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1.
Somayeh Fatahi Faezeh Shabanali-Fami Hadi Moradi 《Education and Information Technologies》2018,23(4):1427-1445
The learning style of a learner is an important parameter in his learning process. Therefore, learning styles should be considered in the design, development, and implementation of e-learning environments to increase learners’ performance. Thus, it is important to be able to automatically determine learning styles of learners in an e-learning environment. In this paper, we propose a sequential pattern mining approach to extract frequent sequential behavior patterns, which can separate learners with different learning styles. In this research, in order to recognize learners’ learning styles, system uses the Myers-Briggs Type Indicator’s (MBTI). The approach has been implemented and tested in an e-learning environment and the results show that learning styles of learners can be predicted with high accuracy. We show that learners with similar learning styles have similar sequential behavior patterns in interaction with an e-learning environment. A lot of frequent sequential behavior patterns were extracted which some of them have a meaningful relation with MBTI dimensions. 相似文献
2.
E-learning allows learners individually to learn “anywhere, anytime” and offers immediate access to specific information. However, learners have different behaviors, learning styles, attitudes, and aptitudes, which affect their learning process, and therefore learning environments need to adapt according to these differences, so as to increase the results of the learning process. In addition, providing the same learning content to all the learners may lead to a reduction in the learner's performance. Hence, there is a need to classify the learners based on their performance and knowledge level. Learner profiles play an important role in making the e-learning environment adaptive. Providing an adaptive learning environment, catering to the changing needs and behavior of the learner can be achieved by evolving dynamic learner profiles. Navigation logs can be used to analyze learners’ behavior over a period of time. In this work, we propose dynamic learner profiling to cater to changing learner behaviors, styles, goals, preferences, performances, knowledge level, learner's state, content difficulty, and feedbacks. Based on the continuous observation of learner preferences and requirements, the learner profile is dynamically updated. Furthermore, we propose an automatic learner classification to construct the learner profile and identify the complexity level of learning content, using the Bayesian belief network and decision tree techniques. We evaluated our system with two traditional adaptive e-learning systems, using static profiles and behavioral aspects, through our performance evaluation method of different learner types. In addition, we compared the actual learners’ data with the system generated results for various types of learners, and showed the increased interest in their learning outcomes. 相似文献
3.
Analyzing learners’ learning behaviors helps teachers understand how learning behaviors of learners influence learning performance. To determine which learning behaviors influence learners’ science-based inquiry learning performance, this work develops an xAPI (Experience Application Programming Interface)-based learning record store module embedded in a Collaborative Web-based Inquiry Science Environment (CWISE) to record detailed data about students’ learning processes. This work discusses whether the significant correlation and cause-effect relationship among science inquiry competence, learning time, and learning performance exist, and examines whether remarkable shifts and differences in the learning behaviors of learners with different learning performances and inquiry competences exist by using sequential pattern mining and lag sequential analysis. The results demonstrate that inquire ability, total learning time in the designed inquiry learning course, and learning time in an inquiry buoyancy simulation experiment are positively correlated with learning performance and can predict learning performance, and the learning time in the inquiry buoyancy simulation experiment appears to be the most significant predictor. The results of lag sequential analyses indicate that learners with high learning performance and high inquiry competence re-adjust hypotheses after performing an inquiry buoyancy simulation experiment, while learners with low learning performance and low inquiry competence lack this critical inquiry learning behavior. This study presents a systematic analysis method to insight the effective learning behaviors in a web-based inquiry learning environment based on mining students’ learning processes, thus providing potential benefits in guiding learners to adjust their learning behaviors and strategies.
相似文献4.
秦文胜 《广东轻工职业技术学院学报》2008,7(3):9-12
Web日志挖掘是利用数据挖掘技术挖掘和分析网络日志,并获取网站使用过程中的有价值的信息和模式的过程。预处理是Web日志挖掘的第一步,也是非常关键的一步,预处理的结果决定了挖掘的效率和质量。本文主要阐述了预处理的一般过程,并针对目前国内外常用的一些预处理技术进行了探讨和分析。 相似文献
5.
