Information and Communications Technology and Education Customized for Fathers of Preterm Infants

2020 ◽  
Vol 39 (2) ◽  
pp. 66-74
Author(s):  
Hyung Nam Kim
Keyword(s):  
Online Education ◽  
Learning Styles ◽  
Preterm Infants ◽  
User Interfaces ◽  
Information And Communications Technology ◽  
Learning System ◽  
Outcome Variable ◽  
Content Analysis Method ◽  
Hands On Learning ◽  
E Learning

PurposeAlthough various educational technology interventions have been introduced to support parents of preterm infants, the interventions tend to focus on mothers over fathers. This study aims to advance understanding of the concerns and needs of fathers and seek opportunities of information technology to support them.Design and SampleA convenience sampling method recruited 18 parents (i.e., ten mothers and eight fathers of preterm infants) for interviews. The interview transcripts were analyzed by the inductive content analysis method.Main Outcome VariableThe analysis identified two main themes (i.e., customized education, learning styles and tools preferred by fathers) and five subthemes (i.e., infant care, self-care, self-regulated online learning, adaptive user interfaces of online education modules, and hands-on learning with multimedia).ResultsThe interviewed parents emphasized the importance of education customized for the fathers of preterm infants, and argued that an e-learning system has the potential to fulfill the fathers' educational needs.

scholarly journals Adaptive Virtual Learning Environment based on Learning Styles for Personalizing E-learning System: Design and Implementation

2020 ◽  
Vol 8 (6) ◽  
pp. 3398-3406
Keyword(s):  
Learning Environment ◽  
Learning Styles ◽  
User Interfaces ◽  
Adaptive Learning ◽  
Architectural Design ◽  
Virtual Learning ◽  
Virtual Learning Environment ◽  
Learning System ◽  
Course Content ◽  
E Learning

Most virtual learning environment fails to recognize that students have different needs when it comes to learning. With the evolving characteristics and tendencies of students, these learning environments must provide adaptation and personalization features for adaptive learning materials, course content and navigational designs to support student’s learning styles. Based from the data mining results of learner behavioral features of five hundred seven (507) tertiary students, an accurate model for classification of student’s learning styles were derived using J48 decision tree algorithm. The model was implemented in a prototype using a framework and a proposed system architectural design of an adaptive virtual learning environment. The study resulted in the development of an adaptive virtual learning environment prototype where learner’s preferences are dynamically diagnosed to intelligently personalize the course content design and user interfaces for them.

Towards a Personalized E-Learning System

2011 ◽  
pp. 2124-2134
Author(s):  
Elvis Wai Chung Leung ◽  
Qing Li
Keyword(s):  
Online Education ◽  
Economic Benefit ◽  
Learning System ◽  
Development Cost ◽  
Web Based ◽  
Course Materials ◽  
Web Based Learning ◽  
Interactive Environment ◽  
E Learning ◽  
The Web

To cope with the increasing trend of learning demand and limited resources, most universities are taking advantage of Web-based technology for their distance education or e-learning (Montelpare & Williams, 2000). One of the reasons is due to the significant price drop of personal computers in recent decades; the Internet and multimedia have penetrated into most households. Moreover, most students prefer to learn from an interactive environment through a self-paced style. Under the Web-based learning model, students can learn anytime, anywhere because they are not required to go to school on schedule (Appelt, 1997). Meanwhile, universities also enjoy the economic benefit due to the large student base that can share the development cost of course materials and other operational expenses. Gradually, more and more universities follow this similar way to provide online education.

scholarly journals Multi-Agent Adaptive e-Learning System Based on Learning Styles

2021 ◽  
Vol 4 (1) ◽  
pp. 1-12
Author(s):  
Faith Ngami Kivuva ◽  
Elizaphan Maina ◽  
Rhoda Gitonga
Keyword(s):  
Learning Styles ◽  
Learning Process ◽  
Intelligent Agents ◽  
Personalized Learning ◽  
Learning Systems ◽  
Learning System ◽  
Personalized Recommendation ◽  
Information Agent ◽  
E Learning ◽  
Multi Agent

Most traditional e-learning system fails to provide the intelligence that a learner may require during their learning process. Different learners have different learning styles but the current e-learning systems are not able to provide personalized learning. In this paper, we discuss how intelligent agents can aid learners in their learning process. Three agents have been developed namely, learner agent, information agent, and tutor agents that will be integrated into a learning management system (Moodle). Learners are provided with a personalized recommendation based on the learning styles.

scholarly journals Learning Styles and Dyslexia Types – Understanding Their Relationship and its Benefits in Adaptive E-learning Systems

2020 ◽  
Vol 14 (15) ◽  
pp. 25
Author(s):  
Aisha Y Alsobhi ◽  
Khaled H Alyoubi
Keyword(s):  
Learning Styles ◽  
Learning Style ◽  
Learning Systems ◽  
Learning System ◽  
Knowledge Level ◽  
Educational Establishment ◽  
E Learning ◽  
User Learning ◽  
The Relationship ◽  
Better Than

Learning is a fundamental element of people’s everyday lives. Learning experiences can take the form of our interactions with others, through attending an educational establishment, etc. Not everyone learns in the same way, and even people who are considered to have a similar standard of abilities or proficiency will exhibit different learning styles. This does not necessarily mean that some students are better than others; it means that students are different from one another. Adaptive e-learning system should be capable of adapting the content to the user learning style, abilities and knowledge level. In this paper, we investigate the benefits of incorporating learning styles and dyslexia type in adaptive e-learning systems. Adaptivity aspects based on dyslexia type and learning styles enrich each other, enabling systems to provide learners with materials which fit their needs more accurately. Besides, consideration of learning styles and dyslexia type can contribute to more accurate student modelling. In this paper, the relationship between learning styles, the Felder–Silverman learning style model (FSLSM), and dyslexia type, is investigated. These relationships will lead to a more reliable student model.

