共查询到20条相似文献，搜索用时 46 毫秒
1.
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
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.
4.
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
5.
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
6.
Renuka Mahajan J. S. Sodhi Vishal Mahajan 《Education and Information Technologies》2016,21(1):123-148
An important research area in education and technology is how the learners use e-learning. By exploring the various factors and relationships between them, we can get an insight into the learners’ behaviors for delivering tailored e-content required by them. Although many tools exist to record detailed navigational activities, they don’t explore the learners’ usage patterns for an adaptive e-learning site. The previous web log data analyses, done so far, have been very limited in their scope as they lack detailed empirical results on the learning technology usage. This paper discusses the detailed results of a case study of web data mining in a specific e-learning application. The main objective of this study is to conduct research on usability and effectiveness of the e-content by analyzing the web log. For this, a suitable data set was retrieved from raw web log records, to which various web mining & statistical techniques could be applied. We have evaluated different features of e-content that can lead to better learning outcomes for the learners, by understanding their navigational behaviors, their interaction with system and their area of interest. We found, for example, what sequence of topics were the most liked and the least liked by the learners; we also found that these patterns, lead us to hypothesize, the correlation and regression analysis between the average time, test score and total attempts. 相似文献
7.
Hosam Al-Samarraie Hassan Selim Fahed Zaqout 《Interactive Learning Environments》2016,24(8):1758-1777
A model is proposed to assess the effect of different content representation design principles on learners’ intuitive beliefs about using e-learning. We hypothesized that the impact of the representation of course contents is mediated by the design principles of alignment, quantity, clarity, simplicity, and affordance, which influence the learner’s intuitive beliefs about using e-learning systems. The model was empirically validated using data collected from a survey administered to university students. This study demonstrates that these design principles are essential predictors of learners’ intuitive beliefs, which in turn directly influence their decisions about using e-learning systems. The findings provide system designers with quasi-quantitative managerial insights into how to motivate users to continue using e-learning systems. 相似文献
8.
How learners can build their own knowledge, which is precisely tailored to their needs and background? This is precisely the question to which this paper attempts to answer by providing a framework for a flexible object-based e-learning environment. The paper recognizes that the general learner modeling alternative is an intractable problem. However, it suggests learning objects construct used as building blocks to root out individual learning deficiencies. The paper also provides an algorithm to construct individual learning routes that are adjusted to learners' profile as well as an open implementation to accommodate the integration of various learning sources. 相似文献
9.
Internet evolution has affected all industrial, commercial, and especially learning activities in the new context of e-learning. Due to cost, time, or flexibility e-learning has been adopted by participators as an alternative training method. By development of computer-based devices and new methods of teaching, e-learning has emerged. The effectiveness of such programs is dependent on powerful learning management systems. In this paper, a neuro-fuzzy approach is proposed based on an evolutionary technique to obtain an optimal learning path for both instructor and learner. The neuro-fuzzy synergy allows the diagnostic model to imitate instructor in diagnosing learners’ characteristics, and equips the intelligent learning environment with reasoning capabilities. These reasoning capabilities can be used to drive pedagogical decisions based on the learning style of the learner. The neuro-fuzzy implementation helps to encode both structured and non-structured knowledge for the instructor. On the other hand, for learners, the neural network approach has been applied to make personalized curriculum profile based on individual learner requirements in a fuzzy environment. 相似文献
10.
Pierre Dillenbourg John A. Self 《European Journal of Psychology of Education - EJPE》1992,7(4):353-372
In most Interactive Learning Environments (ILEs), the human learner interacts with an expert in the domain to be taught. We explored a different approach: the system does not know more than the learner, but learns by interacting with him. A human-computer collaborative learning (HCCL) system includes a micro-world, in which two learners jointly try to solve problems and learn, the human learner and a computerized co-learner. This paper presents the foundations of this artificial co-learner. The collaboration between learners is modelled as “socially distributed cognition’ (SDC). The SDC model connects three ideas: (i) a group is a cognitive system, (ii) reflection is a dialogue with oneself, (iii) social processes are internalised. The key has been to find a computational connection between those ideas. The domain chosen for illustration is the argumentation concerning how some changes to an electoral system affect the results of elections. This argumentation involves a sequence of arguments and their refutations. The basic principle is that learners ‘store’ the structure of this argumentation (dialogue pattern) and ‘replay’ it individually later on. The verbs ‘store’ and ‘replay’ do not refer to a simple ‘record and retrieve’ process. Storage is implemented as the incremental and parameterised evolution of a network of arguments, here called a ‘dialogue pattern’. The learning outcome is a structuration of knowledge (rules) into situation-specific models, used to guide reasoning. We conducted experiments in two settings: with a human and an artificial learner or with two artificial learners. The common findings of these two experiments is that the SDC model generates learning effects provided that the discussion is intensive, i.e. that many arguments are brought into dialogue. The importance of this variable also appears in Hutchins’ (1991) modelling of the evolution of the confirmation bias in groups. It is argued than computational models are heuristic tools, allowing researchers to isolate variables for designing empirical studies with human subjects. 相似文献
11.
