 Lab and Field Methods Field Ecology
• EEES 6607 Data Mgt & Interpretation
• EEES 6600 Foundations of Ecology
• EEES 6930 Ecology Seminar : Intro to Grad. Studies
• CI 5890 Project Based Science
• EEES 5750 Conservation Biology
• Patterns in Biodiversity: Lab & Field
• Ecological Theory
• EEES 6400 Biostatistics
• EEES 5250 Soil Ecology
• Independent Study
• Master’s Project
Project Based Science (PBS)
Project-Based Science organizes science
class around a driving question.
Instruction focuses on answering the
driving question: investigations,
computer work, library research, class
discussions, and student-designed
experiments Krajcik, J., & Czerniak, C. M. (2007). Teaching Science in
Elementary and Middle School. New York: Taylor & Francis
Michelle, Lisa, and Mary Lynn’s PBS Unit
Would you go swimming in Shanty Creek?
1. What is in the water?
a. Quality Testing
b. Living Organism
2. How does it get in there?
a. What are watersheds
b. Identify Local Systems
Value Scale Mean Standard Dev. Effect Size Interpretation
Treatment 16.56 1.75 0.33 small
Control 16.46 1. 78 0.33 small
Mean Standard Dev. Effect Size Interpretation
Treatment 15.48 1.70 -0.45 medium
Control 15.59 1.68 -0.25 small