基于网络的自适应超媒体学习支持系统的研究

针对现有网络学习支持系统不能很好满足学习者个性化学习的需要,我院构建了基于网络的自适应超媒体学习支持系统模型,它是在现有的网络学习支持系统上增加了自适应交互处理模块、自适应教学处理模块、本体推理模块和规则推理模块。本文详细探讨了此模型的自适应支持功能,如为学习者创设动态的自适应学习环境,提供自适应的导航系统和自适应的内容支持等,并给出了自适应学习处理过程。     

基于大数据分析的计算机网络课程自适应学习系统构建

大数据时代数字化的学习资源将呈现爆炸式的增长,面对海量的学习资源,学习者如何选择,或者如何向学习者推送合适的学习资源将成为未来面临的主要问题。针对计算机网络课程授课内容多、知识更新快的问题,通过收集教育过程中的学习行为数据,利用大数据的学习分析技术构建了一个计算机网络自适应学习系统,该系统包含自适应、预测、干预等六大模块,可以针对性地推送学习内容,及时反馈学习者的学习效果,并推荐下一步的学习策略,从而达到因材施教和培养学生自主学习能力的效果。     

基于Bayesian Network的学习资源库推荐系统构建与实现

针对学习资源使用者的特点和当前网络学习模型的不足,提出运用贝叶斯网络建立一种个性化学习者模型。基于用户决策方案指导资源库的建设,提出了一种新的学习资源推荐算法,使学习资源的呈现符合学习者认知发展水平和个性特征,改善资源库的组织结构,实现智能化、个性化的学习资源库推荐系统。实践证明,对于本系统所推荐的学习资源,学习者非常满意。     

概念图智能匹配机制用于支持个性化网络学习

针对个性化网络学习平台中往往只关注学习者学习风格而忽略对学习者认知能力培养的问题提出一种基于概念图的方法对学习者认知能力进行形式化描述。采用自然语言处理及潜在语义分析方法构建基于学习者行为的学习者概念图及领域知识概念图,提出一种基于最大共同子图的匹配算法计算学习者概念图与领域知识概念图之间的相似度,提取学习者的个性化知识缺失、还需要掌握的知识,并以可视化形式呈现一定知识目标领域内学习者的已有知识及需要掌握的知识。实验结果表明,基于概念图的个性化网络学习能够促进学习者及时纠正、完善知识点的理解缺陷,培养学习者的认知能力。     

基于学习对象的内容包装交换模型构建研究

随着现代教育技术的迅猛发展和构建学习型社会需求的不断提高,远程教育为学习者构建了一个适合接受终身教育的学习环境。但是,当前网络学习资源的共享性、可重用性,以及对自适应学习的支持上还尚存众多的问题,这已严重地制约了网络教育快速发展。基于此,该文采用SCORM标准,以学习对象为学习内容组织单位,将学习资源划分为数字资源对象、可共享内容对象和应用数字对象三种组件,对学习资源模型进行封装,为其构建元数据文件、内容清单文件和包交换文件,实现学习内容在不同网络教学系统间的共享和重用,以及可以根据学习者特征、学习需求与学习目的对学习内容和学习路径进行动态调整,从而实现网络自适应学习,提高远程教育的服务质量和学习者的满意度。     

面向网络学习的学习者个性挖掘研究

提出了一种面向个性化网络学习的学习者个性挖掘(Personality mining)及自适应学习策略生成的解决思路,即：通过对样本学习者的个性调查和学习行为模式的分析,挖掘出“行为模式-个性-学习策略”三者之间的关联关系,并据此实现学习者个性的自动获取与自适应学习策略的生成,为学习者提供网络学习的策略推荐。     

