华东师范大学学报(教育科学版)

华东师范大学学报(教育科学版) ›› 2020, Vol. 38 ›› Issue (6): 1-19.doi: 10.16382/j.cnki.1000-5560.2020.06.001

• 特稿 •    下一篇

计算教育学论纲：立场、范式与体系

郑永和, 严晓梅, 王晶莹, 王杨春晓, 刘士玉   

  1. 北京师范大学教育学部，北京 100875
  • 发布日期:2020-06-23
  • 基金资助:
    中国科学院院士咨询项目“我国科学教育发展战略研究”（2018-Z10-A-025）；教育部科学事业费重大项目“教育科学研究战略基地培育”（28500/211700001）

Establishing Computational Education Subject: Position, Paradigm and System

Zheng Yonghe, Yan Xiaomei, Wang Jingying, Wang Yangchunxiao, Liu Shiyu   

  1. Faculty of Education, Beijing Normal University, Beijing 100875, China
  • Published:2020-06-23

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摘要： 大数据的涌现和智能技术的进步推动了教育实践的智能化发展及研究范式的系统性变革，使得计算教育学的产生成为必然和应然。计算主义理论研究的深化、技术的先导式发展和教育大数据的广泛应用都为计算教育学发展提供了基础保障。基于学科建构的视角，计算教育学是以量化教育数据为研究对象，以计算为主要研究方法的新兴学科。计算教育学的核心价值在于针对教育领域的真实问题的实践与应用，以及跨领域综合性研究。研究体系以计算方法为核心，研究范式已经从自上而下的量化研究转向自上而下与自下而上相结合的基于数据的教育规律探索研究。目前计算教育学形成了模拟实验与数据密集型探究共同发展的特征。鉴于目前计算教育学的知识建构相对缺乏，社会建构的规范化雏形尚未形成，需从学科理论和关键技术突破、研究范式和学科知识生成、交互环境与教学应用构建等方面构建学科知识系统化框架，从专业学会建立、人才培养计划、学术评价机制、基金项目资助等方面推动学科外在的社会建构。为推进计算教育学发展成为一门独立、新兴、面向应用的跨领域学科，还需要系统性地加强基础理论研究和实践研究，成立专业学会，建立产学研用一体化的平台，凝聚社会各界的力量推进学科发展。

关键词: 学科建制, 教育计算学, 教育大数据, 数据科学

Abstract: The emergence of big data and the development of smart technology have promoted the intelligent educational practice and the systematic change of its research paradigm. The development of computing theories, technology and big data in education laid the foundations for computational education. Based on the analysis framework of subject construction, computational education is a new subject which use computing technology on quantified educational data to explore the real problems in education. It values practices and cross-disciplinary research. It has a unique research paradigm, based on computing techniques, shifting from top-down research tradition to combined research methods. Nowadays, the main research methods include both computing simulation experiments and data-intensive scientific discovery. This paper argues that computational education still lacks knowledge construction and social construction of the subject. It then puts forward a framework for systematized construction of subject knowledge from the aspects of breakthrough in subject theory and key technologies, research paradigm and generation of subject knowledge, interactive environment and construction of teaching application, and also from the aspects of building professional societies, personnel training plans and academic evaluation. Finally, some constructional suggestions on the subject development of computational education in China are put forward. It is not limited to the development of educational research paradigm based on data science. As an independent, emerging and application-oriented interdisciplinary discipline, computational education needs to systematically strengthen basic theoretical research, applied research, establish professional societies and an integrated platform of production, learning, research and use, and gather the strength of all sectors of society to promote the development of this subject.

Key words: academic subject, computational education, educational big-data, data science