e-Learning process management and the e-learning performance: Results of a European empirical study

2010 ◽  
Vol 55 (2) ◽  
pp. 554-565 ◽  
Author(s):  
Maja Ćukušić ◽  
Nikša Alfirević ◽  
Andrina Granić ◽  
Željko Garača
Keyword(s):  
Empirical Study ◽  
Learning Process ◽  
Process Management ◽  
Learning Performance ◽  
E Learning ◽  
Performance Results

End-User Quality of Experience-Aware Personalized E-Learning

2011 ◽  
pp. 281-301
Author(s):  
Cristina Hava Muntean ◽  
Gabriel-Miro Muntean
Keyword(s):  
Learning Process ◽  
User Satisfaction ◽  
Quality Of Experience ◽  
Learning System ◽  
Learning Performance ◽  
End User ◽  
Delivery Performance ◽  
E Learning ◽  
Result Analysis

Lately, user quality of experience (QoE) during their interaction with a system is a significant factor in the assessment of most systems. However, user QoE is dependent not only on the content served to the users, but also on the performance of the service provided. This chapter describes a novel QoE layer that extends the features of classic adaptive e-learning systems in order to consider delivery performance in the adaptation process and help in providing good user perceived QoE during the learning process. An experimental study compared a classic adaptive e-learning system with one enhanced with the proposed QoE layer. The result analysis compares learner outcome, learning performance, visual quality and usability of the two systems and shows how the QoE layer brings significant benefits to user satisfaction improving the overall learning process.

scholarly journals Predicting students’ performance in e-learning using learning process and behaviour data

2022 ◽  
Vol 12 (1) ◽  
Author(s):  
Feiyue Qiu ◽  
Guodao Zhang ◽  
Xin Sheng ◽  
Lei Jiang ◽  
Lijia Zhu ◽  
...  
Keyword(s):  
Learning Process ◽  
Classification Model ◽  
Learning Performance ◽  
Good Prediction ◽  
Classification Methods ◽  
Learning Behaviour ◽  
E Learning ◽  
Learning Behaviours ◽  
Behaviour Data

AbstractE-learning is achieved by the deep integration of modern education and information technology, and plays an important role in promoting educational equity. With the continuous expansion of user groups and application areas, it has become increasingly important to effectively ensure the quality of e-learning. Currently, one of the methods to ensure the quality of e-learning is to use mutually independent e-learning behaviour data to build a learning performance predictor to achieve real-time supervision and feedback during the learning process. However, this method ignores the inherent correlation between e-learning behaviours. Therefore, we propose the behaviour classification-based e-learning performance (BCEP) prediction framework, which selects the features of e-learning behaviours, uses feature fusion with behaviour data according to the behaviour classification model to obtain the category feature values of each type of behaviour, and finally builds a learning performance predictor based on machine learning. In addition, because existing e-learning behaviour classification methods do not fully consider the process of learning, we also propose an online behaviour classification model based on the e-learning process called the process-behaviour classification (PBC) model. Experimental results with the Open University Learning Analytics Dataset (OULAD) show that the learning performance predictor based on the BCEP prediction framework has a good prediction effect, and the performance of the PBC model in learning performance prediction is better than traditional classification methods. We construct an e-learning performance predictor from a new perspective and provide a new solution for the quantitative evaluation of e-learning classification methods.

An Agent-Based Approach to Process Management in E-Learning Environments

2010 ◽  
pp. 78-91
Author(s):  
Hokyin Lai ◽  
Minhong Wang ◽  
Jingwen He ◽  
Huaiqing Wang
Keyword(s):  
Cognitive Processing ◽  
Learning Process ◽  
Process Model ◽  
Process Management ◽  
Agent Based ◽  
Expected Performance ◽  
E Learning ◽  
Quality Learning ◽  
Active Interaction

Learning is a process to acquire new knowledge. Ideally, this process is the result of an active interaction of key cognitive processes, such as perception, imagery, organization, and elaboration. Quality learning has emphasized on designing a course curriculum or learning process, which can elicit the cognitive processing of learners. However, most e-learning systems nowadays are resources-oriented instead of process-oriented. These systems were designed without adequate support of pedagogical principles to guide the learning process. They have not explained the sequence of how the knowledge was acquired, which, in fact, is extremely important to the quality of learning. This study aims to develop an e-learning environment that enables students to get engaged in their learning process by guiding and customizing their learning process in an adaptive way. The expected performance of the Agent-based e-learning Process model is also evaluated by comparing with traditional e-learning models.

A Virtual Learning Process Environment and Comparison with Conventional E-Learning Systems

2014 ◽  
pp. 107-137
Author(s):  
Ayodeji Adesina ◽  
Derek Molloy
Keyword(s):  
Learning Process ◽  
Process Management ◽  
Course Design ◽  
Virtual Learning ◽  
Learning Processes ◽  
Learning Systems ◽  
Course Materials ◽  
Complex Process ◽  
E Learning ◽  
Flexible Education

Learning is a complex process; an in-depth knowledge of the intricacies of learning processes can help to improve the formulations of effective methods, tools, and technologies to support and enhance learning through the effective management of learning processes. VLEs such as Moodle help facilitate the management of educational courses for students, in particular by helping lecturers and students with course administration. However, the management of the process of learning is inadequate. Once educational course materials are made available on the VLEs, analyses such as what students do with the course materials are difficult to observe in a real-time manner. Therefore, there is a need for the administration and management of the process of learning. This chapter presents a Virtual Learning Process Environment (VLPE) that is based on the Business Process Management (BPM) technology conceptual framework. In contrast to traditional e-learning systems, VLPE focuses on learning process management through the orchestration of flexible education pedagogies around course materials in the form of learning process workflows. Consequently, the effectiveness of any adopted pedagogy can be re-assessed, re-evaluated, and reformed by course designers with the potential to improve course design and learning outcomes.