Insung Jung 《Educational technology research and development : ETR & D》2011,59(4):445-464
The present study was designed to identify the quality dimensions as perceived by adult learners who had taken one or more
e-learning courses offered by higher education institutions in South Korea and to identify and confirm the structural features
of these quality dimensions. The results of the exploratory factor analysis arising from a survey of 299 learners revealed
that from their perspective, there were seven dimensions in evaluating the e-learning quality: Interaction, Staff Support, Institutional Quality Assurance Mechanism, Institutional Credibility, Learner Support, Information
and Publicity and Learning Tasks. And the confirmatory factor analysis with responses obtained from another set of 496 adult learners confirmed a good fit
of the seven-factor model to the observed data. While most of these seven dimensions are supported by previous studies, some
dimensions, such as technology support, content and evaluation/assessment that e-learning providers had highlighted did not
appear to be important for Korean adult learners. Possible explanations for these findings are discussed in relation to learner
characteristics, e-learning design, and culture, and further research topics are suggested. 相似文献
12.
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
13.
“中国学习者”是国际上中国教育研究领域的新兴议题,旨在从国际和比较视野剖析中国学生群体的学习特点,为建构有中国特色的学生学习理论提供重要参考。本文通过对中国学习者研究文献的系统查阅和述评,认为本领域研究可划分为三个阶段：消极刻板评价（20世纪80年代）、破解“中国学习者悖论”（20世纪90年代）、理论探索和反思超越（21世纪初至今）。研究呈现出三个主要特点：价值取向从过于消极到过度积极再趋于客观,研究内容从学习方式向理论探索和影响因素扩展,解释视角从文化主义向教师教学等视角转变。中国研究者需要更多地参与到本领域研究中,持续加强研究的“中国立场”,展现更为真实而复杂的中国学生学习样态,提升在本领域的理论贡献水平和国际话语权,并完善研究思路以服务中国教育教学的改革。 相似文献
14.
Richard E. Snow 《教育心理学家》2013,48(3):151-158
‘'Learner control'’ refers to the proposal that learners will benefit if given more control over the pace or style of instruction they receive. It is often assumed that providing increased learner control will “accommodate”; individual differences. This article argues that such a view is naive. It is argued that research on learner control will benefit from (a) avoidance of reference to panacea, (b) basic work on a detailed taxonomy of the various forms learner control might take, and (c) a substantial review of related research which, while not labelled “learner control,”; has implications for the educational benefits that can be expected from giving learners control of certain aspects of instruction. Research examples are used to explicate these suggestions. It is concluded that no form of individualization of instruction, including learner control, has yet been shown to erase the relevance of prior individual differences to learning from instruction. 相似文献
15.
画像技术在当前精准营销中的应用非常广泛,而其在教育领域尤其是在线学习者的特征识别方面研究较少。文章从学习者的一般特征、学习准备、学习风格、行为特征四个方面对学习者进行分析,提出在线学习者画像描述的总体框架。同时,通过机器学习对在线学习行为数据进行挖掘,文章分别从以上四个方面对学习者画像进行建模研究,重点讨论了学习风格的建模过程,并通过对在线学习者个案分析,阐述了学习者画像在指导学习资源精准推荐、评估在线学习者学业失败或退出风险等方面的应用,为个性化教育实施提供了实践案例。 相似文献
16.
