Global ETD Search

21	Preschool Science: An Examination of Classroom and Teacher Predictors Blaylock, Donna S. 01 December 2019 (has links) Science experiences during the preschool years is important because it helps build brain development in children, and improves school readiness. This exploratory study examined several characteristics of teachers and classrooms to see if any factors predicted time spent on science. Over 120 teachers participated, with teachers from Head Starts, university child development laboratories, home-based preschools, and other private preschool programs. Findings suggest that preschool teachers are quite comfortable with teaching science, but science activities are reported to occur infrequently—one to three times a month. Teachers with higher levels of education and comfort levels with science are reported to be more likely to spend time on science. Additionally, comfort levels with science had the greatest impact on time spent on science after accounting for teacher and classroom demographics. These results suggest that helping teachers feel more comfortable teaching science should be an important target for professional development practices and preservice education. Preschool science teacher comfort predictors of science time teaching science teacher education science inquiry natural observers science in childhood Family, Life Course, and Society
22	Restructuring High School Science Curriculum: A Program Evaluation Robertson, Cathy 01 January 2015 (has links) One rural Midwestern high school discovered a discrepancy among school, state, and national science skill attainment, verified by ACT scores. If students do not acquire vital science skills, they may not perform proficiently on science tests, thus impacting future college options. Inquiry based instruction and constructivism provided the basis for the theoretical framework. This study questioned associations between ACT scores, inquiry science technique usage, and ACT standard usage (Phase 1), and teachers' views on science instruction (Phase 2). This sequential explanatory mixed methods program evaluation included 469 ACT scores, surveys sent to 9 science teachers, and 8 interviews. Phase 1 used the inquiry science implementation scale survey and an ACT college readiness standards workbook to determine proportional associations between datasets. Descriptive statistics, one-sample t tests, and binomial tests were used to analyze Phase 1 data. Phase 2 interviews augmented Phase 1 data and were disassembled, reassembled, and interpreted for parallel viewpoints. Phase 1 data indicated that teachers use a slightly above average amount of inquiry and science ACT standards in the classroom; however, most science students did not test above the curriculum and there were inconsistencies in standards covered. Phase 2 data revealed teachers need time to collaborate and become skilled in inquiry methods to rectify the inconsistencies. The project was an evaluation report. This study will foster positive social change by giving the district a plan: adapt the science curriculum by integrating more ACT and inquiry standards and participate in more professional development that applies inquiry as a tool to increase science skill proficiency, thus generating locally competitive students for college and the workforce. college readiness standards explanatory mixed methods program evaluation science ACT scores science ACT standards science inquiry Science and Mathematics Education Secondary Education and Teaching
23	Real-time Assessment, Prediction, and Scaffolding of Middle School Studentsâ€™ Data Collection Skills within Physical Science Simulations Sao Pedro, Michael A. 25 April 2013 (has links) 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. Behavior Detection Skill Prediction User Modeling Validation Inquiry Learning Environment Science Education Computer-Based Assessment Inquiry Assessment Performance Assessment Science Simulations Science Microworlds Educational Data Mining Formative Assessment Exploratory Learning Environment Open-Ended Learning Environment Science Inquiry Science Assessment Designing and Conducting Experiments Construct Validity Generalizability Text Replay Tagging J48 Decision Trees Bayesian Knowledge Tracing
24	Real-time Assessment, Prediction, and Scaffolding of Middle School Studentsâ€™ Data Collection Skills within Physical Science Simulations Sao Pedro, Michael A. 25 April 2013 (has links) 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. Behavior Detection Skill Prediction User Modeling Validation Inquiry Learning Environment Science Education Computer-Based Assessment Inquiry Assessment Performance Assessment Science Simulations Science Microworlds Educational Data Mining Formative Assessment Exploratory Learning Environment Open-Ended Learning Environment Science Inquiry Science Assessment Designing and Conducting Experiments Construct Validity Generalizability Text Replay Tagging J48 Decision Trees Bayesian Knowledge Tracing
