bluuebunny/crossref_metadata_2025 huggingface dataset:
Consecuencias de la COVID-19 en el uso de aplicaciones móviles y del tiempo de compromiso motor en las clases bilingües y no bilingües de Educación Física en Secundaria
Authors: Martínez Hita Francisco José , García-Cantó Eliseo , Granero-Gallegos Antonio , Gómez-López Manuel
Published: May 2022

La presente investigación trata de conocer cómo afectan los protocolos de seguridad establecidos para la prevención de la COVID-19 en el tiempo de compromiso motor (TCM) en las clases de Educación Física (EF), tanto en castellano como en inglés, y en los planteamientos metodológicos llevados a cabo por el profesorado. Para ello, se diseña un estudio ex post facto en el que se analizan las distintas categorías de tiempo establecidas en las sesiones de EF y la utilización de aplicaciones móviles en doce centros educativos de Secundaria de la comunidad autónoma de Aragón. Los resultados muestran diferencias de TCM con respecto a estudios previos, además existen diferencias significativas (U de Mann-Whitney) en las variables de TCM, tiempo de organización y tiempo empleado en la tarea entre las sesiones realizadas en castellano y las realizadas en inglés. Estos datos revelan la necesidad de continuar investigando acerca de las consecuencias en el área de EF de las medidas adoptadas en relación con la COVID-19 y la importancia que han tenido las aplicaciones móviles como medio para sustituir las sesiones presenciales y compensar el descenso del TCM en las clases de EF.
Virtual-self Identity Construal in Online Video Games: A Repertory Grid Study Protocol
Authors: Gabarnet Adrià , Montesano Adrián , Feixas Guillem
Published: May 2022

The aim of this project is to study the role that online videogames play in the way people build their identities. More specifically, the project is intended to study how people use online videogames and virtual avatars to explore alternative identities. It is possible for people to manifest entirely different versions of themselves through their virtual characters. Sometimes, those alternative identities may be a projection of what players consider ideal versions of themselves. Several variables may strengthen or hinder this capacity to project the ideal self onto a customizable “virtual self”. Some of these factors are inherent to the individual, while others may be more related to the specific game they play. The repertory grid technique will be used to explore online videogame players’ construct systems and to understand their need to explore alternative identities through their videogame characters. Other instruments will also be administrated to measure the degree of immersion that game players experience, to determine which aspects of play are the most appealing to them, and to gather data on their degree of subjective psychological well-being, all in order to assess how these variables, in addition to the others extracted from the repertory grid, may affect this identity exploration.
TÜRKİYE’DE SİVİL TOPLUM KURULUŞLARININ KARŞILAŞTIĞI ENGELLER
Authors: GÖZ Mert Mahir
Published: May 2022

Tüm dünyada olduğu gibi ülkemizde de demokrasi kavramının yükselişe geçmesiyle birlikte sivil toplum kavramı yaygınlık kazanmaya başlamıştır. Özellikle 1980’li yılların sonundan itibaren isminden bahsettirmeye başlayan ekonomik liberalizmin mütemmim cüzü olarak görülen siyasal liberalleşmenin bir sonucu olarak ele alınan sivil toplum kavramı aracılığıyla devletin etki alanları sınırlandırılmıştır. Günümüz itibariyle, siyasal sistemlerde daha etkin bir konum kazanmaya başlayan sivil toplum kuruluşlarının (STK) karşılaştığı birçok sorun alanı bulunmaktadır. Katılım eksikliği, mali kaynak yetersizliği, gelişkin bir demokrasi ve siyasi kültüre sahip olunamaması, ideolojilerin ön plana çıkarılması, şamil siyasi otoriteye eklemlenmek istenmesi ve yönetici kadroların şahsi çıkarları bağlamında STK’ları basamak tahtası gibi görmesi, Türkiye’deki STK’ların temel problemlerindendir. Bu çalışmada Türkiye’deki STK’ların karşılaştığı sorunların neler olduğu ele alınarak, bu sorunlara ilişkin çözüm önerilerinin sunulması amaçlanmaktadır.
GESTÃO UNIVERSITÁRIA E MODELOS DE INTERNACIONALIZAÇÃO NA PERSPECTIVA DA COOPERAÇÃO SOLIDÁRIA
Authors: Pinto de Almeida Bizarria Fabiana , Sampaio Barbosa Flávia Lorenne , Mota Tassigny Monica
Published: May 2022

