As computing has become integral to the practice of science, technology, engineering and mathematics (STEM), the STEM + Computing Partnerships program seeks to address emerging challenges in computational STEM areas through the applied integration of computational thinking (CT) and computing activities within STEM teaching and learning in early childhood education through high school. This project is a Design and Development collaborative effort between the University of Colorado at Boulder and Utah State University aimed at investigating the impact of the SparkFun Smart School platform, a school-based sensing platform, combined with a targeted teacher professional development on teachers' ability to support CT integration and promote student interest and learning. The project will examine the affordances of this sensing platform--an example of a new genre of robust, consumer-grade sensing technologies emerging as part of the Internet of Things.
As computing has become integral to the practice of science, technology, engineering and mathematics (STEM), the STEM + Computing Partnerships program seeks to address emerging challenges in computational STEM areas through the applied integration of computational thinking (CT) and computing activities within STEM teaching and learning in early childhood education through high school. This project is a Design and Development collaborative effort between the University of Colorado at Boulder and Utah State University aimed at investigating the impact of the SparkFun Smart School platform, a school-based sensing platform, combined with a targeted teacher professional development on teachers' ability to support CT integration and promote student interest and learning. The project will examine the affordances of this sensing platform--an example of a new genre of robust, consumer-grade sensing technologies emerging as part of the Internet of Things. Raw data will be collected through a series of wireless sensor nodes measuring sound, light, motion, temperature, pressure, and humidity; a network-enabled hub; a web-based data logging resource for real-time data collection; and programmable motors and effectors for creating interactive displays of phenomena of interest by using materials that produce light, sound, and movement. This expanded environment for doing science enables teachers across STEM disciplines to creatively integrate computational thinking activities into their disciplinary instruction. By selecting personally or locally relevant scientific phenomenon, deploying sensors to collect data streams, and conducting data analyses, students will learn tangible computing processes, collaboratively build interactive displays, and deepen their STEM knowledge. Teachers will form a professional learning community, gain essential content and pedagogical content knowledge, plan and implement lessons that integrate science and computer science practices, and reflect on their instruction and students' learning. The project will develop and study a professional development process, the CT Integration Cycle, based on the Problem-Solving Cycle, a research-based approach developed and studied to support teachers in adapting their lessons and classroom instruction to strengthen student-centered strategies. This professional development model is an ongoing, highly collaborative process, whereby teachers plan, enact, and analyze their instruction using video records of classroom implementation.
The collaborative effort will follow three high-level theoretically principled conjectures that will guide the research and development process: (1) Learning experiences that utilize the sensing platform to investigate phenomena relevant to students' lives will engage diverse learners in CT; (2) Learning experiences that deeply integrate CT practices and science and engineering practices will support students to develop robust CT skills, competencies, and dispositions as well as deepen their understanding of STEM subjects; and (3) An adapted version of the Problem-Solving Cycle can support teachers to productively integrate CT into their STEM instructional planning and classroom implementation. The four sets of research questions of the project are: (1) In what ways, and for which student populations, do the SchoolWide Labs learning experiences deepen interest and engagement in CT?; (2) Which learning experiences are most effective at deepening students' disciplinary science knowledge?; (3) To what degree and in what ways do teachers' planned and enacted sensor-based lessons change over time? Are there differences across teachers and science content areas?; and (4) What professional learning processes and tools support teachers to productively integrate CT using a sensing platform into their disciplinary STEM instruction? The pursued research and development activity will study the full trajectory of teachers' CT integration processes, from lesson planning to lesson enactment. Consistent with the principles of Design-Based Implementation Research, the project will aim to understand implementation variation across disciplines of STEM, with the intention of developing understanding of how best to make the innovation work across a range of carefully sampled contexts. Denver Public Schools will recruit 12 middle school science and integrated STEM teachers (life, Earth, and physical science), organized into 3-4 school-based teams, reaching 2,400 diverse and predominantly low-socioeconomic status middle school learners over the project performance period. Data will be collected from students (surveys, interviews, clickstreams, assessments, and project artifacts); classroom lessons (written plans and videotaped observations); teachers (interviews); and professional development workshops. For analysis of student learning and also for teacher change over time, the project will employ appropriate multilevel models, including two-level hierarchical linear modeling due to the nested nature of the data. A power analysis (using a power level of .80 and an alpha-level of .05) was conducted to determine how many students are needed to detect an educationally meaningful effect of the program (minimum detectable effect size of approximately 0.20). The results of the power analyses showed the study is adequately powered to detect this minimum effect on student-level outcomes. Utah State University will lead the evaluation component of this effort, including formative, iterative, and summative perspectives. It will center on both processes and products. The evaluation questions are: (1) To what extent is the Research-Practice Partnership (RPP) producing research results to foster educational improvement?; How effective are the implementation strategies in terms of addressing a concrete educational need?; (2) To what extent are Design-Based Implementation Research processes involving key participants?; What are impacts of the design processes on beliefs and practices of participants?; Are all participants in the RPP assuming their defined roles effectively?; (3) What are the consequences, intended or not, resulting from the dynamics of the partnership?; (4) Are products being iteratively refined by taking into account feedback from all participants?; and (5) To what extent are the project's products disseminated in ways that help practitioners? The project will generate two toolkits as products to support teacher professional development and classroom instruction. The research will advance theory and knowledge on productive integration processes by studying the types of support STEM teachers need to effectively integrate CT into learning activities that: (a) support equitable engagement of diverse students; and (b) use CT as a vehicle to deepen their students' science knowledge. Further, it will build on and extend research-based principles of three dimensional science learning described in the recently published science education framework (NRC, 2012) as a strategy for productive integration, and contribute to theoretical literature on pedagogical design capacity, curriculum adaptation, and teacher professional learning.
