Many United States secondary students perform poorly on standardized summative science assessments. Situated Assessments using Virtual Environments (SAVE) Science is an innovative assessment project that seeks to capture students' science knowledge and understanding by contextualizing problems in a game-based virtual environment called Scientopolis. Within Scientopolis, students use an "avatar" to interact with non-player characters (NPCs), artifacts, embedded clues and "sci-tools" in order to help solve the problems of the townspeople. In an attempt to increase students' success on assessments, SAVE science places students in an environment where they can use their inquiry skills to solve problems instead of reading long passages which attempt to contextualize questions but ultimately cause construct-irrelevant variance. However, within these assessments reading is still required to access the test questions and character interactions. This dissertation explores how students' in-world performances differ when exposed to a Reading Aloud Accommodation (RAA) treatment in comparison to a control group. Student perceptions of the treatment are also evaluated. While a RAA is typically available for students with learning disabilities or English language learners, within this study, all students were randomly assigned to either the treatment or control, regardless of any demographic factors or learning barriers. The theories of Universal design for learning and brain-based learning advocate for multiple ways for students to engage, comprehend, and illustrate their content knowledge. Further, through providing more ways for students to interact with content, all students should benefit, not just those with learning disabilities. Students in the experimental group listened to the NPCs speak the dialogue that provides them with the problem, clues, and assessment questions, instead of relying on reading skills to gather the information. Overall, students in the treatment group statistically outperformed those in the control. Student perceptions of using the reading aloud accommodation were generally positive. Ideas for future research are presented to investigate the accommodation further. / CITE/Mathematics and Science Education

This research studied the impact of technology integration during science lessons to help prepare fourth graders in a suburban elementary school for the Kansas State Science Assessment. The three instructional methods considered were inquiry-based learning and direct instruction without technology use; inquiry-based learning and direct instruction using laptops; inquirybased learning and direct instruction using an interactive whiteboard. Sixty-one fourth-grade students participated in this study and were divided into three experimental conditions: science classes A, B, and C. Each class received six, 50-minute science test review sessions over a twoweek period. The review sessions alternated each day between direct instruction and inquirybased learning. During the direct instruction sessions, Class A received direct instruction while using an interactive whiteboard; Class B received direct instruction while using laptops; Class C was the control group, and direct instruction was similar to a lecture format. No technology was used with Class C. The inquiry-based learning sessions were the same for all three classes. Science-based pre- and post-tests were administered during the study along with a technology use survey. Data from the Kansas State Reading, Math, and Science assessments were also considered. To determine if performances on the researcher-generated science tests were related to each other, partial correlations controlling for reading and math skills were computed for each group of students. Statistically significant relations between pre- and post-test science knowledge emerged only for the students in the no technology group. Gain scores were also calculated using the Kruskal Wallis test to determine the amount of change between pre- and post-intervention scores. Results indicated that significant group differences between pre- and post-test scores in science content knowledge did not emerge. Next, Kruskal Wallis statistical test was used to determine if there were group differences in use of computers for homework and for non-school work. No statistically significant differences emerged. Lastly, to determine if the gains from preto post-test made by the entire sample (not subgroups) were statistically significant, a onesample Kolmogorov-Smirnov test was used. Results indicated that gains made by the entire sample between pre- and post-tests were statistically significant. / Thesis (M.Ed.)--Wichita State University, College of Education, Dept. of Curriculum and Instruction. / Includes bibliographic references (leaves 36-39).

The aim of the study is: (1) to investigate effects of new science and technology curriculum on 4th and 5th grade students&rsquo / achievement in terms of knowledge and understanding levels outcomes and higher order thinking skills, (2) to investigate effects of new science curriculum on the students&rsquo / attitudes towards science and (3) to examine teachers&rsquo / classroom activities in lessons. The study was conducted in three conveniently selected public elementary schools throughout Yenimahalle district of Ankara with a total of 302 4th and 5th grade students in 2004-2005 spring semester, two pilot schools implementing new science and technology curriculum were assigned to experimental group and one school applying the traditional science curriculum was assigned to control group. The researcher developed the measuring tools, Science Achievement Test for 4th grade, Science Achievement Test for 5th grade, Science Attitude Scale and Teachers&rsquo / Classroom Activities Scale. v The data were analyzed through multivariate analyses of variance (MANOVA). Results showed that the new science and technology curriculum made no difference on the fourth grade students&rsquo / knowledge and understanding level outcomes and higher order thinking skills. On the other hand, it was effective on the fifth grade students&rsquo / higher order thinking skills. The statistical analyses also showed that there were significant differences between the pilot and control group students&rsquo / attitudes towards science in terms of interest, anxiety, and self-efficacy sub-categories in favor of pilot groups. In addition, there were significant differences between the classroom activities of the teachers of pilot and control groups.

