Development of Adaptive Kanji Learning System for Mobile Phone

2010 ◽  
Vol 8 (4) ◽  
pp. 29-41 ◽  
Author(s):  
Mengmeng Li ◽  
Hiroaki Ogata ◽  
Bin Hou ◽  
Satoshi Hashimoto ◽  
Yuqin Liu ◽  
...  
Keyword(s):  
Language Learning ◽  
Mobile Phone ◽  
Learning Style ◽  
Adaptive Learning ◽  
Learning Systems ◽  
Learning System ◽  
Difficulty Level ◽  
Proficiency Level ◽  
Main Emphasis ◽  
Adaptive Learning System

This paper describes an adaptive learning system based on mobile phone email to support the study of Japanese Kanji. In this study, the main emphasis is on using the adaptive learning to resolve one common problem of the mobile-based email or SMS language learning systems. To achieve this goal, the authors main efforts focus on three aspects: sending the contents to a learner following his or her interests, adjusting the difficulty level of the tests to suit the learner’s proficiency level, and adapting the system to his or her learning style. Additionally, this system has already been evaluated by the learners and the results show that most of them benefited from the system and would like to continue using it.

Development of Adaptive Kanji Learning System for Mobile Phone

2012 ◽  
pp. 181-192
Author(s):  
Mengmeng Li ◽  
Hiroaki Ogata ◽  
Bin Hou ◽  
Satoshi Hashimoto ◽  
Yuqin Liu ◽  
...  
Keyword(s):  
Language Learning ◽  
Mobile Phone ◽  
Learning Style ◽  
Adaptive Learning ◽  
Learning Systems ◽  
Learning System ◽  
Difficulty Level ◽  
Proficiency Level ◽  
Main Emphasis ◽  
Adaptive Learning System

This paper describes an adaptive learning system based on mobile phone email to support the study of Japanese Kanji. In this study, the main emphasis is on using the adaptive learning to resolve one common problem of the mobile-based email or SMS language learning systems. To achieve this goal, the authors main efforts focus on three aspects: sending the contents to a learner following his or her interests, adjusting the difficulty level of the tests to suit the learner’s proficiency level, and adapting the system to his or her learning style. Additionally, this system has already been evaluated by the learners and the results show that most of them benefited from the system and would like to continue using it.

scholarly journals Designing and modeling of a multi-agent adaptive learning system (MAALS) using incremental hybrid case-based reasoning (IHCBR)

2020 ◽  
Vol 10 (2) ◽  
pp. 1980
Author(s):  
El Ghouch Nihad ◽  
Kouissi Mohamed ◽  
En-Naimi El Mokhtar
Keyword(s):  
Learning Style ◽  
Adaptive Learning ◽  
Active Agent ◽  
Learning Systems ◽  
Learning System ◽  
Case Based Reasoning ◽  
Dynamic Learning ◽  
Multi Agent ◽  
Adaptive Learning System ◽  
Case Based

Several researches in the field of adaptive learning systems has developed systems and techniques to guide the learner and reduce cognitive overload, making learning adaptation essential to better understand preferences, the constraints and learning habits of the learner. Thus, it is particularly advisable to propose online learning systems that are able to collect and detect information describing the learning process in an automatic and deductive way, and to rely on this information to follow the learner in real time and offer him training according to his dynamic learning pace. This article proposes a multi-agent adaptive learning system to make a real decision based on a current learning situation. This decision will be made by performing a hypride cycle of the Case-Based Reasonning approach in order to follow the learner and provide him with an individualized learning path according to Felder Silverman learning style model and his learning traces to predict his future learning status. To ensure this decision, we assign at each stage of the Incremental Hybrid Case-Based Reasoning at least one active agent performing a particular task and a broker agent that collaborates between the different agents in the system.

scholarly journals Adaptive Learning Systems and Interference in Causal Inference

