With the popularity of e-learning,personalization and ubiquity have become important aspects of online learning.To make learning more personalized and ubiquitous,we propose a learner model for a query-based personaliz...With the popularity of e-learning,personalization and ubiquity have become important aspects of online learning.To make learning more personalized and ubiquitous,we propose a learner model for a query-based personalized learning recommendation system.Several contextual attributes characterize a learner,but considering all of them is costly for a ubiquitous learning system.In this paper,a set of optimal intrinsic and extrinsic contexts of a learner are identified for learner modeling.A total of 208 students are surveyed.DEMATEL(Decision Making Trial and Evaluation Laboratory)technique is used to establish the validity and importance of the identified contexts and find the interdependency among them.The acquiring methods of these contexts are also defined.On the basis of these contexts,the learner model is designed.A layered architecture is presented for interfacing the learner model with a query-based personalized learning recommendation system.In a ubiquitous learning scenario,the necessary adaptive decisions are identified to make a personalized recommendation to a learner.展开更多
为解决传统多元线性回归(Multivariate linear regression,MLR)模型在煤炭发热量预测方面精度不足和适用性有限的问题,提出了一种基于改进自适应增强算法(Adaptive boosting,Adaboost)的煤发热量的预测模型。将随机森林(Random forest,...为解决传统多元线性回归(Multivariate linear regression,MLR)模型在煤炭发热量预测方面精度不足和适用性有限的问题,提出了一种基于改进自适应增强算法(Adaptive boosting,Adaboost)的煤发热量的预测模型。将随机森林(Random forest,RF)作为Adaboost的基学习器,以提高模型在工业煤质分析中的发热量预测精度和泛化能力。研究基于某电厂1万组入炉煤的工业分析数据,选取水分、挥发分、灰分和固定碳作为模型输入,建立煤炭低位发热量的预测模型。通过与传统的多元线性回归方程及其他非线性模型比较,模型展现出更高的预测精度和更好的泛化能力。大样本测试的实验结果表明,本模型的平均绝对百分比误差为0.5417%,均方根误差为0.1304 MJ/kg,拟合度(R^(2))达到0.9799,其在煤炭发热量预测方面优于其他模型。此外,200组真实的混煤工业分析数据的模拟验证,进一步确认了本模型较优的泛化性能。展开更多
为了清晰梳理并准确把握国际“学习者建模”领域的研究热点与脉络,以Web of Science核心期刊数据库2013-2022年间有关“学习者建模”的载文为研究对象,借助CiteSpace等可视化分析软件,对其进行文献计量分析和知识图谱分析。结果表明:“...为了清晰梳理并准确把握国际“学习者建模”领域的研究热点与脉络,以Web of Science核心期刊数据库2013-2022年间有关“学习者建模”的载文为研究对象,借助CiteSpace等可视化分析软件,对其进行文献计量分析和知识图谱分析。结果表明:“学习者建模”研究在过去10年呈现从平稳发展到急剧上升的趋势;美国、澳大利亚和英国在该研究领域起步较早且持续时间较长,中国则在近3年迈开了研究的步伐;IEEE Access是“学习者建模”领域发文量较多的期刊;研究作者、研究机构之间合作偏少;研究热点主要集中在数据训练、智能导师系统、机器学习、人工智能和学习分析等5个方面;过去10年间“学习者建模”研究分为两个阶段,2013-2019年间热点研究为智能导师系统中学习者模型的构建和应用,2019年至今的前沿热点研究是深度学习在“学习者建模”中的应用。在未来研究中可以重点关注以下方面:“学习者建模”领域要加强技术研究和应用研究合作,形成一个良好的合作循环;研究团队互相间要加强合作,要能够跨领域、交叉学科地进行更深一步的交流;继续聚焦新兴技术,将其应用于学习者建模;在大数据和深度学习技术研究不断深入的过程中,要注意数据安全和隐私问题。展开更多
With the advent of computing and communication technologies,it has become possible for a learner to expand his or her knowledge irrespective of the place and time.Web-based learning promotes active and independent lea...With the advent of computing and communication technologies,it has become possible for a learner to expand his or her knowledge irrespective of the place and time.Web-based learning promotes active and independent learning.Large scale e-learning platforms revolutionized the concept of studying and it also paved the way for innovative and effective teaching-learning process.This digital learning improves the quality of teaching and also promotes educational equity.However,the challenges in e-learning platforms include dissimilarities in learner’s ability and needs,lack of student motivation towards learning activities and provision for adaptive learning environment.The quality of learning can be enhanced by analyzing the online learner’s behavioral characteristics and their application of intelligent instructional strategy.It is not possible to identify the difficulties faced during the process through evaluation after the completion of e-learning course.It is thus essential for an e-learning system to include component offering adaptive control of learning and maintain user’s interest level.In this research work,a framework is proposed to analyze the behavior of online learners and motivate the students towards the learning process accordingly so as to increase the rate of learner’s objective attainment.Catering to the demands of e-learner,an intelligent model is presented in this study for e-learning system that apply supervised machine learning algorithm.An adaptive e-learning system suits every category of learner,improves the learner’s performance and paves way for offering personalized learning experiences.展开更多
As increasingly large number of Chinese students study abroad,Chinese students'classrooms behavious have captured attention.In addition to analyzing the factors affecting the learners'willingness to communicat...As increasingly large number of Chinese students study abroad,Chinese students'classrooms behavious have captured attention.In addition to analyzing the factors affecting the learners'willingness to communicate(WTC) in second language(L2),the paper also aims to examine validity of the heuristic model of MacIntyre et al.(1998) in this particular context.Results show that interlocutor,topic and conversational context are the three main situational variables found to affect the Chinese learners'L2 WTC.展开更多
基金This work was supported by the College of Computer and Information Sciences,Prince Sultan University,Saudi Arabia.
