scholarly journals Reinforcement Learning Approach for Adaptive e-Learning Based on Multiple Learner Characteristics

2021 ◽  
Vol 4 (2) ◽  
pp. 55-76
Author(s):  
Dan Oyuga Anne ◽  
Elizaphan Maina
Keyword(s):  
Learning Style ◽  
Affective State ◽  
Learner Characteristics ◽  
Q Learning ◽  
Model Free ◽  
Learning Platform ◽  
Learning Path ◽  
Multiple Characteristics ◽  
E Learning ◽  
Extraction Model

We introduce a novel three stepwise model of adaptive e-learning using multiple learner characteristics. We design a model of a learner attributes enlisting the study domain, summary details of the student and the requirements of the student. We include the theories of learning style to categorize and identify specific individuals so as to improve their experience on the online learning platform and apply it in the model. The affective state extraction model which extracts learner emotions from text inputs during the platform interactions. We finally pass the system extracted information the adaptivity domain which uses the off-policy Q-learning model free algorithm (Jang et al., 2019) to structure the learning path into tutorials, lectures and workshops depending on predefined constraints of learning. Simulated results show better adaptivity incases of multiple characteristics as opposed to single learner characteristics. Further research to include more than three characteristics as in this research.

scholarly journals Sakai: A Mobile Learning Platform

2019 ◽  
Vol 13 (11) ◽  
pp. 95
Author(s):  
Corrienna Abdul Talib ◽  
Hassan Aliyu ◽  
Adi Maimun Abdul Malik ◽  
Kang Hooi Siang ◽  
Igor Novopashenny ◽  
...  
Keyword(s):  
Learning Style ◽  
Mobile Learning ◽  
Research Methodology ◽  
Quantitative Research ◽  
Thinking Skills ◽  
Mobile Technologies ◽  
Electronic Learning ◽  
Learning Platform ◽  
E Learning ◽  
Learning Platforms

These days, humans have been witnessing related technological and social development, by means of which mobile technologies and Internet yield global access to information with mobility of knowledge. Mobile learning platforms are designed based on electronic learning (e-learning) and mobility. It is regarded as a useful way to enhance the learning process. Sakai as a mobile learning platform, design intentions are to be adaptable to any educational purposes, within or outside the institution, dependent on the provision of effectiveness in classroom instruction based on the learning style of the students, extensible in the cultivation of thinking skills in the learner, and efficient in communicating and exchanging data among its enrolled classroom members and other online platforms. This study employed a systematic review of related literature to investigate the predominant research methodology adopted by various scholars to assess necessary factors concerning mobile learning platform. Fifteen articles are selected based on established criteria. The findings indicated that most of the researchers used quantitative research methodology in investigating the effectiveness and concern variable of mobile learning. Also find out is that most of the outcome of the studies include, achievement, perception, pedagogy, motivation and mobile learning platform as a form of educational technology.

scholarly journals Learning Effectiveness and Students’ Perceptions in A Flexible Learning Course

2018 ◽  
Vol 21 (2) ◽  
pp. 44-52 ◽  
Author(s):  
Claude Müller ◽  
Michael Stahl ◽  
Mark Alder ◽  
Maximilian Müller
Keyword(s):  
Learning Style ◽  
Learning Effectiveness ◽  
Classroom Learning ◽  
Flexible Learning ◽  
Instructional Videos ◽  
Learning Time ◽  
Content Assessment ◽  
Learning Path ◽  
E Learning ◽  
Study Format

Abstract With flexible learning, students gain access and flexibility with regard to at least one of the following dimensions: time, place, pace, learning style, content, assessment or learning path. Zurich University of Applied Sciences (ZHAW) has launched a new flexible learning study format called FLEX, a blended learning design allowing students to be more flexible as to when and where they study. It reduces classroom learning time, replacing some of it with an e-learning environment for self-study that includes instructional videos. In a pilot phase, we conducted a semi-experimental study on the learning effectiveness of FLEX. Students’ perceptions of the new study format FLEX were found to be positive. In addition, the final test results of students in the FLEX programme were similar to those of other students, despite classroom learning time was reduced by about half.

