A Learning Object Recommendation System

2014 ◽  
pp. 254-269
Author(s):  
Adriano Pereira ◽  
Iara Augustin
Keyword(s):  
Learning Styles ◽  
Affective Computing ◽  
Recommendation System ◽  
Affective State ◽  
Large Data ◽  
Learning Objects ◽  
Data Availability ◽  
Learning Object ◽  
Affect Detection ◽  
Data Objects

Emotions play a very important role in the learning process. Affective computing studies try to identify users’ affective state, as emotion, using affect models and affect detection techniques, in order to improve human-computer interactions, as in a learning environment. The Internet explosion makes a huge volume of information, including learning objects data, available. In this scenario, recommendation systems help users by selecting and suggesting probable interesting items, dealing with large data availability and decision making problems, and customizing users’ interaction. In u-learning context, students could learn anywhere and anytime, having different options of data objects available. Since different students have different preferences and learning styles, personalization becomes an important feature in u-learning systems. Considering all this, the authors propose the Affective-Recommender, a learning object recommendation system. In this chapter, they describe the system’s requirements and architecture, focusing on affect detection and the recommendation algorithm, an example of use case, and results of system implementation over Moodle LMS.

Adaptation of Descriptive Metadata for Managing Educational Resources in the GREDOS Repository

2018 ◽  
pp. 2063-2085
Author(s):  
Erla M. Morales Morgado ◽  
Rosalynn A. Campos Ortuño ◽  
Ling Ling Yang ◽  
Tránsito Ferreras-Fernández
Keyword(s):  
Learning Styles ◽  
Mobile Apps ◽  
Learning Objects ◽  
Educational Resources ◽  
Learning Object ◽  
Institutional Repository ◽  
Dublin Core ◽  
Digital Repositories ◽  
Learning Object Metadata ◽  
Metadata Mapping

In this chapter the authors describe a Project entitled “Divulgación de Recursos Educativos Digitales (DIRED)” (Divulgation of Digital Educational Resources) addressed to promoting specific educational resources and mobile apps for educational proposals in order to manage them through the institutional repository of the Salamanca University (GREDOS). The authors present a proposal for describing learning objects based on pedagogical information, digital competences and learning styles. The authors also suggest educational information for classifying useful mobile apps. To achieve their suitable access and recovery, the authors focus on the use of Learning Object specific metadata in digital repositories such as LOM (Learning Object Metadata). The authors study the metadata mapping necessary to adapt from LOM to Qualified Dublin Core, because this is the standard used in the GREDOS repository built with a DSpace platform. Finally, the authors present their implementation of Learning Object Description in the GREDOS repository.

scholarly journals Model of Recommendation System for for Indexing and Retrieving the Learning Object based on Multiagent System

Respuestas ◽  
2012 ◽  
Vol 17 (2) ◽  
pp. 21-30
Author(s):  
Ronaldo Lima Rocha Campos ◽  
Rafaela Lunardi Comarella ◽  
Ricardo Azambuja Silveira
Keyword(s):  
Multiagent System ◽  
Recommendation System ◽  
Learning Objects ◽  
Learning Object ◽  
Multi Agent Systems ◽  
Knowledge Domain ◽  
Object Based ◽  
Metadata Standards ◽  
Systems Learning ◽  
Multi Agent

This paper proposes a multiagent system application model for indexing, retrieving and recommendation learning objects stored in different and heterogeneous repositories. The objects within these repositories are described by filled fields using different metadata standards. The searching mechanism covers several different learning object repositories and the same object can be described in these repositories by the use of different types of fields. Aiming to improve accuracy and coverage in terms of recovering a learning object and improve the signification of the results we propose an information retrieval model based on the multiagent system approach and an ontological model to describe the knowledge domain covered.Keywords: AI in education, multi-agent systems, learning objects, recommendation systems. 

scholarly journals Learning Objects Recommendation System: Issues and Approaches for Retrieving, Indexing and Recomend Learning Objects

