Dichotomy in the design studio : adapting to new blended learning environments

Since the architectural design studio learning environment was first established in the early 19th century at the École des Beaux-Arts in Paris, there has been a complete transformation in how the discipline of architecture is practiced and how students of architecture acquire information. Digital technologies allow students to access information instantly and learning is no longer confined to the rigid boundaries of a physical campus environment. In many schools of architecture in Australia, the physical design studio learning environments however, remain largely unchanged. Many learning environments could be mistaken for those last refurbished 30 years ago, being devoid of any significant technological intervention. While some teaching staff are eagerly embracing new digital technologies and attempting to modify their pedagogical approaches, the physical design studio learning environment is resistant to such efforts. In a study aimed at better understanding how staff and students adapt to new blended learning environments, a group of 165 second year architecture students at a large school of architecture in Australia were separated into two different design studio learning environments. 70% of students were allocated to a traditional design studio setting and 30% to a new, high technology embedded, prototype digital learning laboratory. The digital learning laboratory was purpose designed for the case-study users, adapted Student-Centred Active Learning Environment for Undergraduate Programs [SCALE-UP] principles, and built as part of a larger university research project. The architecture students attended the same lectures, followed the same studio curriculum and completed the same pieces of assessment; the only major differences were the teaching staff and physical environment within which the studios were conducted. At the end of the semester, all staff and students were asked to complete a questionnaire about their experiences and preferences within the two respective learning environments. The questionnaire response rate represented the opinions of 100% of the 10 teaching staff and over 70% of the students. Using a qualitative grounded theory approach, data were coded, extrapolated and compared, to reveal emerging key themes. The key themes formed the basis for in-depth interviews and focus groups of teaching staff and students, allowing the researchers to understand the data in more detail. The results of the data verified what had become increasingly evident during the course of the semester: an underlying negative resistance to the new digital studio learning environment, by both staff and students. Many participants openly exhibited a yearning for a return to the traditional design studio learning environments, particularly when the new technology caused frustration, by being unreliable or failing altogether. This paper reports on the study, discusses the negative resistance and explores the major contributors to resistance. The researchers are not aware of any similar previous studies across these particular settings and believe that it offers a necessary and important contribution to emergent research about adaptation to new digital learning environments.

A new approach for power system black-start decision-making with vague set theory

Power system restoration after a large area outage involves many factors, and the procedure is usually very complicated. A decision-making support system could then be developed so as to find the optimal black-start strategy. In order to evaluate candidate black-start strategies, some indices, usually both qualitative and quantitative, are employed. However, it may not be possible to directly synthesize these indices, and different extents of interactions may exist among these indices. In the existing black-start decision-making methods, qualitative and quantitative indices cannot be well synthesized, and the interactions among different indices are not taken into account. The vague set, an extended version of the well-developed fuzzy set, could be employed to deal with decision-making problems with interacting attributes. Given this background, the vague set is first employed in this work to represent the indices for facilitating the comparisons among them. Then, a concept of the vague-valued fuzzy measure is presented, and on that basis a mathematical model for black-start decision-making developed. Compared with the existing methods, the proposed method could deal with the interactions among indices and more reasonably represent the fuzzy information. Finally, an actual power system is served for demonstrating the basic features of the developed model and method.