Schools and School Systems
Our results will inform school systems internationally across grade levels (from middle to high school) for a range of topics (ecology, human biology, mathematics, physics, etc.). Some of the direct school boards are Commission scolaire de Montréal, Commission scolaire Marguerite Bourgeoys Commission scolaire de la Pointe de l’Île English Montreal School Board, Lester B Pearson School Board.
Colleges and Universities
Our results cross disciplines (chemistry, biology, physics, algebra, computer science, engineering, education, medicine) and will improve learning and assessment in higher education.
There is an increasing push for standardized assessments to become technologically rich. This SSHRC-MCRI fills a gap for assessment branches of government and testing companies.
Administrators in early-higher education
Administrators in early-higher education will learn about TREs that best support learning.
Policy Makers in Government.
National and international governments will be interested in our results and can begin to create policy documents for educational assessments using technology.
They can also inform their educational constituents about best practices and impose standards for curriculum, teaching and assessment. We anticipate the results informing the forum on higher education of the Organization for Economic Co-operation and Development (OECD).
Local, provincial, national and international professional organizations will be informed about best learning and assessment practices for specific subject matter areas and for specific grade levels (e.g. Alberta Assessment, Council of Ministers of Education, Canada, US college board SAT; Canadian Patient Safety Institute, Society for Simulation in Health Care, the Royal College of Physicians of Canada; Office of Surgical Education at the University of Alberta, etc.)
Business, Industry and Defense
Our results will inform these constituents of the most effective training solutions for new recruits, leading to more a more competitive and informed workforce. For example, CAE and other simulation based groups.
Our theoretical framework and empirical findings will reach an interdisciplinary group of researchers that will lead to innovations that are the result of sharing methods that cross traditional boundaries. For instance, Learn Lab Pittsburgh Science of Learning Center.
The results will inform individuals of the strategies that can help them monitor and control their own life-long learning pursuits.