Evaluation of creative problem solving abilities in undergraduate structural engineers through interdisciplinary problem based learning

For a structural engineer, effective communication and interaction with architects cannot be underestimated as a key skill to success throughout their professional career. Structural engineers and architects have to share a common language and understanding of each other in order to achieve the most desirable architectural and structural designs. This interaction and engagement develops during their professional career but needs to be nurtured during their undergraduate studies. The objective of this paper is to present the strategies employed to engage higher order thinking in structural engineering students in order to help them solve complex problem-based learning (PBL) design scenarios presented by architecture students. The strategies employed were applied in the experimental setting of an undergraduate module in structural engineering at Queen’s University Belfast in the UK. The strategies employed were active learning to engage with content knowledge, the use of physical conceptual structural models to reinforce key concepts and finally, reinforcing the need for hand sketching of ideas to promote higher order problem-solving. The strategies employed were evaluated through student survey, student feedback and module facilitator (this author) reflection. The strategies were qualitatively perceived by the tutor and quantitatively evaluated by students in a cross-sectional study to help interaction with the architecture students, aid interdisciplinary learning and help students creatively solve problems (through higher order thinking). The students clearly enjoyed this module and in particular interacting with structural engineering tutors and students from another discipline

Pregnancy Planning and Diabetes:A Qualitative Exploration of Women's Attitudes Toward Preconception Care

Introduction: Seeking preconception care is recognized as an important health behavior for women with preexisting diabetes. Yet many women with diabetes do not seek care or advice until after they are pregnant, and many enter pregnancy with suboptimal glycemic control. This study explored the attitudes about pregnancy and preconception care seeking in a group of nonpregnant women with type 1 diabetes mellitus. Methods: In-depth semistructured interviews were completed with 14 nonpregnant women with type 1 diabetes. Results: Analysis of the interview data revealed 4 main themes: 1) the emotional complexity of childbearing decisions, 2) preferences for information related to pregnancy, 3) the importance of being known by your health professional, and 4) frustrations with the medical model of care. Discussion: These findings raise questions about how preconception care should be provided to women with diabetes and highlight the pivotal importance of supportive, familiar relationships between health professionals and women with diabetes in the provision of individualized care and advice. By improving the quality of relationships and communication between health care providers and patients, we will be better able to provide care and advice that is perceived as relevant to the individual, whatever her stage of family planning. © 2012 by the American College of Nurse-Midwives.

A Collaborative Multiagent Framework based on Online Risk-Aware Planning and Decision-Making

Planning is an essential process in teams of multiple agents pursuing a common goal. When the effects of actions undertaken by agents are uncertain, evaluating the potential risk of such actions alongside their utility might lead to more rational decisions upon planning. This challenge has been recently tackled for single agent settings, yet domains with multiple agents that present diverse viewpoints towards risk still necessitate comprehensive decision making mechanisms that balance the utility and risk of actions. In this work, we propose a novel collaborative multi-agent planning framework that integrates (i) a team-level online planner under uncertainty that extends the classical UCT approximate algorithm, and (ii) a preference modeling and multicriteria group decision making approach that allows agents to find accepted and rational solutions for planning problems, predicated on the attitude each agent adopts towards risk. When utilised in risk-pervaded scenarios, the proposed framework can reduce the cost of reaching the common goal sought and increase effectiveness, before making collective decisions by appropriately balancing risk and utility of actions.