This research stream advances research at the intersection between human and artificial cognition. We focus on the relationship between human and artificial cognition, rather than Artificial Intelligence. Our motivation is to deliver accessible and testable hypotheses regarding the ways that cognitive agents intersect with the human cognitive process in learning and knowledge work.  Our model provides insight to educators, policymakers, and business leaders regarding the optimal relationship between which cognitive activities should be handed off to the machine and which should remain the domain of human performance. 

Project List

Trust in Algorithms 

Algorithms are being adopted by institutions, organisations and governments to crunch the vast amounts of information amassed by these social sectors. More importantly, algorithms have great social power as they are being trusted to assist in decision making in high­ and low-­stake contexts. However, given that algorithms are of a statistical nature and have an associated degree of explainability, it can be entertained that a person's level of statistical literacy may play part in the level of trust placed on algorithms. Statistical literacy is essential in that it is needed to make sense of probabilistic and statistic­ related information. This research line examines the role of statistical literacy in trust in algorithms.

Contact person: Dr Fernando Marmolejo-Ramos [email]

Epic Challenges

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Epic Education Foundation: Inspiring Students to Solve Epic Challenges

Students in the 21st century require a combination of soft skills and STEM-based skills to ensure a successful transition into university and the emerging workforce. This course is designed with a project-based curriculum coupled with an enterprise education focus. The innovative nature of the curriculum involves student engagement in an ‘Epic Challenge’, an open-ended, real-world complex problem which does not have an existing or known solution and is multi-disciplinary by nature.

Students will participate in a connected learning environment and work in teams to design their solution for the specified challenge. Through this, students will develop their teamwork skills, knowledge capture skills (problem definition and problem immersion), creative concept generation (creativity tools, creative ideation, concept evaluation), rapid concept development (analysis, prototype, test, design/optimise), and, finally, concept evaluation and selection. Students will also develop STEM skills such as engineering design practices, mathematical literacy, technical expertise and empirical data analysis.

During this program, students will become familiar with space programs, providing them with opportunities to become part of the hub for future space industry development. The final product for this course requires students to present their work in a symposium which will include an audience of real-world engineers and space industry representatives, including NASA astronauts.

Contact person: Dr Rebecca Marrone [website] [email]

Other areas of Interest:

Creativity

Creativity is a core 21st-century skill and examining how people can develop their creativity in an AI world is a crucial challenge. We are currently exploring this topic through several projects. For more information please contact Professor David Cropley or Dr Rebecca Marrone

Contact person: Professor David Cropley, [website] Dr Rebecca Marrone [website]

Sensemaking

Sensemaking is an “open concept” (Pap, 1953, Meehl, 1977) in that it is a term of common use but with fuzzy boundaries and multiple indicators that make it difficult to achieve precision in use. For example, everyday language invokes the concept of sensemaking “Does that make sense?” or “this doesn’t make any sense” in a manner that appeals to an almost intrinsic and universal understanding of the term.

The research in this space is examining “what is uniquely human” in learning, knowledge, and life when technology is increasingly encroaching on domains of cognitive performance that have previously been seen as unique to biological entities with humanity exemplifying the most sophisticated capacity. That is, how do humans make sense of information in this modern learning environment?

Contact person: Professor George Siemens, [website]

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