25	Evaluation of a Novel Biochemistry Course-Based Undergraduate Research Experience (CURE) Stefan M Irby (6326255) 15 May 2019 (has links) <p>Course-based Undergraduate Research Experiences (CUREs) have been described in a range of educational contexts. Although various learning objectives, termed anticipated learning outcomes (ALOs) in this project, have been proposed, processes for identifying them may not be rigorous or well-documented, which can lead to inappropriate assessment and speculation about what students actually learn from CUREs. Additionally, evaluation of CUREs has primarily relied on student and instructor perception data rather than more reliable measures of learning.This dissertation investigated a novel biochemistry laboratory curriculum for a Course-based Undergraduate Research Experience (CURE) known as the Biochemistry Authentic Scientific Inquiry Lab (BASIL). Students participating in this CURE use a combination of computational and biochemical wet-lab techniques to elucidate the function of proteins of known structure but unknown function. The goal of the project was to evaluate the efficacy of the BASIL CURE curriculum for developing students’ research abilities across implementations. Towards achieving this goal, we addressed the following four research questions (RQs): <b>RQ1</b>) How can ALOs be rigorously identified for the BASIL CURE; <b>RQ2</b>) How can the identified ALOs be used to develop a matrix that characterizes the BASIL CURE; <b>RQ3</b>) What are students’ perceptions of their knowledge, confidence and competence regarding their abilities to perform the top-rated ALOs for this CURE; <b>RQ4</b>) What are appropriate assessments for student achievement of the identified ALOs and what is the nature of student learning, and related difficulties, developed by students during the BASIL CURE? To address these RQs, this project focused on the development and use of qualitative and quantitative methods guided by constructivism and situated cognition theoretical frameworks. Data was collected using a range of instruments including, content analysis, Qualtrics surveys, open-ended questions and interviews, in order to identify ALOs and to determine student learning for the BASIL CURE. Analysis of the qualitative data was through inductive coding guided by the concept-reasoning-mode (CRM) model and the assessment triangle, while analysis of quantitative data was done by using standard statistical techniques (e.g. conducting a parried t-test and effect size). The results led to the development of a novel method for identifying ALOs, namely a process for identifying course-based undergraduate research abilities (PICURA; RQ1; Irby, Pelaez, & Anderson 2018b). Application of PICURA to the BASIL CURE resulted in the identification and rating by instructors of a wide range of ALOs, termed course-based undergraduate research abilities (CURAs), which were formulated into a matrix (RQs 2; Irby, Pelaez, & Anderson, 2018a,). The matrix was, in turn, used to characterize the BASIL CURE and to inform the design of student assessments aimed at evaluating student development of the identified CURAs (RQs 4; Irby, Pelaez, & Anderson, 2018a). Preliminary findings from implementation of the open-ended assessments in a small case study of students, revealed a range of student competencies for selected top-rated CURAs as well as evidence for student difficulties (RQ4). In this way we were able to confirm that students are developing some of the ALOs as actual learning outcomes which we term VLOs or verified learning outcomes. In addition, a participant perception indicator (PPI) survey was used to gauge students’ perceptions of their gains in knowledge, experience, and confidence during the BASIL CURE and, therefore, to inform which CURAs should be specifically targeted for assessment in specific BASIL implementations (RQ3;). These results indicate that, across implementations of the CURE, students perceived significant gains with large effect sizes in their knowledge, experience, and confidence for items on the PPI survey (RQ3;). In our view, the results of this dissertation will make important contributions to the CURE literature, as well as to the biochemistry education and assessment literature in general. More specifically, it will significantly improve understanding of the nature of student learning from CUREs and how to identify ALOs and design assessments that reveal what students actually learn from such CUREs - an area where there has been a dearth of available knowledge in the past. The outcomes of this dissertation could also help instructors and administrators identify and align assessments with the actual features of a CURE (or courses in general), use the identified CURAs to ensure the material fits departmental or university needs, and evaluate the benefits of students participating in these innovative curricula. Future research will focus on expanding the development and validation of assessments so that practitioners can better evaluate the efficacy of their CUREs for developing the research competencies of their undergraduate students and continue to render improvements to their curricula.</p> Biochemistry Education Course-based Undergraduate Research Course-based Research Experiences CURE anticipated learning outcomes ALOs ALO CURAs research abilities PICURA ALO matrix BASIL weighted-relevance WR verified learning outcomes VLOs CUREs biochemistry computational biochemistry bioinformatics biochemistry education chemistry education chemistry teaching laboratory upper-division ACE-Bio experimental competencies Authentic science inquiry chemical education assessment assessment design Student understanding student difficulties biochemistry laboratory experiments biochemistry teaching laboratory chemistry teaching laboratory chemistry teaching laboratories predicting protein function protein inquiry-based learning inquiry-based teaching content analysis open-ended survey interviews semi-structured interviews PPI participant perception indicator assessment triangle CRM conceptual reasoning mode conceptual-reasoning-mode model curriculum evaluation experimental abilities discovery skills learning objectives learning outcomes LO LOs collaborations collaborative course implementation implementation student difficuluties experimental learning experimental literacy data-representation ACE-Bio Network Likert-survey

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