scholarly journals Online Learning Styles Identification Model, Based on the Analysis of User Interactions Within an E-Learning Platforms, Using Neural Networks and Fuzzy Logic

2018 ◽  
Vol 7 (3.13) ◽  
pp. 76
Author(s):  
L Alfaro ◽  
C Rivera ◽  
J Luna-Urquizo ◽  
E Castañeda ◽  
F Fialho
Keyword(s):  
Fuzzy Logic ◽  
Learning Styles ◽  
Learning Style ◽  
User Behavior ◽  
Backpropagation Neural Network ◽  
User Interactions ◽  
Learning Platform ◽  
Proposed Model ◽  
E Learning ◽  
Learning Platforms

Individual Learning Style identification is an essential aspect in the development of intelligent or adaptive e-Learning platforms. Traditional methods are based on the application of questionnaires or psychological tests, which may not be the most appropriate in all cases. The proposed model is based on the analysis of user behavior through the study of their interactions within an e-Learning platform, using a multilayer Backpropagation Neural Network and Fuzzy Logic concepts, for the preprocessing of the inputs and the categorization of the outputs.                                                                              

scholarly journals E-learning e futuri studenti in mobilità internazionale. Riflessioni su aspetti e potenzialità di un corso di lingua italiana

2021 ◽  
Vol 19 (2) ◽  
Author(s):  
Alessandra Pettinelli ◽  
Chiara Sola ◽  
Monique Cintra ◽  
Luca Avellini
Keyword(s):  
Cultural Knowledge ◽  
Course Structure ◽  
Structure Selection ◽  
Learning Platform ◽  
Learning Path ◽  
E Learning ◽  
Exchange Programme ◽  
The One ◽  
The University ◽  
Self Learning

The A1 online Italian course offered by the CLA (University Linguistic Centre) of the University of Perugia, is one of the results achieved during various research projects, which has contributed, on the one hand, to the internationalization of the Institution, on the other, to the enhancement of digital technologies providing future university mobility students with the opportunity to acquire linguistic-cultural knowledge, even before the beginning of their mobility exchange programme in Italy. The experience reported in this article reflects on an evolving work, describing its design phase – course structure, selection and creation of linguistic and didactic materials, tools available in the Moodle open-source learning platform – and its subsequent phases of course activation and verification. Throughout the entire project, we focused on two fundamental aspects: inspiring and maintaining student motivation in addition to constructing an assisted, and above all, interactive self-learning path.

scholarly journals Analysing the relationship between learning styles and navigation behaviour in web-based educational system

2010 ◽  
pp. 400-421 ◽  
Keyword(s):  
Learning Styles ◽  
Computer Science ◽  
Learning Style ◽  
Web Based ◽  
Learning Platform ◽  
Web Based Learning ◽  
Index Of Learning Styles ◽  
Type Indicator ◽  
E Learning ◽  
The Relationship

The aim of our research is to automatically deduce the learning style from the analysis of browsing behaviour. To find how to deduce the learning style, we are investigating, in this paper, the relationships between the learner’s navigation behaviour and his/her learning style in web-based learning. To explore this relation, we carried out an experiment with 27 students of computer science at the engineering school (ESI-Algeria). The students used a hypermedia course on an e-learning platform. The learners’ navigation behaviour is evaluated using a navigation type indicator that we propose and calculate based on trace analysis. The findings are presented with regard to the learning styles measured using the Index of Learning Styles by (Felder and Solomon 1996). We conclude with a discussion of these results.

scholarly journals An ESL Online Classroom Experience in Oman during Covid-19

2020 ◽  
Author(s):  
Syerina Syahrin ◽  
Abdelrahman Abdalla Salih
Keyword(s):  
Online Learning ◽  
Learning Styles ◽  
Learning Style ◽  
Undergraduate Students ◽  
Learning Experience ◽  
Online Classroom ◽  
Learning Platform ◽  
E Learning ◽  
Learning Styles Inventory ◽  
The Relationship

