سامانه های توصیه‌گر برای یادگیری الکترونیکی
ترجمه نشده

سامانه های توصیه‌گر برای یادگیری الکترونیکی

عنوان فارسی مقاله: روند تحقیق در سامانه های توصیه‌گر برای یادگیری الکترونیکی: بررسی منظم مقالات ژورنال SSCI از سال ۲۰۱۴ تا ۲۰۱۸
عنوان انگلیسی مقاله: The research trends in recommender systems for e-learning: A systematic review of SSCI journal articles from 2014 to 2018
مجله/کنفرانس: مجله انجمن آسیایی دانشگاههای آزاد - Asian Association of Open Universities Journal
رشته های تحصیلی مرتبط: علوم تربیتی
گرایش های تحصیلی مرتبط: تکنولوژی آموزشی
کلمات کلیدی فارسی: مرور ادبیات، رفتار یادگیری، ارزیابی سامانه توصیه‌گر یادگیری الکترونیکی، فناوری توصیه
کلمات کلیدی انگلیسی: Literature review، Learning behaviour، Assessment of e-learning recommender system، Recommendation technology
نوع نگارش مقاله: مقاله پژوهشی (Research Article)
نمایه: DOAJ
شناسه دیجیتال (DOI): https://doi.org/10.1108/AAOUJ-03-2019-0015
دانشگاه: Department of Mathematics and Information Technology, Education University of Hong Kong, Hong Kong, Hong Kong
صفحات مقاله انگلیسی: 16
ناشر: امرالد - Emeraldinsight
نوع ارائه مقاله: ژورنال
نوع مقاله: ISI
سال انتشار مقاله: 2019
شناسه ISSN: 2414-6994
فرمت مقاله انگلیسی: PDF
وضعیت ترجمه: ترجمه نشده است
قیمت مقاله انگلیسی: رایگان
آیا این مقاله بیس است: خیر
آیا این مقاله مدل مفهومی دارد: ندارد
آیا این مقاله پرسشنامه دارد: ندارد
آیا این مقاله متغیر دارد: ندارد
کد محصول: E12737
رفرنس: دارای رفرنس در داخل متن و انتهای مقاله
فهرست مطالب (انگلیسی)

Abstract

Introduction

Research methodology

Research results

Discussion

Conclusion

References

بخشی از مقاله (انگلیسی)

Abstract

Purpose - A recommendation algorithm is typically applied to speculate on users’ preferences based on their behavioral characteristics. The purpose of this paper is to provide a systematic review of recommendation systems by collecting related journal articles from the last five years (i.e. from 2014 to 2018). This paper aims to study the correlations between recommendation technologies and e-learning systems.

Design/methodology/approach - The paper reviews the relevant articles using five assessment aspects. A coding scheme was put forward that includes the following: the metrics for the e-learning system, the evaluation metrics for the recommendation algorithms, the recommendation filtering technology, the phases of the recommendation process and the learning outcomes of the system.

Findings - The research indicates that most e-learning systems will adopt the adaptive mechanism as a primary metric, and accuracy is a vital evaluation indicator for recommendation algorithms. In existing e-learning recommender systems, the most common recommendation filtering technology is hybrid filtering. The information collection phase is an important process recognized by most studies. Finally, the learning outcomes of the recommender system can be achieved through two key indicators: affections and correlations.

Originality/value – The recommendation technology works effectively in closing the gap between the information producer and the information consumer. This technology could help learners find the information they are interested in as well as send them a valuable message. The opportunities and challenges of the current study are discussed; the results of this study could provide a guideline for future research.

Introduction

E-learning is defined as an instruction tool that provides knowledge and helps facilitate learning by use of a digital device or a web technology (Clark and Mayer, 2016). In comparison with traditional instruction modes and learning approaches, the use of e-learning is more effective for learning purposes. For example, early research (McClusky, 1947) showed that the educational film, as a delivery medium on an e-learning system, has better learning outcomes because it contributes to achieving educational goals. Further, e-learning is a type of new learning style that could be a solution for lifelong personal learning (Zhang et al., 2004), as learners can learn without the limitations of time and place. Fundamentally, it is of great value for educational reform and development. To be specific, e-learning is widely regarded as “educational technology, information and communication technology (ICT), multimedia learning, technology-enhanced learning (TEL), computer-based instruction (CBI), a virtual learning environment (VLE), mobile learning” (Ridwan, 2015) and so on. With the progress of information and communication technology development, e-learning system provides support for educational management. Due to the importance of e-learning system, many researchers have expended much effort on the research of emerging educational technologies on e-learning platforms through some theoretical models or frameworks.