The National Academy of Engineering is conducting a comprehensive examination of the current state of integrated Science, Technology, Engineering and Mathematics (STEM) education in K-12 schools. STEM education is a recognized priority for K-12 education but to date most of the attention and funding has been focused on improving the single-letter components of STEM and mainly only science and mathematics. This study focuses attention on the potential benefits of teaching and learning that combine or integrate essential content and processes of two or more of the four STEM disciplines with particular emphasis on technology and engineering. Preliminary evidence suggests that integrated STEM may produce gains in students' academic interest and achievement as well as influence career aspirations. The goal of the study is to craft a research agenda that will examine the value of an integrated STEM education to students (K-12) in terms of learning achievement, motivation, and career aspirations. The final report summarizes the findings from the data gathering and analysis and the committee's conclusions and recommendations for a research agenda. This report is disseminated through presentations to relevant groups, publication of print and online articles and editorials and briefings to relevant stakeholders. About 75% of the funding for this study is provided through private foundations

The study is done by a carefully selected project committee of 12-14 experts in diverse fields relevant to the focus of the effort appointed by the president of the National Academy of Engineering. They are supported by knowledgeable Academy staff. The Committee meets six times over 30 months. The first workshop is to devise a conceptual framework or taxonomy of the multiple ways integration can occur. Other workshops inform the Committee about specific issues relevant to integrated STEM education. The project includes a review of the literature on integrated teaching and learning, primary qualitative research on the current practices in integrated teaching (surveys, curriculum analyses, interviews and site visits), and review of policy at the district, state, and national levels. The goal of the study is to develop a research agenda that will examine the value of an integrated STEM education to students (K-12) in terms of learning achievement, motivation, and career aspirations. An external evaluator assesses the data gathering effort, the project's communication and outreach efforts and the impact of the final report. Surveys and/or interviews with workshop participants and others determine how the report influences the national discussion STEM education. The final evaluation report distills the lessons learned and the implications for next steps in studying the integrated STEM concept.

The project and the final consensus report are designed to inform stakeholder groups that have an interest in understanding the limits and potential of integrated STEM. The stakeholders include federal and state agencies with a role in education, foundations, STEM teacher organizations and STEM professional societies as well as practitioners and the general public.

The Models of Professional Development for Mathematics Teachers project is conducting a comprehensive study of professional development models designed for mathematics teachers in grades K-12. The research team will identify key constructs and frameworks within professional development programs and identify types of professional development models. The goals of the project are to encourage researchers and professional developers to reconceptualize mathematics professional development, develop a shared language, and renew discussions on effective professional development for teachers of mathematics. The project team includes faculty and students at North Carolina State University and a research scientist at American Institutes for Research. The project team is coding and analyzing descriptive data on mathematics professional development (MPD) gathered from studying mathematics teacher education research literature. They are also conducting interviews with authors of the studies they have identified. The project is investigating the general question: What are the various models used by mathematics teacher educators when designing and implementing mathematics professional development? Specifically, they are asking: 1. What are similarities and differences across goals, theoretical frameworks, contexts and structures that exist in the design of MPD offered to K-12 teachers? 2. How does the field name and define various characteristics of MPD? 3. How can the characteristics of the various MPD designs be grouped into meaningful models? What are the main elements that define these models? The researchers hope that their efforts to describe models of professional development will help educators to move away from professional development designed around a few salient features and move toward professional development models that contain a theoretical framework and coherent features that work together. They want professional developers and researchers to use a common language to study and assess professional development. Their analysis of existing professional development projects in mathematics teaching will offer the following outcomes: 1. An empirically established definition of characteristics and models of MPD, with explanations of the various elements that comprise these models. 2. A coding protocol for use in the classification of MPD models and the organization of current information about existing MPD. 3. A theoretical framework for organizing knowledge about MPD that can foster new ways to think about these models in the design of innovative MPD for teachers. 4. A set of research-related innovations such as new hypotheses for studying MPD, new approaches to testing the explanatory and predictive validity of various features of professional development, and new formats for describing the state of the art in MPD. 5. Concepts that can support a revision of what is meant by best practices or effective features of MPD. 6. An open-source, web-based, searchable database with descriptions of various MPD. This exploratory project will provide an opportunity for the mathematics education field to learn more about professional development and approaches to conducting research on professional development.

This DR K-12 Exploratory Project conducted by Education Development Center, Inc.(EDC) and The Scripps Institution of Oceanography (Scripps)will address the question: In what ways can research on learning inform the design of interfaces and technology tools to be used by students accessing large scientific data bases? Expertise about this question is scattered among a variety of disciplines, including: science education research related to geology, climate science, and ecology; mathematics and statistics education research; and educational psychology. Consequently, there is no synthesis of knowledge about how to support precollege students' and teachers' use of large scientific data bases. Oceans of Data will therefore (1) conduct a systematic survey of the widely-dispersed research literature and (2) develop and disseminate a knowledge status report, a resource offering guidance for making these large scientific data bases accessible to and usable by high school science classes. This report will inform the work of three target audiences: (1) large science cyberinfrastructure projects concerned with serving student users; (2) intermediary developers (e.g., publishers, research and development organizations, and software development companies) of digital interfaces and tools that can make cyberinfrastructure data appropriate for use by pre-college learners; and (3) education researchers. Most immediately, the project results will be applied directly to the NSF-funded Ocean Observatory Initiative (OOI) cyberinfrastructure project at Scripps.

