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Statistical modeling continues to gain prominence in the secondary curriculum, and recent recommendations to emphasize data science and computational thinking may soon position algorithmic models into the school curriculum. Many teachers’ preparation for and experiences teaching statistical modeling have focused on probabilistic models. Subsequently, much of the research literature related to the teachers’ understanding has focused on probabilistic models. This study explores the extent to which secondary statistics teachers appear to understand ideas of statistical modeling, specifically the processes of model building and evaluation, when introduced using classification trees, a type of algorithmic model. Results of this study suggest that while teachers were able to read and build classification tree models, they experienced more difficulty when evaluating models. Further research could continue to explore possible learning trajectories, technology tools, and pedagogical approaches for using classification trees to introduce ideas of statistical modeling.

The present study aimed to examine the contributions of two separate Pinyin skills and oral vocabulary to Chinese word reading of 70 third graders in a U.S. Mandarin Immersion program where Pinyin was introduced at Grade 3. Hierarchical regression analyses showed that Pinyin initial-final spelling—the skill to spell Chinese syllables using Pinyin letters—and oral vocabulary were uniquely associated with Chinese word reading, after accounting for the effects of phonological awareness and the other Pinyin skill of tone identification. The variance in Chinese word reading explained by tone identification was fully accounted for by oral vocabulary, Pinyin initial–final spelling, and phonological awareness, suggesting that tone identification might involve both phonology- and meaning-related processes. Oral vocabulary and tone identification explained more shared variance in Chinese word reading than the two code-related skills of phonological awareness and Pinyin initial-final spelling. The importance of meaning-related skills in learning the deep orthography of Chinese characters for Chinese L2 young learners is discussed.

Statistical modeling allows students to construct and improve representations based on their experiences. A model development sequence is used with fifth graders to build models for comparing two distributions of the flight durations of paper helicopters. Emphasis is on the role of the teacher and using models as evidence.

This quantitative study examined the link between food insecurity and mental health concerns among a sample of 1,229 undergraduate students at a large, public university. Using logistic regression,...

Understanding effects on the overall well-being of the communities affected by the Pak Mun Dam construction would fill in the gaps in existing knowledge and facilitate a deeper discussion of the factors that impact overall wellbeing. The Pak Mun Dam was finished in 1994 and from that point on there have been changes affecting local residents. This study attempts to understand the impact of those changes from a well being perspective using primary data collected from residents in villages close to the dam site. Structural Equation Model (SEM) was method for this research analysis. Results from a structural model show that social and economic well-being are important factors that impact the overall well-being of the affected residents from the Pak Mun Dam area. Furthermore, we discuss how information from 20 items within seven dimensions of the well-being measurement model can be used to develop more efficient strategies and policies to increase well-being capital.

Recientemente el razonamiento estadistico ha sido de vital importancia no solo en el analisis cuantitativo, sino tambien en la interpretacion de graficos a todos los niveles educativos. Existen estudiantes que pueden realizar distintos calculos de manera casi inmediata, sin embargo, no pueden interpretar o exponer sus ideas en un grafico. De esta manera, el presente trabajo pretende realizar un diagnostico de los problemas que tienen los alumnos de licenciaturas economico-administrativas para leer e interpretar graficos en su curso de estadistica. Para ello se aplico una prueba en su version en espanol de Comprehensive Assessment of Outcomes in Statistics (CAOS). Dicho instrumento permite determinar como interpreta su razonamiento sobre distintos tipos de graficos estadisticos y en algunos casos determinar que tipo de calculo se requiere para ello. El instrumento se aplico a una muestra de 138 estudiantes de licenciaturas del area economico-administrativas de la Universidad de Guadalajara durante el semestre de enero-junio del 2018. Los resultados muestran que un gran porcentaje de los alumnos confunden la distribucion normal con una uniforme, no distinguen que un sesgo se puede determinar por sus medidas de tendencia central o dispersion, entre otras dificultades de razonamiento estadistico. Esto puede ser debido a la deficiencia que existe en la ensenanza de la estadistica, una preparacion matematica insuficiente de los estudiantes, entre otros factores.