文摘With the popularity of e-learning,personalization and ubiquity have become important aspects of online learning.To make learning more personalized and ubiquitous,we propose a learner model for a query-based personalized learning recommendation system.Several contextual attributes characterize a learner,but considering all of them is costly for a ubiquitous learning system.In this paper,a set of optimal intrinsic and extrinsic contexts of a learner are identified for learner modeling.A total of 208 students are surveyed.DEMATEL(Decision Making Trial and Evaluation Laboratory)technique is used to establish the validity and importance of the identified contexts and find the interdependency among them.The acquiring methods of these contexts are also defined.On the basis of these contexts,the learner model is designed.A layered architecture is presented for interfacing the learner model with a query-based personalized learning recommendation system.In a ubiquitous learning scenario,the necessary adaptive decisions are identified to make a personalized recommendation to a learner.
文摘为了清晰梳理并准确把握国际“学习者建模”领域的研究热点与脉络,以Web of Science核心期刊数据库2013-2022年间有关“学习者建模”的载文为研究对象,借助CiteSpace等可视化分析软件,对其进行文献计量分析和知识图谱分析。结果表明:“学习者建模”研究在过去10年呈现从平稳发展到急剧上升的趋势;美国、澳大利亚和英国在该研究领域起步较早且持续时间较长,中国则在近3年迈开了研究的步伐;IEEE Access是“学习者建模”领域发文量较多的期刊;研究作者、研究机构之间合作偏少;研究热点主要集中在数据训练、智能导师系统、机器学习、人工智能和学习分析等5个方面;过去10年间“学习者建模”研究分为两个阶段,2013-2019年间热点研究为智能导师系统中学习者模型的构建和应用,2019年至今的前沿热点研究是深度学习在“学习者建模”中的应用。在未来研究中可以重点关注以下方面:“学习者建模”领域要加强技术研究和应用研究合作,形成一个良好的合作循环;研究团队互相间要加强合作,要能够跨领域、交叉学科地进行更深一步的交流;继续聚焦新兴技术,将其应用于学习者建模;在大数据和深度学习技术研究不断深入的过程中,要注意数据安全和隐私问题。
文摘With the advent of computing and communication technologies,it has become possible for a learner to expand his or her knowledge irrespective of the place and time.Web-based learning promotes active and independent learning.Large scale e-learning platforms revolutionized the concept of studying and it also paved the way for innovative and effective teaching-learning process.This digital learning improves the quality of teaching and also promotes educational equity.However,the challenges in e-learning platforms include dissimilarities in learner’s ability and needs,lack of student motivation towards learning activities and provision for adaptive learning environment.The quality of learning can be enhanced by analyzing the online learner’s behavioral characteristics and their application of intelligent instructional strategy.It is not possible to identify the difficulties faced during the process through evaluation after the completion of e-learning course.It is thus essential for an e-learning system to include component offering adaptive control of learning and maintain user’s interest level.In this research work,a framework is proposed to analyze the behavior of online learners and motivate the students towards the learning process accordingly so as to increase the rate of learner’s objective attainment.Catering to the demands of e-learner,an intelligent model is presented in this study for e-learning system that apply supervised machine learning algorithm.An adaptive e-learning system suits every category of learner,improves the learner’s performance and paves way for offering personalized learning experiences.
文摘As increasingly large number of Chinese students study abroad,Chinese students'classrooms behavious have captured attention.In addition to analyzing the factors affecting the learners'willingness to communicate(WTC) in second language(L2),the paper also aims to examine validity of the heuristic model of MacIntyre et al.(1998) in this particular context.Results show that interlocutor,topic and conversational context are the three main situational variables found to affect the Chinese learners'L2 WTC.
