Knowledge-based interventions for promote conservation behavior: Stories as replacements for direct experience

Report of the Environmental Psychology Lab (EPLab) at the University of Michigan, School of Natural Resources and Environment, Ann Arbor, MI 48109A sustainable planet is not possible without widespread environmental stewardship behavior. Society's resource-costly lifestyles present an historic challenge. Never before have so many behaviors needed to change in so short a time. More challenging is that they must stay changed. This report discusses a potentially effective technique for achieving such goals, the use of knowledge-based narratives. The report begins by developing a theoretical framework for understanding this technique, then presents the important elements of such interventions and ends by providing examples of the use of the technique.U.S. Environmental Protection Agency, Region 3, Pollution Prevention Office, 841 Chestnut Building, Philadelphia, PA 19107-4431http://deepblue.lib.umich.edu/bitstream/2027.42/84331/1/De_Young,_Gilbert,_Manning_&_Weissman_(1993)_Knowledge-based_interventions_for_promoting_conservation_behavior,_Literature_review.pd

Feeling the landscape: six psychological studies into landscape experience

In de zes studies van deze dissertatie zijn een aantal zowel praktische als theoretische vraagstukken met betrekking tot de beleving van landschap onderzocht. Landschapsbeleving wordt gedefinieerd als een dynamisch proces, als het resultaat van interacties tussen cultureel en biologisch bepaalde, algemene determinanten van de ervaring. In de studies wordt een aantal verschillende psychologische theoriën getoetst, en samen tonen deze het belang aan van psychologisch onderzoek naar landschapsbeleving. Het is de toepassing van methodologiën en theoretische perspectieven uit de psychologie, die het mogelijk heeft gemaakt tot de inzichten te komen over de interactie tussen mens en landschap, die het resultaat zijn van deze studie

A constructive theory of automated ideation

In this thesis we explore the field of automated artefact generation in computational creativity with the aim of proposing methods of generation of ideas with cultural value. We focus on two kinds of ideas: fictional concepts and socially embedded concepts. For fictional concepts, we introduce a novel method based on the non-existence-conjectures made by the HR automated theory formation system. We further introduce the notion of typicality of an example with respect to a concept into HR. This leads to methods for ordering fictional concepts with respect to three measurements: novelty, vagueness and stimulation. We ran an experiment to produce thousands of definitions of fictional animals and then compared the software's evaluations of the non-fictional concepts with those obtained through a survey consulting sixty people. The results showed that two of the three measurements have a correlation with human notions.For socially embedded concepts, we apply a typicality-based classification method, the Rational Model of Classification (RMC), to a set of data obtained from Twitter. The aim being the creation of a set of concepts that naturally associate to an initial topic. We applied the RMC to four sets of tweets, each corresponding to one of four initial topics. The result was a set of clusters per topic, each cluster having a definition consisting of a set of words that appeared recurrently in the tweets. A survey was used to ask people to guess the topic given a set of definitions and to rate the artistic relevance of these definitions. The results showed both high association percentage and high relevance scores. A second survey was used to compare the rankings on the social impact of each of the definitions. The results obtained show a weak positive correlation between the two rankings. Our experiments show that it is possible to automatically generate ideas with the purpose of using them for artefact generation. This is an important step for the automation of computational creativity because most of the available artefact generation systems do not explicitly undertake idea generation. Moreover, our experiments introduce new ways of using the notion of typicality and show how these uses can be integrated in both the generation and evaluation of ideas.Open Acces

Mathematical practice, crowdsourcing, and social machines

The highest level of mathematics has traditionally been seen as a solitary endeavour, to produce a proof for review and acceptance by research peers. Mathematics is now at a remarkable inflexion point, with new technology radically extending the power and limits of individuals. Crowdsourcing pulls together diverse experts to solve problems; symbolic computation tackles huge routine calculations; and computers check proofs too long and complicated for humans to comprehend. Mathematical practice is an emerging interdisciplinary field which draws on philosophy and social science to understand how mathematics is produced. Online mathematical activity provides a novel and rich source of data for empirical investigation of mathematical practice - for example the community question answering system {\it mathoverflow} contains around 40,000 mathematical conversations, and {\it polymath} collaborations provide transcripts of the process of discovering proofs. Our preliminary investigations have demonstrated the importance of "soft" aspects such as analogy and creativity, alongside deduction and proof, in the production of mathematics, and have given us new ways to think about the roles of people and machines in creating new mathematical knowledge. We discuss further investigation of these resources and what it might reveal. Crowdsourced mathematical activity is an example of a "social machine", a new paradigm, identified by Berners-Lee, for viewing a combination of people and computers as a single problem-solving entity, and the subject of major international research endeavours. We outline a future research agenda for mathematics social machines, a combination of people, computers, and mathematical archives to create and apply mathematics, with the potential to change the way people do mathematics, and to transform the reach, pace, and impact of mathematics research.Comment: To appear, Springer LNCS, Proceedings of Conferences on Intelligent Computer Mathematics, CICM 2013, July 2013 Bath, U

Predictors of recall and reading time for seductive and nonseductive text segments

This correlational study explored how concreteness, relevance, importance, and interestingness related to the recall of seductive details and base text, while controlling for text coherence, and student background knowledge. Previous research has provided evidence for the significant relationship between these variables and the seductive details effect in particular and text recall in general. However, this is the first study to consider all these variables simultaneously. A group of 68 undergraduates read an expository text on lightning formation, performed an immediate test on free recall, and rated each text sentence for concreteness, relevance, importance, and interestingness. A simple regression analysis revealed that only interest significantly improved students\u27 recall of seductive sentences. However, none of the four ratings or the reading time predicted recall of base text sentences. Results regarding reading time demonstrated that seductive sentences were read faster than base text sentences. Strong positive correlation was revealed between relevance and importance. This result indicated that in the absence of explicit relevance instruction, relevance and importance could be used interchangeably. Significant positive correlation was revealed between concreteness and interest. However, this correlation was lower than expected. This result was interpreted in the light of Dual Coding Theory

