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Sustaining Positive Change & Wildcard

Room 3665 (Session B)

Practice

no session D

2:15 - 2:45 Research | Marta Samokishyn & Rachel Moylan & Maddie Hare, Saint Paul University & University of British Columbia & University of Ottawa Decoding New Literacies: Core Concepts & Competencies of Algorithm Literacy Literacy is defined as being deictic in nature, i.e. its definition can “change rapidly as [its] context changes” (Leu et al., 2018, p. 319). As new technologies and social challenges emerge, new literacies appear to respond to the needs, challenges, and opportunities associated with this change, in fact, “new technologies regularly and repeatedly transform previous literacies, continually redefining what it means to become literate” (Leu et al., 2018, p. 327; Lund et al., 2023). While algorithm literacy has been talked about for a while, according to Dogruel and colleagues (2022), it is still in its infancy and remains a relatively new field of study. In fact, while there is an increasing awareness among many about the impact of algorithmic systems on our socio-digital ecosystems, algorithm literacies have not yet been widely incorporated into the corpus of North American post-secondary education (Head et al., 2020). This calls for the increased visibility of algorithm literacy among scholars, as well as clear definitions that could inform the practice. This research stems from a pressing need to understand the core elements of algorithm literacy as a growing field. The presenters will provide theoretical findings of a systematic literature review about functional definitions of algorithm literacy, its’ core concepts and competencies. These theoretical findings of this study will lay the foundation for those who engage in the curriculum development and delivery of algorithm literacy intervention in the educational context.

Exploring Playful Hybrid Teaching Practices in Higher Education: Insights from the Playful Hybrid Higher Education Project

3:00 - 3:20

There is a new 20min concurrent session after this: 3:25 - 3:45 Practice | Deborah Exelby, Athabasca University Getting the right mix - A risk-based approach to blended learning design for healthcare workplace training Ensuring employees are competent and confident to perform their duties relies on new employee orientation and ongoing training. Currently, there is no industry standard or evidence-informed decision framework to determine when to use face-to-face or online delivery for blended learning in the healthcare workplace. This design case and thesis research investigates how instructional designers use blended learning to ethically balance the patient safety and budget demands that an ever-changing and high-tech workplace creates, by exploring the question: Is there a relationship between the risk of learning content and the mix of online or face-to-face delivery of healthcare workplace training? A mixed methods survey design and correlation analysis was used to gather healthcare workplace instructional designers’ perceptions and preferences about blended learning design by examining their use of learning modalities and interaction techniques in relation to their perceived risk of the content to be learned. The goal of this in-progress thesis research is to verify the design case and develop a risk-based decision tool that aids instructional designers to determine the right mix of blended learning that meets the cost, resource, patient safety and ethical constraints of the healthcare learning environment.

Maryville University