The collaborative effort will follow three high-level theoretically principled conjectures that will guide the research and development process: (1) Learning experiences that utilize the sensing platform to investigate phenomena relevant to students' lives will engage diverse learners in CT; (2) Learning experiences that deeply integrate CT practices and science and engineering practices will support students to develop robust CT skills, competencies, and dispositions as well as deepen their understanding of STEM subjects; and (3) An adapted version of the Problem-Solving Cycle can support teachers to productively integrate CT into their STEM instructional planning and classroom implementation. The four sets of research questions of the project are: (1) In what ways, and for which student populations, do the SchoolWide Labs learning experiences deepen interest and engagement in CT?; (2) Which learning experiences are most effective at deepening students' disciplinary science knowledge?; (3) To what degree and in what ways do teachers' planned and enacted sensor-based lessons change over time? Are there differences across teachers and science content areas?; and (4) What professional learning processes and tools support teachers to productively integrate CT using a sensing platform into their disciplinary STEM instruction? The pursued research and development activity will study the full trajectory of teachers' CT integration processes, from lesson planning to lesson enactment. Consistent with the principles of Design-Based Implementation Research, the project will aim to understand implementation variation across disciplines of STEM, with the intention of developing understanding of how best to make the innovation work across a range of carefully sampled contexts. Denver Public Schools will recruit 12 middle school science and integrated STEM teachers (life, Earth, and physical science), organized into 3-4 school-based teams, reaching 2,400 diverse and predominantly low-socioeconomic status middle school learners over the project performance period. Data will be collected from students (surveys, interviews, clickstreams, assessments, and project artifacts); classroom lessons (written plans and videotaped observations); teachers (interviews); and professional development workshops. For analysis of student learning and also for teacher change over time, the project will employ appropriate multilevel models, including two-level hierarchical linear modeling due to the nested nature of the data. A power analysis (using a power level of .80 and an alpha-level of .05) was conducted to determine how many students are needed to detect an educationally meaningful effect of the program (minimum detectable effect size of approximately 0.20). The results of the power analyses showed the study is adequately powered to detect this minimum effect on student-level outcomes. Utah State University will lead the evaluation component of this effort, including formative, iterative, and summative perspectives. It will center on both processes and products. The evaluation questions are: (1) To what extent is the Research-Practice Partnership (RPP) producing research results to foster educational improvement?; How effective are the implementation strategies in terms of addressing a concrete educational need?; (2) To what extent are Design-Based Implementation Research processes involving key participants?; What are impacts of the design processes on beliefs and practices of participants?; Are all participants in the RPP assuming their defined roles effectively?; (3) What are the consequences, intended or not, resulting from the dynamics of the partnership?; (4) Are products being iteratively refined by taking into account feedback from all participants?; and (5) To what extent are the project's products disseminated in ways that help practitioners? The project will generate two toolkits as products to support teacher professional development and classroom instruction. The research will advance theory and knowledge on productive integration processes by studying the types of support STEM teachers need to effectively integrate CT into learning activities that: (a) support equitable engagement of diverse students; and (b) use CT as a vehicle to deepen their students' science knowledge. Further, it will build on and extend research-based principles of three dimensional science learning described in the recently published science education framework (NRC, 2012) as a strategy for productive integration, and contribute to theoretical literature on pedagogical design capacity, curriculum adaptation, and teacher professional learning.