Statistical thinking partially depends upon an iterative process by which essential features of a problem setting are identified and mapped onto an abstract model or archetype, and then translated back into the context of the original problem setting (Wild and Pfannkuch 1999). Assessment in introductory statistics often relies on tasks that present students with data in context and expects them to choose and describe an appropriate model. This study explores post-secondary student responses to an alternative task that prompts students to clearly identify a sample, population, statistic, and parameter using a context of their own invention. The data include free text narrative responses of a random sample of 500 students from a sample of more than 1600 introductory statistics students. Results suggest that students' responses often portrayed sample and population accurately. Portrayals of statistic and parameter were less reliable and were associated with descriptions of a wide variety of other concepts. Responses frequently attributed a variable of some kind to the statistic, or a study design detail to the parameter. Implications for instruction and research are discussed, including a call for emphasis on a modeling paradigm in introductory statistics.

Statistical modeling is a core component of statistical thinking and has been identified by several countries as a curricular goal for secondary education. However, many secondary teachers have minimal preparation for teaching this topic. The goal of this research study is to learn about teachers’ perceptions of the role statistical models play in statistical inference and how these perceived purposes affect their reasoning about statistical models and inference. Problem-solving interviews were conducted with four in-service teachers who had recently taught a modeling and simulation-based introductory statistics course. Teachers’ responses suggest they may not see modeling variation as the primary purpose of statistical modeling and instead substitute two other purposes: making a decision and replicating the data collection process. Suggestions for how to build on teachers’ transitional conceptions and refocus attention on modeling variation are discussed.

Teaching from an informal statistical inference perspective can address the challenge of teaching statistics in a coherent way. We argue that activities that promote model-based reasoning address two additional challenges: providing a coherent sequence of topics and promoting the application of knowledge to novel situations. We take a models and modeling perspective as a framework for designing and implementing an instructional sequence of model development tasks focused on developing primary students’ generalized models for drawing informal inferences when comparing two sets of data. This study was conducted with 26 Year 5 students (ages 10-11). Our study provides empirical evidence for how a modeling perspective can bring together lines of research that hold potential for the teaching and learning of inferential reasoning. First published November 2017 at Statistics Education Research Journal Archives

We examined effects of research-based early writing intervention delivered within a data-based instruction (DBI) framework for children with intensive needs. We randomly assigned 46 students with and without disabilities in Grades 1 to 3 within classrooms to either treatment or control. Treatment students received research-based early writing intervention within a DBI framework for 30 min, 3 times per week, for 12 weeks. Control students received business-as-usual writing instruction. We measured writing performance using curriculum-based measures (CBM) and Woodcock Johnson III Tests of Achievement (WJ III). We found significant treatment effects on CBM outcomes (Hedges g = 0.74 to 1.36). We also found a significant interaction between special education status and condition on the WJ III favoring treatment students with disabilities (Hedges g = 0.45 to 0.70). Findings provide preliminary support for using a combination of research-based intervention and DBI with students with intensive writing needs.

There is a need for more effective rehabilitation methods for individuals post-stroke. Occupational Therapy Task-Oriented (TO) approach has not been evaluated in a randomized clinical trial. The purpose of this study was to evaluate functional and impairment efficacies of TO approach on the more-affected Upper Extremity (UE) of persons post-stroke. A randomized single-blinded cross-over trial recruited 20 participants post-stroke (mean chronicity = 62 months) who demonstrated at least 10° active more-affected shoulder flexion and abduction and elbow flexion-extension. Participants were randomized into immediate (n = 10) and delayed intervention (n = 10) groups. Immediate group had 6 weeks of 3 hr/week TO intervention followed by 6 weeks of no-intervention control. Delayed intervention group underwent the reversed order. Functional measures included Canadian Occupational Performance Measure (COPM), Motor Activity Log (MAL), and Wolf Motor Function Test (WMFT). Impairment measures included UE Active Range of Motion (AROM) and handheld dynamometry strength. Measurements were obtained at baseline, cross over, and end of the study. TO intervention showed statistically higher functional change scores. COPM performance and satisfaction scores were 2.83 and 3.46 units greater respectively (p

