Cities and the real world

It is generally recognized that modern cities pose many problems for their inhabitants and contribute to environmental damage. However, neither planners nor scientists give adequate consideration to cities’ place in the evolutionary process and the planet's ecological system. By recognizing these connections and natural laws, planning would become more realistic, and meaningful progress could be made in solving serious social and environmental problems. Some basic problems influencing urban form are discussed, and a schematic example of how we might approach the planning of urban settlements is presented.     

Initial validation of the coach-created Empowering and Disempowering Motivational Climate Questionnaire (EDMCQ-C)

This article employs Duda's (2013) hierarchical conceptualization of the coach-created motivational climate to inform the validation of a questionnaire (Empowering and Disempowering Motivational Climate Questionnaire-Coach; EDMCQ-C) that assesses junior athletes' perceptions of the social environmental dimensions proposed by achievement goal theory and self-determination theory. Confirmatory factor analyses (CFA) were initially employed to reduce the number of items required to measure the targeted climate dimensions. A series of competing models were then tested to determine the best representation of the questionnaire's factor structure. The findings revealed that exploratory structural equation modelling (ESEM) provided a better fit of the data to the hypothesised model than CFA solutions. Specifically, the bi-factor ESEM provided the best fit, although parameter estimates suggest that none of the ESEM solutions replicated the underlying theoretical model of the motivational climate proposed by Duda (2013). The evidence from this study suggests that the EDMCQ-C is a promising, parsimonious questionnaire to assess empowering and disempowering facets of the motivational climate albeit the development of the questionnaire remains a work in progress.     

Effectiveness in top management group meetings: The role of goal clarity,focused communication,and learning behavior

Bang, H., Fuglesang, S. L., Ovesen, M. R. & Eilertsen, D. E. (2010). Effectiveness in top management group meetings: The role of goal clarity, focused communication, and learning behavior. Scandinavian Journal of Psychology, 51, 253–261. To explore the relationship between goal clarity, focused communication, learning behavior, and team effectiveness (i.e., task performance, relationship quality, and member satisfaction), self‐report and observer data from eight top management groups that processed 56 agenda items during meetings were analyzed. We found that goal clarity and focused communication was positively related to team effectiveness. The effect of goal clarity on team effectiveness was partially mediated by focused communication. Speaking up when a goal was unclear increased focused communication, task performance and relationship quality. Speaking up when the discussion was off track was not related to task performance and member satisfaction, and was negatively related to relationship quality. These findings have implications for how to conduct an effective management meeting.     

Incomplete Ecological Futures

Abstract

The scenario planning literature has so far not provided a detailed study of the negative policy consequences which could unfold from an incomplete realization of future scenarios. In order to address this shortcoming, the article analyses four GSG scenarios – Market Forces, Policy Reform, Eco-Communalism, and New Sustainability Paradigm – and associate them with a theory of environmental politics – respectively, the Environmental Kuznets Curve hypothesis, the a-growth theory, the degrowth proposal, and ecomodernism. Then, through a literature review of those theories, the article explores the dynamics which could prevent humanity from realizing the visions of sustainable futures enshrined into the four scenarios; by doing so, the article provides a picture of how GSG’s and similar scenarios might become incomplete ecological futures.     

Assessing Mathematics Misunderstandings via Bayesian Inverse Planning

Online educational technologies offer opportunities for providing individualized feedback and detailed profiles of students' skills. Yet many technologies for mathematics education assess students based only on the correctness of either their final answers or responses to individual steps. In contrast, examining the choices students make for how to solve the equation and the ways in which they might answer incorrectly offers the opportunity to obtain a more nuanced perspective of their algebra skills. To automatically make sense of step-by-step solutions, we propose a Bayesian inverse planning model for equation solving that computes an assessment of a learner's skills based on her pattern of errors in individual steps and her choices about what sequence of problem-solving steps to take. Bayesian inverse planning builds on existing machine learning tools to create a generative model relating (mis)-understandings to equation solving choices. Two behavioral experiments demonstrate that the model can interpret people's equation solving and that its assessments are consistent with those of experienced teachers. A third experiment uses this model to tailor guidance for learners based on individual differences in misunderstandings, closing the loop between assessing understanding, and using that assessment within an educational technology. Finally, because the bottleneck in applying inverse planning to a new domain is in creating the model of possible student misunderstandings, we show how to combine inverse planning with an existing production rule model to make inferences about student misunderstandings of fraction arithmetic.     

Scenario Planning: The Basics

This article covers the basics of scenario planning: Why scenarios? What are scenarios? How do you develop scenarios? After covering the preliminaries—the constitution of the scenario team; interviews; research; the identification of a focal issue; set and setting for a scenario workshop; staffing; the trajectory of a scenario planning project—the article moves on to describe several methods for identifying a finite set of diverse scenario logics. After a set of scenarios has been developed, there are several different routes from scenarios to strategy. Early indicators can help identify which of several scenarios is in fact unfolding.