指向深度学习的信息化教育生态构建——基于联合国教科文组织亚太教育局指标体系的分析
The Construction of Ecosystem for Deep-learning Oriented Informationalized Education——Analysis Based on the Index System of the UNESCO Asia-Pacific Education Bureau
陈静静 1谈杨2
作者信息
- 1. 上海师范大学 教育学院,上海 200234
- 2. 复旦大学 管理学院,上海 200433
- 折叠
摘要
联合国教科文组织亚太教育局将教学法与信息技术的融合分为四个阶段:萌芽阶段、应用阶段、融合阶段和转型阶段.参照相关指标可以分析出我国在线教学尚处于萌芽和应用阶段,主要特征表现为:教师信息技术水平偏低,在线教学以"独白"为主;学生在线自主学习能力不足,信息技术素养有待提升;信息技术与教学的深度融合不够,需进一步形成个性化、智能化学习空间;教育体系按照传统模式运转,"以人为本"的治理生态需进一步形成.为解决这些问题,走向信息化的融合和转型发展阶段,文本基于学生深度学习需求的教育生态重构,将教师作为深度学习的设计者和创造者,学生则成为以真实问题解决为核心的协同创造者,以信息技术构建开放灵活的自主学习平台,从而构建自主自治的高质量教育公共服务体系.
Abstract
The UNESCO Asia-Pacific Education Bureau divides the integration of teaching methods and information technology into four stages:germination stage,application stage,integration stage and transformation stage.With reference to relevant indicators,it can be analyzed that online teaching in China is still in its infancy and application stage.The main features are as follows:teachers'information technology level is low,and online teaching is dominated by'monologue';students'online self-learning ability is insufficient,and information technology literacy needs to be improved;the deep integration of information technology and teaching is not enough,and personalized and intelligent learning space has not yet been formed.The education system operates according to the traditional model,and the'people-oriented'governance ecology has not yet been formed.In order to solve these problems and move towards the stage of integration and transformation of informatization,this paper reconstructs the educational ecology based on the needs of students'deep learning.Teachers are regarded as designers and creators of deep learning,and students become collaborative creators with real problem solving as the core.Information technology is used to build an open and flexible self-learning platform,so as to build an autonomous and high-quality education public service system.
关键词
在线教学/教育信息化/发展阶段/趋势预测/深度学习Key words
Online Teaching/Education Informationization/Development Stage/Trend Prediction/Deep Learning引用本文复制引用
出版年
2024