A major initial step in professionalizing intercultural relations as an applied field of study is to determine the ethical concerns of people actively involved in both scholarship and practice. Some intercultural relations organizations have established committees to develop standards of ethical behavior. There are many anecdotal accounts of unethical practices but there have been few systematic studies of such practices. This is the first large comprehensive quantitative survey of intercultural experts that contrasts and compares the concerns of both scholars and practitioners. The purpose of this exploratory study is to identify major ethical issues in the field of intercultural relations. Members of two major professional organizations were asked to identify what they believe are the major ethical concerns in the field of intercultural relations. Members of one organization were mostly intercultural practitioners while the other included mostly scholars. The results revealed that although there were great similarities in ethical concerns, there were also differences that were most likely a result of the two different professions. Of course, there were also some respondents who were members of both organizations and both professions. We identify, differentiate, and prioritize ethical concerns of scholars and practitioners. Although some differences were found in the types and ranking of ethical concerns, members of both professions believe that perpetuating cultural stereotypes and deceptively presenting one's intercultural relations training skills are the top two major ethical concerns, followed by misuse of training tools or instruments and delivering services that are not in the best interests of clients.

First published November 2014 at Statistics Education Research Journal Archives

First published November 2014 at Statistics Education Research Journal Archives

Since the nineties, atmospheric measurement systems have been deployed at Reunion Island, mainly for monitoring the atmospheric composition in the framework of NDSC/NDACC (Network for the Detection of Stratospheric< /i> Change/Network for the Detection of Atmospheric Composition Change). The location of Reunion Island presents a great interest because there are very few multi-instrumented stations in the tropics and particularly in the southern hemisphere. In 2012, a new observatory was commissioned in Maïdo at 2200 m above sea level: it hosts various instruments for atmospheric measurements, including lidar systems, spectro-radiometers and in situ gas and aerosol measurements. This new high-altitude Maïdo station provides an opportunity: 1. to improve the performance of the optical instruments above the marine boundary layer, and to open new perspectives on upper troposphere and lower stratosphere studies; 2. to develop in situ measurements of the atmospheric composition for climate change surveys, in a reference site in the tropical/subtropical region of the southern hemisphere; 3. to offer trans-national access to host experiments or measurement campaigns for focused process studies. © 2013 Author(s)., SCOPUS: ar.j, info:eu-repo/semantics/published

While models are an important concept in statistics, few introductory statistics courses at the tertiary level put models at the core of the curriculum. This paper reports on a radically different approach to teaching statistics at the tertiary level, one that uses models and simulation as the organizing theme of the course. The focus on modeling and simulation—along with inference—was facilitated by having students use TinkerPlots™ software for all modeling and analysis. Results from a 3-month teaching experiment suggest that a course focused on modeling and simulation through randomization and resampling methods in which students learn to think using a powerful and conceptual modeling tool can foster ways of thinking statistically. Furthermore, such an approach seems to help students develop experiences with and appreciation for the science and practice of statistics.

SERJ has provided a high quality professional publication venue for researchers in statistics education for close to a decade. This paper presents a review of the articles published to explore what they suggest about the field of statistics education, the researchers, the questions addressed, and the growing knowledge base on teaching and learning statistics. We present a detailed analysis of these articles in order to address the following questions: What is being published and why, who is publishing research in SERJ, how is the research being carried out, and what do the results suggest about future research? Implications for future directions in statistics education research are suggested. First published November 2011 at Statistics Education Research Journal: Archives

This study investigated gender differences in science learning between two pedagogical approaches: traditional lecture and narrative case studies using personal response systems (‘clickers’). Thirteen instructors of introductory biology classes at 12 different institutions across the USA and Canada used two types of pedagogy (Clicker Cases and traditional lecture) to teach eight topic areas. Three different sets of multiple regression analysis were conducted for three separate dependent variables: posttest score, change in score from posttest to final, and transfer score. Interactions between gender and pedagogical approach were found across the three analyses. Women either performed better with Clicker Cases, or about the same with either instructional method, but men performed markedly better with lectures in most topic areas. Our results suggest that men and women experience two pedagogical approaches—Clicker Cases and lectures—differently, and that Clicker Cases are more favorable for women than for men.

