In this quasi-experimental study, the effects of lexical coverage through pseudo word manipulation in dialogue comprehension are investigated. Forty-four first-year students in a Japanese university ...listened to five dialogues at different lexical coverage levels: 98%, 95%, 90%, 85%, and 83%. The results of the comprehension tests confirm the results seen in narrative, monologic lexical coverage studies that it is possible for intermediate EFL learners to attain adequate listening comprehension on texts with as little as 90% lexical coverage. However, variation in participants’ scores on higher lexical coverage dialogues suggest pseudo word distribution and topic familiarity might be acting as confounding variables in lexical coverage studies which use pseudo word manipulation. Suggestions for methodological reform for future projects on this subject are provided.
Low-cost sensors for particulate matter mass (PM) enable spatially dense, high temporal resolution measurements of air quality that traditional reference monitoring cannot. Low-cost PM sensors are ...especially beneficial in low and middle-income countries where few, if any, reference grade measurements exist and in areas where the concentration fields of air pollutants have significant spatial gradients. Unfortunately, low-cost PM sensors also come with a number of challenges that must be addressed if their data products are to be used for anything more than a qualitative characterization of air quality. The various PM sensors used in low-cost monitors are all subject to biases and calibration dependencies, corrections for which range from relatively straightforward (e.g. meteorology, age of sensor) to complex (e.g. aerosol source, composition, refractive index). The methods for correcting and calibrating these biases and dependencies that have been used in the literature likewise range from simple linear and quadratic models to complex machine learning algorithms. Here we review the needs and challenges when trying to get high-quality data from low-cost sensors. We also present a set of best practices to follow to obtain high-quality data from these low-cost sensors.
•Low-cost sensors (LCS) give air pollution data at high spatial/temporal resolution.•Challenges in obtaining high quality data from low-cost PM sensors are reviewed.•Current methods of correcting LCS data are reviewed, best practices are suggested.•To better evaluate LCS corrections, both accuracy and bias should be reported.
Introduction
Dungeons & Dragons (D&D) is a cooperative tabletop roleplaying game in which players gather together to tell stories. Expert players have a wealth of experiences and game knowledge from ...which to draw upon while playing the game. Novices, on the other hand, have little experience to depend on when navigating the first few gaming sessions.
Objectives
The primary objective of this investigation was to describe how different novices become socialized to the D&D culture in this small community at the beginning of a new gaming campaign.
Methods
The present study is a cross-sectional qualitative participant observation of D&D novice socialization through the lens of communities of practice (CoP). Observation and interviews of two experts and five novice fifth edition D&D players revealed interactions and choices made by players related to the dissemination of cultural and practical knowledge and the fluidity of player and character identity within the scope of observed gameplay.
Results
The results showed that for some novices explicit in-game training was required to learn their role at the table, but socialization could come more quickly for novices who took extra steps to gain experience by engaging in the wider distributed and virtual community through online forums or viewing streamed actual-play D&D games. Three interaction types—player-to-player, player-to-dungeon master (DM), and character-to-character—for three distinct purposes—understanding game mechanics, describing scenes, and interacting in narrative—were observed. Additionally, the character choices regarding gender and in-game actions were explored.
Conclusion
The cooperative nature of D&D can afford novices explicit training from expert players at the table. However, as was observed during the game and confirmed in the interviews, socialization into this D&D gaming community also came from legitimate peripheral participation of the novices who engaged in the wider, virtual D&D community through online forums, actual-play streams and podcasts, and general knowledge of the fantasy genre.
This study develops a new limited information estimator for random intercept Multilevel Structural Equation Models (MSEM). It is based on the Model Implied Instrumental Variable Two-Stage Least ...Squares (MIIV-2SLS) estimator, which has been shown to be an excellent alternative or supplement to maximum likelihood (ML) in SEMs (Bollen,
1996
). We also develop a multilevel overidentification test statistic that applies to equations at the within or between levels. Our Monte Carlo simulation analysis suggests that MIIV-2SLS is more robust than ML to misspecification at within or between levels, performs well given fewer than 100 clusters, and shows that our multilevel overidentification test for equations performs well at both levels of the model.