Introdução: A argumentação da pesquisa centra-se em dois temas que se relevaram nucleares para um debate propositivo: Modelo de Universidade e Gestão Universitária. Método: Por meio da Análise Crítica dos Discursos, vinte e uma entrevistas com gestores de uma Universidade Federal reportam saberes e práticas com base em duas conjunturas não formalmente instituídas. Resultado: De um lado, evidencia-se uma Política de Internacionalização, que se propaga com suporte no consenso em torno na inevitabilidade de um modelo de universidade que se organiza pela dependência acadêmica. De outro, uma Política de Integração Internacional afirma a diversidade cultural como seara de atuação da Universidade, mas que se apresenta como inviabilidade/invisibilidade no campo político-acadêmico externo e interno. Discussão: A cooperação internacional solidária e a interculturalidade, sugere desdobramentos na perceptiva da gestão do projeto da Universidade, convergente com a identificação dos desafios, a abordagem destes e a reflexão sobre a proposta da gestão universitária de modo a realizar a missão dessa Instituição. Conclusão: O embate entre modelos, políticas e concepções teóricas implicadas reforça a afirmação da necessidade de, antes, avançar na compreensão do como instituir uma universidade sob uma lógica diversa do que organiza o saber e o fazer corrente.
Source Apportionment and Evolution of N-containing Aerosols at a Rural Cloud Forest in Taiwan by Isotope Analysis
Authors: Chen Ting-Yu , Chen Chia-Li , Chen Yi-Chi , Chou Charles C.-K. , Ren Haojia , Hung Hui-Ming
Published: May 2022

Abstract. Ammonium and nitrate are two major N-containing aerosol compositions. The deposition of N-containing aerosols has impacts on regional ecology and the biogeochemical cycle. In this study, aerosols in a rural cloud forest (Xitou in Taiwan) were studied using 15N and 18O isotope analysis to assess the sources and formation pathways of the local N-containing aerosols linking to a metropolitan. Aerosol samples were collected for different size ranges using a micro-orifice uniform deposit impactor (MOUDI) on a half-day basis in December 2018. The chemical functional groups were analyzed using a Fourier transformed infrared spectroscopy with attenuated total reflection technique (FTIR-ATR), while the isotope analysis was performed using a gas chromatography-isotope ratio mass spectrometer (GC-IRMS). The average measured aerosol concentration (PM10) was 0.98 (ranging from 0.15 to 3.31) and 0.25 (ranging from 0.00 to 1.51) μg/m3 for NH4+ and NO3-, respectively. In general, a higher functional group concentration was observed during the daytime by a factor of 1.5 to 6 than nighttime, likely due to the transportation of pollutants from upper stream urban and industrial regions through the local sea breeze combined with valley wind. The presence of fog can further elevate the concentration by a factor of 2 to 3, resulting from the stronger inversion and lower boundary layer height. The higher NH4+ concentration in fine particles under foggy conditions can further promote submicron-sized NO3- formation via aqueous phase dissolution with NH4+ neutralization. Furthermore, the higher RH during fog events shifted the mass distribution of aerosol functional groups to a larger mode size. By comparing the δ15N value directly or the analysis using a statistical isotope mixing model, MixSIAR, the NH4+ is probably originated from the industries, coal-fired power plants (CFPP), or fertilizer plants, while NO3- might be contributed from the CFPP, industrial or urban sources. The overall δ18O of NO3- is +72.66 ‰ ± 3.42 ‰, similar to that in other winter Asia studies, suggesting the major formation pathway via O3 oxidation (δ18O = +72.5 to 101.67 ‰). However, a lower δ18O (< +67 ‰) for particles less than 0.56 μm during foggy daytime suggests the local contribution via the peroxyl radical oxidation before partitioning into aerosol phase under foggy conditions. Overall, the δ15N and δ18O distribution profiles as a function of particle size in the studied rural forest site reveal the evolution of aerosol composition from remote coastal regions with chemical processes along the transport process, which can be further affected by weather conditions such as fog events.
Assessing stakeholder climate data needs for farm-level decision-making in the U.S. Corn Belt
Authors: Clark Suzanna , Wolfinger J. Felix , Kenney Melissa A. , Gerst Michael D. , Roop Heidi A.
Published: May 2022

Abstract. Across the Midwest region of the United States, agriculturalists make decisions on a variety of time scales, ranging from daily to weekly, monthly, and seasonally. Ever improving forecasts and decision support tools could assist the decision-making process, particularly in the context of a changing and increasingly variable climate. To be usable, however, the information produced by these forecasts and tools should be salient, credible, legitimate, and iterative, qualities which are achieved through deliberate co-production with stakeholders. This study uses a document analysis approach to explore stakeholder climate information needs and priorities in the U.S. Corn Belt. Through the analysis of 50 documents, we find that stakeholders are primarily concerned with practical and tactical decision making, including from whom they get their information, the application of information to agricultural, water, and risk management, and desired economic outcomes. The information that stakeholders desire is less focused on social issues, environmental issues, or long-term climate resilience. This study can inform the development of future decision support tools, identify known gaps in climate information services to reduce stakeholder fatigue, and serve as an example to scientists trying to understand stakeholder needs in other regions and specialties.
A new global dataset of mountain glacier centerline and length
Authors: Zhang Dahong , Zhou Gang , Li Wen , Zhang Shiqiang , Yao Xiaojun , Wei Shimei
Published: May 2022

