摘要
开展日益复杂的教育和心理学研究亟须创新数据收集和处理手段。人工智能可以帮助研究者收集具有高生态效度、动态、精准的数据,还有助于分析处理海量、多模态的数据,从而弥补传统研究手段的诸多不足。因此,教育和心理学研究与人工智能的结合是未来发展的一大方向。然而在智能化进程中也不能过度依赖数据驱动的研究方法,融合自上而下的理论驱动和自下而上的数据驱动手段至关重要。
The demand for innovative data collection and processing methods has increased due to the growing complexity of research inquiries in education and psychology.Artificial intelligence can assist researchers in precisely collecting dynamic data while achieving high ecological validity.It can also be used to analyze massive amounts of multimodal data,thereby addressing the limitations associated with traditional research methods.Consequently,integrating education,psychology,and artificial intelligence should be considered a pivotal direction for future research development.However,avoiding excessive reliance on data-driven approaches is crucial when incorporating AI into research endeavours.The fusion of top-down theory-driven approaches and bottom-up data-driven approaches holds equal importance in intelligent education and psychological research.
作者
刘冬予
骆方
LIU Dongyu;LUO Fang(The University of Hong Kong,Hong Kong 999077,China;Beijing Normal University,Bei Jing 100091,China)
出处
《中国考试》
CSSCI
北大核心
2024年第3期18-27,共10页
journal of China Examinations
基金
2023年度国家自然科学基金“面向复杂系统多目标性的形式化框架、能力测评理论及方法研究”(62377003)。
关键词
人工智能
大数据
多模态数据
机器学习
数据处理
artificial intelligence
big data
multimodal data
machine learning
data processing