This paper aimed to investigate the online learning experience of a group of ESL students at a higher learning institution in Oman during the Covid-19. The paper studied the interaction between the students’ preferred online learning style and the technologies the students experienced on the e-learning platform (Moodle) for the particular ESL course. The rationale for investigating the relationship between the students’ learning styles and the technologies the students experienced is to evaluate if the learning style and the technologies complement each other. It is also aimed to provide an evaluation of an ESL e-learning course by considering the different technologies that can be incorporated into the e-learning classroom to meet the different learning styles. Data was gathered from 32 undergraduate students by utilizing Kolb’s Learning Styles Inventory. The study included analysis of Moodle utilizing Warburton’s Technologies in Use (2007) to develop an understanding of the technologies the students experienced online. The results of the study revealed that the majority of the students’ preferred learning style is reflected in the technologies they experienced in the online classroom. As the relationship of the technology in use and the students learning style preference in the classroom complements each other, the study revealed that the emphasis of the particular skill-based pedagogy ESL classroom is on receptive skills (listening and reading). The lack of the students’ productive skills (speaking and writing) is a cause for concern to the ESL course instructors, policymakers, and the wider community.

scholarly journals Optimal Hierarchical Learning Path Design With Reinforcement Learning

2020 ◽  
Vol 45 (1) ◽  
pp. 54-70
Author(s):  
Xiao Li ◽  
Hanchen Xu ◽  
Jinming Zhang ◽  
Hua-hua Chang
Keyword(s):  
Reinforcement Learning ◽  
Learning System ◽  
Learning Material ◽  
Optimal Learning ◽  
Model Free ◽  
Learning Path ◽  
The Hierarchical Structure ◽  
E Learning ◽  
Efficient Learning ◽  
Skills Learning

E-learning systems are capable of providing more adaptive and efficient learning experiences for learners than traditional classroom settings. A key component of such systems is the learning policy. The learning policy is an algorithm that designs the learning paths or rather it selects learning materials for learners based on information such as the learners’ current progresses and skills, learning material contents. In this article, the authors address the problem of finding the optimal learning policy. To this end, a model for learners’ hierarchical skills in the E-learning system is first developed. Based on the hierarchical skill model and the classical cognitive diagnosis model, a framework to model various mastery levels related to hierarchical skills is further developed. The optimal learning path in consideration of the hierarchical structure of skills is found by applying a model-free reinforcement learning method, which does not require any assumption about learners’ learning transition processes. The effectiveness of the proposed framework is demonstrated via simulation studies.

scholarly journals A Comprehensive Framework for Adaptive E-Learning Management System

2019 ◽  
Vol 9 (2) ◽  
pp. 4846-4854
Keyword(s):  
Learning Style ◽  
Adaptive Learning ◽  
Learning Algorithm ◽  
Individual Learning ◽  
Learning Abilities ◽  
Learning Path ◽  
E Learning ◽  
The Individual ◽  
Comprehensive Framework ◽  
Learning Types

The various e-Learning systems in recent times found to be ineffective in directing the individual learning style with the preferred learning abilities. Focusing on this inadequacy, this paper proposes a comprehensive study from the different styles on the existing frameworks engaging an adaptive learning algorithm that applies a data stream technique using Machine Learning for a better learning path. The adaptation process insists or allow the user to modify the parameters and to adapt the behaviour according to the system assumption. When the system adapts to a personal concept and responds, it is said to be a personalized process. This concentrate and generates more ideas and style towards student-centric learning and creating a new learning path for an individual or group of learners. This generic framework is grounded on four-dimension. This framework tailors the learning style according to the individual learning types by creating a specific learning objective by incorporating learning modules, personalization and learner Noesis with technologies

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