2015 ◽  
Vol 4 (4) ◽  
pp. 69-82
Author(s):  
Ricardo Azambuja Silveira ◽  
Rafaela Lunardi Comarella ◽  
Ronaldo Lima Rocha Campos ◽  
Jonas Vian ◽  
Fernando De La Prieta
Keyword(s):  
Multiagent System ◽  
Recommendation System ◽  
Learning Objects ◽  
Learning Object ◽  
Data Standards ◽  
Knowledge Domain ◽  
Improve Accuracy ◽  
Different Types ◽  
Learning Object Repositories ◽  
Ontological Model

This paper discusses some important issues regarding the the management of Learning objects covering searching over repositories and different approaches of recommendation systems and presents a multiagent system based application model for indexing, retrieving and recommending learning objects stored in different and heterogeneous repositories. The objects within these repositories are described by filled fields using different metadata (data about data) standards. The searching mechanism covers several different learning object repositories and the same object can be described in these repositories by the use of different types of fields. Aiming to improve accuracy and coverage in terms of recovering a learning object and improve the relevance of the results we propose an information retrieval model based on a multiagent system approach and an ontological model to describe the covered knowledge domain.

Learning Object Retrieval and Aggregation Based on Learning Styles

2016 ◽  
Vol 55 (6) ◽  
pp. 757-788
Author(s):  
Aldo Ramirez-Arellano ◽  
Juan Bory-Reyes ◽  
Luis Manuel Hernández-Simón
Keyword(s):  
Learning Styles ◽  
Student Learning ◽  
Learning Style ◽  
Learning Objects ◽  
Experimental Results ◽  
Learning Object ◽  
Learning Performance ◽  
Second Step ◽  
Object Retrieval ◽  
Merging Process

The main goal of this article is to develop a Management System for Merging Learning Objects (msMLO), which offers an approach that retrieves learning objects (LOs) based on students’ learning styles and term-based queries, which produces a new outcome with a better score. The msMLO faces the task of retrieving LOs via two steps: The first step ranks LOs using a unified learning style model and creates better LOs by merging the top-ranked LOs. The second step maps LOs onto a hierarchy of concepts to avoid duplicated topics. An experiment was conducted to evaluate this approach in an applied computing course. A total of 84 students were randomly split into four groups. The experimental results demonstrated that the msMLO is a promising approach that provides useful LOs based on students’ learning styles and the merging process for reusing stored LOs. Furthermore, this approach improves overall student learning performance and reduces the number of LOs reviewed.

scholarly journals The Architecture of Learning Object Repositories

10.28945/2910 ◽  
2005 ◽  
Author(s):  
Ismar Frango Silveira ◽  
Nizam Omar ◽  
Pollyana Notargiacomo Mustaro
Keyword(s):  
Learning Styles ◽  
Learning Process ◽  
Large Scale ◽  
Learning Objects ◽  
Learning Processes ◽  
Learning Object ◽  
Mediated Learning ◽  
Pedagogical Content ◽  
Wide Range ◽  
Teaching Learning

The definition used for learning objects considers them as any digital entity which can be used, reused or referenced during a technology-mediated learning process. Nowadays, this concept has became essential to the development of pedagogical content to be used in large scale educational projects to which are engaged a wide number of educational agents - students, teachers and faculty staff. Guaranteeing reusability of pedagogical content allows its use on different contexts. Therefore, a repository of learning objects that has a well-defined metadata structure can be used to customize learning processes. Recent researches on Learning Object have been contributing on the search of patterns for instructional content development, in order to make them adaptive, generic, portable and scalable enough to improve their potential for reusability. Besides, a wide range of virtual learning environments has been proposed to support these learning objects, with their properties and characteristics. Nonetheless, the great challenge still remains on how adaptive can a learning object be. There are several levels of adaptation that can be reached, and these levels can be established regarding to a wide range of different aspects on teaching-learning processes, varying from the need of keeping track of students’ evolution on building a specified piece of desired knowledge, until their learning styles, a multi-dimensional measure that are not only individual-dependant, but are also influenced by a range of factors so diverse as environment, inter-relational issues and psychological aspects related to how a student deal with certain sort of knowledge to be constructed, or skill to be developed. An architecture for learning objects repositories that intends to be general enough to support different pedagogical approaches and adaptation levels is presented. Such architecture is based on five different but co-related tiers: Syllabus Tier, which encapsulates all organization of learning objects that persist on the Reusable Learning Objects Tier. To select and present these objects in a way that adaptation to students’ background, learning styles and temporal motivation is responsibility of Apprentice Model Tier and Learning Styles Tier, that together drive Presentation Tier to dynamically built the most adequate interface to each student. Therefore, multiple presentations for the same learning object can make learning process more significant to students.