Within statistics education, there is a growing interest in understanding students' application of understanding about variability and sampling given the relative lack of research in either area (Shaughnessy, 2007). The task examined in this paper elicited students' knowledge of these concepts within a small-group problem solving task completed by teams of first-year engineering students. In the Nanoroughness task, teams of students designed a procedure for quantifying the roughness of a material surface using digital images generated by atomic force microscopy. The procedure required students to apply statistical methods in order to aggregate the data. The focus of this article is the subsequent analysis of the responses to the task and the questions raised by that analysis. The Nanoroughness task is unique but critical as a statistical modeling task for two reasons. First, the students needed to use statistical measures to develop a measure that would describe a qualitative characteristic (roughness) without any prompting as to what statistical procedures were relevant. There are different ways to conceptualize roughness of a surface. Sandpaper’s roughness depends on the grain size of the sand. A road may be rough if it has randomly occurring large holes but smoother if the bumps are evenly distributed. The challenge in developing quantitative measures to define qualitative characteristics is that different quantitative analyses emphasize different variables and the students needed to both analyze and apply statistical procedures relevant to the context. For instance, determining which member of a set is the "most rough" or the "least rough" will depend on what measurements were selected, and how those measures were analyzed. The second unique characteristic of the task is that the students also needed to define a sampling procedure for an image that would facilitate quantifying the variability in the surface portrayed in the digital image. Usually when students need to take measurements of a population, the population is a discrete set of objects. In this case, the data set was a continuous surface. From the data set, the students need to determine the relevant population (e.g., every point on the surface, every peak on the surface, peaks and valleys). Such continuous populations are not unique within engineering and the sciences and occur in a variety of contexts where characteristics need to be measured and operationally defined. The task was implemented in a first-year engineering course that served as an introduction to basic tools of engineering with an emphasis on MatLab® and Excel® as technological tools. The Nanoroughness task was used in the course to introduce students to the real work of engineers who must not only calculate statistics but also analyze and interpret the results. Our research asked a two-part question. First, what is the quality of student responses to the Nanoroughness task? To answer this we looked at the viability of the model they had created and how well they had explained their procedure for comparing the roughness of images. Second, what statistical models were elicited by the task? We specifically looked at the sampling methods students used and then how the students analyzed the data set they had created. In this paper, we describe the quantitative and qualitative analyses we completed of a sample of student responses.

Although interactive technology is presumed to increase student understanding in large classes, no previous research studies have empirically explored the effects of Clicker Cases on students’ performance. A Clicker Case is a story (e.g., a problem someone is facing) that uses clickers (student response systems) to engage students in understanding the meaning of the science contained within the story. Using an experimental randomized Solomon design across 11 institutions, we found that Clicker Cases increased student understanding more than PowerPoint lectures in large introductory biology classrooms, although there was variation across institutions and topics. By examining student performance in conjunction with faculty experience, we found that strong Clicker Cases created dissonance, captured attention and involved students in interpreting data or making decisions. This study provides a model for collaborative research across multiple institutions and demonstrates the need for using multiple institutions and topics in research on education.

First published November 2011 at Statistics Education Research Journal: Archives

Summary The Assessment Resource Tools for Improving Statistical Thinking (ARTIST) Web site was developed to provide high-quality assessment resources for faculty who teach statistics at the tertiary level but resources are also useful to statistics teachers at the secondary level. This article describes some of the numerous ARTIST resources and suggests ways teachers may use these assessment resources.

International audience; Sixteen years of ozone measurements (1992-2006) at Reunion Island (21°S, 55.5°E) have been processed to detect stratospheric signatures on each single ozone profile. The characterisation method consists in the advection of the potential vorticity (PV) over two to ten days of backtrajectory with the lagrangian trajectory code LACYTRAJ. LACYTRAJ is a Trajectory-Reverse Domain Filling code using the ERA40 ECMWF database and allowing the reconstruction of high resolution advected PV profiles. Correlation between high values of ozone mixing ratio and high PV is interpreted as a stratospheric signature. A climatology of STE events at Reunion has been derived and reveals that STE events occur more frequently during spring (SON) and summer (DJF). The method is tested for a set of PV threshold values (i.e. 1 PVU, 1.5 PVU and 2 PVU) and for a set of duration of backtrajectories (i.e. 2 days, 5 days and 10 days). The number of detected STE is sensitive to PV threshold values and duration criterions. For instance, the number of stratospheric intrusions detected in October with a 1.5 PVU criterion ranges between 25% (2 days of backtrajectories) and 56% (10 days of backtrajectories). The vertical distributions of STE show intrusions covering the whole free troposphere (between 7 and 15 km) and mainly located in the upper troposphere. Finally, results show that an important number of stratospheric intrusions are detected during spring and in the upper troposphere what points at the contribution of the stratospheric source to the tropospheric ozone spring maximum which is strongly influenced by the biomass burning emissions from South Africa and Madagascar.

