Fen Luo
Biographic Data
| ID | 6305829 |
|---|---|
| NAME | Fen Luo |
| GIVEN NAMES | Fen |
| FAMILY NAME | Luo |
| SIGNATURE | LUO F |
| AFFILIATIONS | Jiangxi Normal University |
| ORCID | 0000-0002-7338-731X |
| VERIFIED | Yes |
| TOTAL WORKS | 12 |
| TOTAL CITATIONS | 11 |
| AUTHOR COUNT | 12 |
| EDITOR COUNT | 0 |
| FIRST PUBLICATION YEAR | 2013 |
| LATEST PUBLICATION YEAR | 2024 |
| H-INDEX | 2 |
Development of Online Calibration Method based on SCAD penalty and EM perspective in CD-CAT
摘要: G-DINA (the generalized deterministic input, noisy and gate)模型限制条件少, 应用范围广, 满足大量心理与教育评估测验数据的要求。研究提出一种适用于G-DINA等模型的同时标定新题Q矩阵与项目参数的认知诊断计算机化自适应测验(CD-CAT)在线标定新方法SCADOCM, 以期促进CD-CAT在实践中的推广与应用。本研究分别基于模拟题库以及真实题库进行研究, 结果表明:相比传统的SIE方法, SCADOCM在各实验条件下均具有较为理想的标定精度与标定效率, 应用前景较好; SIE方法不适用于饱和的G-DINA等模型, 其各实验条件下的Q矩阵标定精度均较低
Young Adults’ Perception of Forests Using Landscape-Image-Sketching Technique
The forest-landscape image is the bridge for communication between human beings and the forest. The aim of this paper is to construct the landscape-image conceptual model from the personal perception of the forest, with what people are looking at and how they are viewing themselves as a part of the forest. This research constructed a forest-landscape image by young adults by utilizing the landscape-image-sketching technique and selecting 140 youn…
A Generalized Diagnostic Classification Modeling Framework Integrating Differential Speediness
To advance the theoretical foundation of incorporating response times (RTs) into diagnostic classification models (DCMs), this study attempts to further derive, test and illustrate a generalized modeling framework (known as the JVRT-LCDM) that can simultaneously analyze response accuracy and differential speediness based on an existing method (Zhan et al., British Journal of Mathematical and Statistical Psychology, 71(2), 262–286, 2018). The JVRT…
A high-efficiency and new online calibration method in CD-CAT based on information gain of entropy and EM algorithm
摘要: 项目增补(Item Replenishing)对认知诊断计算机自适应测验(CD-CAT)题库的维护有着至关重要的作用, 而在线标定是一种重要的项目增补方式。基于数据挖掘中特征选择(Feature Selection)的思路, 提出一种高效的基于熵的信息增益的在线标定方法(记为IGEOCM), 该方法利用被试在新旧题上的作答联合估计新题的Q矩阵和项目参数。研究采用Monte Carlo模拟实验验证所开发新方法的效果, 并同时与已有的在线标定方法SIE、SIE-R-BIC和RMSEA-N进行比较。结果表明:新开发的IGEOCM在各实验条件下均具有较好的项目标定精度和项目估计效率, 且整体上优于已有的SIE等方法; 同时, IGEOCM标定新题所需的时间低于SIE等方法。总之, 研究为CD-CAT题库中项目的增补提供了一种更为高效、准确的方法
The Psychological Impact of the Covid-19 Pandemic on Teenagers in China
A new dual-objective CD-CAT item selection method based on the Gini index
摘要
Changing travel patterns in China and ‘carbon footprint’ implications for a domestic tourist destination
Liujunzi Tang, a famous traditional Chinese medicine, ameliorates cigarette smoke-induced mouse model of COPD
The role of institutions in the production of space for tourism
Empirical research on construction of a measurement framework for tourism carbon emission in China
Evaluating the Consistency of Test Items Relative to the Cognitive Model for Educational Cognitive Diagnosis
摘要: 构建正确的认知模型是成功进行认知诊断的关键之一, 如果认知诊断测验不能完整准确地代表这个认知模型, 这个测验的效度就存在问题。属性及其层级可以表示一个认知模型。在认知模型正确基础上, 给出了一个计量公式以衡量认知诊断测验能够多大程度上代表认知模型; 对于不止包含一个知识状态的等价类及其形成原因进行了分析, 对Cui等人的属性层级相合性指标(HCI)提出修改建议, 以更好地探查数据与专家给出的认知模型的一致性
Dynamic and Comprehensive Item Selection Strategies for Computerized Adaptive Testing Based on Graded Response Model
摘要: 多级评分可以提供更多关于被试的信息, 是计算机化自适应测验的一个发展方向, 选题策略是计算机化自适应测验的研究重点。对于多级评分的等级反应模型, 本文拟用区间估计的思想改进近期提出的几种选题策略, 并且将两级评分b-STR和a-STR推广到多级评分以改进最大信息量选题策略。Monte Carlo模拟实验表明在达到或接近原有选题策略测验精度的基础上, 本文提出的几种新选题策略有的能够有效降低测验长度, 有的可以极大降低项目曝光率