网络环境下自适应学习系统研究

针对网络环境下自适应学习系统发展中遇到的新问题,如学习者个性特征的挖掘及自适应学习策略的生成等,提出了一种新的自适应学习系统,即在建立个性化学习者模型的基础上,进一步研究相应的数据挖掘算法在自适应学习中的应用,得到学习者的个性特征与学习行为之间的关联规则,并最终生成自适应的学习策略提供给学习者;仿真研究表明,本系统设计先进,较好地实现了学习过程的自适应性。     

自适应算法在网络学习系统的应用研究

随着现代信息技术与教育产业的深度融合,建设远程开放式的网络学习平台已成为构建智慧校园网的核心;同时也为构建学习型社会,实现终身教育提供了环境支撑和技术保障。主要着手于自适应算法研究,以网络学习者为对象,针对网络学习平台中存在的问题,设想将自适应算法引入到网络学习平台中,设计一个包含自适应网络学习模型、学习者信息模型、智能学习诊断模型的网络学习系统。以期系统能够有效地完善现有网络学习在动态导航、智能诊断、师生交互、因材施教等方面存在的不足,并从根本上改变传统按部就班式的学习模式,实现将资源按照学习者的个体特征和学习需求自动地生成学习内容序列,从而实现个性化的学生学习与教师辅导,以此来提升远程教育的服务质量。     

基于机器学习的英语词汇自适应学习模型

研发一个实现机器学习算法的英语词汇自适应学习模型,该模型记录了学习者对学习内容自我选择的情况,进而反映出学习者的个性差异.同时,作为一种动态建模学习工具,其关键参数是条件概率,用于测量学习者某个认知特征对某种学习内容的适应性关系,因此将该参数称为适应度.学习者每次对一个单词完成学习内容的自我选择,适应度随之更新一次,视为一次训练;通过训练,不断调整适应度,修改和维护模型自身.模型将所要解决的问题抽象为一系列数学公式,公式参考了AdaBoost算法公式;模型的求解流程参照了基于项目反应理论的自适应测验过程.本模型能够持续迭代适应度直至稳定,最终推送出与他相适应的学习内容.文章首先介绍国内外相关研究及选题价值,接着阐述模型的理论依据,继而重点论述模型的构建,最后给予例证.     

适应性超媒体技术：网络学习中个体差异影响之解决策略

网络学习为学习者的认知过程带来各种便利的同时,也为部分学习者带来了学习的障碍。随着网络学习的进一步推广,个体差异对于网络学习的影响逐渐受到重视,如何提高网络学习的适应性成为当前研究的热点问题。本文从提高网络学习的适应性这一需求出发,分析适应性超媒体技术在网络学习中的应用。     

Learning programming via worked-examples: Relation of learning styles to cognitive load

This paper describes an experiment that compared learners with contrasting learning styles, Active vs. Reflective, using three different strategies for learning programming via worked-examples: Paired-method, Structure-emphasising, and Completion. The quality of the learners’ acquired cognitive schemata was assessed in terms of their post-test performance. The experiment investigated variations in learners’ cognitive load, taking both the learning strategies and the learners’ learning styles into account. Overall, the results of the experiment were inconsistent. In comparing the effects of the strategies during the learning phase, the study found significant differences in cognitive load. Unexpectedly, no differences were then detected either in cognitive load or in performance during the post-test (post-test). In comparing the effects of the learning styles during the learning phase and the transfer phase, medium effect sizes suggested that learning style may have had an effect on cognitive load. However, no significant difference was observed in performance during the post-test.     

Web-based learning programs: Use by learners with various cognitive styles

To consider how Web-based learning program is utilized by learners with different cognitive styles, this study presents a Web-based learning system (WBLS) and analyzes learners’ browsing data recorded in the log file to identify how learners’ cognitive styles and learning behavior are related. In order to develop an adapted WBLS, this study also proposes a design model for system designers to tailor the preferences linked with each cognitive style. The samples comprise 105 third-grade Accounting Information System course students from a technology university in central Taiwan. Analytical results demonstrate that learners with different cognitive styles have similar but linear learning approaches, and learners with different cognitive styles adopt different navigation tools to process learning.     