scholarly journals Using an Intelligent Tutoring System to Support Learners’ WMC in e-learning: Application in Mathematics Learning

2018 ◽  
Vol 13 (12) ◽  
pp. 142 ◽  
Author(s):  
Bouchra El Mamoun ◽  
Mohamed Erradi ◽  
Abderrahim El Mhouti
Keyword(s):  
Academic Success ◽  
Learning Process ◽  
Mathematics Learning ◽  
Learning Performance ◽  
Educational Technologies ◽  
Mental Work ◽  
Term Memory ◽  
Learning Content ◽  
Learning Platform ◽  
E Learning

Learning is a complex process linked to a number of individual, cognitive and affective characteristics of the learner. In this context, the learner’s Working Memory (WM) concept has also been identified as a preacher of learning performance. In the learning process, solving a problem is an essential part of the learner's WM. Its capacity and performance are predictive factors of academic success. The success of the given problem depends on a good selection, processing and transformation of this information. This mental work within the WM requires a good WM Capacity (WMC). The improvement of the WMC needs some strategies which focus on the learning content and the use of educational technologies in the learning process. Encouraged by the results of previous research, this work aims to harness the potential of educational technologies to enhance the learners' WM ability in learning mathematics in an e-learning environment. In order to help learners with low WMC in e-learning, this paper proposes to set up an e-learning platform integrating an Intelligent Tutorial System (ITS). The purpose of this ITS is to manage the limited ability of the learner's WM by adopting strategies that improve the transition of mathematical knowledge from short-term memory to long-term memory. The proposed ITS generates e-learning content that will serve to improve the learner's WMC, and subsequently improve his learning performance.

A Virtual Learning Process Environment and Comparison with Conventional E-Learning Systems

2016 ◽  
pp. 839-865 ◽  
Author(s):  
Ayodeji Adesina ◽  
Derek Molloy
Keyword(s):  
Learning Process ◽  
Process Management ◽  
Course Design ◽  
Virtual Learning ◽  
Learning Processes ◽  
Learning Systems ◽  
Course Materials ◽  
Complex Process ◽  
E Learning ◽  
Flexible Education

Learning is a complex process; an in-depth knowledge of the intricacies of learning processes can help to improve the formulations of effective methods, tools, and technologies to support and enhance learning through the effective management of learning processes. VLEs such as Moodle help facilitate the management of educational courses for students, in particular by helping lecturers and students with course administration. However, the management of the process of learning is inadequate. Once educational course materials are made available on the VLEs, analyses such as what students do with the course materials are difficult to observe in a real-time manner. Therefore, there is a need for the administration and management of the process of learning. This chapter presents a Virtual Learning Process Environment (VLPE) that is based on the Business Process Management (BPM) technology conceptual framework. In contrast to traditional e-learning systems, VLPE focuses on learning process management through the orchestration of flexible education pedagogies around course materials in the form of learning process workflows. Consequently, the effectiveness of any adopted pedagogy can be re-assessed, re-evaluated, and reformed by course designers with the potential to improve course design and learning outcomes.

End-User Quality of Experience-Aware Personalized E-Learning

2008 ◽  
pp. 154-174 ◽  
Author(s):  
Cristina Hava Muntean ◽  
Gabriel-Miro Muntean
Keyword(s):  
Learning Process ◽  
User Satisfaction ◽  
Quality Of Experience ◽  
Learning System ◽  
Learning Performance ◽  
End User ◽  
Delivery Performance ◽  
E Learning ◽  
Result Analysis

Lately, user quality of experience (QoE) during their interaction with a system is a significant factor in the assessment of most systems. However, user QoE is dependent not only on the content served to the users, but also on the performance of the service provided. This chapter describes a novel QoE Layer that extends the features of classic adaptive e-learning systems in order to consider delivery performance in the adaptation process and help in providing good user perceived QoE during the learning process. An experimental study compared a classic adaptive e-learning system with one enhanced with the proposed QoE Layer. The result analysis compares learner outcome, learning performance, visual quality and usability of the two systems and shows how the QoE Layer brings significant benefits to user satisfaction improving the overall learning process.

The Role of Interactive and Synchronized Multimedia Content in E-Learning

2011 ◽  
pp. 232-250
Author(s):  
Dongsong Zhang ◽  
Lina Zhou
Keyword(s):  
Empirical Study ◽  
Knowledge Construction ◽  
Learning Systems ◽  
Learning System ◽  
Learning Performance ◽  
Multimedia Content ◽  
Significant Evidence ◽  
Learning Content ◽  
E Learning

Multimedia-based e-learning systems have become increasingly available. Many of them, however, do not provide sufficient interactivity to learners. E-learners have little control over learning content and process to meet their individual needs. Therefore, the challenges include how to integrate instructional material in different media, and how to provide flexible process control in an e-learning environment to enable personalized knowledge construction and improve learning effectiveness. We propose an e-learning system with interactive multimedia that can help learners better understand learning content and achieve comparable learning performance to that of classroom learning. The results from an empirical study provide significant evidence to support our proposition. The chapter also discusses several important issues towards building effective and sharable multimedia-based e-learning systems.

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