Informal inferential reasoning is a relatively recent concept in the research literature. Several research studies have defined this type of cognitive process in slightly different ways. In this paper, a working definition of informal inferential reasoning based on an analysis of the key aspects of statistical inference, and on research from educational psychology, science education, and mathematics education is presented. Based on the literature reviewed and the working definition, suggestions are made for the types of tasks that can be used to study the nature and development of informal inferential reasoning. Suggestions for future research are offered along with implications for teaching. First published November 2008 at Statistics Education Research Journal: Archives

This paper describes the development of the CAOS test, designed to measure students’ conceptual understanding of important statistical ideas, across three years of revision and testing, content validation, and realiability analysis. Results are reported from a large scale class testing and item responses are compared from pretest to posttest in order to learn more about areas in which students demonstrated improved performance from beginning to end of the course, as well as areas that showed no improvement or decreased performance. Items that showed an increase in students’ misconceptions about particular statistical concepts were also examined. The paper concludes with a discussion of implications for students’ understanding of different statistical topics, followed by suggestions for further research. First published November 2007 at Statistics Education Research Journal: Archives

The current study applied five formulas for distributing parental incomes at divorce to 414 court case records in Minnesota and evaluated which formulas and actual court orders provided sufficient incomes for male and female-headed households. The study further explored influences of pre-divorce gross income levels, household/genders, and lengths of marriage on the post-divorce income-to-needs ratios (ITN) produced by the five formulas and actual court orders, using MANOVA. Results were interpreted using distributive justice principles of equity, needs, and contributions. Males have higher ITN with each alternative, except the income-sharing formula. The actual court orders and the income-sharing formula produce the largest discrepancy between male and female ITN and the highest percentage of females living below poverty level guidelines.

This study investigated introductory statistics students’ conceptual understanding of the standard deviation. A computer environment was designed to promote students’ ability to coordinate characteristics of variation of values about the mean with the size of the standard deviation as a measure of that variation. Twelve students participated in an interview divided into two primary phases, an exploration phase where students rearranged histogram bars to produce the largest and smallest standard deviation, and a testing phase where students compared the sizes of the standard deviation of two distributions. Analysis of data revealed conceptions and strategies that students used to construct their arrangements and make comparisons. In general, students moved from simple, one-dimensional understandings of the standard deviation that did not consider variation about the mean to more mean-centered conceptualizations that coordinated the effects of frequency (density) and deviation from the mean. Discussions of the results and implications for instruction and further research are presented. First published May 2005 at Statistics Education Research Journal: Archives

Acid layers of volcanic origin detected in polar snow and ice layers are commonly used to document past volcanic activity on a global scale or, conversely, to date polar ice cores. Although most cataclysmic eruptions of the last two centuries (Pinatubo, El Chichon, Agung, Krakatoa, Cosiguina, Tambora, etc.) occurred in the tropics, cold tropical glaciers have not been used for the reconstruction of past volcanism. The glaciochemical study of a 137 m ice core drilled in 1999 close to the summit of Nevado Illimani (Eastern Bolivian Andes, 16°37' S, 67°46' W, 6350 m asl) demonstrates, for the first time, that such eruptions are recorded by both their tropospheric and stratospheric deposits. An 80-year ice sequence (1918-1998) and the Tambora years have been analyzed in detail. In several cases, ash, chloride and fluoride were also detected. The ice records of the Pinatubo (1991), Agung (1963) and Tambora (1815) eruptions are discussed in detail. The potential impact of less important regional eruptions is discussed.

A 137 m ice-core drilled from Eastern Bolivian Andes at Nevado Illimani (16°37'S, 67°46'W, 6350 m asl) allows studying historical concentrations of heavy metals in South America aerosol along the 20 th century. About 50 m of this ice-core were dated by multi-proxy analysis, providing a record of environmental variations of about 80 years from 1919 to 1999. Elemental concentrations for 45 chemical species (Li to U) in 744 samples along the upper 50 m ice-core section were determined by Inductively Coupled Plasma-Mass Spectrometry. This work focuses on heavy metal concentrations along the ice-core profile. Further discussion on other trace elements is given elsewhere [1]. Most elements like Al, Fe, La, Th and U show a pattern for concentration averages and standard deviations with little variation along 20 th century, evidencing their natural origin. Other heavy metals like: Pb, Mo, Zn, Cd, Ni, Co and Cu show increases in average concentrations and standard deviations from the beginning of 20 th century to recent years. For example, Cu average concentration values change from 0.604±0.440 ng g -1 to 3.46±3.02 ng g -1 along 20 th century. Time evolution of these elements concentrations' may be related to local economic growth and human activities in South America.