课堂环境下的学习行为是学习者进行知识学习的外在表现形式,对学习行为模式的识别有助于教师把握不同学习群体的特征规律,从而设计差异化教学干预方案,以改善学生的学习成效。在文献分析的基础上,文章首先以苏南某地区J中学的初中生为调查对象进行了问卷调查,并基于分析结果对课堂学习行为进行分类与编码;随后,文章采用聚类分析法对不同学习行为进行序列转换分析,并设计了基于课堂表现数据的学习行为模式识别模型;最后,文章采用滞后序列分析法对不同类型学习者的学习行为序列转换进行分析,挖掘了不同类型学习者存在的问题学习行为,在此基础上设计了基于问题学习行为的教学干预机制,以帮助学习者转换学习行为模式,进而提高学习效果。 相似文献
6.
Mojtaba Salehi Isa Nakhai Kamalabadi Mohammad Bagher Ghaznavi Ghoushchi 《Education and Information Technologies》2014,19(4):713-735
Material recommender system is a significant part of e-learning systems for personalization and recommendation of appropriate materials to learners. However, in the existing recommendation algorithms, dynamic interests and multi-preference of learners and multidimensional-attribute of materials are not fully considered simultaneously. Moreover, these algorithms cannot effectively use the learner’s historical sequential patterns of material accessing in recommendation. For addressing these problems and improving the accuracy and quality of recommendation, a new material recommender system framework based on sequential pattern mining and multidimensional attribute-based collaborative filtering (CF) is proposed. In the sequential pattern based approach, modified Apriori and PrefixSpan algorithms are implemented to discover latent patterns in accessing of materials and use them for recommendation. Leaner Preference Tree (LPT) is introduced to take into account multidimensional-attribute of materials, and learners’ rating and model dynamic and multi-preference of learners in the multidimensional attribute-based CF approach. Finally, the recommendation results of two approaches are combined using cascade, weighted and mixed methods. The proposed method outperforms the previous algorithms on the classification accuracy measures and the learner’s real learning preference can be satisfied accurately according to the real-time up dated contextual information. 相似文献
7.
Anat Cohen Udi Shimony Rafi Nachmias Tal Soffer 《British journal of educational technology : journal of the Council for Educational Technology》2019,50(1):177-198
This study explores and characterizes learners' participation patterns in MOOC forums, as well as the factors that correlate with learners' participation. Educational data mining and learning analytics methods were used to retrieve and analyze the learners' interpersonal interaction data, which had accumulated in the Coursera log files. The content in the forums was categorized based on Henri's criteria and converted into quantitative values that could be compared and visualized. It was found that only 20% of the learners were collaborating in the forums throughout the entire course and were responsible for 50% of the total posts. A portion of them earned the name “Super Active.” The analyses not only demonstrated the volume of activity and its pattern but also revealed the content of the discussions, which helped to highlight the needs and reasons for students' usage of the forums. The content analysis showed intensity in the “Cognitive” and “Discipline” categories. Thus, forum participants benefit from discussions not only socially but disciplinarily and cognitively as well. Furthermore, even though a strong significant correlation was found between the learners’ completion status and their activity in the forums, a group of learners, who did not complete the course, was highly active. 相似文献
8.
王春霞 《商丘师范学院学报》2005,21(5):71-74
在数据挖掘研究领域中，Web日志挖掘是Web使用挖掘的一个分支。它作为Web挖掘的一个重要组成部分，具有独特的理论和实践意义．通过介绍Web日志挖掘的概念，系统阐述了Web日志挖掘的全过程：数据收集、数据预处理、模式识别、实际应用．说明Web日志挖掘应用广泛，能够实现网站的优化问题． 相似文献
9.
Kumar Laxman 《Instructional Science》2011,39(6):881-900
Solving real-world problems is an effective learning activity that promotes meaningful learning in formal educational settings.
