Promoting metacognition in first year anatomy laboratories using plasticine modeling and drawing activities: a pilot study of the "blank page" technique

Many first year students of anatomy and physiology courses demonstrate an inability to self-regulate their learning. To help students increase their awareness of their own learning in a first year undergraduate anatomy course, we piloted an exercise that incorporated the processes of (1) active learning: drawing and plasticine modeling and (2) metacognition: planning, monitoring, reaction, and reflection. The activity was termed "blank page" because all learning cues were removed and students had to create models and diagrams from reflection and recall. Two hundred and eighty-two students responded to a questionnaire reporting qualitative feedback on the exercise. Based on student responses, the "blank page" activity was a positive learning experience and confirmed a need to teach metacognitive skills. From this pilot study, we established that drawing or plasticine modeling is an excellent vehicle for demonstration of the metacognitive processes that enable self-regulation: a known predictor of academic success.     

Development and validation of scales to measure environmental responsibility,character development,and attitudes toward school

This investigation examines the use of structural equation modeling (SEM) procedures to develop and validate scales to measure environmental responsibility, character development and leadership, and attitudes toward school for environmental education programs servicing middle school children. The scales represent outcomes commonly of interest to environmental education programs and also to after‐school and positive youth development activities. First, we developed the scales using confirmatory factor analysis (CFA) and then we used multi‐group longitudinal CFA to cross‐validate the model with data collected before participation in the environmental education program, immediately after the program, and three months later. The results support a three‐factor model, producing three scales that appear to be valid and reliable.     

基于等级考试的VB参数传递教学研究

提出了目前计算机等级考试中参数传递相关内容的考查重点,以实例分析的形式对其进行了详细阐述,并提出了教学过程中的注意点。     

高职院校《数学建模》教材建设初探

分析了目前发行的《数学建模》教材现状,根据高职培养目标、课程设置和学生的基础情况,指出数学建模教材存在的问题,结合高职院校的实际进行改革,突出了高职特色。     

人工蜂群算法在多元线性回归中的应用

提出了用人工蜂群算法解决多元线性回归问题.通过计算机仿真测试,表明人工蜂群算法在多元线性回归分析的参数估计问题中是有效的、实用的.     

浅议智能调节器在过程控制系统中的应用

智能调节器在工业生产中的应用越来越广泛.以智能调节器为控制器,适当进行参数设置,可以构成多种过程控制系统.这些系统可以对液位、温度和流量等热工参量进行定值控制.研究智能调节器的应用领域和使用方法,有助于在实践中提高工业生产的智能化水平.     

浅析戏剧语言中主位结构应用的演变

以信息为核心的主位结构在语言实践中被广泛应用、研究。戏剧语篇的语言主位结构作为形式范畴,在不同戏剧作品、戏剧场景中演变为不同的表现形态,主位结构所对应的信息结构、隐含的信息参数也随之发生变化,使戏剧语言元功能得到解读,并直接作用于戏剧效果。     

探究式教学在研究生课程教学中的实践

以＂系统建模与参数估计＂课程的教学为例,探讨探究式教学方法在研究生课程教学中的实践方式。通过分析研究生教学的特点,指出探究式教学在研究生教学中的重要地位。从课堂讨论、专题讨论和课后实践与课程报告三个方面给出探究式教学的实施方法,并指出实施过程中需要注意的几个问题。这些教学方法经过＂系统建模与参数估计＂课程的实践后,取得很好的效果。     

变频变压供水系统设计与研究

通过对阀门控制、变频恒压和变频变压三种供水系统数学模型进行比较,设计出一种变频变压供水系统,通过对该系统模型的分析表明,该系统的节能效果优于目前普遍使用的变频恒压供水系统。     

Mining social influence in science and vice-versa: A topic correlation approach

There is no doubt that scientific discoveries have always brought changes to society. New technologies help solve social problems such as transportation and education, while research brings benefits such as curing diseases and improving food production. Despite the impacts caused by science and society on each other, this relationship is rarely studied and they are often seen as different universes. Previous literature focuses only on a single domain, detecting social demands or research fronts for example, without ever crossing the results for new insights. In this work, we create a system that is able to assess the relationship between social and scholar data using the topics discussed in social networks and research topics. We use the articles as science sensors and humans as social sensors via social networks. Topic modeling algorithms are used to extract and label social subjects and research themes and then topic correlation metrics are used to create links between them if they have a significant relationship. The proposed system is based on topic modeling, labeling and correlation from heterogeneous sources, so it can be used in a variety of scenarios. We make an evaluation of the approach using a large-scale Twitter corpus combined with a PubMed article corpus. In both of them, we work with data of the Zika epidemic in the world, as this scenario provides topics and discussions on both domains. Our work was capable of discovering links between various topics of different domains, which suggests that some of the relationships can be automatically inferred by the sensors. Results can open new opportunities for forecasting social behavior, assess community interest in a scientific subject or directing research to the population welfare.