This study investigated validity evidence for the Science Literacy Assessment, an instrument designed to assess middle school students’ ability to think scientifically as well as their motivation and beliefs about science (Fives, Huebner, Birnbaum, & Nicolich, 2014). Specifically, three sources of evidence were considered; internal structure, concurrent criterion-related, and predictive criterion-related. Exploratory factor analysis was utilized to examine the underlying factor structure of each of the instrument’s two components, motivation and beliefs related to science and demonstrated scientific literacy. Pearson product-moment correlations were calculated to determine the relationship between scores on the motivation and belief component of the Science Literacy Assessment and two instruments widely used to assess students’ attitudes toward science, the Modified Attitudes Toward Science Inventory (Weinburg & Steele, 2000), and the STEM Career Interest Survey (Kier, Blanchard, Osborne, & Albert, 2014). Finally, the extent to which scores on the Science Literacy Assessment predict scores on a general science knowledge instrument was assessed with the use of bivariate linear regression. Results suggested that, for the middle school student sample, the Science Literacy Assessment has appropriate psychometric properties for use with middle school students. Due to an insufficient high school sample size, validity evidence for this group was inconclusive.

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Despite widespread recognition by science educators, researchers and K-12 frameworks that scientific inquiry should be an essential part of science education, typical classrooms and assessments still emphasize rote vocabulary, facts, and formulas. One of several reasons for this is that the rigorous assessment of complex inquiry skills is still in its infancy. Though progress has been made, there are still many challenges that hinder inquiry from being assessed in a meaningful, scalable, reliable and timely manner. To address some of these challenges and to realize the possibility of formative assessment of inquiry, we describe a novel approach for evaluating, tracking, and scaffolding inquiry process skills. These skills are demonstrated as students experiment with computer-based simulations. In this work, we focus on two skills related to data collection, designing controlled experiments and testing stated hypotheses. Central to this approach is the use and extension of techniques developed in the Intelligent Tutoring Systems and Educational Data Mining communities to handle the variety of ways in which students can demonstrate skills. To evaluate students' skills, we iteratively developed data-mined models (detectors) that can discern when students test their articulated hypotheses and design controlled experiments. To aggregate and track students' developing latent skill across activities, we use and extend the Bayesian Knowledge-Tracing framework (Corbett & Anderson, 1995). As part of this work, we directly address the scalability and reliability of these models' predictions because we tested how well they predict for student data not used to build them. When doing so, we found that these models demonstrate the potential to scale because they can correctly evaluate and track students' inquiry skills. The ability to evaluate students' inquiry also enables the system to provide automated, individualized feedback to students as they experiment. As part of this work, we also describe an approach to provide such scaffolding to students. We also tested the efficacy of these scaffolds by conducting a study to determine how scaffolding impacts acquisition and transfer of skill across science topics. When doing so, we found that students who received scaffolding versus students who did not were better able to acquire skills in the topic in which they practiced, and also transfer skills to a second topic when was scaffolding removed. Our overall findings suggest that computer-based simulations augmented with real-time feedback can be used to reliably measure the inquiry skills of interest and can help students learn how to demonstrate these skills. As such, our assessment approach and system as a whole shows promise as a way to formatively assess students' inquiry.

Despite widespread recognition by science educators, researchers and K-12 frameworks that scientific inquiry should be an essential part of science education, typical classrooms and assessments still emphasize rote vocabulary, facts, and formulas. One of several reasons for this is that the rigorous assessment of complex inquiry skills is still in its infancy. Though progress has been made, there are still many challenges that hinder inquiry from being assessed in a meaningful, scalable, reliable and timely manner. To address some of these challenges and to realize the possibility of formative assessment of inquiry, we describe a novel approach for evaluating, tracking, and scaffolding inquiry process skills. These skills are demonstrated as students experiment with computer-based simulations. In this work, we focus on two skills related to data collection, designing controlled experiments and testing stated hypotheses. Central to this approach is the use and extension of techniques developed in the Intelligent Tutoring Systems and Educational Data Mining communities to handle the variety of ways in which students can demonstrate skills. To evaluate students' skills, we iteratively developed data-mined models (detectors) that can discern when students test their articulated hypotheses and design controlled experiments. To aggregate and track students' developing latent skill across activities, we use and extend the Bayesian Knowledge-Tracing framework (Corbett & Anderson, 1995). As part of this work, we directly address the scalability and reliability of these models' predictions because we tested how well they predict for student data not used to build them. When doing so, we found that these models demonstrate the potential to scale because they can correctly evaluate and track students' inquiry skills. The ability to evaluate students' inquiry also enables the system to provide automated, individualized feedback to students as they experiment. As part of this work, we also describe an approach to provide such scaffolding to students. We also tested the efficacy of these scaffolds by conducting a study to determine how scaffolding impacts acquisition and transfer of skill across science topics. When doing so, we found that students who received scaffolding versus students who did not were better able to acquire skills in the topic in which they practiced, and also transfer skills to a second topic when was scaffolding removed. Our overall findings suggest that computer-based simulations augmented with real-time feedback can be used to reliably measure the inquiry skills of interest and can help students learn how to demonstrate these skills. As such, our assessment approach and system as a whole shows promise as a way to formatively assess students' inquiry.