Problems can be classified as being either well structured or ill structured. Internet information search approaches have
an influential role to play in the successful performance of problem solving. A better understanding of how students differentially
model information search strategies and movements in tackling well- and ill-structured problems is essential for creating
engaging problem-solving environments for students. Static measures, such as the number of accessed nodes or links, or the
number of times particular web browser function buttons are clicked, are limited in their ability to analyze attributes of
information search patterns. A more dynamic and spatial representation of web movements and navigational patterns can be realized
through the use of navigational paths as data. The two path-specific structural metrics that can be used to assess network-based
navigational paths in relation to the structuredness of the problem-solving task are compactness and stratum. These metrics are, respectively, the indicators of the connectedness and linearity of network-based structures defining students’ online navigational visitations during the problem-solving sessions. This
study explored the relevance and utility of these two metrics in analyzing the navigational movements of learners in seeking
out electronic information to accomplish successful problem solving. The outcome findings of this study show that well- and
ill-structured problems demand different cognitive and information seeking navigational approaches. The differing values of
the two path metrics in analyzing the search movements organized by students in attending to well- and ill-structured problems
were a direct result of the contrasting patterns of navigational path movements. The search patterns associated with well-structured
problem solving tended to be more linear and less connected, whereas those related to ill-structured problem solving were
more distributed and inter-connected. 相似文献
10.
Pragya Dwivedi Vibhor Kant Kamal K. Bharadwaj 《Education and Information Technologies》2018,23(2):819-836
With the rapid advancement of information and communication technologies, e-learning has gained a considerable attention in recent years. Many researchers have attempted to develop various e-learning systems with personalized learning mechanisms for assisting learners so that they can learn more efficiently. In this context, curriculum sequencing is considered as an important concern for developing more efficient personalized e-learning systems. A more effective personalized e-learning recommender system should recommend a sequence of learning materials called learning path, in an appropriate order with a starting and ending point, rather than a sequence of unordered learning materials. Further the recommended sequence should also match the learner preferences for enhancing their learning capabilities. Moreover, the length of recommended sequence cannot be fixed for each learner because these learners differ from one another in their preferences such as knowledge levels, learning styles, emotions, etc. In this paper, we present an effective learning path recommendation system (LPRS) for e-learners through a variable length genetic algorithm (VLGA) by considering learners’ learning styles and knowledge levels. Experimental results are presented to demonstrate the effectiveness of the proposed LPRS in e-learning environment. 相似文献
11.
Drawing from social resource-social capital theory, this paper aims to clarify and characterize the role of harmonious learner–instructor and learner–learner relationships in promoting experience and retaining learners in online learning environments. Hypotheses are tested by applying a structural equation model and the data are collected from a survey of online learning website (n?=?539). The results suggest that harmonious relationships have a positive impact on learners’ experience (i.e. perceived performance, enjoyment and social presence), which, in turn, strengthen learners’ continuous intention to use the e-learning platform. And learners’ expertise moderates the relationships between harmonious relationships and learner experience. Based on the analysis results, this study can provide educational institutions with useful tactics to retain learners in the e-learning environments. 相似文献
12.
刘焕 《河北软件职业技术学院学报》2011,13(2):58-60
随着网络资源日益丰富,搜索引擎从资源的查准率上已经显得力不从心。如果能在数字学习中应用数据挖掘技术的话,必然能使学习效果事半功倍。鉴于此,针对学习者在新增学习领域或新增学习兴趣的情况下,提出基于适应性的智能型推荐学习服务系统,使学习者在学习过程中,能给予快速与准确的推荐。 相似文献
13.
Many researchers who are interested in studying students’ online self-regulated learning (SRL) have heavily relied on self-reported surveys. Data mining is an alternative technique that can be used to discover students’ SRL patterns from large data logs saved on a course management system. The purpose of this study was to identify students’ online SRL patterns with the use of data mining techniques. We examined both self-reported self-regulation surveys and log files to predict online students’ achievements and found using log files was more powerful in predicting students’ achievements in an online course than self-reported survey data. Discussions to enhance teaching and learning practices with the use of data mining are provided. 相似文献
14.
Abyaa Abir Khalidi Idrissi Mohammed Bennani Samir 《Educational technology research and development : ETR & D》2019,67(5):1105-1143
The field of adaptive e-learning is continuously developing. More research is being conducted in this area as adaptive e-learning aims to provide learners with adaptive learning paths and content, according to their individual characteristics and needs, which makes e-learning more efficient and effective. The learner model, which is a representation of different learner’s characteristics, plays a key role in this adaptation. This paper presents a systematic literature review about learner modelling during the last 5 years, describing the different modelled characteristics and the adopted modelling techniques and modeling types: automatic modeling and collaborative modeling. 107 publications were selected and analyzed, and six categories of the modelled characteristics were identified. This literature review contributes to the identification of the learners’ individual traits and presents the most used modelling techniques for each of them. It also identifies the latest research trends of Learner Modeling and generates future research directions in this field.