Self-directed learning in simulation-based discovery environments

SIMQUEST is an authoring system for designing and creating simulation-based learning environments. The special character of SIMQUEST learning environments is that they include cognitive support for learners which means that they provide learners with support in the discovery process. In SIMQUEST learning environments, a balance is sought between direct guidance of the learning process and sufficient freedom for learners to regulate the learning process themselves. This paper describes the basic mechanisms of the SIMQUEST learning and authoring environments. The functionality authors have in providing the learner with guidance and some of the experiences on how authors use these opportunities and learners employ the cognitive support are reported.     

Superiority of collaborative learning with complex tasks: A research note on an alternative affective explanation

Kirschner, Paas, and Kirschner (2009c) used the theoretical framework of cognitive load to explain why the learning of a group of collaborating individuals was more efficient than that of individuals learning alone with high-complexity tasks but not with low-complexity tasks. The authors argued that collaboration circumvented the limitations of an individual’s working memory by creating an expanded cognitive capacity and by allowing for the distribution of cognitive load among group members. Inspired by research on efficacy, this study explored an alternative affective explanation of the results. By measuring the amount of mental effort learners expected to invest in working on a learning task before actually carrying out the task, this study showed that learners who had to collaboratively solve a high-complexity problem expected to invest less mental effort than learners who had to solve the problem alone. When confronted with low-complexity tasks, the expected amount of mental effort did not differ.     

Towards an Online Continuous Adaptation Mechanism (OCAM) for Enhanced Engagement: An EEG Study

ABSTRACT

Individual preferences for learning environments can be linked to a specific behavior. The tendency of such behavior can somehow be associated with an individual’s ability to cognitively engage in the learning process without being distracted by other stimuli. An online continuous adaptation mechanism (OCAM) of learning contents was developed in order to regulate the presentation of learning contents based on changes in the learner’s aptitude level. This was claimed to stimulate a better cognitive and emotional response among learners, thus stimulating their engagement. A total of 41 students (36 male and 5 female; age 20–25 years) participated in this study. The results revealed that learners’ levels of concentration and cognitive load were positively influenced by the OCAM, which significantly increased their engagement. Our findings can be used to inform designers and developers of online learning systems about the importance of regulating the presentation of learning contents according to the aptitude level of individual learners. The proposed OCAM can improve learners’ ability to process specific information meaningfully and make the inferences necessary for understanding the learning content.     

The relationship between learning styles and cognitive traits – Getting additional information for improving student modelling

Student modelling is an important process for adaptive virtual learning environments. Student models include a range of information about the learners such as their domain competence, learning style or cognitive traits. To be able to adapt to the learners’ needs in an appropriate way, a reliable student model is necessary, but getting enough information about a learner is quite challenging. Therefore, mechanisms are needed to support the detection process of the required information. In this paper, we investigate the relationship between learning styles, in particular, those pertaining to the Felder–Silverman learning style model and working memory capacity, one of the cognitive traits included in the cognitive trait model. The identified relationship is derived from links between learning styles, cognitive styles, and working memory capacity which are based on studies from the literature. As a result, we demonstrate that learners with high working memory capacity tend to prefer a reflective, intuitive, and sequential learning style whereas learners with low working memory capacity tend to prefer an active, sensing, visual, and global learning style. This interaction can be used to improve the student model. Systems which are able to detect either only cognitive traits or only learning styles retrieve additional information through the identified relationship. Otherwise, for systems that already incorporate learning styles and cognitive traits, the interaction can be used to improve the detection process of both by including the additional information of a learning style into the detection process of cognitive traits and vice versa. This leads to a more reliable student model.     