Heba Fasihuddin Geoff Skinner Rukshan Athauda 《Education and Information Technologies》2017,22(3):807-825
Open learning represents a new form of online learning where courses are provided freely online for large numbers of learners. MOOCs are examples of this form of learning. The authors see an opportunity for personalising open learning environments by adapting to learners’ learning styles and providing adaptive support to meet individual learner needs and preferences. Identifying learning styles of learners in open learning environments is crucial to providing adaptive support. Learning styles refer to the manner in which learners receive and perceive information. In the literature, a number of learning style models have been proposed. The Felder and Silverman Learning Styles Model (FSLSM) has been selected as the most appropriate model for open learning. In previous studies two approaches have been used to automatically identify learning styles based on the FSLSM. These approaches are known as the data-driven method and the literature-based method. In the literature, the literature-based method has been shown to be more accurate in identifying learning styles. This method relies on tracking learners’ interactions with the provided learning objects based on a set of pre-determined patterns that help in inferring learning styles. The patterns are monitored based on pre-identified threshold values. This paper aims to apply the literature-based method to open learning environments and introduce the optimal patterns and threshold values for identifying learning styles based on the FSLSM. To achieve this aim, a study was conducted whereby a prototype that simulates the open learning environment was developed and piloted on an undergraduate IT course so that learner behaviour could be tracked and data could be collected. Next, different sets of threshold values from the literature were considered along with some updated threshold values considering the context of open learning environments, and the precision of identifying learning styles was calculated. Eighty-three students participated in the study and used the developed prototype. Precision results from different threshold values presented in the literature along with customised threshold values for this study are reported and analysed in this paper. It is shown that threshold values derived from literature and customised to suit open learning environments provide a high level of accuracy in identifying learning styles. The paper presents the first study of its kind in evaluating threshold values and precision in identifying learning styles based on the FSLSM in open learning environments. The results are promising and indicate that the proposed methodology is efficient in detecting learning styles in open learning environments and useful for developing an adaptive framework. 相似文献
17.
Personalized education—the systematic adaptation of instruction to individual learners—has been a long-striven goal. We review research on personalized education that has been conducted in the laboratory, in the classroom, and in digital learning environments. Across all learning environments, we find that personalization is most successful when relevant learner characteristics are measured repeatedly during the learning process and when these data are used to adapt instruction in a systematic way. Building on these observations, we propose a novel, dynamic framework of personalization that conceptualizes learners as dynamic entities that change during and in interaction with the instructional process. As these dynamics manifest on different timescales, so do the opportunities for instructional adaptations—ranging from setting appropriate learning goals at the macroscale to reacting to affective-motivational fluctuations at the microscale. We argue that instructional design needs to take these dynamics into account in order to adapt to a specific learner at a specific point in time. Finally, we provide some examples of successful, dynamic adaptations and discuss future directions that arise from a dynamic conceptualization of personalization.
相似文献18.
Swarm intelligence approaches, such as ant colony optimization (ACO), are used in adaptive e-learning systems and provide an effective method for finding optimal learning paths based on self-organization. The aim of this paper is to develop an improved modeling of adaptive tutoring systems using ACO. In this model, the learning object is personalized based on learning and solving problem styles. The purposed algorithm, based on ACO, generates the adaptive optimal learning path. The algorithm describes an architecture which supports the recording, processing and presentation of collective learner behavior designed to create a feedback loop informing learners of successful paths towards the attainment of learning goals. The algorithm parameters are tuned dynamically to conform to the actual pedagogical process. The article includes the results of implementation and experiment represent this algorithm is able to provide its main purpose which is finding optimal learning paths based on learning styles and improved performance of previous adaptive tutoring systems. 相似文献
19.
A vast body of research has indicated the importance of distinguishing new vs. continuing students’ learning experiences in blended and online environments. Continuing learners may have developed learning and coping mechanisms for ‘surviving’ in such learning environments, while new learners might still need to adjust their learning approaches to the new learning context. In this large-scale replication study, we investigated whether and how the learning satisfaction experiences of 16,670 new vs. 99,976 continuing students were different. Using logistical regression modelling of learner satisfaction scores of 422 undergraduate blended and online modules (including 232 learner and module learning design variables), our findings indicated that new learners indeed differed subtly in their learning and teaching experiences across two consecutive academic years. The minor differences in key drivers between the 2014 and 2015 cohorts also indicate that institutions need to continuously monitor and act upon changing learning needs. 相似文献
20.
Supachanun Wanapu Chun Che Fung Nittaya Kerdprasop Nisachol Chamnongsri Suphakit Niwattanakul 《Education and Information Technologies》2016,21(5):1113-1134
The issues of accessibility, management, storage and organization of Learning Objects (LOs) in education systems are a high priority of the Thai Government. Incorporating personalized learning or learning styles in a learning object management system to improve the accessibility of LOs has been addressed continuously in the Thai education system. A proposed Learning Object Management Model (LOMM) is discussed in this paper which aims to adapt and optimize the learning process based on characteristics of the individual learners. This study aims to find the correlation between learning styles and LOs characteristics in the LOMM. Decision Tree and Apriori algorithms were used to generate a predictive model for the classification of learners. Development of the predictive model was based on survey results from 1,586 high school students in Nakhon Ratchasima province, Thailand. The diverse LOs characteristics were analyzed in order to find the correlation with learning styles of the learners. The classification model consists of 24 sub-models used to predict a learner’s class based on 8 groups of LOs characteristics. The best accuracy obtained in the study was 80.23%. Finally, for the next phase this approach has been designed to support the proposed LOMM and it is expected that it could be readily applied to other e-learning systems and digital repositories. 相似文献