A 137 m ice core drilled in 1999 from Eastern Bolivian Andes at the summit of Nevado Illimani (16º 37' S, 67º 46' W, 6350 m asl) was analyzed at high temporal resolution, allowing a characterization of trace elements in Andean aerosol trapped in the ice during the 20th century. The upper 50 m of the ice core were dated by multi-proxy analysis of stable isotopes (d18O and d2H), 137Cs and Ca+2 content, electrical conductivity, and insoluble microparticle content, together with reference historical horizons from atmospheric nuclear tests and known volcanic eruptions. This 50 m section corresponds to a record of environmental variations spanning about 80 years from 1919 to 1999. It was cut in 744 sub-samples under laminar flow in a clean bench, which were analyzed by Ion Chromatography for major ionic concentration, by a particle counter for insoluble aerosol content, and by Inductively Coupled Plasma Mass Spectrometry (ICP-MS) for the concentration of 45 chemical species from Li to U. This paper focuses on results of trace element concentrations measured by ICP-MS. The high temporal resolution used in the analyses allowed classifying samples as belonging to dry or wet seasons. During wet season elemental concentrations are low and samples show high crustal enrichment factors. During dry seasons the situation is opposite, with high elemental concentrations and low crustal enrichments. For example, with salt lakes as main sources in the region, average Li concentration during the 20th century is 0.035 and 0.90 ng g-1 for wet and dry seasons, respectively. Illimani average seasonal concentration ranges cover the spectrum of elemental concentration measurements at another Andean ice core site (Sajama) for most soil-related elements. Regional crustal dust load in the deposits was found to be overwhelming during dry season, obfuscating the contribution of biomass burning material. Marked temporal trends from the onset of 20th century to more recent years were identified for the concentrations of several trace species of anthropic origin, especially for Cu, As, Zn, Cd, Co, Ni and Cr. Among these elements, Cu shows average wet season crustal enrichment factors above 103, while the others range between 102 to about 5x102. P and K show moderate average wet season enrichment factors, suggesting an impact of natural biogenic emissions from the Amazon Basin. Pb has multiple anthropic sources in the region, from mining activities in the beginning of 20th century to automotive fuel after 1950s. From the large number of samples analyzed from Illimani, it was possible to derive an effective chemical characterization of the deposited background Andean soil dust aerosol during 20th century.

First published May 2012 at Statistics Education Research Journal: Archives

A path model was constructed mapping the effect of career decision-making self-efficacy (CDMSE) and degree utility on persistence of underprepared college students. The path model accounted for 21 percent of the variance in intent to persist and 27 percent of the variance in student persistence. The final structural model adds to the literature on student persistence in several ways. First, it suggests the importance of Degree Utility for this population: Students who believed college would provide employment opportunities and better careers were more likely to persist. Second, it confirms that CDMSE has a direct effect on social and academic integration and an indirect effect on persistence. Implications for research include developing and testing interventions to enhance CDMSE. Implications for practice include providing career counseling and advising that identifies the connection between employment opportunities and academic course, program, or degree completion and engaging in practices that increase CDMSE.