Abstract. Length is one of the key determinants of glacier geometry and is an important parameter of glacier inventory and modeling; glacier centerlines are crucial inputs for many glaciological applications. In this study, the centerlines and maximum lengths of global glaciers were extracted using an automatic extraction algorithm based on the latest global glacier inventory data, digital elevation data (DEM), and European allocation theory. The glacier polygons were reconstructed according to the geometric principle and an automatic checking algorithm for the global glacier outlines was designed to filter erroneous or unsupported glacier outlines. The DEMs of global glacier-covered regions were compiled using available DEMs. An updated automatic extraction tool was designed independently, and a parameterization scheme with empirical thresholds was applied for data production. The accuracy of the dataset was evaluated using random assessment with visible interpretation and comparative analysis with another dataset. The 10,764 erroneous glacier polygons, 7,174 ice caps, and 419 nominal glaciers from the Randolph Glacier Inventory (RGI) version 6.0 were identified and excluded, accounting for 8.25 % of the total. In total, 198,137 glacier centerlines were generated, accounting for 99.74 % of the total input glaciers and 91.52 % of the RGI v6.0. The accuracy of glacier centerlines was 89.68 %. The comparison between the dataset and previous datasets suggested that the majority of glacier centerlines were slightly longer than those in RGI v6.0. The extraction method of this study has a strong ability to obtain the maximum length of glaciers, meaning that the maximum lengths of some glaciers were likely underestimated in the past. The dataset constructed includes 14 sub-datasets, such as the global glacier centerline dataset, global glacier maximum length dataset, and global glacier DEM dataset, all of which can be found at link: https://doi.org/10.11922/sciencedb.01643 (Zhang and Zhang, 2022).
Training a supermodel with noisy and sparse observations: a case study with CPT and the synch rule on SPEEDO – v.1
Authors: Schevenhoven Francine , Carrassi Alberto
Published: May 2022

Abstract. As an alternative to using the standard multi-model ensemble (MME) approach to combine the output of different models to improve prediction skill, models can also be combined dynamically to form a so-called supermodel. The supermodel approach enables a quicker correction of the model errors. In this study we connect different versions of SPEEDO, a global atmosphere-ocean-land model of intermediate complexity, into a supermodel. We focus on a weighted supermodel, in which the supermodel state is a weighted superposition of different imperfect model states. The estimation, “the training”, of the optimal weights of this combination is a critical aspect in the construction of a supermodel. In our previous works two algorithms were developed: (i) cross pollination in time (CPT)-based technique and (ii) a synchronization-based learning rule (synch rule). Those algorithms have so far been applied under the assumption of complete and noise-free observations. Here we go beyond and consider the more realistic case of noisy data that do not cover the full system's state and are not taken at each model's computational time step. We revise the training methods to cope with this observational scenario, while still being able to estimate accurate weights. In the synch rule an additional term is introduced to maintain physical balances, while in CPT nudging terms are added to let the models stay closer to the observations during training. Furthermore, we propose a novel formulation of the CPT method allowing the weights to be negative. This makes it possible for CPT to deal with cases in which the individual model biases have the same sign, a situation that hampers constructing a skillfully weighted supermodel based on positive weights. With these developments, both CPT and the synch rule have been made suitable to train a supermodel consisting of state of the art weather and climate models.
Modeling the high-mercury wet deposition in the southeastern US with WRF-GC-Hg v1.0
Authors: Xu Xiaotian , Feng Xu , Lin Haipeng , Zhang Peng , Huang Shaojian , Song Zhengcheng , Peng Yiming , Fu Tzung-May , Zhang Yanxu
Published: May 2022

Abstract. High-mercury wet deposition in the southeastern United
States has been noticed for many years. Previous studies came up with a
theory that it was associated with high-altitude divalent mercury scavenged
by convective precipitation. Given the coarse resolution of previous models
(e.g., GEOS-Chem), this theory is still not fully tested. Here we employed a
newly developed WRF-GEOS-Chem (WRF-GC; WRF: Weather Research Forecasting) model implemented with mercury
simulation (WRF-GC-Hg v1.0). We conduct extensive model benchmarking by
comparing WRF-GC with different resolutions (from 50 to 25 km) to
GEOS-Chem output (4∘ × 5∘) and data from
the Mercury Deposition Network (MDN) in July–September 2013. The comparison of
mercury wet deposition from two models presents high-mercury wet
deposition in the southeastern United States. We divided simulation results
by heights (2, 4, 6, 8 km), different types of precipitation
(large-scale and convective), and combinations of these two variations
together and find most mercury wet deposition concentrates on higher level
and is caused by convective precipitation. Therefore, we conclude that it is
the deep convection that caused enhanced mercury wet deposition in the
southeastern United States.
Flood generation: process patterns from the raindrop to the ocean
Authors: Blöschl Günter
Published: May 2022

