Presented by:Bethany White (The University of Western Ontario) & Alison Gibbs (University of Toronto)
AbstractTechnology has tremendous potential to support the learning of statistics and increasing numbers of instructors are starting to incorporate technology in new and more sophisticated ways (Mills and Raju, 2011). As Garfield & Ben-Zvi (2008) pointed out, technology can be a powerful tool to support statistics learning through rich student-centred instruction but its use requires careful design to ensure appropriate scaffolding of student interaction with the technology to ensure the learning outcomes are achieved. Even though it is tempting to adopt new technologies as they emerge, we must be careful not to let the technology dictate the learning that occurs; rather it’s the desired learning outcomes that should drive which technologies are used and how they are used. This session will be motivated by the “backwards design” process (Wiggins and McTighe, 2005) which emphasizes the instructor’s role as the designer of student learning processes, linking learning outcomes to assessments, ensuring they are supported by appropriate learning activities. We will select some of the key learning outcomes from technology-enhanced courses we have taught, including blended, flipped, and completely online courses (including a MOOC as well as ‘for-credit’ courses at two Canadian universities) and describe ways we have integrated different kinds of technology to help students achieve these outcomes. Some of the technologies that will be mentioned include: - Shiny applets and R, - audience response systems, - interactive videos, - online quizzes, and - existing online learning objects. There will be opportunities for participants to brainstorm ideas and contribute to the discussion throughout this session. Our goal is that participants leave the session with at least one new idea for a technology-enabled activity or assessment that can be adapted for use in their courses. References: Garfield, JB, and Ben-Zvi, D (2008) Developing students’ statistical reasoning: Connecting research and teaching practice. Springer. Mills, JD, and Raju, D (2011) “Teaching Statistics Online: A decade’s review of the literature about what works”. Journal of Statistics Education, available at www.amstat.org/publications/jse/v19n2/mills.pdf. Wiggins, G and McTighe, J (2005) Understanding by Design, 2nd edition. Association for Supervision and Curriculum Development.
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