Personalized Learning Course Planner with E-learning DSS using user profile

نویسندگان

  • Hwa-Young Jeong
  • Cheol-Rim Choi
  • Young-Jae Song
چکیده

Various methods of e-learning systems, based on information and communications, and geared towards improving learning effectiveness and students’ attention span, have been studied. However, most e-learning systems force students to follow the learning course or content established by a teacher. These methods are convenient, but they limit the effectiveness of e-learning. To overcome this limitation and increase effective learning, new techniques that reflect alternative learning styles, such as adaptive learning and personalized learning, have been studied. In this study, we proposed a Personalized Learning Course Planner (PLCP) that allows students to easily select the learning course they desire. User profile data was collected from the students’ initial priorities about learning contents as well as the test scores after their study. E-Learning Decision Support System (ELDSS) in PLCP suggests an appropriate learning course organization, according to calculated results based on the user profile data. To verify the effectiveness of the proposed system, we implemented an English learning system consisting of PLCP. We conducted an experiment with 30 university students and evaluated students’ satisfaction by questionnaire analysis. The results indicate that the proposed system improved learning effectiveness and student satisfaction. Further investigation of the participants indicated that suggesting a learning course suitable for students’ previous test scores and priorities encouraged students to concentrate on the lesson. 2011 Elsevier Ltd. All rights reserved.

برای دانلود رایگان متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

A Personalized E-Learning System Based on User Profile Constructed Using Information Fusion

In this paper, we describe a personalized e-learning system which can automatically adapt to the interests and levels of learners. The system is designed based on the IEEE Learning Technology Systems Architecture (IEEE LTSA) to achieve high scalability and reusability. A feedback extractor with fusion capability is proposed to combine multiple feedback measures to infer user preferences. User p...

متن کامل

Semantic Learning Service Personalized

To provide users with more suitable and personalized service, personalization is widely used in various fields. Current e-Learning systems search for learning resources using information search technology, based on the keywords that selected or inputted by the user. Due to lack of semantic analysis for keywords and exploring the user contexts, the system cannot provide a good learning experimen...

متن کامل

Personalized e-Learning – a Goal Oriented Approach

A major drawback of current e-learning systems is that they are too disconnected from learner’s learning preferences and learning goals. There has been a high demanding for learner centric e-learning systems. Research on personalized e-learning is emerging in recent years. However, most of the current research is focused on user profile modeling, and learning styles research, etc. In this paper...

متن کامل

Time-decayed User Profile for Second Language Vocabulary Learning System

Vocabulary learning is the foundation of second language learning. Many E-learning systems have been developed to help learners to learn vocabulary efficiently. Most of these systems employ Ebbinghaus Forgetting Curve to make the review schedule for learners. However, learners are different in learning ability and the review schedule based on Ebbinghaus Forgetting Curve may be not fit for every...

متن کامل

Using Semantic Web to support Advanced Web-Based Environment

In the learning environments, users would be helpless without the assistance of powerful searching and browsing tools to find their way. Web-based e-learning systems are normally used by a wide variety of learners with different skills, background, preferences, and learning styles. In this paper, we perform the personalized semantic search and recommendation of learning contents on the learning...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

عنوان ژورنال:
  • Expert Syst. Appl.

دوره 39  شماره 

صفحات  -

تاریخ انتشار 2012