Learning styles and cognitive traits – Their relationship and its benefits in web-based educational systems

Different learners have different needs; they differ, for example, in their learning goals, their prior knowledge, their learning styles, and their cognitive abilities. Adaptive web-based educational systems aim to cater individual learners by customizing courses to suit their needs. In this paper, we investigate the benefits of incorporating learning styles and cognitive traits in web-based educational systems. Adaptivity aspects based on cognitive traits and learning styles enrich each other, enabling systems to provide learners with courses which fit their needs more accurately. Furthermore, consideration of learning styles and cognitive traits can contribute to more accurate student modelling. In this paper, the relationship between learning styles, in particular the Felder–Silverman learning style model (FSLSM), and working memory capacity, a cognitive trait, is investigated. For adaptive educational systems that consider either only learning styles or only cognitive traits, the additional information can be used to provide more holistic adaptivity. For systems that already incorporate both learning styles and cognitive traits, the relationship can be used to improve the detection process of both by including the additional information of learning style into the detection process of cognitive traits and vice versa. This leads to a more reliable student model.     

Environmental support hypothesis in designing multimedia training for older adults: Is less always more?

This study explores younger and older adults learning of MS Publisher functionalities from a multimedia tutorial. Twenty younger and twenty three older adults assigned to a redundant (experimental) or non-redundant (control) condition were taught how to create a greeting card, while the results of their learning were assessed with immediate and delayed performance measures. While younger learners benefited from a non-redundant condition, older learners exhibited an opposite trend. Redundant condition was beneficial for their performance efficiency on a set of a transfer tasks, and their troubleshooting performance during the delayed session. From a cognitive load perspective, using a redundant text along with an audio narration overloads learner’s working memory by placing more strain on the visual pathway and not providing any additional cognitive advantage. From an environmental support standpoint and decreased processing resources view of cognitive aging, providing additional representational support helps reducing the task demands for older adults and results in better learning. The results have cognitive and practical implications for the design of multimedia learning environments for older adults.     

Learning with desktop virtual reality: Low spatial ability learners are more positively affected

This study aims to verify the learning effectiveness of a desktop virtual reality (VR)-based learning environment, and to investigate the effects of desktop VR-based learning environment on learners with different spatial abilities. The learning outcome was measured cognitively through academic performance. A quasi pretest–posttest experimental design was employed for this study. A total of 431 high school students from four randomly selected schools participated in this study where they were randomly assigned to either experimental or control groups based on intact classes. Findings indicate a significant difference in the performance achievement between the two groups with students performed better using desktop virtual reality. A possible explanation is that the desktop virtual reality instructional intervention has helped to reduce extraneous cognitive load and engages learners in active processing of instructional material to increase germane cognitive load. A significant interaction effect was found between the learning mode and spatial ability with regard to the performance achievement. Further analysis shows a significant difference in the performance of low spatial ability learners in the experimental and control groups, but no statistically significant difference in the performance of high spatial learners in both groups. The results signify that low spatial ability learners' performance, compared with high spatial ability learners, appeared to be more positively affected by the desktop VR-based learning environment which is supported by the ability-as-compensator hypothesis, and can be explained by the cognitive load theory.     

Is single or dual channel with different English proficiencies better for English listening comprehension,cognitive load and attitude in ubiquitous learning environment?

The purpose of the present study was to examine the effects of English proficiency (low vs. high) and material presentation mode (single channel vs. dual channel) on English listening comprehension, cognitive load and learning attitude in a ubiquitous learning environment. An experimental learning activity was implemented using PDA as a learning tool to facilitate learning. A quasi-experimental design was employed with university students participating in the experiment. The results revealed that (a) high English proficiency learners had significantly better English listening comprehension and lower intrinsic and extraneous load than low English proficiency learners; (b) both high and low English proficiency learners learning with dual channel had significantly better English listening comprehension and held more positive attitude toward the ubiquitous learning environment than learners learning with single channel; (c) for learners learning with single channel, low English proficiency learners had significantly higher extraneous load than high English proficiency learners; and (d) for low English proficiency learners, learners who learned with dual channel possessed significantly lower extraneous load than learners who learned with single channel. The suggestions for educators and instructional designers were also discussed in the present study.