This project is developing, validating, and evaluating computer modeling-based formative assessments to improve student learning in chemistry. Activities include developing a series of computer models related to key topics in high school chemistry, developing questions to probe student understanding of matter and energy, identifying teaching and learning resources appropriate for different levels of student conceptual understanding, and developing professional development resources on integrating formative assessments into high school chemistry courses.
This project employs sensing technologies to help transform students' physical actions during play into a set of symbolic (computer) representations in a physics simulation and to engage the children in a developmentally appropriate and powerful form of scientific modeling. The students are in grades K–1 at UCLA's elementary school, and the intervention is based on the existing content unit on Force and Motion.
This project focuses on the challenge of using assessment of relevant STEM content to improve K-12 teaching and learning. CLEAR takes advantage of new technologies and research findings to investigate ways that science assessments can both capture and contribute to cumulative, integrated learning of standards-based concepts in middle school courses. The project will research new forms of assessment that document students' accumulation of knowledge and also serve as learning events.
The CLEAR project takes advantage of new technologies and research findings to investigate ways that science assessments can both capture and contribute to cumulative, integrated learning of standards-based concepts in middle school courses.
Our research investigates how instructional activities can help middle school students develop a cumulative, integrated understanding of energy. Energy is a unifying scientific concept that has been shown to be difficult to learn due to its complexity and abstract nature.
This project studies teaching practices in a year-long high school algebra course that integrates hand-held and other electronic devices. Of particular interest is how these technologies can support learners' capacity to efficiently and effectively draw on the distributed intelligences that technical and social networks make available. The investigation focuses on collaborative learning tasks centered on collective mathematical objects, such as functions, expressions, and coordinates that participants in a group must jointly manipulate through networked computers.
This project uses new psychometric techniques to create a technological tool that could evaluate how well students in the 4th-8th mathematics and science classrooms respond to complex performance tasks. The purpose of this tool is to improve the instruction of teachers in mathematics and science. It will produce real-time individualized diagnoses of instructional needs to help teachers plan instruction that specifically addresses the learning needs of each student in that class.
This project addresses the Measurement goal under the Mathematics and Science Education research program. Specifically, we propose developing and refining an assessment development, delivery, scoring, and report-generating system in the area of mathematics, centered on statistics and modeling. We have been engaged with colleagues at Vanderbilt University in designing a formative assessment system to support (and help evaluate) their innovative curriculum in this area: the Assessing Data Modeling and Statistical Reasoning (ADM) system developed by Rich Lehrer and his colleagues (Lehrer & Schauble, 2007). This assessment system has been created using the principles of the BEAR Assessment System (BAS; Wilson, 2005), and it and the curriculum it supports is currently being used in several states (WI, AK, TN), and is being adopted into a broader curriculum that is widely used. The aim of the current project is: (a) to refine a set of software programs that the Berkeley Evaluation and Assessment Research (BEAR) Center has been developing over the last 10 years that support the development, calibration, use and training for the assessment system, and to develop software interconnections among those programs to allow them to operate seamlessly for users whose roles range from assessment developers to teachers to school administrators, to those who provide professional development for teachers; (b) as a first full trial of that software, to embed the existing ADM materials in the software, construct computer-deliverable and computer-scorable task equivalents of the current item bank, and develop new computerized reports and support materials for teachers; and (c) to investigate the usefulness of this new software in the context of the ADM curriculum.
The positive effects of innovative assessments are widely acknowledged (Black & Wiliam, 1998), and we are happy that the BAS is seen as one such innovation. But we are strongly concerned that the good effects that one can find from early-adopters of such innovations will not be sustained unless the considerable burden of teacher scoring of their students’ formative assessments is lightened. We believe that it is essential that teachers become experts in interpreting their student’s responses to assessments. But, equally, we see that it is wise to then relieve them of the burden of continual scoring of large amounts of student work. Hence, the strategy we have adopted is to involve teachers early on in a deep program of professional development that will include close work with curriculum materials, assessments and student responses to assessments (preferably including a large proportion of work from their own students). However, once teachers have shown their mastery of the role of scorer and interpreter of such student products, we then provide the teacher with computerized assessments that will deliver and score equivalent assessments for their students, and generate rich interpretational materials to help them with diagnosis and planning. We expect that teachers will still be called upon to evaluate unusual student responses, and also will need to carry out occasional hand-scoring to keep up their mastery and to adapt to innovations in the curriculum.
This project develops mixed-initiative dialog and speech recognition technologies to encourage students to speak and reason about science concepts. It is part of a larger collaboration to help fourth and fifth grade students who are not achieving their potential in high quality inquiry-based programs. The larger collaboration develops and evaluates a computer program, MyST, to interactively engage students in spoken tutorial dialogs of four science investigations to reinforce and extend their understanding of science concepts.
This project is focusing on the redesign of popular commercial video games to support students’ understanding of Newtonian mechanics. In support of this goal, SURGE develops and implements design principles for game-based learning environments, integrating research on conceptual change, cognitive processing-based design, and socio-cognitive scripting. These enhanced games bridge the gap between student learning in non-formal game environments and the formalized knowledge structures learned in school by leveraging and integrating the strengths of each.
This project is developing a system for producing automated professional mentoring while students play computer games based on STEM professions. The project explores a specific hypothesis about STEM mentoring: A sociocultural model as the basis of an automated tutoring system can provide a computational model of participation in a community of practice, which produces effective professional feedback from nonplayercharacters in a STEM learning game.
This project investigates the potential of online role-playing games for scientific literacy through the iterative design and research of Saving Lake Wingra, an online role-playing game around a controversial development project in an urban area. Saving Lake Wingra positions players as ecologists, department of natural resources officials, or journalists investigating a rash of health problems at a local lake, and then creating and debating solutions.
The project addresses the relatively poor mathematics achievement of students who are not proficient in English. It includes research on how English language learners in beginning algebra classes solve math word problems with different text characteristics. The results of this research inform the development of technology-based resources to support ELLs’ ability to learn mathematics through instruction in English, including tutorials in math vocabulary, integrated glossaries, and interactive assistance with forming equations from word problem text.