Learning Object Recommender System for Personalised Learning

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Learning process includes three components- they are students, teacher, and learning materials. From teacher’s point of view, teaching is an activity to deliver information and skill to students with some goals to be achieved. From students’ point of view, learning is an activity to acquire information from teacher to achieve goals set by the teacher. Students with their prior knowledge acquire new information from teacher. Here, social constructivism paradigm can help students learn collaborative and sharing knowledge each other. Basically, knowledge, which is needed to be achieved according to the course, mainly does not get influenced by how many Learning Objects (LOs) the students have read, but how relevant Learning Objects that have retrieved and learned. Student who has high prior knowledge according to the course, need LOs that is different from other student who has low prior knowledge. Hence, personalisation features are needed which adaptively facilitate student in monitoring their learning progress and provide any resources or learning material that suitable to what they need. This personalisation feature implemented in the e-learning system developed in Faculty of Computer Science (Fasilkom) University of Indonesia (UI) has been named SCELE.

This is always assumed that students have the prior knowledge to any course. However, in reality it is not always the case. Hence, Learning Object Recommender (LOR) is needed in order to enhance quality of discussion in building new knowledge by improving student’s prior knowledge. This research In the University of Indonesia in line with the running system, Student Centered E-Learning Environment (SCELE) is built based on open source LMS, Moodle. SCELE is integrated with digital library system called Library Automation and Digital Archive (LONTAR) and Learning Object Manager (LOM). LONTAR can handle resources sharing and LOM manages resources, like upload, search and update resources. From Social Constructivism’s perspective, SCELE has features to facilitate discussion among students and teachers (instructors).

The Existing System: SCELE, LONTAR, and LOM

Faculty of Computer Science (Fasilkom), University of Indonesia (UI) implements LMS called Student Centered E-Learning Environment (SCELE) for e-learning which is developed using enterprise resource planning approach. SCELE is developed based on open source LMS, Moodle. Moodle’s main features support SCELE, such as communication tools synchronous (chatting) and asynchronous (news and discussion forum), user management, assessment, and also course management. Moodle has been so that it can meet the student-centered learning model requirements. The works are development of space for integrating course graph and assessment graph, integration LONTAR digital library, and integration of Learning Object Manager (LOM) module to SCELE.

Student-centered learning paradigm has been adopted through SCELE as an attempt to change old learning paradigm, which focus on teacher to focus on student. According to R. Cannon in Guide to support the implementation of the Learning and Teaching Plan Year 2000, ACUE, The University of Adelaide, 2000, definition of student-centered learning is:

“Student-centered learning describes ways of thinking about learning and teaching that emphasise student responsibility for such activities as planning learning, interacting with teachers and other students, researching, and assessing learning.”

By using this approach, it is believed that student can meet new learning experience and can exercise active and collaborative learning.

Goals of teaching-learning activities especially in higher education are not only knowledge transfer, but also the development of analytical-thinking (soft skill), that are very useful to face and solve the complexities of real world problems.

The idea of student-centered learning is not limited to campus-based teaching and learning but it can be extended to distance learning.  Overall, establishing student-centered, e-learning systems for distance learning will improve the quality of education, at the same time as increasing the possible number of students’ participating in higher education. In order to accomplish such objectives, digital library application LONTAR and LOM module are integrated.

Architecture of Learning Object Recommender

Based on the existing curriculum and analysis on SCELE, Learning Object Recommender’s architecture has been designed that focus on prior knowledge assessment. Writers propose four main components:

Prior knowledge assessment engine: This function is used for generating instrument of assessments, such as pre-assessment, mid-assessment, and final-assessment. An assessment contains several questions related to the course and type of assessment.

Records of students’ performance: Used to collect all results of assessment; then the data of all assessment for each student can be analysed for tracking student’s learning progress. Measuring student’s learning progress can be done by comparing results of assessment.

LO repository: Used to manage LOs after creation and manage their version.

LO recommender: This function used to provide LOs for students based on result of assessment.

LONTAR: Library automation and digital archive

Digital library is a system, which has various service and information object to support users who need the information object. The information object can still be a book or paper, but the metadata is formatted electronically which can be accessed through digital devices. Digital library feature is integration of LONTAR digital library into e-learning system, SCELE. By using this feature, users can search documents in the library.

Learning Object Manager

Learning Object Manager (LOM) is a feature used as repository of learning materials (LOs) which has upload, download, and searching facility. The definition of LO from Learning Technology Standards Committee – Institute of Electrical and Electronic Engineers, is:

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