In November and December 2008, ground-based mobile lidar (GBML) measurements were carried out on Reunion Island (Indian Ocean, $$21^{\circ }07^{\prime }\hbox {S}, 55^{\circ }32^{\prime }\hbox {E}$$ , 700 km east of Madagascar) with an ultraviolet (355 nm) aerosol-backscatter lidar. Complex substructures were identified within the planetary boundary layer (PBL). A 500-m-resolution non-hydrostatic model was used to simulate the dynamics of the lower troposphere for two observation periods characteristic of the two main weather regimes in this season: the “trade-wind” regime and the “breeze” regime. The model captured the observed structures with a high degree of realism compared to the GBML. A complete diurnal cycle of the PBL along the south coast of the island during a “trade-wind” day was observed and simulated. The PBL depth was found to be anti-correlated with the wind speed. The model showed that the PBL along the coast behaved as a shallow-water flow in hydraulic theory. As the flow accelerated in response to lateral constriction, conversion of potential into kinetic energy forced the PBL top downwards. This favoured rapid transport of concentrated surface emissions within the contracted surface layer, with a possible impact on air quality. GBML observations were also conducted during the early morning of a “breeze” day on the western slope of the Maido mountain (2,200 m), at the top of which a new atmospheric observatory has been in operation since 2012. Both model and GBML revealed two superposed layers. The upper layer, higher than approximately 1,600 m above mean sea level, corresponded to free tropospheric air driven by the trade winds. Below, westerly counterflow advection of humid marine air occurred as a result of wake vortices in the lee of the island. The model suggests that free-tropospheric conditions prevail at the observatory from the second half of the night to mid-morning.

As part of an investigation of lead in precipitation, we sampled rainwater over a 2 year period at four locations in intertropical Africa. We clearly identified crustal dust and anthropogenic sources for lead in rain using measured concentrations, correlation matrices, enrichment factors, and the distribution of lead between dissolved and particulate fractions. In Niger, mean and most individual sample crustal enrichment factors are less than 10, suggesting the dominance of the crustal dust source for lead in rainwater at that site. Nevertheless, the few enrichment factors greater than 10 and an estimate of the concentration of noncrustal lead in rainwaters from this site suggest anthropogenic sources may be important as well. In the Central African Republic, high individual sample (600) and mean (10.5) crustal enrichment factors indicate a noncrustal source for lead in rain. Very weak correlations between lead and other elements (e.g., Rb) for both total and dissolved fractions argue against a biogenic source and suggest an anthropogenic source. In Cameroon, individual sample and mean crustal enrichment factors are greater than 10, indicating a noncrustal source for lead in rainwater. We suggest the possibility of a biogenic lead source that would partly explain its correlation to Rb in dissolved and total rain fractions. For all stations, lead crustal enrichment factors decrease with increases in aluminium concentrations (i.e., mineral dust) and with increases in the fraction of soluble lead in rainwater. Thus lead in rain appears to be made up primarily of two types of particles; mineral dust particles with low solubility and highly soluble anthropogenic and/or biogenic particles.

Precipitation accumulating on the Greenland and Antarctic ice sheets records several key parameters (temperature, accumulation, composition of atmospheric gases and aerosols) of primary interest for documenting the past global environment over recent climatic cycles and the chemistry of the preindustrial atmosphere. Several deep ice cores from Antarctica and Greenland have been studied over the last fifteen years. In both hemispheres, temperature records (based on stable isotope measurements in water) show the succession of glacial and interglacial periods. However, detailed features of the climatic stages are not identical in Antarctica and in Greenland. A tight link between global climate and greenhouse gas concentrations was discovered, CO2 and CH4 concentrations being lower in glacial conditions by about 80 and 0.3 ppmv, respectively, with respect to their pre-industrial levels of 280 and 0.65 ppmv. Coldest stages are also characterized by higher sea-salt and crustal aerosol concentrations. In Greenland, contrary to Antarctica, ice-age ice is alkaline. Gas-derived aerosol (in particular, sulfate) concentrations are generally higher for glacial periods, but not similar in both the hemispheres. Marine and continental biomass-related species are significant in Antarctica and Greenland ice, respectively. Finally, the growing impact of anthropogenic activities on the atmospheric composition is well recorded in both polar regions for long-lived compounds (in particular greenhouse gases), but mostly in Greenland for short-lived pollutants.

Following the successful application of Bandura's (1977) theory of self-efficacy to the treatment of career indecision (Betz & Hackett, 1981; Hackett & Betz, 1981), Taylor and Betz (1983) developed the Career Decision-Making Self-Efficacy (CDMSE) scale. CDMSE identifies the extent to which students have confidence (self-efficacy) in their ability to engage in educational and occupational planning and decision-making. The Taylor and Betz (1983) study identified five sub-scales: Self-Appraisal, Occupational Information, Goal Selection, Planning, and Problem-Solving. Each sub-scale consisted of ten items. Using principal components factor analysis with varimax rotation, the total variance accounted for by factor scores of the five sub-scales equaled 52%. However, it was noted that since most of the items had relatively large loadings on more than one factor, the structure was not clear-cut, and therefore, the scale potentially represented a single and rather large general factor. Research has provided support for the validity of the CDMSE instrument (Betz & Hackett, 1986; Robbins, 1985; Taylor & Popma, 1990), and the concept has been widely adapted (Brown, Lent, & Larkin, 1989; Lent, Brown, & Larkin, 1984, 1986, 1987; Lent, Larkin, & Brown, 1989; Nevill & Schlecker, 1988; Peterson, 1993a, 1993b; Rotberg, Brown, & Ware, 1987; Shelton, 1990; Stumpf & Brief, 1987). However, the nature of career decision-making self-efficacy, as a construct is still being explored.

