学生模型 meaning in English
student model
Examples
- This paper studied the implementation of pattern scheduling , including the definition of instruction pattern , the relations among instruction , student model and instruction resources , the presentation of patterns in mipits and the management of instruction pattern such as the addition , deletion and alternation . in order to break the whole control on instruction process of single instruction pattern , this paper proposed the instruction method of " globle instruction plan - instruciton pattern scheduling - local instruction plan in a certain instruction pattern " , discoursed a new knowledge model and curricula architecture model , and based on these model this paper designed the instruction plan and realized the pattern scheduling . at the same time this paper studied the software architecture of mipits , and proposed a layered model of mipits in which it can use agent technology
本文为了便于mipits系统对多种教学模式的管理，对智能教学系统中教学模式进行了定义，阐述了教学模式与学生模型、教学资源的关系以及教学模式在智能教学系统中的表示形式、系统对教学模式的管理(教学模式的增加，删除，更新等)方法，使得mipits系统能对多种教学模式进行灵活的管理；为了打破单一教学模式对整个教学过程的控制，论文提出了“全局教学规划? ?教学模式调度? ?模式内局部教学规划”的教学解决方案，阐述了一种新型的适合学生进行知识建构的知识模型和课程结构模型，并以此模型驱动教学规划的设计，并根据学生模型和教学资源的相关信息，实现了教学模式的灵活调度；由于具有多种教学模式，相对于一般的智能教学系统， mipits的体系结构发生了改智能教学系统中多种教学模式调度的研究与实现中文摘要变，论文提出了在复杂、动态和开放环境下，包括使用agent技术在内的mipits系统层次体系结构模型的解决方案:研究并解决了包括ageni在内的mipits系统各部分的协同问题，特别是复杂系统中ageni与non一ageni部分的通信协同问题。 - And the experiment has proved that the integration of instruction strategy and instruction resource based on the student model can solve the problem of the personalized organization of network - based instruction resource , which can help implement the personalized instruction on network - based instruction platform
实验表明， sarom的基于学生模型的教学策略和教学资网络教学资源自适应研究?摘要源整合能够提供个性化的网络教学资源，有助于实现网络教学平台的教学资源自适应组织。 - This model contains student model module that analyzes users ’ personalized learning requests , teacher model module that is used to distill business rules , design teaching objects and learning contents , and agent group that is assistant of accomplishing learning process containing learning content management agent , answering agent , communication agent , evaluation agent , statistical and analysis agent
该模型包括分析用户个性化学习需求的学生模型模块,提取业务规则、设计教学目标和学习内容等的教师模型模块,以及辅助完成学习过程的agent群? ?学习内容管理agent ,答疑agent ,交流agent ,评价agent和统计分析agent 。 - Based on the analysis of the learning theory and instructionual design , we understand the procedure and regulation of learning , recognizing how to improve the learning environments and instructional procedure , so our its could implement on a better pedagogy theory ; presented in xml , the subject knowledge could be more suitable to be manipulated by computer tutor , to develop an individual learning environments . auto - generating paper is a constrained multi - object optimization problem , this paper presents a way based on genetic algorithm ( ga ) to solve the problem , and discuss how to choose an individual coding to improve the efficiency of ga according the problem ; when establishing the student model , we consider the mental factor as well as the cognitive factor
基于对学习理论和教学设计的分析、总结，了解了人类学习活动的过程和内在规律，以及如何优化学习环境和教学过程，从而使智能教学系统建立在先进的教育理论基础上；基于xml技术的学科知识表示，使它更便于计算机导师进行加工，形成个性化的学习环境；自动组卷是一个带约束的多目标优化问题，本文提出通过遗传算法来解决，并分析了如何根据实际问题选择个性化的编码方案，提高遗传算法的效率；在建立学生模型时，除了考广西大学硕士论文基于web的智能教学系统的研究虑认知因素还考虑了心理因素。 - And to model the field - nonspecific information is to evaluate the accepted level of the new knowledge for students . " java tutorial " is taken as an example curriculum , which is disassembled into 298 knowledge items and the mastery of each knowledge item can be expressed into 4 levels . thereafter , partial order among these knowledge items is set up so as to ascertain the causality on bayesian networks
论文中以《 java教程》为例，将该门课程划分成298个知识项，并为每个知识项定义了四个状态来表示学生对知识项的掌握程度，然后在这些知识项之间建立偏序关系以确定贝叶斯网络的因果推理关系，最后为每个知识项确定先验概率，这样就建立了覆盖型的贝叶斯网络学生模型。