Abstract. This article reviews river flood generation processes and
flow paths across space scales. The scale steps include the pore, profile,
hillslope, catchment, regional and continental scales, representing a scale
range of a total of 10 orders of magnitude. Although the processes differ
between the scales, there are notable similarities. At all scales, there are
media patterns that control the flow of water and are themselves influenced
by the flow of water. The processes are therefore not spatially random (as
in thermodynamics) but organized, and preferential flow is the rule rather
than the exception. Hydrological connectivity, i.e. the presence of coherent
flow paths, is an essential characteristic at all scales. There are similar
controls on water flow and thus on flood generation at all scales but
with different relative magnitudes. Processes at lower scales affect flood
generation at larger scales, not simply as a multiple repetition of pore-scale processes but through interactions which cause emergent behaviour of
process patterns. For this reason, when modelling these processes, the scale
transitions need to be simplified in a way that reflects the relevant
structures (e.g. connectivity) and boundary conditions (e.g. groundwater
table) at each scale. In conclusion, it is argued that upscaling as the mere
multiple application of small-scale process descriptions will not capture
the larger-scale patterns of flood generation. Instead, there is a need to
learn from observed patterns of flood generation processes at all spatial
scales.
High-resolution (1 km) satellite rainfall estimation from SM2RAIN applied to Sentinel-1: Po River basin as a case study
Authors: Filippucci Paolo , Brocca Luca , Quast Raphael , Ciabatta Luca , Saltalippi Carla , Wagner Wolfgang , Tarpanelli Angelica
Published: May 2022

Abstract. The use of satellite sensors to infer rainfall
measurements has become a widely used practice in recent years, but their
spatial resolution usually exceeds 10 km, due to technological
limitations. This poses an important constraint on its use for applications
such as water resource management, index insurance evaluation or
hydrological models, which require more and more detailed information. In this work, the algorithm SM2RAIN (Soil Moisture to Rain) for rainfall
estimation is applied to two soil moisture products over the Po River basin: a
high-resolution soil moisture product derived from Sentinel-1, named S1-RT1,
characterized by 1 km spatial resolution (500 m spacing), and a 25
(12.5 km spacing) product derived from ASCAT, resampled to the same grid as
S1-RT1. In order to overcome the need for calibration and to allow for its
global application, a parameterized version of SM2RAIN algorithm was adopted
along with the standard one. The capabilities in estimating rainfall of each
obtained product were then compared, to assess both the parameterized
SM2RAIN performances and the added value of Sentinel-1 high spatial
resolution. The results show that good estimates of rainfall are obtainable from
Sentinel-1 when considering aggregation time steps greater than 1 d, since
the low temporal resolution of this sensor (from 1.5 to 4 d over Europe)
prevents its application for infer daily rainfall. On average, the ASCAT-derived rainfall product performs better than S1-RT1, even if the
performances are equally good when 30 d accumulated rainfall is
considered (resulting in a mean Pearson correlation for the parameterized
SM2RAIN product of 0.74 and 0.73, respectively). Notwithstanding this, the
products obtained from Sentinel-1 outperform those from ASCAT in specific
areas, like in valleys inside mountain regions and most of the plains,
confirming the added value of the high-spatial-resolution information in
obtaining spatially detailed rainfall. Finally, the performances of the
parameterized products are similar to those obtained with the calibrated
SM2RAIN algorithm, confirming the reliability of the parameterized algorithm
for rainfall estimation in this area and fostering the possibility to apply
SM2RAIN worldwide, even without the availability of a rainfall benchmark
product.
Interval estimates for statistical communication: problems and possible solutions
Authors:   La Trobe University, Cumming Geoff , Fidler Fiona ,   La Trobe University and University of Melbourne
Published: May 2022

In many behavioural and social sciences reformers are urging wider use of interval estimates. We believe confidence intervals can improve research communication markedly, but several problems are raised by our empirical studies of how people understand and misunderstand intervals. We describe three of these problems: an incorrect belief about confidence interval overlap and its relation to statistical significance; failure to distinguish between confidence intervals and standard error bars; and finally, neglect of the importance of research design in applying and interpreting intervals. Our suggested solution is better guidelines, or ‘rules of eye’, and improved graphical presentations to assist with confidence interval presentation and interpretation. The rules of eye are also pedagogic tools, for teaching deeper understanding of interval estimates. By confronting existing misconceptions, these guidelines should facilitate conceptual change in thinking not only about interval estimates themselves, but also the often misunderstood concept of statistical significance.
Visualizing data with dynamic graphics in excel
Authors:   AgResearch, Henderson Hatold
Published: May 2022

Data Visualisation tools provide deep insight into the structure of data. Dynamic statistical graphics are now widely available in many statistical packages, and even in Excel. I will give examples of the use of dynamic statistical graphics in statistical practice using Excel. Using such techniques, the internally assessed components of NCEA statistics can be presented by students in ways which are relevant, up-to-date and easy to understand.
The role of national statistics institutions in the use and understanding of official statistics in the compulsory education sector
Authors:   Statistics New Zealand, McGuinness Gareth , Hooper Lesley ,   Statistics New Zealand
Published: May 2022