Structural equation models (SEMs) are widely used to handle multiequation systems that involve latent variables, multiple indicators, and measurement error. Maximum likelihood (ML) and diagonally ...weighted least squares (DWLS) dominate the estimation of SEMs with continuous or categorical endogenous variables, respectively. When a model is correctly specified, ML and DWLS function well. But, in the face of incorrect structures or nonconvergence, their performance can seriously deteriorate. Model implied instrumental variable, two stage least squares (MIIV-2SLS) estimates and tests individual equations, is more robust to misspecifications, and is noniterative, thus avoiding nonconvergence. This article is an overview and tutorial on MIIV-2SLS. It reviews the six major steps in using MIIV-2SLS: (a) model specification; (b) model identification; (c) latent to observed (L2O) variable transformation; (d) finding MIIVs; (e) using 2SLS; and (f) tests of overidentified equations. Each step is illustrated using a running empirical example from Reisenzein's (1986) randomized experiment on helping behavior. We also explain and illustrate the analytic conditions under which an equation estimated with MIIV-2SLS is robust to structural misspecifications. We include additional sections on MIIV approaches using a covariance matrix and mean vector as data input, conducting multilevel SEM, analyzing categorical endogenous variables, causal inference, and extensions and applications. Online supplemental material illustrates input code for all examples and simulations using the R package MIIVsem.
Translational AbstractTheories in psychology hypothesize relationships between abstract variables that we can only imperfectly measure. To test these ideas requires models with latent variables to represent these abstract concepts and multiple measures to anchor the latent variables to those we can observe. Researchers routinely use latent variable structural equation models (SEMs) to test psychological theories and explanations, as well as to refine our measures. Current methods to estimate and test such models focus on the whole system under the assumption that the model is a fully accurate portrayal of reality. In the common situation of models as approximations to reality, these techniques are susceptible to spreading errors from one part of the system to another. This article describes an alternative approach, Model Implied instrumental variable, two stage least squares (MIIV-2SLS), with a focus on individual equations that better limits the spread of model misspecification errors that often occur. This didactic article describes the major steps to using MIIV-2SLS illustrated with an empirical example. It also describes its conditions for robustness as well as the wide variety of areas in which the MIIV-2SLS estimator applies and highlights a number of recent extensions to the method.
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When generating scores to represent latent constructs, analysts have a choice between applying psychometric approaches that are principled but that can be complicated and time-intensive versus ...applying simple and fast, but less precise approaches, such as sum or mean scoring. We explain the reasons for preferring modern psychometric approaches: namely, use of unequal item weights and severity parameters, the ability to account for local dependence and differential item functioning, and the use of covariate information to more efficiently estimate factor scores. We describe moderated nonlinear factor analysis (MNLFA), a relatively new, highly flexible approach that allows analysts to develop precise factor score estimates that address limitations of sum score, mean score, and traditional factor analytic approaches to scoring. We then outline the steps involved in using the MNLFA scoring approach and discuss the circumstances in which this approach is preferred. To overcome the difficulty of implementing MNLFA models in practice, we developed an R package, aMNLFA, that automates much of the rule-based scoring process. We illustrate the use of aMNLFA with an empirical example of scoring alcohol involvement in a longitudinal study of 6998 adolescents and compare performance of MNLFA scores with traditional factor analysis and sum scores based on the same set of 12 items. MNLFA scores retain more meaningful variation than other approaches. We conclude with practical guidelines for scoring.
•Moderated nonlinear factor analysis generates more precise scores than traditional methods.•We created an R package (aMNLFA) to facilitate application of this approach.•Application of the package is illustrated.•Factor scores generated using aMNLFA contained more meaningful variation than sum scores.