2021 ◽  
Author(s):  
Alexander Olof Savi ◽  
Nick ten Broeke ◽  
Abe Dirk Hofman
Keyword(s):  
Causal Inference ◽  
Adaptive Learning ◽  
External Validity ◽  
Learning Systems ◽  
Learning System ◽  
Adaptive Learning System ◽  
Adaptive Learning Systems

Adaptive learning systems can be susceptible to between-subject cross-condition interference by design. This interference has important implications for the implementation and evaluation of A/B tests in such systems, as it obstructs causal inference and hurts external validity. We illustrate the problem in an Elo based adaptive learning system, discuss sources and degrees of interference, and provide solutions, using an example in the study of dropout.

The Learning Style-Based Adaptive Learning System Architecture

2015 ◽  
Vol 5 (2) ◽  
pp. 1-10 ◽  
Author(s):  
Chyun-Chyi Chen ◽  
Po-Sheng Chiu ◽  
Yueh-Min Huang
Keyword(s):  
Learning Styles ◽  
Learning Style ◽  
Adaptive Learning ◽  
System Architecture ◽  
Learning System ◽  
Learning Materials ◽  
Learning Path ◽  
Different Types ◽  
Learning System Architecture ◽  
Adaptive Learning System

In the current study of learning process that show learners will take a different way and use different types of learning resources in order to learning better. Any many researchers also agree that learning materials must be able to meet the various learning styles of learners. Therefore, let learners can effective to improve their learning, for different learning styles of learners should be given different types of learning materials. In this paper the authors propose a learner's learning style-based adaptive learning system architecture that is designed to help learners advance their on-line learning along an adaptive learning path. The investigation emphasizes the relationship of learning content to the learning style of each participant in adaptive learning. An adaptive learning rule was developed to identify how learners of different learning styles may associate those contents which have the higher probability of being useful to form an optimal learning path. In this adaptive learning system architecture, it will according to different learning styles given different types of learning materials and will according to learner's profile to adjust learner's learning style for providing suitable learning materials.

scholarly journals SCIENCE EDUCATION ADAPTIVE LEARNING SYSTEM AS A COMPUTER-BASED SCIENCE LEARNING WITH LEARNING STYLE VARIATIONS

2018 ◽  
Vol 17 (4) ◽  
pp. 711-727 ◽  
Author(s):  
Zulfiani Zulfiani ◽  
Iwan Permana Suwarna ◽  
Sujiyo Miranto
Keyword(s):  
Learning Styles ◽  
Learning Style ◽  
Adaptive Learning ◽  
Science Learning ◽  
Learning System ◽  
Learning Material ◽  
Learning Approaches ◽  
Slow Learners ◽  
Computer Based ◽  
Adaptive Learning System

Students with their different learning styles also have their own different learning approaches, and teachers cannot simultaneously facilitate them all. Teachers’ limitation in serving all students’ learning styles can be anticipated by the use of computer-based instructions. This research aims to develop ScEd-Adaptive Learning System (ScEd-ASL) as a computer-based science learning media by accommodating students’ learning style variations. The research method used is a mixed method at junior high schools in Tangerang Selatan. The final product of the research is a special learning media appropriate to students’ visual, aural, read/write and kinesthetic learning styles. The uniqueness of the media is its form of integrated science materials, accommodating fast and slow learners, and appropriate to their learning styles. ScEd-Adaptive Learning System as a developed computer-based science learning media was declared as good and valid by four media experts and five learning material experts. ScEd-ALS for kinesthetic style has a high effectivity to improve students learning mastery (100%), consecutively aural (63%), read/write (55%), and visual (20%). This media development can be continued with the Android version or iOS to make it more operationally practical. Keywords: adaptive learning system, science learning media, computer-based instruction, learning style.

