five

Does Work-Integrated Curriculum Transformation Affect Learning Experience, Student Competencies, and Learning Interactions? The Role of Teaching Strategy Moderation

收藏
Mendeley Data2024-04-17 更新2024-06-26 收录
下载链接:
https://data.mendeley.com/datasets/pvxwffxnwh
下载链接
链接失效反馈
资源简介:
Explanation of data related to the transformation of the Work Integrated Curriculum (X), Learning Experience Instrument (Y), Students' Competences Instrument (Y), Learning Interaction Instrument (Y), and Teaching Strategies Instrument (Z) may be related to collection, analysis and use data in the context of curriculum development and educational evaluation. The following is an explanation of each variable: 1. Work Integrated Curriculum Transformation (X): It refers to the process or change in an educational curriculum that incorporates work experience or practice as an integral part of a student's learning. Data associated with variable 2. Learning Experience Instrument (Y): It includes tools or methods used to measure or evaluate student learning experiences. Data associated with variable Y may include the results of surveys, questionnaires, or observations that measure students' perceptions of the quality of their learning experience. 3. Students' Competences (Y) Instrument: It refers to tools or methods used to assess or measure students' competence in various areas, such as academic skills, practical skills, or social skills. Data associated with this Y variable may include test results, projects, or student portfolios that demonstrate their level of competency. 4. Learning Interaction Instrument (Y): It refers to the tools or methods used to study or evaluate interactions between students, between students and teachers, or between students and learning materials. Data associated with variable Y might include classroom observations, analysis of group discussions, or results of interactive evaluations in learning environments. 5. Teaching Strategies Instrument (Z): This refers to the tools or methods used by teachers to teach material to students. Data associated with variable Z may include information about the types of teaching strategies used, teaching evaluation methods, or students' responses to those strategies. Collecting data related to variables X, Y, and Z can help educational institutions to measure the effectiveness of curriculum transformation, understand student learning experiences, evaluate student competency levels, analyze interactions in the learning environment, and improve teaching strategies to improve learning outcomes. Analysis of this data can provide valuable insights for better curriculum development and improving the overall quality of education.
创建时间:
2024-04-10
用户留言
有没有相关的论文或文献参考?
这个数据集是基于什么背景创建的?
数据集的作者是谁?
能帮我联系到这个数据集的作者吗?
这个数据集如何下载?
点击留言
数据主题
具身智能
数据集  4099个
机构  8个
大模型
数据集  439个
机构  10个
无人机
数据集  37个
机构  6个
指令微调
数据集  36个
机构  6个
蛋白质结构
数据集  50个
机构  8个
空间智能
数据集  21个
机构  5个
5,000+
优质数据集
54 个
任务类型
进入经典数据集
热门数据集

SAVEE

SAVEE(Surrey Audio-Visual Expressed Emotion)数据集包含480个音频和视频文件,由4名男性英语母语者在7种不同的情绪状态下录制。这些情绪包括愤怒、高兴、悲伤、惊讶、恐惧、厌恶和中性。每个文件的时长约为3秒,总时长约为24分钟。该数据集主要用于情感识别研究。

kahlan.eps.surrey.ac.uk 收录

YouTube-English

该数据集包含从各种YouTube频道提取的英语音频片段以及相应的转录元数据。数据用于训练自动语音识别(ASR)模型。数据来源于YouTube频道,处理过程包括下载、分割和保存音频及元数据。数据集总结部分详细列出了每个频道的视频数量、持续时间和占总数据集的百分比。

huggingface 收录

中国劳动力动态调查

“中国劳动力动态调查” (China Labor-force Dynamics Survey,简称 CLDS)是“985”三期“中山大学社会科学特色数据库建设”专项内容,CLDS的目的是通过对中国城乡以村/居为追踪范围的家庭、劳动力个体开展每两年一次的动态追踪调查,系统地监测村/居社区的社会结构和家庭、劳动力个体的变化与相互影响,建立劳动力、家庭和社区三个层次上的追踪数据库,从而为进行实证导向的高质量的理论研究和政策研究提供基础数据。

中国学术调查数据资料库 收录

FACED

FACED数据集是由清华大学脑与智能实验室和智能技术与系统国家重点实验室共同创建,包含从123名参与者收集的32通道EEG信号,用于情感计算研究。数据集通过记录参与者观看28个情感诱发视频片段时的EEG信号构建,旨在通过EEG信号分析情感状态。创建过程中,数据经过标准化和统一预处理,设计了四个EEG分类任务。该数据集主要应用于情感识别和脑机接口领域,旨在解决情感计算中的分类问题,提高情感识别的准确性和效率。

arXiv 收录

UIEB, U45, LSUI

本仓库提供了水下图像增强方法和数据集的实现,包括UIEB、U45和LSUI等数据集,用于支持水下图像增强的研究和开发。

github 收录