scholarly journals Learning Objects: Adaptive Retrieval through Learning Styles

10.28945/3009 ◽  
2006 ◽  
Author(s):  
Pollyana Mustaro ◽  
Ismar Silveira
Keyword(s):  
Learning Styles ◽  
Learning Style ◽  
Learning Objects ◽  
Learning Object ◽  
Learning Context ◽  
Learning Abilities ◽  
Technological Advances ◽  
Metadata Annotation ◽  
Starting Point ◽  
Specific Learning

Nowadays, the amount of information grows in an exponential way, mainly because of technological advances in media. This scenario claims for the development of different skills in order to increase learning abilities, making them personal and customizable. Such factor is significant in a changing society, which implies in a range of mechanisms which would allow to identify, in a non-intrusive way, which learning style some specific student would prefer to perform in order to build knowledge from some learning object under a learning context. This requires defining some strategies in order to recognize adult learner’s learning styles for some specific learning context. This work is based on theoretical references of Felder, Kolb and Gardner, proposing the implementation of a metadata annotation to identificate prime learning styles that are present in specific learning objects. This classification constitutes a starting point to recover learning objects from a repository according to apprentice’s profile and experiences. As a result, the effectiveness of the use of learning objects will be improved.

Re-Purposeable Learning Objects Based on Teaching and Learning Styles

2009 ◽  
pp. 1224-1231
Author(s):  
Sunand Bhattacharya ◽  
Jeremy Dunning ◽  
Abtar Kaur ◽  
David Daniels
Keyword(s):  
Distance Education ◽  
Learning Styles ◽  
Knowledge Base ◽  
Teaching And Learning ◽  
Learning Objects ◽  
Traditional Classroom ◽  
Learning Object ◽  
Topic Area ◽  
Web Based ◽  
Excellent Teachers

Web-based distance learning is hampered in many cases by a failure to deliver material in a manner consistent with the ways in which students learn and instructors teach best in traditional environments (Samoriski, 2002). Excellent teachers are successful because of the ways in which they mediate content and place the content within the context of the subject matter. It is not the specific content or images the successful teacher presents, but rather the manner in which they are presented and framed within the scope of the topic area. Excellent teachers teach by presenting the content and then providing the students with substantive opportunities to apply the content to real-world problems in an effort to promote critical thinking on the part of the student. This is a highly interactive process with much information being transmitted between the student and the instructor. The interchange between the instructor and the student helps the student build a knowledge base with the assistance of the instructor’s experience and expertise in the topic area. The exact nature of the interchange is not predetermined and depends to a great extent on the creativity and breadth of experience of the instructor. The successful instructor adjusts his or her interaction with the students to the learning styles best suited to them. How do we provide the learner with this important component of traditional classroom education in asynchronous distance education or technology-mediated traditional classes? Web-based instruction is rapidly becoming the preferred mode of distance education, and we must adapt our instructional interaction styles to this medium. Our students now expect more interactive and immersive materials in Web-based learning than that typically provided in the traditional classroom or correspondence distance education (Samoriski, 2002). The TALON learning object system is a series of repurposeable learning object templates based on styles of teaching and learning as described by Dunning et al. (2003). These flash-based templates allow instructors to design and execute interactive learning objects in approximately 10% of the time required to create them from first principles, because the use of them requires little or no alteration of existing source code or writing of additional code (Abtar, Dunning, Harvinder, & Halimatolhanin, 2004; Dunning et al., 2004). The fact that the learning objects are based on the successful learning styles experienced in the traditional classroom ensures that the student is both engaged and allowed to build a knowledge base about the content being covered.

