WEATHER AND CLIMATE AS EVENTS: CONTRIBUTIONS TO THE PUBLIC IDEA OF CLIMATE CHANGE

One aspect of the psychology of weather and climate concerns the multiple meanings that may be associated with weather and climate as event. Atmospheric scientists and journalists have increasingly described both weather and climate as event. In this paper, the authors documented the increasing use of weather and climate as events in the scholarly literature of the American Meteorological Society and in newspaper articles over time. The authors also conducted pathfinder network scaling analyses with event-related terms to assess the meanings of events in academic and journalistic writing. The analyses suggested four contexts of event meanings: (1) study of ordinary weather or climate occurrences, (2) the study and attribution of severe and extreme weather, (3) societal impacts of weather, and (4) the public lexicon. Communicating about weather and climates as event contributes to the development and evolution of the public idea of climate change. The burgeoning of event in discourse contributes to the public idea of climate change in at least three ways: (1) events contribute specificity to the more general idea of climate change; (2) events contribute experientiality of climate change, and (3) events contribute exemplification to the public idea of climate change to the extent that weather events can be attributed to climate change.

Visualizing the Evolution of Mobile Learning Research

The aim of this chapter is to investigate the scope and change of m-learning literature over a period of thirteen years. The chapter takes an author co-citation approach where patterns are revealed in mlearning publications between the years 2002 and 2015. The author co-citation analysis is a kind of bibliometrics, and Power Flow Network Library (PFNET) analysis method to obtain the intellectual structure of the m-learning field. A PFNET is a psychometric scaling method where a network of associative nodes is generated using specific values. The method is based on graph theory and has been used to explore knowledge connections. The method is referred to as a pathfinder network for representing segments of knowledge in a branched manner. The method can also be used for developing consensus building or recognizing expertise in a specific area. In this study, it was found that the m-learning research focus on design and effectiveness of m-learning environments, developing a pedagogic framework for m-learning, adoption and proliferation of m-learning-assisted language learning, collaborative m-learning, and augmented reality. Assessing the results of factor analysis together with the PFNET graphics, the subfields show the fundamental orientations of the field, and the main themes will be the focus of future research.

The Influence of Rating Method on Knowledge Structures

Pathfinder network scaling has been used widely to assess knowledge acquisition and inform interface design. While a large body of research agrees on the validity of this technique to develop knowledge structures, the rating task becomes cumbersome when users are faced with a large number of concepts to relate. Thus, a new rating method was created to help users determine the relationships between concepts. This new interface allows subjects to judge proximity by arranging concepts in visual space on a target. Traditionally, subjects were presented the concepts in pairs and made ratings on Likert Scales. Students ( N = 88) at the Air Force Academy used both methods to rate the similarity of basic flying concepts. Results showed that the new method was more sensitive to differences in knowledge structures between experienced and inexperienced pilots ( p < .01). Experienced subjects also preferred the new target method compared to the traditional rating method. The relative efficiency of the two methods is discussed.