The project design for developing this resource involves a multi-stage review, coding, and analysis of the literature. The coding protocol framing this effort focuses on categories of data representations (such as maps, graphs, 3D representations, animations and multiple data representations) processes of working with data ( such as finding and selecting data, reading data representations, creating data representations, and pattern recognition) and cross-cutting themes (such as visual perception, spatial perception and visualization, cognitive load, and mental models) Work is being conducted under the aegis of an advisory committee: researchers and technology developers in the above-mentioned domains, expert teachers, and individuals representing the target audiences. Advisors will also evaluate the resulting product, as will an additional cadre of targeted end-users.

The Oceans of Data knowledge status report will present: the literature review results; recommendations for designing effective interfaces and technology tools for students; guidelines, based on tenets of universal design for learning (UDL) for designing software for diverse student populations; and suggested avenues for future research to address identified gaps. The project therefore will enable the bridging of science cyberinfrastructure projects in a number of disciplines with pre-college education. Ultimately, students will have unprecedented opportunities to analyze and draw conclusions from cyberinfrastructure data and, thus, to engage in new modes of data-driven science practice.

Doing science requires that students learn to create evidence-based arguments (EBAs), defined as claims connected to supporting evidence via premises. The question chosen for study by a new researcher at Utah State University is: How can argumentation ability be enhanced among middle school students? This study involves 325 middle school students in 12 class sections from 3 school districts in Utah and Idaho. First, students in middle school science classrooms will be introduced to problem-based learning (PBL) units that allow them to investigate ill-structured science problems. These activities provide students with something about which to argue: something that they have explored personally and with which they have grappled. Next, they will construct arguments using a powerful computer technology, the Connection Log, developed by the PI. The Connection Log provides a scaffold for building arguments, allowing each student to write about his/her reasoning and compare it to arguments built by peers. The study investigates how the Connection Log improves the quality of students' arguments. It also explores whether students are able to transfer what they have learned to new situations that call for argumentation.

This study is set in 6th and 7th grade science classrooms with students of diverse SES, ethnicity, and achievement levels. The Connection Log software supports middle school students with written prompts on a computer screen that take students through the construction of an argument. The system allows students to share their arguments with other members of their PBL group. The first generation version of the Connection Log asks students to:

1. define the problem, or state the problem in their own words

2. determine needed information, or decide on evidence they need to find to solve the problem

3. find and organize needed information

4. develop a claim, or make an assertion stating a possible problem solution

5. link evidence to claim, linking specific, relevant data to assertions

The model will be optimized through a process of design-based research. The study uses a mixed methods research design employing argument evaluation tests, video, interviews, database information, debate ratings, and a mental models measure, to evaluate student progress.

This study is important because research has shown that students do not automatically come to school prepared to create evidence-based arguments. Middle school students face three major challenges in argumentation: adequately representing the central problem of the unit; determining and obtaining the most relevant evidence; and synthesizing gathered information to construct a sound argument. Argumentation ability is crucial to STEM performance and to access to STEM careers. Without the ability to formulate arguments based upon evidence, middle school students are likely to be left out of the STEM pipeline, avoid STEM careers, and have less ability to critically evaluate and understand scientific findings as citizens. By testing and refining the Connection Log, the project has the potential for scaling up for use in science classrooms (and beyond) throughout the United States.

The University of Georgia will carry out a two-year Synthesis Project that aims to provide a comprehensive review of the research and practices for modeling-based instruction (MBI) in K-12 science education. The project will synthesize existing literature on MBI in K-12 science education over the last three decades. It will rigorously code and examine the literature to conceptualize the landscape of the theoretical frameworks of MBI approaches, identify the effective design features of modeling-based learning environments with an emphasis on technology-enhanced ones, and identify the most effective MBI practices that are associated with successful student learning through a meta-analysis.

The project will build a systematic and analytic framework to conceptualize MBI, recommend best design strategies of technology-based modeling environments, evaluate MBI teacher professional development strategies associated with improved student learning, and propose appropriate assessment strategies created to evaluate and inform MBI. In addition to the comprehensive analysis of the theory and design of MBI, a meta-analysis will study the four components of student learning: theory, design, implementation, and assessment. Based on qualified quantitative studies, an examination of the four components will be made to evaluate how different empirical studies have established their effectiveness, examine the correlations among key components, and chart the impact of associated factors on student learning.

TERC researchers are collaborating with STEM educators, curriculum/software developers, scientists, social scientists, and statisticians to explore:

• how large scientific and social scientific data sets could provide a vehicle for secondary students to learn about statistical ideas
• how developing an understanding of statistics could contribute to learning about the science and social science content
• the characteristics of curricular supports and software tools that could promote rigorous engagement with statistical ideas among secondary students

The project builds on the increasing availability of a variety of large data sets, and on students’ inherent interest in data sets related to “hot” topics such as the environment and climate change, the human genome, economic justice issues, space exploration, and medical research.

Through reviewing literature and discussing ideas with advisors and colleagues, the project developed several hypotheses about potential affordances for students in working with large data sets. In the final year of the project, we tested several of these hypotheses by developing activities and using interviews and observations of secondary students engaging with these activities to gather evidence of their potential, analyzing and writing about these interviews, presenting this work at conferences, and submitting a paper about this work to a peer-reviewed journal.