A Study of Learning Behavioral Engagement in Live Teaching

Based on the related theories and research results of learning behavioral engagement, this study constructed an evaluation framework of learning behavioral engagement in live teaching, which included 24 indicators in three dimensions: compliance with norms, learning participation and social participation. A small-class live English learning for younger students on the ClassIn was taken as a case study program. Five younger students attended this English learning course of 16 lessons totaling 950 minutes. The preset indicators were preliminarily examined based on the teaching records and the recorded course data. Then, experts in the field of educational technology were invited to develop the learning behavioral engagement dimensions and indicator weightings by using the Analytic Hierarchy Process, and to determine the evaluation indicator system for the evaluation of learning behavioral engagement. Finally, based on this framework, the characteristics of learning behavioral engagement of the case course were analyzed, and the influences of students’ individual factors, teaching and environmental factors on learning behavioral engagement in live teaching were investigated.     

面向群体智能塑造未来教育:一项重要研究课题

群体智能指群体在完成一系列不同任务时表现出的综合能力,是面向未来复杂情境中跨学科、综合型任务解决过程必不可少的关键要素。教育现代化进程中的群体智能教育是面向未来培养公民信息素养、合作能力、问题解决能力的重要载体和实现目标。文章基于当前研究领域中对群体智能基本概念的辨析和探索,从国际视野出发,剖析基于不同的技术手段对群体智能教育的探索和实践,提出教育信息化时代中国教育领域中进一步强化群体智能教育、推动"五育并举"、促进培养复合型人才的可行路径。     

Measuring cognitive load and cognition: metrics for technology-enhanced learning

This critical and reflective literature review examines international research published over the last decade to summarise the different kinds of measures that have been used to explore cognitive load and critiques the strengths and limitations of those focussed on the development of direct empirical approaches. Over the last 40?years, cognitive load theory has become established as one of the most successful and influential theoretical explanations of cognitive processing during learning. Despite this success, attempts to obtain direct objective measures of the theory's central theoretical construct – cognitive load – have proved elusive. This obstacle represents the most significant outstanding challenge for successfully embedding the theoretical and experimental work on cognitive load in empirical data from authentic learning situations. Progress to date on the theoretical and practical approaches to cognitive load are discussed along with the influences of individual differences on cognitive load in order to assess the prospects for the development and application of direct empirical measures of cognitive load especially in technology-rich contexts.     

试论中学语文阅读教学中文本意义的多元阐释

随着教育改革的不断深入,文章意义的解读从单一化向多元化转变,阅读教学重视体现学生的主体性,培养学生的创造性思维,发挥学生的潜能,让学生对作品进行自由、广泛、深入的认识,形成自己独特解悟。认识这些重要性后就要做到:一、课堂学习学生要实现由学"答"到学"问"的转变;二、在合作学习小组中,对文章进行评读,互赖促进;三、在自主探索中体验求知的快乐;四、尊重学生情感,正确看待学生个体差异,做好同步与差异的统一;五、鼓励学生养成健康时尚并富有个性的审美观;六、保证学生课外阅读正常有效的进行。     

解释学的文本理解观与教师观念变革

立足解释学关于文本的不同视角,审视教师的课程观和学生观,并提出建立以新解释学的文本观为指导的课程观和学生观。     

A machine learning approach for automatic detection and classification of changes of direction from player tracking data in professional tennis

ABSTRACT

The purpose of this study was to develop an automated method for identifying and classifying change of direction (COD) movements in professional tennis using tracking data. Three sport science and strength and conditioning experts coded match-play footage of nineteen professional tennis players (9 male and 10 female) from the Australian Open Grand Slam for COD of medium and high intensity. A total of 1,494 changes were identified and aligned with 2D player position sampled at 25 Hz based on camera tracking data. Several machine learning classifiers were trained and tested on a set of 1,128 time-motion features. A random forest algorithm was found to have the best out-of-sample performance, classifying medium and high intensity changes with an F1-score of 0.729. This research offers a novel and applicable way for utilising player tracking data and machine learning techniques to automatically identify and classify COD movements in professional tennis.     

A Bayesian feature selection paradigm for text classification

The automated classification of texts into predefined categories has witnessed a booming interest, due to the increased availability of documents in digital form and the ensuing need to organize them. An important problem for text classification is feature selection, whose goals are to improve classification effectiveness, computational efficiency, or both. Due to categorization unbalancedness and feature sparsity in social text collection, filter methods may work poorly. In this paper, we perform feature selection in the training process, automatically selecting the best feature subset by learning, from a set of preclassified documents, the characteristics of the categories. We propose a generative probabilistic model, describing categories by distributions, handling the feature selection problem by introducing a binary exclusion/inclusion latent vector, which is updated via an efficient Metropolis search. Real-life examples illustrate the effectiveness of the approach.     

中国服务创新中商业方法专利的应用现状与前景预测

商业方法专利是保护服务业知识产权的一种新方法,本文从理论研究出发,阐述服务创新的主要内容和知识产权保护方法,以中国国家知识产权局检索到的商业方法数据进行现状分析,利用趋势曲线模型预测法进行前景预测,最后用trend函数对预测结果进行检验。结果表明中国应顺应趋势、与时俱进,通过专利法的及时修订,尽快将商业方法专利纳入到中国专利法的可专利主题范畴以及专利制度的保护框架之内。     

空心课文——大学英语教材的批判

空心课文在大学英语教材中所产生的危害,导致课文没有实实在在的内容,没有增加信息和知识。文章提出大学英语教材应该增加扩展非语言知识信息,以解决空心课文的问题。     

播客的社会文本意义解读

本文从符号学和传播学的视角,对国内外迅速兴起的“播客”现象进行较为深入的文本意义解读。笔者认为,作为社会文本的播客,其意义是:在播客特定的语境下,人们借助不同的符号系统,使“自我实现”得到最大的满足并正逐步融入社会。从编码者的角度看,这种“自我的实现”的特点是,话语权力的获得和“超符号”的自由交流。而译码者的“自我实现”的特点,则是通过解释权的回归,使可读的文本和可写的文本得以沟通。