A resource created by Deakin pre-service History teachers Short Description: The teaching …
A resource created by Deakin pre-service History teachers
Short Description: The teaching and learning activities in this book were designed by pre-service History teachers at Deakin University, Australia. The activities cover a wide range of topics from ancient history through to early twenty-first century history and are designed to develop students' historical thinking.
Long Description: Most learning and teaching activities that get created in initial teacher education courses never get seen again once they are assessed as part of an assignment. However, pre-service History teachers undertaking a Master of Teaching at Deakin University have created and shared some of the learning and teaching activities they designed as part of a renewable assignment. This Open Education Resource (OER) contains activities on ancient history, empires, twentieth century world history and even early twenty-first century history, with a focus on building historical thinking. It showcases their emerging content and pedagogical understanding as well as their capacity to engage with open pedagogy and design copyright compliant materials. Although the activities have been mostly designed around the curriculum requirements of the Victorian Certificate of Education (VCE), they are easily adapted to fit other state and international curriculum contexts.
Word Count: 37875
(Note: This resource's metadata has been created automatically by reformatting and/or combining the information that the author initially provided as part of a bulk import process.)
This lesson in part of Software Carpentry workshop and teach novice programmers …
This lesson in part of Software Carpentry workshop and teach novice programmers to write modular code and best practices for using R for data analysis. an introduction to R for non-programmers using gapminder data The goal of this lesson is to teach novice programmers to write modular code and best practices for using R for data analysis. R is commonly used in many scientific disciplines for statistical analysis and its array of third-party packages. We find that many scientists who come to Software Carpentry workshops use R and want to learn more. The emphasis of these materials is to give attendees a strong foundation in the fundamentals of R, and to teach best practices for scientific computing: breaking down analyses into modular units, task automation, and encapsulation. Note that this workshop will focus on teaching the fundamentals of the programming language R, and will not teach statistical analysis. The lesson contains more material than can be taught in a day. The instructor notes page has some suggested lesson plans suitable for a one or half day workshop. A variety of third party packages are used throughout this workshop. These are not necessarily the best, nor are they comprehensive, but they are packages we find useful, and have been chosen primarily for their usability.
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Your remixing, redistributing, or making derivatives works comes with some restrictions, including how it is shared.
Your redistributing comes with some restrictions. Do not remix or make derivative works.
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Copyrighted materials, available under Fair Use and the TEACH Act for US-based educators, or other custom arrangements. Go to the resource provider to see their individual restrictions.