scholarly journals Learning Objects in Online Education: A Systemic Approach

2020 ◽  
Vol 3 (2) ◽  
pp. 142
Author(s):  
Gerardo Quiroz Vieyra ◽  
Luis Fernando Muñoz González
Keyword(s):  
Online Education ◽  
Curriculum Design ◽  
Learning Objects ◽  
Learning System ◽  
Systemic Approach ◽  
Quality Model ◽  
Digital Repositories ◽  
E Learning ◽  
Teaching Learning ◽  
Bloom Taxonomy

In the construction of learning objects, as digital instructional material that is delivered to students, the level of learning to which they are directed must be considered first of all, according to the Bloom taxonomy or any other that is used, applicable to the e-learning, taking advantage of the digital resources that are currently available, multimedia for creation, digital repositories for storage and internet for access. Learning objects are built with pedagogical and technological elements that follow a process in themselves, subject to an educational model, instructional design, curriculum design and learning objectives as precedents, with stages very similar to those of design, construction and operation of an information system. Given their nature of digital entities, learning capsules that contain information and knowledge, the Data Quality Model of the ISO / IEC 25012: 2008 standard is also applicable, which guarantees the quality of the content and their access and availability. The creation of learning objects must also obey an educational strategy and be considered holistically in the e-learning system, that is, use a systemic approach throughout the teaching-learning process, including learning objects, considering harmonization , performance and quality in all its stages.

scholarly journals Intelligent Edutab Box: Supporting Real-Time Face-to-Face Collaborative Learning

2021 ◽  
Vol 25 (2) ◽  
pp. 258-269
Author(s):  
Yuto Omae ◽  
Kazutaka Mizukoshi ◽  
Tatsuro Furuya ◽  
Takayuki Oshima ◽  
Norihisa Sakakibara ◽  
...  
Keyword(s):  
Collaborative Learning ◽  
Real Time ◽  
Information And Communications Technology ◽  
Learning System ◽  
Computer Supported Collaborative Learning ◽  
Learning Groups ◽  
Educational Benefits ◽  
Face To Face ◽  
E Learning ◽  
Learning Analysis

Educational benefits of collaborative learning have been demonstrated in several studies and various systems have been developed to date. Numerous efforts have been made to enhance these benefits by supporting collaborative learning with information and communications technology. These efforts have primarily involved support for constructing collaborative learning groups, for collaborative learning in e-learning environments, and for collaborative learning analysis. This study aims to develop a computer-supported collaborative learning system that supports instructors in real time to facilitate collaborative learning in a face-to-face environment with multiple learners at the same time to provide enhanced support. Both the learner and instructor have one tablet terminal and conduct collaborative learning in a single classroom. Herein, the learner can use the tablet to save an educational log and freely browse the educational log of another learner. By referencing the educational logs, learners can learn through face-to-face communication. Additionally, the instructor can determine (1) who is viewing whose educational log and to what extent and (2) which learner is struggling to achieve targets. Herein, an overview of the proposed system is provided and the results obtained using the proposed system are reported to evaluate its effectiveness.

The influence of learning style on satisfaction and learning effectiveness in the asynchronous web-based learning system

2017 ◽  
Vol 35 (4) ◽  
pp. 473-489 ◽  
Author(s):  
Fei-Fei Cheng ◽  
Chui-Chen Chiu ◽  
Chin-Shan Wu ◽  
Der-Chian Tsaih
Keyword(s):  
Learning Styles ◽  
Learning Style ◽  
Learning System ◽  
Learning Effectiveness ◽  
Web Based ◽  
Content Type ◽  
Web Based Learning ◽  
Significant Difference ◽  
E Learning ◽  
The Web

Purpose The purpose of this paper is to investigate the effect of user’s learning style (including accommodators, divergers, convergers, and assimilators) on user’s satisfaction on the web-based learning system and their learning effectiveness. Design/methodology/approach This experimental research used the college students from a technology institute in Taiwan as the subject sources. By using the Kolb’s learning style model, the students are classified as four types of learners: convergers, divergers, assimilators, and accommodators. The authors analyzed the relationships among the different learning styles with their effectiveness of learning and satisfaction of using the web-based learning system. The mediation effect of gender is also presented. Findings This research indicates that: first, the satisfaction of the web-based learning system has significant influence on the learning performance of learners; second, different learning styles learners have no significant effect to the satisfaction on using the web-based learning system; third, learning effectiveness has significant difference among different learning style learners on the web-based learning system; the learning effectiveness of accommodators and divergers was significantly higher than the assimilators; fourth, different learning styles learners show significant difference in gender proportion. In addition to accommodators, whose proportion of women is higher than men, the other three learning styles’ proportions in men are higher than women. Research limitations/implications This study was grounded in the Kolb’s learning style theory. The authors provide implications for academic studies in e-learning research stream that aimed at understanding the role of learning style as well as gender differences in the asynchronous web-based learning system. Practical implications Results from this study provided the implications for students, educators, and e-learning system designers. The design of teaching materials as well as functions of e-learning systems should take learners’ learning style into consideration to ensure the best learning outcome. Originality/value This study examined the students’ learning style as well as gender differences in the asynchronous web-based learning system. An experiment was conducted to ensure the data were collected in a controlled environment, thus, offer the value that most of the prior study lacks.

Sign in / Sign up

Export Citation Format

Share Document