scholarly journals Re-Purposeable Learning Objects Based on Teaching and Learning Styles

2012 ◽  
Vol 2 (4) ◽  
pp. 1-11
Author(s):  
Jeremy Dunning ◽  
Kellie Donoghue ◽  
Abtar Kaur ◽  
David Daniels
Keyword(s):  
Online Education ◽  
Learning Styles ◽  
Teaching And Learning ◽  
Source Code ◽  
Learning Objects ◽  
Learning Object ◽  
High Quality ◽  
New Learning ◽  
Specific Teaching ◽  
The Cost

The interactive, multimedia learning object has become an important part of high quality online education. The cost of producing such learning objects can be prohibitive. Re-purposeable learning objects made with learning object templates allow instructors with little or no programming experience to produce highly interactive and immersive learning objects. These learning object templates are based on key styles of teaching and learning and can be used to create and customize new learning objects within those styles, without creating new source code. The templates allow instructors to create learning objects simply by inserting text, and media (images, movies, etc.) because they closely mimic specific teaching strategies.

Adaptation of Descriptive Metadata for Managing Educational Resources in the GREDOS Repository

2014 ◽  
Vol 10 (4) ◽  
pp. 50-72 ◽  
Author(s):  
Erla M. Morales Morgado ◽  
Rosalynn A. Campos Ortuño ◽  
Ling Ling Yang ◽  
Tránsito Ferreras-Fernández
Keyword(s):  
Learning Styles ◽  
Mobile Apps ◽  
Learning Objects ◽  
Educational Resources ◽  
Learning Object ◽  
Dublin Core ◽  
Digital Repositories ◽  
Object Description ◽  
Learning Object Metadata ◽  
Metadata Mapping

In this paper the authors describe a Project entitled “Divulgación de Recursos Educativos Digitales (DIRED)” (Divulgation of Digital Educational Resources) addressed to promoting specific educational resources and mobile apps for educational proposals in order to manage them through the institutional repository of the Salamanca University (GREDOS). The authors present a proposal for describing learning objects based on pedagogical information, digital competences and learning styles. The authors also suggest educational information for classifying useful mobile apps. To achieve their suitable access and recovery, the authors focus on the use of Learning Object specific metadata in digital repositories such as LOM (Learning Object Metadata). The authors study the metadata mapping necessary to adapt from LOM to Qualified Dublin Core, because this is the standard used in the GREDOS repository built with a DSpace platform. Finally, the authors present their implementation of Learning Object Description in the GREDOS repository.

scholarly journals Kaanbal: A Mobile Learning Platform Focused on Monitoring and Customization of Learning

2021 ◽  
Vol 16 (01) ◽  
pp. 18
Author(s):  
César Huerta-Guerrero ◽  
Eduardo Lopez-Dominguez ◽  
Yesenia Hernández-Velázquez ◽  
Saul Domínguez-Isidro ◽  
Arturo Cueto-García ◽  
...  
Keyword(s):  
Learning Styles ◽  
Mobile Learning ◽  
Learning Objects ◽  
Learning Object ◽  
Educational Models ◽  
Generator System ◽  
Usability Assessment ◽  
Learning Platform ◽  
Class Room ◽  
Main Components

For the new educational models, it is essential to include teaching strategies that allow students to customize their learning based on their competencies, skills, and preferences, as well as strategies that support individual monitoring of student learning. However, the implementation of these strategies in teaching is complex for professors, and it gets complicated, as the number of students in the class-room increases. In this work, the design and development of a mobile learning platform are presented, which provides the professor and student with multiple services for the learning monitoring and customization based on learning styles, context information, and mobile learning objects. Our platform is composed of three main components: (1) A mobile learning object generator system, (2) A learning object repository, and (3) A student-oriented mobile application. The in-tegration of these three components allows and facilitates the professor the im-plementation of various strategies for monitoring and customization of learning systematically. We carried out a usability assessment of the learning object gener-ator system through a field study with five research professors. According to the obtained results, the learning object generator system presents a good acceptance, satisfaction, and applicability from the professors' perspective.

Sign in / Sign up

Export Citation Format

Share Document