Statistics New Zealand, like many national statistics institutions (NSIs), is charged with increasing the use and understanding of official statistics in the wider community. This seemingly insignificant outcome is driving radical changes in the way NSIs communicate their statistics to their audiences. One area where NSIs are increasingly working to communicate statistics is the compulsory education sector. Helping primary and secondary school students use and understand statistics is regarded as one of the best ways to promote the long- term use and understanding of official statistics. While there are many ways to build this statistical capability in young people, an emerging policy strand suggests that it is not realistic for NSIs such as Statistics New Zealand to embark on statistical education programmes of their own. Instead, it is argued that they should focus on three planks: encouraging agencies for education policy to place a high value on statistics education; influencing curriculum development (in statistics and other subjects) to include significant official statistics components; and providing targeted official statistics resources to support curricular components. This paper critically examines this approach to achieving the desired relationship between NSIs and the compulsory education sector, from a New Zealand perspective.
Data analysis or how high school students “read” statistics
Authors:   Université du Québec à Montréal, Gattuso Linda , Bourdeau Marc ,   École Polytechnique de Montréal
Published: May 2022

In most countries, statistics are included in the mathematics curriculum and taught by mathematics teachers. This leads to students learning the elements of statistical concepts as mathematical and to more emphasis placed on being able to compute different measures (e.g. mean, median, standard deviation) rather than their meaning and use. Moreover, in Quebec, the high school curriculum favours a scattered presentation of statistical concepts: tables and simple graphical representations are seen in the first year; averages, medians and histograms in the third; position measures in the fourth and some aspects of correlation and standard deviation are seen in the fifth. Some elements of probability are seen in the second year. But “statistics requires a different kind of thinking” (Cobb & Moore, 1997). Is it possible by making students compute statistical measures to foster the development of statistical thinking and prepare to draw conclusions from different data sets - all important abilities for “reading” statistics, an essential part of communication. This study attempts to determine if high school graduates develop the ability to effectively interpret the use and meaning of statistics (i.e. develop a “statistical way of thinking”). To this purpose we investigated (a) if a mode of data representation (1) list of data, (2) graphical, (3) principal location and dispersion parameters (mean, median, quartiles, standard deviation, etc), influences the students’ answers, (b) if students take into account the context of the data in their analysis, and (3) if students’ reasoning reveals “statistical thinking” as described in McGatha, Cobb and McClain (1998). A multiplicative argument combined with the use of the context in which the data are presented is preferable to an argument using only one point or only one measure (usually the mean) or only an arithmetic reasoning. To do so, a questionnaire with seven items asking students to choose from two or three samples and to justify the choice was presented to 141 fifth year high school students in the three different modes of presentation mentioned above. The results show that almost one third of the students revealed correct statistical thinking and another 41 % take the whole sample into account. The majority of the explanations are linked to the context. However, for some students more difficult tasks seemed to trigger a more global interpretation.
Communicating student performance data to school teachers
Authors:   School Research Evaluation and Measurement Services, Holmes-Smith Philip
Published: May 2022

The results from national studies of student ability are analysed using Item Response Theory (IRT). This theory describes the relationship between the ability of students taking a test and the difficulty of each item on that test. Using the assumption that a test item is a hard item if only the brightest students answer it correctly and that bright students are those students who can answer even the hardest items correctly, IRT is a generalized iterative procedure that can be used to simultaneously estimate both the difficulty of items on a test and the ability of those taking the test. This talk will give an overview of this technique and will demonstrate its use in measuring student ability. In particular the use of IRT models to construct Maths ability scores will be briefly discussed and how the results are communicated to teachers discussed.
How important are communication skills for ‘good’ statistics students? — an international perspective
Authors:   University of Sydney, Gordon Sue , Reid Anna ,   Macquarie University, Petocz Peter ,   Macquarie University
Published: May 2022

What do statistics teachers believe makes a good student of statistics? What part does the ability to communicate statistical results and ideas play in this judgement? In this paper, we investigate these questions and suggest answers based on a recent empirical study carried out by e-mail interview with IASE members from around the world. The responses alert us to the diversity of views on the relative importance of statistical communication held by statistics educators in service courses. Some teachers propose that communication skills are essential to learning statistics at university, others do not mention communication. In any discussion on statistical communication, we should be aware of the range of views held by statistics educators themselves, and the range of views that they communicate to students through their teaching.
Summative assessment strategies for statistical learning: development, administration, and scoring of authentic and performance assessments
Authors:   Ringling College of Art and Design, Dickinson Wendy , Onwuegbuzie Anthony ,   University of South Florida, Hines Constance ,   University of South Florida, Hall Bruce ,   University of South Florida
Published: May 2022