Evaluating the Consistency of Test Items Relative to the Cognitive Model for Educational Cognitive Diagnosis
摘要: 构建正确的认知模型是成功进行认知诊断的关键之一, 如果认知诊断测验不能完整准确地代表这个认知模型, 这个测验的效度就存在问题。属性及其层级可以表示一个认知模型。在认知模型正确基础上, 给出了一个计量公式以衡量认知诊断测验能够多大程度上代表认知模型; 对于不止包含一个知识状态的等价类及其形成原因进行了分析, 对Cui等人的属性层级相合性指标(HCI)提出修改建议, 以更好地探查数据与专家给出的认知模型的一致性
Dynamic and Comprehensive Item Selection Strategies for Computerized Adaptive Testing Based on Graded Response Model
摘要: 多级评分可以提供更多关于被试的信息, 是计算机化自适应测验的一个发展方向, 选题策略是计算机化自适应测验的研究重点。对于多级评分的等级反应模型, 本文拟用区间估计的思想改进近期提出的几种选题策略, 并且将两级评分b-STR和a-STR推广到多级评分以改进最大信息量选题策略。Monte Carlo模拟实验表明在达到或接近原有选题策略测验精度的基础上, 本文提出的几种新选题策略有的能够有效降低测验长度, 有的可以极大降低项目曝光率
Empirical research on construction of a measurement framework for tourism carbon emission in China
Liujunzi Tang, a famous traditional Chinese medicine, ameliorates cigarette smoke-induced mouse model of COPD
The role of institutions in the production of space for tourism
Changing travel patterns in China and ‘carbon footprint’ implications for a domestic tourist destination
The Psychological Impact of the Covid-19 Pandemic on Teenagers in China
A new dual-objective CD-CAT item selection method based on the Gini index
摘要
A high-efficiency and new online calibration method in CD-CAT based on information gain of entropy and EM algorithm
摘要: 项目增补(Item Replenishing)对认知诊断计算机自适应测验(CD-CAT)题库的维护有着至关重要的作用, 而在线标定是一种重要的项目增补方式。基于数据挖掘中特征选择(Feature Selection)的思路, 提出一种高效的基于熵的信息增益的在线标定方法(记为IGEOCM), 该方法利用被试在新旧题上的作答联合估计新题的Q矩阵和项目参数。研究采用Monte Carlo模拟实验验证所开发新方法的效果, 并同时与已有的在线标定方法SIE、SIE-R-BIC和RMSEA-N进行比较。结果表明:新开发的IGEOCM在各实验条件下均具有较好的项目标定精度和项目估计效率, 且整体上优于已有的SIE等方法; 同时, IGEOCM标定新题所需的时间低于SIE等方法。总之, 研究为CD-CAT题库中项目的增补提供了一种更为高效、准确的方法
A Generalized Diagnostic Classification Modeling Framework Integrating Differential Speediness
To advance the theoretical foundation of incorporating response times (RTs) into diagnostic classification models (DCMs), this study attempts to further derive, test and illustrate a generalized modeling framework (known as the JVRT-LCDM) that can simultaneously analyze response accuracy and differential speediness based on an existing method (Zhan et al., British Journal of Mathematical and Statistical Psychology, 71(2), 262–286, 2018). The JVRT…
Young Adults’ Perception of Forests Using Landscape-Image-Sketching Technique
The forest-landscape image is the bridge for communication between human beings and the forest. The aim of this paper is to construct the landscape-image conceptual model from the personal perception of the forest, with what people are looking at and how they are viewing themselves as a part of the forest. This research constructed a forest-landscape image by young adults by utilizing the landscape-image-sketching technique and selecting 140 youn…
Development of Online Calibration Method based on SCAD penalty and EM perspective in CD-CAT
摘要: G-DINA (the generalized deterministic input, noisy and gate)模型限制条件少, 应用范围广, 满足大量心理与教育评估测验数据的要求。研究提出一种适用于G-DINA等模型的同时标定新题Q矩阵与项目参数的认知诊断计算机化自适应测验(CD-CAT)在线标定新方法SCADOCM, 以期促进CD-CAT在实践中的推广与应用。本研究分别基于模拟题库以及真实题库进行研究, 结果表明:相比传统的SIE方法, SCADOCM在各实验条件下均具有较为理想的标定精度与标定效率, 应用前景较好; SIE方法不适用于饱和的G-DINA等模型, 其各实验条件下的Q矩阵标定精度均较低
Computer Science (7 works) · Mathematics (6 works) · Statistics (6 works) · Artificial Intelligence (5 works) · Data mining (5 works) · Psychology (5 works) · China (4 works) · Geography (4 works) · Business (3 works) · Economics (3 works)