System Approach to Information Open Learning System Design

The Open Educational Resource (OER) movement has reached its tipping point in recent years due to advancement of technologies. The OpenCourseWare (OCW) of MIT, for instance, has inspired higher education institutions around the world to deploy OCW systems that provide educational contents free of charge to lifelong learners. In Taiwan, the Opensource Opencourse Prototype System (OOPS; www.myoops.org) plays a significant role in enabling Chinese-speaking learners to benefit from this global movement. Although OOPS has attracted hundreds of thousands of users with open courses translated into Chinese, understanding who these users are and why they chose this particular venue to advance their informal and lifelong learning remains elusive. As a result, the OOPS and other compatible open courseware portals around the world are often challenged by issues related to user engagement that could ultimately determine the sustainability of any open courseware portals. From the perspective of learning system design, it is impossible to develop and deploy effective user engagement strategies without knowing who the users are and what drive them to use the open learning system. To address this issue, this chapter, informed by open courseware users’ feedback, proposes a game-based learning approach situated in virtual worlds to improve and sustain user engagement in open learning environments.

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Value-Satisfaction Grid of E-Learning Systems

Assessing the Value of E-Learning Systems ◽

10.4018/978-1-59140-726-3.ch005 ◽

2006 ◽

pp. 116-122

Author(s):

Yair Levy

Keyword(s):

System Approach ◽

Two Dimensions ◽

Learning Systems ◽

Learning System ◽

Assessment Tools ◽

Mediated Learning ◽

Perceived Effectiveness ◽

E Learning ◽

Significant Achievement ◽

Complete Set

This chapter provides the rationale of the first of three tools suggested in this book to assess value and satisfaction of e-learning systems in order to provide an assessment of the effectiveness of such systems. The other two tools are presented in the following chapter. The first tool proposed by the conceptual model is the Value-Satisfaction grid which aggregates the learners’ value and satisfaction with e-learning systems in order to indicate the learners’ perceived effectiveness of e-learning systems. The Value-Satisfaction grid also helps indicate the action and improvement priorities that are needed for the characteristics and dimensions of an e-learning system under study. A proposed method of aggregation of learners’ perceived value of e-learning systems and satisfaction with e-learning systems to construct the Value-Satisfaction grid and the two tools presented in the following chapter is also presented in this chapter. The understanding of the Value-Satisfaction grid provides the first building block toward a complete set of assessment tools of learners’ perceived effectiveness of e-learning systems. The development of this set of tools is a significant achievement as scholars have suggested that prior research in technology mediated learning (TML) lacked the overall system approach and concentrated only on one or two dimensions at a time (Alavi & Leidner, 2001a, p. 9).

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Towards Increasing the Efficiency of E-Learning Systems Using Recommendation System Approach

Utilizing Educational Data Mining Techniques for Improved Learning - Advances in Educational Technologies and Instructional Design ◽

10.4018/978-1-7998-0010-1.ch003 ◽

2020 ◽

pp. 35-55

Author(s):

Zameer Gulzar ◽

L. Arun Raj ◽

A. Anny Leema

Keyword(s):

System Approach ◽

Recommendation System ◽

Learning Systems ◽

Learning Objectives ◽

Learning System ◽

E Learning ◽

Flexible Delivery ◽

Algorithmic Techniques ◽

Information Optimization ◽

Almost All

Data mining approaches have been tried in e-learning systems for information optimization and knowledge extraction to make decisions. In recent years, the recommendation system has gained popularity in every field be it e-commerce, entertainment, sports, healthcare, news, etc. However, in e-learning system, the recommender systems were not effectively utilized in comparison to other domains and thus emerged as a bottleneck for almost all e-learning systems for not offering flexible delivery of the learning resources. Current e-learning systems lack personalization features, and the information is presented in a static way despite their varying learning objectives and needs. The aim of recommender system is to personalize the information with respect to learner interest. The objective of this study is to highlight various algorithmic techniques that can be used to improve information retrieval process to provide effective recommendations to learners for improving their performance and satisfaction level.

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