This paper describes three original assessments developed for use in undergraduate- and graduate-level mathematics and statistics courses: (a) the context-dependent item set (undergraduate); (b) the visual data display project (undergraduate); and (c) the statistics notebook (graduate). The goal of each assessment was to measure student learning of statistical concepts and methodology, gauge the student’s ability to apply those concepts in context, and provide an opportunity for students to appreciate statistics as a way to investigate, summarize, and explain phenomena of interest. Examples of all three assessments and rubrics are available for presentation.
Assessing assessment: a formal study of the benefits of assessment in a final year undergraduate statistics course
Authors:   University College Cork, Murphy Patrick
Published: May 2022

Students learn by doing: unfortunately many only do as little as is required of them to meet formal assessment requirements. We examine how a radical change in assessment strategy was chosen as a method of improving the learning experience for a group of students engaged in a final year undergraduate course in Time Series. In 2006, following attempts to change student attitudes through the use of different teaching techniques, we decided instead to focus on altering our assessment strategies. This paper will show that assessment appears to be one of the most effective tools to improve learning. While we remain committed to investigating and implementing improved methods for course delivery, our recent experience indicates the need to complement those methods with innovative assessment to improve the whole learning experience.
Can probability combinations/ estimations be assessed in preschoolers with the use of computers (PowerPoint)?
Authors:   University of Ioannina, Nikiforidou Z , Pange J ,   University of Ioannina
Published: May 2022

The aim of this study is to assess and investigate how many combinations can be manipulated by preschoolers in a probabilistic task. The task was computer- based and included 3 trials with alterations among the colour- combinations and proportions of the sample space. With the use of intuitive thinking or more concrete reasoning children at the age of 5-6, showed that they posses the notion of most/least likely when there are 2 and 3 combinations (not 4).
Assessing understanding of the concept of interaction in analysis of variance
Authors:   University of Denver, Green Kathy
Published: May 2022

Students have difficulty understanding the concept of interaction in analysis of variance, implications of the presence of a significant interaction for interpretation of main effects, and appropriate follow-up procedures. While grasping computational procedures and how to get software to generate the appropriate terms, interpretation and communication of results poses a challenge. In this paper exercises for teaching interpretation of interaction are presented. The context was an anova course designed for doctoral students in a college of education. These students are typically interested in substantive research areas such as counseling or educational administration, so the course is applied in nature. The approach taken to teaching interaction was scaffolding or layering of skills. Students first listened to explanations and examples of what interaction is and answered multiple choice questions oriented to comprehension and application outside of class. They then worked in small groups in class to calculate interaction terms both by hand and using statistical software. Next students wrote both technical summaries of results suitable for submission to a journal and one-paragraph “press releases,” both of which were critiqued by the course instructor and graduate teaching assistant. These exercises were standard across students and were highly structured. Students then received different data sets and were asked to repeat the analysis, technical, and brief write-up of results for the new data as a homework exercise. The “press releases” were the basis of 5-minute in-class presentations done to encourage verbal communication of results. After the presentation, classmates were given a 3-item quiz about their understanding of the results just presented. The quiz responses were used as feedback to the presenter about the effectiveness of their communication. Successes and failures of this approach are discussed as are thoughts about future directions in teaching about interaction.
Thoughts about the development of tools for cognitive diagnosis of students’ writings in an e-learning environment
Authors:   Maastricht University, Imbos Tjaart
Published: May 2022

Students can be stimulated to become active learners using a tool for active writing. In our university we developed such a tool: POLARIS. Active writings of students about statistical concepts are valuable for the students and the teacher. In their writings students show their understanding of statistical topics. The problem then is how to interpret the writings of students in relation to their proficiency in statistics. Advances in cognitive psychology have extended our understanding of students’ learning and broadened the range of performances that can be used to acquire evidence about the developing abilities of the students. Furthermore advanced technology has made it possible to capture complex performances of students in assessment settings. In this paper the advances in both domains will be explored in order to propose a system to monitor and diagnose students’ on going learning.
Weaving assessment for student learning in probabilistic reasoning at the introductory tertiary level
Authors:   Queensland University of Technology, Macgillivray Helen
Published: May 2022

For any course in a student’s degree program, the assessment should be part of an integrated assessment and learning package, with the components of the package combining to meet the learning objectives in a steady development of skills and operational knowledge that take account of the students’ various prior and future learnings. This paper considers such a package for an introductory course in probability and distributional modelling, including its objectives with reference to the nature of statistical thinking in probabilistic and distributional modelling, and general assessment principles. A new component of assessment to strengthen the problem-solving environment and to better address some of the objectives is described, together with student and tutor feedback and student data.
Fathoming Student Learning: a Survey Based Approach Using Fathom Surveys to Formative Assessment in an AP-Statistics Classroom
Authors:   KCP Technologies, Parvate Vishakha , Finzer William ,   KCP Technologies, Beals Cynthia ,   Catlin Gabel School, Gould Robert ,   UCLA
Published: May 2022