A fundamental understanding of the processes that control
Antarctic aerosols is necessary in determining the aerosol impacts on
climate-relevant processes from Antarctic ice cores to clouds. The ...first in
situ observational online composition measurements by an aerosol mass
spectrometer (AMS) of Antarctic aerosols were only recently performed during
the Two-Season Ozone Depletion and Interaction with Aerosols Campaign
(2ODIAC). 2ODIAC was deployed to sea ice on the Ross Sea near McMurdo
Station over two field seasons: austral spring–summer 2014 and
winter–spring 2015. The results presented here focus on the overall trends
in aerosol composition primarily as functions of air masses and local
meteorological conditions. The results suggest that the impact of long-range
air mass back trajectories on either the absolute or relative concentrations
of the aerosol constituents measured by (and inferred from) an AMS at a
coastal location is small relative to the impact of local meteorology.
However, when the data are parsed by wind speed, two observations become
clear. First, a critical wind speed is required to loft snow from the
surface, which, in turn, increases particle counts in all measured size bins.
Second, elevated wind speeds showed increased aerosol chloride and sodium.
Further inspection of the AMS data shows that the increased chloride
concentrations have more of a “fast-vaporizing” nature than chloride
measured at low wind speed. Also presented are the Cl:Na ratios of
snow samples and aerosol filter samples, as measured by ion chromatography,
as well as non-chloride aerosol constituents measured by the AMS.
Additionally, submicron aerosol iodine and bromine concentrations as
functions of wind speed are also presented. The results presented here
suggest that aerosol composition in coastal Antarctica is a strong function
of wind speed and that the mechanisms determining aerosol composition are
likely linked to blowing snow.
In the current study, we used an analogue integrative data analysis (IDA) design to test optimal scoring strategies for harmonizing alcohol- and drug-use consequence measures with varying degrees of ...alteration across four study conditions. We evaluated performance of mean, confirmatory factor analysis (CFA), and moderated nonlinear factor analysis (MNLFA) scores based on traditional indices of reliability (test–retest, internal, and score recovery or parallel forms) and validity. Participants in the analogue study included 854 college students (46% male; 21% African American, 5% Hispanic/Latino, 56% European American) who completed two versions of the altered measures at two sessions, separated by 2 weeks. As expected, mean, CFA, and MNLFA scores all resulted in scales with lower reliability given increasing scale alteration (with less fidelity to formerly developed scales) and shorter scale length. MNLFA and CFA scores, however, showed greater validity than mean scores, demonstrating stronger relationships with external correlates. Implications for measurement harmonization in the context of IDA are discussed.
Understanding the sources and evolution of aerosols is crucial for constraining the impacts that aerosols have on a global scale. An unanswered question in atmospheric science is the source and ...evolution of the Antarctic aerosol population. Previous work over the continent has primarily utilized low temporal resolution aerosol filters to answer questions about the chemical composition of Antarctic aerosols. Bulk aerosol sampling has been useful in identifying seasonal cycles in the aerosol populations, especially in populations that have been attributed to Southern Ocean phytoplankton emissions. However, real-time, high-resolution chemical composition data are necessary to identify the mechanisms and exact timing of changes in the Antarctic aerosol. The recent 2ODIAC (2-Season Ozone Depletion and Interaction with Aerosols Campaign) field campaign saw the first ever deployment of a real-time, high-resolution aerosol mass spectrometer (SP-AMS – soot particle aerosol mass spectrometer – or AMS) to the continent. Data obtained from the AMS, and a suite of other aerosol, gas-phase, and meteorological instruments, are presented here. In particular, this paper focuses on the aerosol population over coastal Antarctica and the evolution of that population in austral spring. Results indicate that there exists a sulfate mode in Antarctica that is externally mixed with a mass mode vacuum aerodynamic diameter of 250 nm. Springtime increases in sulfate aerosol are observed and attributed to biogenic sources, in agreement with previous research identifying phytoplankton activity as the source of the aerosol. Furthermore, the total Antarctic aerosol population is shown to undergo three distinct phases during the winter to summer transition. The first phase is dominated by highly aged sulfate particles comprising the majority of the aerosol mass at low wind speed. The second phase, previously unidentified, is the generation of a sub-250 nm aerosol population of unknown composition. The second phase appears as a transitional phase during the extended polar sunrise. The third phase is marked by an increased importance of biogenically derived sulfate to the total aerosol population (photolysis of dimethyl sulfate and methanesulfonic acid (DMS and MSA)). The increased importance of MSA is identified both through the direct, real-time measurement of aerosol MSA and through the use of positive matrix factorization on the sulfur-containing ions in the high-resolution mass-spectral data. Given the importance of sub-250 nm particles, the aforementioned second phase suggests that early austral spring is the season where new particle formation mechanisms are likely to have the largest contribution to the aerosol population in Antarctica.
