This project will create technology-enhanced classroom activities and resources that increase student learning of science practices in high school biology, chemistry, and physics. InquirySpace will incorporate several innovative technological and pedagogical features that will enable students to undertake scientific experimentation that closely mirrors current science research and learn what it means to be a scientist.
This project will create technology-enhanced classroom activities and resources that increase student learning of science practices in high school biology, chemistry, and physics courses. The project addresses the urgent national priority to improve science education as envisioned in the Next Generation Science Standards (NGSS) by focusing less on learning facts and equations and instead providing students with the time, skills, and resources to experience the conduct of science and what it means to be a scientist. This project builds on prior work that created a sequence of physics activities that significantly improved students' abilities to undertake data-based experiments and led to productive independent investigations. The goal of the InquirySpace project is to improve this physics sequence, extend the approach to biology and chemistry, and adapt the materials to the needs of diverse students by integrating tailored formative feedback in real time. The result will be student and teacher materials that any school can use to allow students to experience the excitement and essence of scientific investigations as an integral part of science instruction. The project plans to create and iteratively revise learning materials and technologies, and will be tested in 48 diverse classroom settings. The educational impact of the project's approach will be compared with that of business-as-usual approaches used by teachers to investigate to what extent it empowers students to undertake self-directed experiments. To facilitate the widest possible use of the project, a complete set of materials, software, teacher professional development resources, and curriculum design documents will be available online at the project website, an online teacher professional development course, and teacher community sites. The Discovery Research K-12 program (DRK-12) seeks to significantly enhance the learning and teaching of science, technology, engineering and mathematics (STEM) by preK-12 students and teachers, through research and development of innovative resources, models and tools (RMTs). Projects in the DRK-12 program build on fundamental research in STEM education and prior research and development efforts that provide theoretical and empirical justification for proposed projects.
InquirySpace will incorporate several innovative technological and pedagogical features that will enable students to undertake scientific experimentation that closely mirrors current science research. These features will include (1) educational games to teach data analysis and interpretation skills needed in the approach, (2) reduced dependence on reading and writing through the use of screencast instructions and reports, (3) increased reliance on graphical analysis that can make equations unnecessary, and (4) extensive use of formative feedback generated from student logs. The project uses an overarching framework called Parameter Space Reasoning (PSR) to scaffold students through a type of experimentation applicable to a very large class of experiments. PSR involves an integrated set of science practices related to a question that can be answered with a series of data collection runs for different values of independent variables. Data can be collected from sensors attached to the computer, analysis of videos, scientific databases, or computational models. A variety of visual analytic tools will be provided to reveal patterns in the graphs. Research will be conducted in three phases: design and development of technology-enhanced learning materials through design-based research, estimation of educational impact using a quasi-experimental design, and feasibility testing across diverse classroom settings. The project will use two analytical algorithms to diagnose students' learning of data analysis and interpretation practices so that teachers and students can modify their actions based on formative feedback in real time. These algorithms use computationally optimized calculations to model the growth of student thinking and investigation patterns and provide actionable information to teachers and students almost instantly. Because formative feedback can improve instruction in any field, this is a major development that has wide potential.