This paper describes a classroom experience using a data gathering and analysis tool to scaffold a learning process that involves classroom surveys as a means of gathering formative assessment data.. An AP-Statistics class uses data about their own sleep patterns to investigate measures of variability. The class applies various measures of variability to the sleep data set and comments on their efficacy using a survey created in Fathom. The students comment on the measures in groups, rate the measures, and provide justifications. Students in a statistics class should find themselves routinely engaged in data analysis. Asking students to comment on invented measures of variability provides valuable formative assessment data for the instructor.
Using peer assessment of project presentations to develop skills as consumers of statistical information
Authors:   International University of Monaco, Sisto Michelle
Published: May 2022

This paper begins with a description of several learning goals of the two-course Introductory Statistics sequence for undergraduate business students at the International University of Monaco, and then focuses on the goals of communicating statistical results and becoming critical consumers of statistical information. As our students are business students, we aim for them to become both producers and literate consumers of statistical analysis. In line with reform movements in Statistics Education and the GAISE guidelines, we are working to implement teaching strategies and assessment methods that align instruction and assessment with our learning goals. One of the main instructional tools we use is group projects with elements of peer and self assessment. This paper describes how peer evaluations are carried out, how they are summarized and why we believe that explicitly incorporating these self and peer assessments has improved student learning both in communicating and in consuming statistical information.
Enhancing student understanding in statistical inference – assessing the effectiveness of a computer interaction
Authors:   Swinburne University of Technology, Francis Glenda , Kokonis Sue ,   Swinburne University of Technology, Lipson Kay ,   Swinburne University of Technology
Published: May 2022

A new simulation has been developed to facilitate developmental learning of statistical inference. This simulation has been designed in the light of current multimedia design principals and cognitive theory. While many simulations have been developed to help students understand a variety of statistical concepts, evaluations of what these simulations actually achieve have been relatively scarce. This paper presents a model for the evaluation of simulations. In particular, the paper discusses the way in which the development of the students’ conceptual understanding has been assessed. Some preliminary results from the evaluation of this specific project are presented.
Assessing student learning in first-year quantitative courses at Babson college: implementation and analysis
Authors:   Babson College, Mckenzie Jr. John , Rybolt William ,   Babson College
Published: May 2022

This paper reports on the implementation of the experiments we designed to assess how well our first-year students learn statistics and mathematics with electronic quizzes. It describes many issues that arose in our attempts to study the impact of such quizzes. An explanation of these issues should assist others who wish to assess the impact of technology in the classroom. The paper concludes with a preliminary analysis of the data from our experiments in fall semester of 2006 and a description of similar experiments planned for the spring semester of 2007.
Evaluating pedagogical techniques in introductory statistics: proficiency grading and assignment resubmission
Authors:   Villanova University, Posner Michael
Published: May 2022

How do innovative pedagogical techniques improve learning and mastery of introductory statistics? This research study examines proficiency grading and assignment resubmission and compares them to traditional statistical teaching methodology in two introductory statistics classes. The control class received traditional numeric grades, while the experimental class received grades on a three-tiered proficiency ranking and the opportunity to resubmit assignments to increase their proficiency score. Students in the control class scored higher on a common final exam (although not statistically significant), and believed the material was better taught, while students in the experimental class claimed to have learned more and were more satisfied with the grading in the course. Future research will expand data gathering and improve the research design.
Assessing undergraduate students of a statistics course in environmental science
Authors:   Universidad Politécnica, Capilla Carmen
Published: May 2022

This paper presents a case study of assessing an applied statistics course. The assessment includes 10 computer lab activities, that students may voluntary complete during the fall semester. An individual voluntary project is also incorporated as part of the assessment. At the end of the semester there is a final examination about the course contents. These assessment methods and the difficulties to implement them are discussed. Students have heterogeneous backgrounds. Some of them show fear and anxiety towards the subject. This interferes with the implementation of the assessment and implies discipline problems.
Assessing the knowledge of future middle school teachers in statistics by lesson design
Authors:   Texas State University, Sorto Alejandra
Published: May 2022

In this paper, an assessment project conducted in a class for future middle school teachers in statistics is presented. The project consisted of designing and presenting a lesson that addressed a statistical concept taught in middle school following the Japanese Lesson Study model. Future teachers were asked to identify the big ideas covered, its connections to previous and future content by aligning the lesson to state, national standards, and the GAISE recommendations, make predictions about students misunderstandings based on readings about statistics education research, propose activities or procedures on how to teach the concept, and create an evaluation plan. Lessons were presented in pairs to the entire class and the “best” lesson presented to actual 5th graders at a local middle school. Final reflections and evaluations from prospective teachers are discussed.
Comparative Study of Efficacy and Safety of Mini-craniotomy under Local Anaesthesia versus General Anaesthesia for Chronic Subdural Hematoma
Authors: Mehndi Masih Dr. Shah , Kumar Dr. Mukesh , Kumar Dr. Ravi
Published: May 2022

