Dealing with non‐normality: an introduction and step‐by‐step guide using R

The article presents some notes on normalization and illustrates these procedures using graphing functions in R. Using real data, the paper also presents an R package and online Shiny app that efficiently transforms variables in large datasets.     

Using an R shiny to enhance the learning experience of confidence intervals

Many students find understanding confidence intervals difficult, especially because of the amalgamation of concepts such as confidence levels, standard error, point estimates and sample sizes. An R Shiny application was created to assist the learning process of confidence intervals using graphics and data from the US National Basketball Association.     

Optimal Sample Allocation in Group-Randomized Mediation Studies with a Group-Level Mediator

We derive sample-allocation formulas that maximize the power of several mediation tests in two-level–group-randomized studies under a linear cost structure and fixed budget. The results suggest that the optimal individual sample size is typically smaller than that associated with the detection of a main effect and is frequently less than 10 under parameter values commonly seen in the literature. However, the optimal sample allocation can be heavily influenced by the group-to-individual cost ratio, the ratio of the treatment-mediator to mediator-outcome path coefficients, and the outcome variance structure. We illustrate these findings with a hypothetical group-randomized trial examining a school-discipline reform policy. To encourage utilization of the sample allocation formulas we implement them in the R package PowerUpR and powerupr Shiny application.     

Using Shiny to illustrate the probability density function concept

The transition from the probability mass function for discrete random variables to the probability density function for continuous random variables is not straightforward, especially to students from the health and social sciences. An R Shiny application was created to assist the learning process of probability density function.     

民事诉讼和解效力之研究

民事诉讼和解一经成立,便与确定判决有同一的效力。但是,和解与确定判决有同一的效力,是否效果全部相同,不无疑问。诉讼和解的效力应当包括羁束力、形式的确定力、执行力和形成力。从和解是当事人自主解决纠纷的方式出发,为保障当事人对瑕疵和解申请救济的途径,应当否定诉讼和解的既判力。     

Testing the Intervention Effect in Single-Case Experiments: A Monte Carlo Simulation Study

This article reports on a Monte Carlo simulation study, evaluating two approaches for testing the intervention effect in replicated randomized AB designs: two-level hierarchical linear modeling (HLM) and using the additive method to combine randomization test p values (RTcombiP). Four factors were manipulated: mean intervention effect, number of cases included in a study, number of measurement occasions for each case, and between-case variance. Under the simulated conditions, Type I error rate was under control at the nominal 5% level for both HLM and RTcombiP. Furthermore, for both procedures, a larger number of combined cases resulted in higher statistical power, with many realistic conditions reaching statistical power of 80% or higher. Smaller values for the between-case variance resulted in higher power for HLM. A larger number of data points resulted in higher power for RTcombiP.     

应用对比分析和错误分析对外语教学的启示

在对应用对比分析和错误分析的定义、发展过程的分析的基础上,对其进行批判性探索,并在5所不同类型的高校做调研,对学生在语言上的错误进行分类、分析和探究错误原因,得出三个主要的具体原因,即套用句型错误、母语干扰、规则僵化,并最终通过错误分析对教学进行指导,得到有益的启示。     

大学新生英语口语错误及相关对策探微

笔者通过对比研究以了解大学新生口语错误的主要类型、产生根源及可用纠错策略。研究数据表明,加强词汇知识运用、交际策略的训练等方法可有效提高学生语言交际的成功率。此外,注重大学与高中英语教学衔接将有助于学生顺利跨越高中与大学英语学习之间的"门槛"。     

具有遗传印记效应传递/不平衡检验(TDT)的功效(英文)

根据Knapp在 1999年提出的求TDT渐近功效的方法 ,应用标准的统计大样本理论 ,从两个方面对Knapp的方法进行了推广 :(1)在疾病的遗传中考查了遗传印记的影响 ;(2 )在求概率时考查了标记位点与候选疾病位点之间的位置关系 .     

三相电能表分组误差的调配问题

电能计量是电力节能的一种重要手段，而计量器具的误差直接影响计量的准确性。本文针对三相电表中存在的误差因素分析，提出解决方法来提高计量的准确性。     

Learning from Apps and Objects: The Human Touch

In three studies, we examined children's geography learning from a physical puzzle and an app designed to mimic the puzzle. In Study 1, 5‐ and 6‐year‐olds were taught Australia's states by an experimenter using a puzzle or were taught by an app. Children learned significantly more states from instruction with the puzzle than when they used the app independently. When children were allowed to bring home the puzzle or app for 1 week in Study 2, total learning between conditions was comparable. Length and frequency of use were related to learning only for puzzle users. In Study 3, children were taught the geography lesson by an experimenter using the app. Children's learning from this social app condition was equal to the social puzzle condition but higher than the solo app condition of the earlier studies, suggesting that learning from digital devices is most successful when supplemented with in‐person social interaction.     

Visual Foxpro程序中错误的识别和避免

就面向对象Visaul Foxpro语言在编程过程中常见错误的识别和避免进行了概括和归纳。     

Investigating the effectiveness of gamification on supply chain operations knowledge and practice

The use of gamification to enhance learning in education has been well documented. However, little is known about whether gamification can impact supply chain management knowledge and behaviors among healthcare professionals. In this study, we tested the effectiveness of a simulation app (ShipShape) designed and developed to gamify the fundamental concepts of supply chain management. We field tested the effectiveness of the app to impact knowledge gain and supply chain practice by asking healthcare professionals to use the app in their day-to-day operations. We collected longitudinal data spanning the period before and after the introduction of the app. The analysis and results of different types of data collected provide support for the positive impact of the app on both supply chain knowledge and practice among healthcare professionals.     