Nitrogen oxides are key compounds for the oxidation capacity of the troposphere. NOx concentrations depend on the proximity of sources because of their short atmospheric lifetime. An accurate knowledge of the distribution of their sources and sinks is therefore crucial. At global scale, the dominant sources of nitrogen oxides - combustions of fossil fuel (∼50%) and biomass burning (∼20%) - are basically anthropogenic. Natural sources, including lightning and microbial activity in soils, represent therefore less than 30% of total emissions. Fertilizer use in agriculture constitutes an anthropogenic perturbation to the microbial source. The methods to estimate the magnitude and distribution of these dominant sources of nitrogen oxides are discussed. Some minor sources which may play a specific role in tropospheric chemistry such as NOx emission from aircraft in the upper troposphere or input from production in the stratosphere from N2O photodissociation are also considered.

This chapter describes the development of students’ thinking as they experienced an innovative introductory statistics curriculum that replaced traditional content and methods with an approach based on simulation and resampling. The methods employed in the curriculum were based on a framework for inference that had students specify a chance model, draw repeated samples of simulated data, create a distribution of summary measures, and use the distribution to evaluate a claim. Students used TinkerPlots™ software to resample simulated data from chance processes and models, as well as to explore the distribution of summary measures. The software incorporates many features of a ″Monte Carlo Workbench″ (see Biehler, 1997a) that allows students to visualize the entire modeling process. Problem solving interviews were conducted with five students after five weeks of the curriculum. These interviews revealed that students were beginning to develop an understanding of important concepts underlying the process of statistical inference. The results suggest that students are able to create and use appropriate chance models and simulations to draw statistical inferences after only a few weeks of instruction in an introductory course. The interviews also suggest that TinkerPlots™ provides students with a memorable, visual medium to support the development of their thinking and reasoning.

This article describes a computer-assisted, interdisciplinary course in decision making developed to promote student participation, critical thinking, and enhanced decision making through the use of interactive experimental paradigms. The course uses Macintosh computers for simple data entry and presentation, for more complex calculations and extended graphics, and for stimulus presentation and data collection. Students experience firsthand 20 psychology and economics exercises that illustrate a range of biases and heuristics known to affect decision making and that allow for examination and evaluation of students’ decision-making tactics.

Ozone has been observed in elevated concentrations by satellites over areas previously believed to be ‘background’. There is meteorological evidence, that these ozone ‘plumes’ found over the Atlantic Ocean originate from vegetation fires on the African continent.

Gaseous nitrogen compounds (NO x , NO y , NH3, N2O) were measured at ground level in smoke plumes of prescribed savanna fires in Lamto, in the southern Ivory Coast, during the FOS/DECAFE experiment in January 1991. During the flaming phase, the linear regression between δ[NO x ] and δ[CO2] (differences in concentration between smoke plumes and atmosheric background) results volumic emission ratio δ[NO x ]/δ[CO2]=1.37×10−3 with only slight differences between heading and backing fires. Nearly 90% of the nitrogen oxides are emitted as NO. Average emission ratios of other compounds are: 1.91, 0.047, and 0.145×10−3 for NO y , NH3 and N2O, respectively. The emission ratios obtained during this field experiment are compred with corresponding values measured during former experiments with the same plant species in combustion chambers. An accurate determination of both the biomass actually burned and of the plant nitrogen content, allows an assessment of emission fluxes of N-compounds from Guinean savanna burns. Preliminary results dealing with the influence of fire on biogenic emissions from soils are also reported.

This paper reports on an instrument designed to assess the practices and beliefs of instructors of introductory statistics courses across the disciplines. Funded by a grant from the National Scienc...