Background: Mini-craniotomy is generally better than burr whole drainage for chronic subdural hematoma (CSDH) as there are less chances of recurrence and need for re-surgery in this technique. But generally mini craniotomy is performed under general anaesthesia and this is found to be associated with post-operative complication in earlier studies. The same procedure when carried under local anaesthesia is expected to cause less post-operative complications.
Aim: To compare the efficacy and safety of min-craniotomy under general anaesthesia and local anaesthesia for CSDH. Material & Methods: It was a retrospective study in which patients of age 50 years or higher that have undergone mini-craniotomy under general or local anaesthesia were included. Pre-operative condition, surgery duration and post-operative complications were taken from patient’s medical records and compared.
Results: Sixty patients were included in the study. Thirty-two of these patients underwent mini-craniotomy under LA and thirty-eight under GA. Improvement was better in patients who underwent the surgery under local anaesthesia than the general anaesthesia group. Post-operative complications like pneumonia and DVT (Deep Venous Thrombosis) were less frequent in local anaesthesia group.
Conclusion: Mini-craniotomy performed under local anaesthesia is found to have same efficacy than the same procedure performed under general anaesthesia. It is also found to have less chance of recurrence, reoperation and postoperative complication. So, mini-craniotomy under local anaesthesia can be better alternative for CSDH.

Keywords: Mini-craniotomy, Local anaesthesia, General anaesthesia, chronic subdural hematoma.
Condition Monitoring and Predictive Maintenance of Industrial IoT Systems using Fog Computing
Authors:   Department of Information Technology, Thiagarajar College of Engineering, Madurai, India, D Malarvizhi , Padmavathi S
Published: May 2022

Condition Monitoring and Predictive Maintenance are emerging in the Industrial environments for effective maintenance of the assets and the machinery. This involves monitoring the equipment in an effective way to prevent unexpected failures and unplanned downtimes in the production environment. The scope of this work is to provide high level details on Condition Monitoring which in turn is used for Predictive Maintenance. This paper proposes a novel infrastructure to use the Fog computing layer in industrial environments, in order to prevent failures before they happen, allowing seamless monitoring of the production environment and thus preventing catastrophic system failures in advance.
Textual Sentiment Analysis using Machine Learning and NLP: A Review
Authors:   Department of CSE, RNTU, Bhopal, India, Sharma Neha , Veenadhari S , Kulhare Rachna
Published: May 2022

One of the most prominent parts of opinion mining is sentiment analysis that is used to extract emotion from textual features. Through this process, it can be determined whether a piece of writing is positive, negative, or neutral. This paper presents a review on the sentiment analysis task using textual data. A sentiment analysis system for text com-bines Natural Language Processing (NLP) and Machine Learning Techniques to assign weighted sentiment scores to the entities, topics, themes, and categories within a sentence or phrase. One of the prominent parts of opinion mining is depression detection. Nowadays, a significant section of society is affected by depression due to mental stress. So, it is also a considerable concern. There may be several reasons for depression, especially in adults. Different people have different symptoms, and its identification is a significant challenge. Most people feel shy to accept that they suffer from depression, while some people are unaware of their depressed mental health. The objective of this paper is to analyze recently developed frameworks for the diagnosis of sentiment and depression level of an individual. This paper directs towards creating a single framework in the future for depression and sentiment analysis.
A Comprehensive Review of Optimization Algorithms for Nonlinear Systems
Authors:   Netaji Subhas Institute of Technology, New Delhi, India, Srivastava Vishal , Srivastava Smriti
Published: May 2022

The practical problems are full of nonlinearity and uncertainty due to their dynamic behavior. The uncertainties, parameters variations and other constraints make nonlinear systems very complex. To deal with such system dynamics and uncertainties, soft computing techniques are widely used. Optimization algorithms are one of the most effective and simple soft computing techniques.In literature, several controllers and control mythologies are being discussed to evaluate the system performance. Optimization algorithms are one of the popular soft computing techniques, used with different controllers like conventional PID, fuzzy logic, ANN, and many others to handle system nonlinearities and enhance the performance. These optimization algorithms not only improve the performance effectively but also gave robust response towards the nonlinearities. The proper selection of algorithm is a very important aspect to find the best solution. Here three categories of algorithms i.e. from swarm-based algorithms particle swarm optimization (PSO), grasshopper optimization algorithm (GOA), grey wolf optimization (GWO), whale optimization algorithm (WOA), gravitational search algorithm (GSA) from physics based and teaching learning based optimization (TLBO) from human-based have been reviewed for nonlinear systems. Most of the algorithms are suffering from either of abilities i.e. exploration or exploitation so sometimes they are not able to give optimal solution. To overcome with this problem, recently hybrid approach of algorithms has been widely used in which the better sides of the individual algorithms are utilized.