智能学习系统中作业习惯建模研究  

Study on Modeling of Homework Habits in Intelligent Learning System

作　　者：殷宝媛[1] 武法提 YIN Baoyuan;WU Fati(School of Educational Science,Harbin Normal University,Harbin Heilongjiang 150080;Engineering Research Center of Digital Learning and Education Public Service Ministry of Education,Beijing 100875)

机构地区：[1]哈尔滨师范大学教育科学学院,黑龙江哈尔滨150080 [2]数字学习与教育公共服务教育部工程研究中心,北京100875

出　　处：《电化教育研究》2021年第7期61-67,共7页E-education Research

基　　金：教育部人文社会科学研究青年基金项目“互联网+教育背景下学生学习习惯的测评模型研究”(项目编号:18YJC880109)。

摘　　要：作业习惯与学习者的学业成就紧密相关,作业习惯的建模是智能学习系统设计中亟待解决的问题。本研究应用混合式研究方法,依据多层次作业模型,确定“学业拖延”和“学业勤奋”作为两个重要且可以测量的作业习惯的维度,分别表征作业时间和作业努力这两类核心的作业行为。构建了包括做题拖延和提交拖延的学业拖延习惯子模型,应用聚类实现了对学业拖延习惯的诊断,定义了“无拖延习惯者”“严重拖延习惯者”“提交作业拖延者”“做作业拖延者”四类学习者。以时间投入—专注度模型为理论框架,构建了包括时间投入和专注度的学业勤奋习惯子模型,应用人工神经网络实现对学业勤奋习惯进行诊断,诊断出五种勤奋度的级别,并验证了模型的有效性。Homework habits are closely related to learners'academic achievement and the modeling of homework habits is an urgent problem in the design of intelligent learning system.Based on a multi-level homework model,this study adopts a hybrid research approach to identify"academic procrastination"and"academic diligence"as two important and measurable dimensions of homework habits,which represent the two core types of homework behaviors:homework time and homework effort.A sub-model of academic procrastination habits is constructed,including procrastination in doing and submitting.Clustering is applied to diagnose the habit of academic procrastination,and four types of learners are defined as"non-procrastinators","severe procrastinators","procrastinators in submitting"and"procrastinators in doing".Based on the theoretical framework of time investment and focus model,a sub-model of academic diligence habits including time investment and focus is constructed.The artificial neural network is used to diagnose the academic diligence habits,as a result,five levels of diligence are diagnosed,and the validity of the model is verified.

关 键 词：学习习惯 作业习惯 学业拖延 学业勤奋 智能学习系统 建模 

分 类 号：G434[文化科学—教育学]