simSchool, a game-like simulation that develops teaching skills, will be disseminated via an international network of colleges of education and be scaled to reach all future teachers in the U.S. The application dynamically simulates classroom learner behaviors, emulates teaching and learning activities, and has been shown to generate relevant benefits concerning mastery of deeper learning outcomes such as self-efficacy, critical thinking, complex problem solving, & collaboration. The “Leverage” learning analytics engine will supply deeper levels of analysis. The international network includes the Society for Information Technology and Teacher Education and the Association for the Advancement of Computing in Education.
The goal of our innovation is to support deeper learning by a larger number and broader diversity of undergraduate students who have the potential to be the next generation of teachers, enabling them to develop the teaching skills, confidence, and attitudes needed to complete a certification program and stay in the profession beyond three years after graduation.
Students say that simSchool allows practice with students that have particular learning needs, teaches them what kinds of activities engage and effectively reach different kinds of students, allows them try out new teaching ideas without causing disasters in real classrooms, and helps them learn to provide better learning opportunities and accommodations for any kind of student.
Faculty and staff say that simSchool allows them to introduce diversity in gender, ethnicity, and learning differences; provides a safe environment for practice and reflection; and creates data for research on teaching and learning. They particularly like the ability to create unique student profiles, put challenging students into simulated classrooms, and wrap additional content into a teaching module that enhances their courses in educational foundations, psychology of learning, instructional design, classroom management, and teaching methods.
We know it’s working because new NGLC-supported studies in 2011 and 2012 validated and extended findings from 2007 and 2009 showing that significant gains are made in confidence (teaching self-efficacy), skills (e.g. understanding student characteristics and creating and sequencing tasks), and attitudes about teaching (e.g. that the locus of control for learning is in the hands of the teacher, not the background or characteristics of the student). We also know it’s working because the network of users is rapidly growing, there is word-of-mouth buzz, and the number of independent research studies by graduate students and professors is growing.
In five years, we imagine we will be in most of the effective teacher education programs in the world where technology has transformed the vision, learning opportunities and practices that prepare teachers in the 21st Century. We conservatively expect to serve over 500,000 users in 1000 higher education institutions in 150 countries.
So far, our most surprising development has been the extent of content creation by users. We thought that by the end of our first 15 months, we would have slightly over a dozen modules created primarily by us, and almost no other new content. But we have over 1000 pieces of content created by users, including unique simulated students, new tasks, and new modules being shared in an open source library.
We are looking for partners to help us go to scale, improve the learning and teaching model possibilities, and contribute to new kinds of research made possible by learning analytics and dynamic tracking of user behaviors. To help us scale, we would like to find policy leaders at national and international levels who have a stake in teacher quality, as well as people with marketing channels and dissemination capabilities that effectively reach networks of teachers, education faculty and other human resource trainers. To contribute to new kinds of research on teaching and learning, we are looking for partners with expertise and an interest in developing a new synthesis of data mining, psychometrics, dynamic assessment, and game-based learning methods, as well as people with an interest in computational learning theory and cognitive science.
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Postal Code: 23327