Combustion of biomass, garbage, and fossil fuels in South Asia has led to poor air quality in the region and has uncertain climate forcing impacts. Online measurements of submicron aerosol (PM1) ...emissions were conducted as part of the Nepal Ambient Monitoring and Source Testing Experiment (NAMaSTE) to investigate and report emission factors (EFs) and vacuum aerodynamic diameter (dva) size distributions from prevalent but poorly characterized combustion sources. The online aerosol instrumentation included a “mini” aerosol mass spectrometer (mAMS) and a dual-spot eight-channel aethalometer (AE33). The mAMS measured non-refractory PM1 mass, composition, and size. The AE33-measured black carbon (BC) mass and estimated light absorption at 370 nm due to organic aerosol or brown carbon. Complementary gas-phase measurements of carbon dioxide (CO2), carbon monoxide (CO), and methane (CH4) were collected using a Picarro Inc. cavity ring-down spectrometer (CRDS) to calculate fuel-based EFs using the carbon mass balance approach. The investigated emission sources include open garbage burning, diesel-powered irrigation pumps, idling motorcycles, traditional cookstoves fueled with dung and wood, agricultural residue fires, and coal-fired brick-making kilns, all of which were tested in the field. Open-garbage-burning emissions, which included mixed refuse and segregated plastics, were found to have some of the largest PM1 EFs (3.77–19.8 g kg−1) and the highest variability of the investigated emission sources. Non-refractory organic aerosol (OA) size distributions measured by the mAMS from garbage-burning emissions were observed to have lognormal mode dva values ranging from 145 to 380 nm. Particle-phase hydrogen chloride (HCl) was observed from open garbage burning and was attributed to the burning of chlorinated plastics. Emissions from two diesel-powered irrigation pumps with different operational ages were tested during NAMaSTE. Organic aerosol and BC were the primary components of the emissions and the OA size distributions were centered at ∼80 nm dva. The older pump was observed to have significantly larger EFOA than the newer pump (5.18 g kg−1 compared to 0.45 g kg−1) and similar EFBC. Emissions from two distinct types of coal-fired brick-making kilns were investigated. The less advanced, intermittently fired clamp kiln was observed to have relatively large EFs of inorganic aerosol, including sulfate (0.48 g kg−1) and ammonium (0.17 g kg−1), compared to the other investigated emission sources. The clamp kiln was also observed to have the largest absorption Ångström exponent (AAE = 4) and organic carbon (OC) to BC ratio (OC : BC = 52). The continuously fired zigzag kiln was observed to have the largest fraction of sulfate emissions with an EFSO4 of 0.96 g kg−1. Non-refractory aerosol size distributions for the brick kilns were centered at ∼400 nm dva. The biomass burning samples were all observed to have significant fractions of OA and non-refractory chloride; based on the size distribution results, the chloride was mostly externally mixed from the OA. The dung-fueled traditional cookstoves were observed to emit ammonium, suggesting that the chloride emissions were partially neutralized. In addition to reporting EFs and size distributions, aerosol optical properties and mass ratios of OC to BC were investigated to make comparisons with other NAMaSTE results (i.e., online photoacoustic extinctiometer (PAX) and off-line filter based) and the existing literature. This work provides critical field measurements of aerosol emissions from important yet under-characterized combustion sources common to South Asia and the developing world.
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