The Learning Style-Based Adaptive Learning System Architecture

2016 ◽  
pp. 608-618
Author(s):  
Chyun-Chyi Chen ◽  
Po-Sheng Chiu ◽  
Yueh-Min Huang
Keyword(s):  
Learning Styles ◽  
Learning Style ◽  
Adaptive Learning ◽  
System Architecture ◽  
Learning System ◽  
Learning Materials ◽  
Learning Path ◽  
Different Types ◽  
Learning System Architecture ◽  
Adaptive Learning System

In the current study of learning process that show learners will take a different way and use different types of learning resources in order to learning better. Any many researchers also agree that learning materials must be able to meet the various learning styles of learners. Therefore, let learners can effective to improve their learning, for different learning styles of learners should be given different types of learning materials. In this paper the authors propose a learner's learning style-based adaptive learning system architecture that is designed to help learners advance their on-line learning along an adaptive learning path. The investigation emphasizes the relationship of learning content to the learning style of each participant in adaptive learning. An adaptive learning rule was developed to identify how learners of different learning styles may associate those contents which have the higher probability of being useful to form an optimal learning path. In this adaptive learning system architecture, it will according to different learning styles given different types of learning materials and will according to learner's profile to adjust learner's learning style for providing suitable learning materials.

scholarly journals Benefits of Adaptive Learning Transfer from Typing-Based Learning to Speech-Based Learning

2021 ◽  
Author(s):  
Thomas Wilschut ◽  
Florian Sense ◽  
Maarten van der Velde ◽  
Zafeirios Fountas ◽  
Sarah Maass ◽  
...  
Keyword(s):  
Language Learning ◽  
Real Time ◽  
Word Learning ◽  
Adaptive Learning ◽  
Learning Algorithm ◽  
Foreign Language Learning ◽  
Learning Systems ◽  
Learning System ◽  
Learning Performance ◽  
Adaptive Learning Systems

Memorising vocabulary is an important aspect of formal foreign-language learning. Advances in cognitive psychology have led to the development of adaptive learning systems that make vocabulary learning more efficient. One way these computer-based systems optimize learning is by measuring learning performance in real time to create optimal repetition schedules for individual learners. While such adaptive learning systems have been successfully applied to word learning using keyboard-based input, they have thus far seen little application in spoken word learning. Here we present a system for adaptive, speech-based word learning using an adaptive model that was developed for and tested with typing-based word learning. We show that typing- and speech-based learning result in similar behavioral patterns that can be used to reliably estimate individual memory processes, and we extend earlier findings demonstrating that a response-time based adaptive learning system outperforms an accuracy-based, Leitner flashcard learning algorithm. In short, we show that adaptive learning benefits transfer from typing-based learning, to speech based learning. Our work provides a basis for the development of language learning applications that use real-time pronunciation assessment software to score the accuracy of the learner's pronunciations. The development of adaptive, speech-based learning applications is important for two reasons. First, by focusing on speech, the model can be applied for individuals whose typing skills are insufficient---as is demonstrated by the successful application of the model in an elderly participant population. Second, speech-based learning models are educationally relevant because they focus on what may be the most important aspect of language learning: to practice speech.

scholarly journals Interactive monitoring and assessment of knowledge based on an adaptive learning system

2018 ◽  
Vol 19 (12) ◽  
pp. 1051-1054
Author(s):  
Lyudmyla Dzhuguryan
Keyword(s):  
Learning Process ◽  
Adaptive Learning ◽  
Learning Systems ◽  
Learning System ◽  
Technical Aspects ◽  
Software Products ◽  
Knowledge Based ◽  
Adaptive Learning System ◽  
Adaptive Learning Systems

The article deals with the problems, disadvantages and advantages of using adaptive learning systems in interactive monitoring and assessment of knowledge. Methodical and technical aspects of interactive monitoring and assessment of knowledge based on the adaptive learning system are defined. The schemes of the algorithms based on which the learning process with simultaneous interactive monitoring and assessment of knowledge is realized is offered. Recommendations on the use of software products for the implementation of interactive monitoring and assessment of knowledge based on an adaptive learning system are proposed.

Sign in / Sign up

Export Citation Format

Share Document