The design studio as liminal space

This study focuses on the efficacy of design studio as a form of teaching and learning, where traditional approaches can act to position the tutor as a defender of the knowledge community rather than a discourse guide for the student. The broad curriculum of architectural education with its divergent outcomes resulting from project based learning also makes it difficult to agree on what constitutes the fundamental elements of the curriculum. The research used an approach based on threshold concepts to assist in identifying and overcoming these shortcomings. Such approaches have been described as 'liminal': holding the learner in a supportive 'in-between' state where learning resources can be directed to that which is troublesome and conceptually difficult. The study involved the use of practices to identify troublesome knowledge in design studio and conceptualise blended learning as part of a liminal studio space.

Brief response to Ashton and colleagues regarding Fractionating Human Intelligence

Ashton and colleagues concede in their response (Ashton, Lee, & Visser, in this issue), that neuroimaging methods provide a relatively unambiguous measure of the levels to which cognitive tasks co-recruit dif- ferent functional brain networks (task mixing). It is also evident from their response that they now accept that task mixing differs from the blended models of the classic literature. However, they still have not grasped how the neuroimaging data can help to constrain models of the neural basis of higher order ‘g’. Specifically, they claim that our analyses are invalid as we assume that functional networks have uncorrelated capacities. They use the simple analogy of a set of exercises that recruit multiple muscle groups to varying extents and highlight the fact that individual differences in strength may correlate across muscle groups. Contrary to their claim, we did not assume in the original article (Hampshire, High- field, Parkin, & Owen, 2012) that functional networks had uncorrelated capacities; instead, the analyses were specifically designed to estimate the scale of those correlations, which we referred to as spatially ‘diffuse’ factors