JASP is an open-source statistics program that is free, friendly, and flexible. Armed with an easy-to-use GUI, JASP allows both classical and Bayesian analyses.
The recent release of the Next Generation Science Standards (NGSS) offers a new challenge and opportunity for science. Science practices are the social interactions, tools and language that scientist use as they construct, evaluate and communicate scientific knowledge. The effective integration of science practices into classrooms can better support a wide range of students, including those typically underrepresented in science, to develop greater scientific literacy.
Effective integration of science practices in classrooms requires instructional leadership to support that change. Instructional leaders can include a variety of different individuals including, but not limited to, school principals, district leaders, coaches and lead teachers. The ILSP team is developing tools to support instructional leaders in the science practices.
Vision
Our vision for supporting instructional leaders in their work with teachers to improve science teaching and learning stems from our approach to instructional supervision and science instruction.
Our orientation to supervision is rooted in the importance of strong instructional leadership. We seek to support leaders in their work with teachers as they promote a growth mindset, foster frequent and ongoing opportunities for feedback, sustain a commitment to teacher development over time, and engage in collaborative practices.
The STEM Teaching Tools site has tools that can help you teach science, technology, engineering and math (STEM). We are currently focused on supporting the teaching of the Next Generation Science Standards (NGSS). Each tool is focused on a specific issue and leverages the best knowledge from research and practice. Under the News section, you can learn a bit more about how you might use them. This article provides background on this effort. Review more resources in our Tools area and check out the online "short courses" shown below.
TensorFlow™ is an open source software library for numerical computation using data flow graphs. Nodes in the graph represent mathematical operations, while the graph edges represent the multidimensional data arrays (tensors) communicated between them. The flexible architecture allows you to deploy computation to one or more CPUs or GPUs in a desktop, server, or mobile device with a single API. TensorFlow was originally developed by researchers and engineers working on the Google Brain Team within Google's Machine Intelligence research organization for the purposes of conducting machine learning and deep neural networks research, but the system is general enough to be applicable in a wide variety of other domains as well.