The effect of negative feedback on motivation : a meta-analytic investigation

textAlthough the most prominent view in psychological theory has been that negative feedback should generally have a detrimental impact on motivation, competing perspectives and caveats on this prominent view have suggested that negative feedback may sometimes have neutral or even positive effects on motivation. A meta-analysis of 79 studies examined the effect of negative feedback on motivation and related outcomes with both child and adult samples. Results indicated that negative feedback compared to positive feedback decreased intrinsic motivation and perceived competence. This effect is much smaller when compared to neutral or no feedback. Moderator tests revealed that the effect of negative feedback seems to be less demotivating when a) the feedback statement includes instructional details to improve, b) compared to objective versus normative standards, and c) the task is interesting. Implications for future research and applications to real-world settings are discussed.Educational Psycholog

A Longitudinal Mixed Methods Study of Norwegian Preservice Teachers’ Beliefs About Sources of Teaching Knowledge and Motivation to Learn From Theory and Practice

We set out to investigate preservice teachers’ beliefs about sources of teaching knowledge and their motivation to learn from practice and theory in teacher education in a longitudinal study (n = 96, at the beginning of the study). Participants placed more trust in experiential knowledge sources compared with formalized sources and participants’ beliefs about sources of teaching knowledge generally predicted their motivation to learn from different sources. Quantitative results were further supported and elaborated by qualitative interview data that suggested development of preservice teachers’ beliefs about sources of teaching knowledge and their understanding of the relation between theoretical and practical knowledge over time. The findings extend existing literature by providing a window on how (preservice) teachers may articulate their views about sources of teaching knowledge and relations between theory and practice, with expected consequences for teaching practice. Implications for teacher educators’ practice are also discussed.publishedVersio

Art as Communication: Employing Gricean Principles of Communication as a Model for Art Appreciation

Abstract How and why artworks elicit varied preferences and judgments among different individuals remains a topic with many unresolved issues. For instance, individuals with little artistic experience tend to show little appreciation for abstract art, even though such works often show a highly skilled organization of visual elements. A key aspect of a positive aesthetic experience concerns the ability of viewers to construct meaning. I propose that viewers attempt to make meaning of artworks due to a sense that art is a communicative process. Here I attempt an application of one intentionalist model of communication, the Gricean framework, to visual art. I examine a great deal of empirical psychological research on art appreciation and subsume the research under the Gricean model. A survey instrument was developed to capture artistic communication and assess its usefulness in predicting aesthetic liking. A key component to this model is the cooperative principle, the implicit agreement of those engaged in a dialogue are doing so with the intent to be understood. With the cooperative principle established four maxims follow to facilitate meaning making in verbal discourse; quality, quantity, meaning, and relation. These maxims along with intent were operationalized according to prior literature and measured on a 6-point Likert scale. Using Rasch analysis over several rounds of testing with artists and non-artists, the survey instrument was refined; the interitem correlations for each construct were robust and reliable. Hierarchical liner modeling was used to assess the predictive power of each maxim and intent for aesthetic liking for both artists and non-artist for images that range in their level of abstractedness. The level one analysis showed significant effects for all variables with positive coefficients, indicating that maxim fulfillment (or understanding nonfulfillment as intentional) was related to increased liking. The level two analysis showed that all maxims with the exception of quantity maintained their relative weight in predicting liking; quantity was more effective in predicting liking as images became more representational. Artist and non-artist differences in maxim fulfillment, intent, and liking were examined for the four most abstract and representational images following the logic that differences seen in previous research for these two groups might be a function of understanding nonfulfillment of the maxims to be intentional. There were no differences seen for artists and non-artists for the four most representational images. However, for the four most abstract images there were differences seen for all the maxims and liking but not for intent; the differences were in the direction of the artists having significantly higher mean ratings. The nonsignificant intent scores indicate that even with abstract artworks the cooperative principle is met for both groups therefore it can be argued that artists see intentional nonfulfillment whereas non-artists see violations. In order to disrupt the cooperative principle in study two creator type (animal, child, and artist) was varied with the expectation that viewers would not expect an animal to communicate in a similar way as a child or an artist. Hierarchical linear modeling was done separately for each attributed creator type for each maxim in predicting liking. All maxims and intent when looked at individually were significant predictors of liking for the attributed child creator, although the coefficient for quantity was negative indicating the less visual elements, or less fulfillment, the more images were liked; all but quantity were significant predictors for the attributed animal and artist. The disagreement of quantity from the first study could be a function of the abstractness of the images, which was necessary for them to be plausibly created by any of the three creator types. A follow-up ANOVA showed that intent did not vary as a function of creator type. A median split was performed to indicate those who are low and high in intent to examine patterns in the data. All follow-up factorial ANOVAs showed intent as a significant between-subjects factor with results indicating those high in intent provided higher evaluations for each maxim and liking. These findings are interesting because they give support to the idea that those who are engaged in the process of wanting to understand or make meaning rate the maxims and liking different than those who are less engaged cooperatively. Also of interest is that there are high and low intent individuals in each of the three creator types; so the use of animals in this study did not push the limit of the cooperative principle quite far enough. Future studies would have to examine this issue. It could be that individuals automatically engage with art as a place to derive meaning and there isn\u27t a way to push this factor. The take home however is that the Gricean framework thus far has shown to be a fruitful means of capturing perceived artistic communication and how that contributes to liking. It is possible to create measurement tools for other art types, such as music, performance, or literature