Learning Neuroscience with Technology: a Scaffolded,Active Learning Approach

Mobile applications (apps) for learning technical scientific content are becoming increasingly popular in educational settings. Neuroscience is often considered complex and challenging for most students to understand conceptually. iNeuron is a recently developed iOS app that teaches basic neuroscience in the context of a series of scaffolded challenges to create neural circuits and increase understanding of nervous system structure and function. In this study, four different ways to implement the app within a classroom setting were explored. The goal of the study was to determine the app’s effectiveness under conditions closely approximating real-world use and to evaluate whether collaborative play and student-driven navigational features contributed to its effectiveness. Students used the app either individually or in small groups and used a version with either a fixed or variable learning sequence. Student performance on a pre- and post-neuroscience content assessment was analyzed and compared between students who used the app and a control group receiving standard instruction, and logged app data were analyzed. Significantly, greater learning gains were found for all students who used the app compared to control. All four implementation modes were effective in producing student learning gains relative to controls, but did not differ in their effectiveness to one another. In addition, students demonstrated transfer of information learned in one context to another within the app. These results suggest that teacher-led neuroscience instruction can be effectively supported by a scaffolded, technology-based curriculum which can be implemented in multiple ways to enhance student learning.     

Distribution network planning algorithm based on Hopfield neural network

1 Introduction An urban power system is a very important part othe power system and requires a huge investment for itconstruction and operation. This investment can bsubstantially reduced by a system approach to urbapower system planning which is not an easy task due tits dependence upon urban geography conditions. Foexample, feeder lines must be laid along urban streeUp to now, several mathematical models analgorithms have been developed to plan urban powesystem. Peponis and Papadopoulos [1]…     

Researching educational apps: ecologies,technologies, subjectivities and learning regimes

ABSTRACT

Apps are becoming increasingly important in education. However, critical educational research has hardly ever undertaken up-close analyses of educational apps. This article provides an extensive analysis of one ‘learning to code' app called Grasshopper. Drawing from the field of Science and Technology Studies, the article adopts a theoretical framework that situates app analyses at the dimensions of apps' situated ecologies, their platform and algorithmic technologies, the enacted user subjectivities and, as the sum of these previous dimensions, the projected learning regimes. Making use of the methodological entry points of app websites, stores and interfaces, the article makes visible and analyzes the app’s infrastructural settings, actively invokes different app situations, and uses these to advance the inquiry by offering a multidimensional point of view that navigates different scalar dimensions of educational apps. In doing so, the article examines learning to code through its concrete sociomaterial practices, and the specific pedagogies and sorts of education that are employed in order to bring about such learning.     

An Exercise to Introduce Power

In introductory statistics courses, the concept of power is usually presented in the context of testing hypotheses about the population mean. We instead propose an exercise that uses a binomial probability table to introduce the idea of power in the context of testing a population proportion.     

低功率因数瓦特表应用的有关问题的探讨

详细介绍了低功率因数瓦特表在测量中应该注意的问题，给出了功率表的测量原理和读数方法，讨论了测量不同功率时的接线方式。当被测电路的功率比较小时，采用直接和功率表相接方法；当被测电路的电压和电流超过仪表电压和电流的最大额定值时，就要用互感器和仪表相接。对使用互感器和功率表相接时的测量误差进行了分析。     

浅析供电系统电能计量误差

电能计量装置作为供用电双方贸易结算和企业内部技术考核电能的依据,它的准确与否极为重要.从电能表、互感器、二次接线三个方面对电能计量误差进行了简要分析,并有针对性地提出了降低电能计量误差的一些应对措施.     

Selecting educational apps for preschool children: How useful are website app rating systems?

In the present paper, we assess whether website rating systems are useful for selecting educational apps for preschool age children. We selected the 10 highest scoring and 10 lowest scoring apps for 2–4-year-olds from two widely used websites (Good App Guide; Common Sense Media). Apps rated highly by the two websites had a higher educational potential as assessed by a validated questionnaire for evaluating the educational potential of apps and were more likely to include a learning goal and feedback compared to low scoring apps. However, high scoring apps scored on average just 9/20 for indicators of educational potential, and both high and low scoring apps had poor language quality as determined by psycholinguistic and construction type analyses. We argue that website rating systems should also include quality of feedback, adjustable content, social interactions, storyline and a more fine-grained analysis of language in their assessments.

Practitioner notes

What is already known about this topic

• Appropriately designed apps for preschool age children have the potential to teach early school readiness skills.
• Selecting high quality educational apps for preschool age children is challenging.
• The children's app marketplace is currently unregulated.

What this paper adds

• We assess whether two leading app rating websites are useful for selecting educational apps for preschool age children.
• Children's apps rated highly by two app website rating systems had a higher educational potential than low rated apps as measured by a research informed app evaluation tool.
• In-depth analysis of the language in apps shows that highly rated children's apps on app rating websites may not enrich a child's early language environment.

Implications for practice and/or policy

• Children's app rating website assessments should include potential for feedback, language, adjustable content, storyline and social interactions.
• Policy should be implemented for app ratings in the app stores or on website app rating systems.