相似文献15.
Klaus-Dieter Schewe Bernhard Thalheim Aleksander Binemann-Zdanowicz Roland Kaschek Thomas Kuss Bernd Tschiedel 《Education and Information Technologies》2005,10(1-2):83-110
Starting from a general framework for web-based e-learning systems that is based on an abstraction layer model, this paper presents a conceptual modelling approach, which captures the modelling of learners, the modelling of courses, the personalisation of courses, and the management of data in e-learning systems. Courses are modelled by outline graphs, which are further refined by some form of process algebra. The linguistic analysis of word fields referring to an application domain helps to set up these course outlines. Learners are modelled by classifying value combinations for their characteristic properties. Each learner type gives rise to intentions as well as rights and obligations in using a learning system. Intentions can be formalised as postconditions, while rights and obligations lead to deontic constraints. The intentions can be used for the personalisation of the learning system to a learner type. Finally, the management of data in an e-learning system is approached on two different levels dealing with the content of individual learning units and the integrated content of the whole system, respectively. This leads to supporting databases and views defined on them. 相似文献
16.
无障碍网络学习环境的设计与开发流程综述 总被引：1，自引：0，他引：1
无障碍网络学习环境可以实现所有的网络学习者,包括残疾用户在内,都能够同等程度、同等水平地获取学习内容。该文首先从四个方面介绍了无障碍网络学习环境的基本特征;其次,分析与无障碍网络学习环境设计与开发有关的WCAG 1.0、Sec- tion 508和e-GIF三个技术标准;再次,具体介绍无障碍网络学习环境的设计与开发流程;最后,对无障碍网络学习环境的发展前景进行综合分析。 相似文献
17.
以教育的信息化带动教育的现代化已经成为教育领域的广泛共识。千禧年一代的学习者,是所谓＂数字土著＂的一代,伴随信息技术成长的经历,造就了他们特有的认知、态度及行为习惯;与此同时,发展学习者的创新与终身学习的能力,是时代的要求也是当前教育变革所面临的挑战。为了更有针对性地为千禧年的学习者提供基于数字技术的创新学习机会,有必要对千禧年学习者的数字土著特征进行调研,对其学习方式的特点、行为习惯以及数字技术在其学习活动中所扮演的角色进行分析,并据此找到适合千禧年学习者的、基于数字技术的创新学习方式需求,提出适合＂他们＂的学习技术。 相似文献
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混合学习强调线下课堂教学和线上自主学习的混合以实现优势互补,其中学习者的在线自我调节学习能力显得异常重要。文章旨在揭示学习者的在线自我调节学习能力存在哪些潜在类别,不同类别学习者是否具有不同的在线自我调节学习行为过程模型,以及这对于在线自我调节学习环境的设计有何启示。研究首先对239名学习者的在线自我调节学习能力进行测评,然后使用潜在剖面分析方法对测评数据进行分析,发现样本学习者可以分为高、中、低三种不同水平的自我调节学习剖面类别。然后分别对三种类别学习者的在线自我调节学习行为数据进行过程挖掘,研究发现:(1)学习者的自我调节学习能力更多体现在执行阶段的行为上;(2)中高水平自我调节学习者的在线学习行为表现出更强的认知和元认知策略;(3)高水平自我调节学习者体现出更有效的时间管理策略与更强的整体规划能力。因此,在线自我调节学习环境需要引入自适应支持机制,为学习者提供适应性的过程和策略支持。 相似文献
20.
Ioannis Kazanidis Theodosios Theodosiou Ioannis Petasakis Stavros Valsamidis 《Interactive Learning Environments》2016,24(3):472-486
Database files and additional log files of Learning Management Systems (LMSs) contain an enormous volume of data which usually remain unexploited. A new methodology is proposed in order to analyse these data both on the level of both the courses and the learners. Specifically, regression analysis is proposed as a first step in the methodology in order to explore how e-learning contents and characteristics of the course (such as a theory or lab course, a first- or second-year course, etc.) influence performance. Further investigation of each course, according to learners' usage, is achieved by archetypal analysis, which pinpoints the typical usage. The proposed methodology was successfully applied to LMS data from a Greek University. The results confirmed the validity of the approach and showed a relationship between the educational content which was provided and its usage by the learners. 相似文献