Complementing subjective with objective data in analysing expertise: A machine-learning approach applied to badminton     

Olivier Dieu  Christophe Schnitzler  Clément Llena  François Potdevin 《Journal of sports sciences》2020,38(17):1943-1952

ABSTRACT

This study aimed to assess which combination of subjective and empirical data might help to identify the expertise level. A group of 10 expert coaches classified 40 participants in 5 different expertise groups based on the video footage of the rallies. The expertise levels were determined using a typology based on a continuum of 5 conative stages: (1) structural, (2) functional, (3) technical, (4) contextual, and (5) expertise. The video allowed empirical measurement of the duration of the rallies, and tri-axial accelerometers measured the intensity of the player’s involvement. A principal component analysis showed that two dimensions explained 54.9% of the total variance in the data and that conative stage and empirical parameters during rallies (duration, intensity of the game) were correlated with axis 1, whereas duration and acceleration data between rallies were correlated with axis 2. A random forest algorithm showed that among the parameters considered, acceleration, duration of the rallies, and time between rallies could predict conative stages with a prediction accuracy above possibility.

This study suggests that performance analysis benefits from the confrontation of subjective and objective data in order to design training plans according to the expertise level of the participants.  相似文献   

Score Reporting for Examinees with Incomplete Data on Large‐Scale Educational Assessments     

Sandip Sinharay 《Educational Measurement》2021,40(1):79-91

Technical difficulties occasionally lead to missing item scores and hence to incomplete data on computerized tests. It is not straightforward to report scores to the examinees whose data are incomplete due to technical difficulties. Such reporting essentially involves imputation of missing scores. In this paper, a simulation study based on data from three educational tests is used to compare the performances of six approaches for imputation of missing scores. One of the approaches, based on data mining, is the first application of its kind to the problem of imputation of missing data. The approach based on data mining and a multiple imputation approach based on chained equations led to the most accurate imputation of missing scores, and hence to most accurate score reporting. A simple approach based on linear regression performed the next best overall. Several recommendations are made regarding the reporting of scores to examinees with incomplete data.  相似文献   

高校矿业类专业人才培养模式探讨   总被引：6，自引：0，他引：6  

何廷峻  汪佑武 《淮南职业技术学院学报》2005,5(1):103-105

分析了采矿工程专业教学的现状和存在的问题，通过调查研究，吸收国内外成功的教学改革经验，对采矿工程专业人才培养模式、教学内容、教学计划、教学体系等问题进行了探讨。  相似文献   

基于Oracle Spatial的空间查询技术及其优化     

熊雷 《教育技术导刊》2008,7(8):7-9

从Oracle Spatial的空间查询分析出发,结合实例分析了它的查询模型、空间算子以及常用的空间函数,最后给出了Oracle Spatial中空间查询的优化建议。  相似文献   

Affordances of narrative and numerical data: A social-semiotic approach to data use     

《Studies in Educational Evaluation》2021

Data use in education is a sensemaking process in which practitioners and researchers interact with different systems of meaning such as anecdotes or spreadsheets. The representational qualities of data and their influence on practice are critical but less well-discussed aspects of data use. Drawing on social semiotics, this theoretical article proposes that data should be discussed in terms of narrative and numerical modes of representation. Narrative data typically consist of protagonists and actions organized in a temporal structure, while numerical data typically consist of mathematical notations and visual representations such as graphs and figures. We argue that the representational properties of these two modes affect how data are interpreted and acted upon. We then present two contrasting cases from New Zealand and Norway of how affordances affect teachers’ data use processes. Finally, we discuss five challenges arising from our theorization about the affordances of data.  相似文献   

Capacity building to bridge data use and instructional improvement through evidence on student thinking     

《Studies in Educational Evaluation》2021

While schools and systems across the globe promote data-driven decision making, teachers often struggle to use data, especially from external assessments, to inform daily instruction. In this paper, we examine teacher capacity building for a less typical form of data use - evidence on student thinking. We draw on data from a longitudinal, in-depth qualitative study involving middle school math teachers who were engaged in an instructional improvement project. Findings show that data use occurred when evidence from student thinking was introduced as part of the instructional planning process. This shift was facilitated by an instructional coach whose capacity building efforts with teachers focused on coherence, specifically planning high quality instruction and using data effectively, while also meeting district pacing and unit planning goals. When teachers put new strategies into practice, feedback from formative assessment data allowed teachers to identify and address misconceptions in student thinking. Learning how to use data as part of instruction helped teachers build capacity to reflect on their own practice. Implications for theory, practice, and research are discussed.  相似文献   

基于关联分析的计算机软件数据挖掘技术     

陈翠娟 《安阳师范学院学报》2021,(2):28-31

计算机软件蕴含大量工作信息,有效挖掘软件数据信息之间的内在关联是信息时代对软件应用的潜在要求。针对经典Apriori算法挖掘数据效率低、复杂度高的问题,提出一种改进Apriori算法用于挖掘计算机软件数据的关联规则。为计算机软件算法设置双重支持度阈值,即频繁项集与非频繁项集支持度阈值,快速获得强关联的频繁项集;在此基础上基于映射规则重构事务数据库,压缩数据库规模,减少算法的剪枝操作,降低计算机软件数据关联规则挖掘复杂度。以人力资源类计算机软件数据为例展开关联分析测试,结果显示,该算法挖掘的关联信息与人力资源实际管理情况一致,相比经典Apriori算法其效率有所提升。  相似文献   

计算机文化基础MOOC平台互动教学实践探索     

任会峰  阚希  陆松  董庆超 《教育技术导刊》2021,19(12):43-47

针对大学各学科培养目标存在差异,以及学生入学时计算机基础不平衡等教育教学现状,依托大规模开放在线课程（MOOC）平台,以计算机文化基础课程为例,从开课前、授课中、结课后3个阶段分别论述开设课程、组织授课和追踪反馈等多个教学环节的实践过程,并形成闭合环路,探索面向应用能力培养的互动教学模式,同时探讨教学中存在的问题及解决办法。抽组测试发现,混合教学的及格率达到98%,相比传统教学提高了18%,约33%的学生自主选择混合式学习,表明MOOC平台的混合教学有利于培养学生的计算思维,提高其计算机应用能力,最后分析MOOC平台采用大数据挖掘技术的重要性和可行性。  相似文献   

应用型课程改革实践——以“数据结构”为例     

黄芳 《教育教学论坛》2021,(13):75-78

应用型课程是应用型高校转型的关键,是实现应用型人才培养的主渠道。“数据结构”是计算机专业的核心课程,在整个专业课程体系中处于承上启下的核心地位。通过分析目前“数据结构”课程教学中存在的问题,遵循“应用型课程建设七要素”,提出基于“工作过程系统化”的应用型本科院校“数据结构”课程体系教学改革,并从课程定位、课程设计、课程实施、课程考核与评价几个方面阐述了应用型教学改革实践。  相似文献   

运用数据挖掘技术预测客户购买倾向--方法与实证研究     

王萍 《情报科学》2005,23(5):738-741

商家大部促销行为，其实都是针对客户的促销，分类模型的主要功能是根据客户数据的属性将他们分派到不同的组中。本文提出利用数据挖掘技术建立客户购买意向分类模型，利用这种分类模型可以预测客户的购买倾向。  相似文献