Vocabulary Learning System Research Articles

Design of an English vocabulary e-learning recommendation system based on word bag model and recurrent neural network algorithm

This article takes learning English vocabulary as the foundation, constructs precise classification strategies, and designs a recommendation system for English vocabulary learning. This article constructs a recommendation system for English vocabulary learning based on the word bag calculation model and recursive neural network calculation method, which has great significance, and also conducts in-depth research on this system. Thus, a classification calculation method based on the word bag calculation model was proposed. The calculation method in this paper is different from traditional calculation methods, and the classification accuracy in this paper is higher. Meanwhile, recurrent neural networks themselves have one or more feedback loops that can feed back information from the neural network to other neural networks, resulting in recurrent networks with different structures. After a series of research results, it has been found that the SIFT method takes longer to extract than the SURF method, and the number of extracted features is relatively large. Therefore, the recommendation system for English vocabulary learning proposed in this article can be improved according to the different needs of users, in order to better meet their individual requirements.

Development of a novel robot-assisted vocabulary learning system using pure synthetic data

This study investigates the application of deep learning methods trained on synthetic data for the robust detection of vocabulary flashcards, an essential aspect of robot-assisted language learning (RALL). Despite its importance, flashcard detection has not been extensively researched in RALL systems, and it poses significant challenges due to the extensive data collection and annotation needed, especially given the large number of classes involved. These models need to generalize well to different real-world environments. To address these issues, a novel robotic platform designed for flashcard-based vocabulary learning is proposed, supported by a synthetic data generation pipeline using high dynamic range images (HDRIs) and synthetic human actors. The proposed pipeline offers an efficient data generation method and significantly enhances model generalisability to various environments. The proposed method was evaluated with five object detection models based on several challenging real-world datasets, each containing more than 200 class labels. The object detection models trained based on the proposed synthetic datasets (HDRI and HDRI+Humans) demonstrated outstanding performance, achieving median mean average precision (mAP) scores of 0.797 and 0.778. The proposed method achieves this performance without needing to be trained with real data. A comprehensive analysis comparing the proposed method with other synthetic data generation techniques is presented, and its potential for improving vocabulary flashcard detection in RALL systems is highlighted. The data and models are available at https://github.com/aimlab-mu/aimrobot.

Intelligent Recommendation System for English Vocabulary Learning – Based on Crowdsensing

Abstract With the advent of the artificial intelligence era, the traditional methods of online learning can no longer meet people’s personalised needs. Take the English vocabulary memory APP, which is widely used in the market of learning software, as an example. At present, there are various factors that make it difficult for learners to improve their learning efficiency, reduce their learning enthusiasm and enhance their learning effects. Therefore, in this paper, the application of machine learning algorithm in intelligent recommendation of English vocabulary learning is studied, and an intelligent recommendation system for English vocabulary learning based on crowdsensing is established. In its functional module, machine learning algorithms such as clustering algorithm, word vector training and collaborative filtering recommendation are used to realise the intelligent recommendation in the system. Finally, accurate resources of recommendation for user groups with different needs, interest characteristics and abilities improves the efficiency of English vocabulary learning.

A Study on the Development of Korean Vocabulary Learning System Using Periodic Repetitive Method: Focusing on the criteria for selecting vocabulary for learning and information construction method

목적 본 연구의 목적은 유학생의 학업 수학 능력을 향상하는 데 일조할 수 있는 웹 기반 방식의 시스템을 개발하는 방안에 대해 논하는 데 있다. 이 과정에서 특히 학습용 어휘를 선정하는 기준과 정보를 구축하는 방법, 주의점 등을 집중적으로 논하고자 하였다. 방법 한국어 어휘 학습 시스템 개발은 학습 환경을 ‘분석’하고, 시스템과 콘텐츠를 ‘설계’하며, 설계한 내용을 기반으로 구체적인 ‘개발’에 들어가는 과정을 거친다. 본 연구에서 제안하는 어휘 학습 시스템은 ‘주기적인 반복’을 할 수 있도록 설계하였는데, 학습자의 요구를 조사하여 하루 학습량 및 학습 시간, 어휘 정보의 제시 범위 등을 결정하였고, 이를 시스템 설계 시 반영하였다. 결과 연구와 개발 과정을 통해 인지적인 변별 과정을 통한 학습 어휘 재설정, 주기적인 반복, 게임과 같은 흥미 요소의 결합 등을 반영한 어휘 학습 시스템이 설계되었다. 한국어 어휘 학습 시스템 설계 시 어휘의 제시 범위 선정, 다의어 처리 방법, 학습용 어휘 번역 정보 구축 방안, 학습용 예문 구성 방안 등에 대해 심도 깊은 논의가 이루어졌다. 결론 본고에서 제안하는 어휘 학습 시스템은 학습자의 자가 인지 과정을 통해 아는 어휘와 모르는 어휘를 구분한 뒤 모르는 어휘 학습에 집중하게 하고, 주기적인 반복을 통해 망각을 최소화함으로써 중고급 단계의 무수히 많은 어휘를 빠르게 습득할 수 있도록 도움을 줄 수 있다. 어휘 학습 시스템을 설계하고 개발하는 한국어교육 연구자들은 어휘를 선정하고 제시하는 방안에 대해 지속적으로 연구를 진행하여야 한다. 또한 학습 효과 증빙과 온/오프라인 결합 수업, 다양한 유형의 어휘 학습 시스템 개발에 대해서도 지속적으로 추가 연구가 이루어질 필요가 있다.

Constructing a Word-embedding-based Computer Assisted English Vocabulary Teaching and Learning System

Constructing a Word-embedding-based Computer Assisted English Vocabulary Teaching and Learning System

Effects of performance goal orientations on learning performance and in‐game performance in digital game‐based learning

AbstractBackgroundPerformance goal orientations are influential motivational factors for predicting learning performance. However, a lack of attention has been paid to investigating the effects of performance goal orientations on learning performance and in‐game performance in the context of digital game‐based learning.ObjectivesThis study implemented a game‐based English vocabulary learning system and investigated how performance goal orientations affected learners' learning performance and in‐game performance.MethodsA total of 59 non‐English major university students participated in this study, divided into performance‐approach learners (PAPL) and performance‐avoidance learners (PAVL) based on their performance goal orientations. The English vocabulary listening test and log data were collected for conducting quantitative analyses.Results and conclusionsThe results showed that the PAPL outperformed the PAVL in learning performance, whereas the two groups demonstrated similar gain scores and overall in‐game performance. Moreover, the results showed that the PAVL's learning performance was strongly associated with all aspects of in‐game performance in the learning activities. Conversely, the PAPL's learning performance was only associated with two aspects of in‐game performance in the competition activities.ImplicationsThe findings of this study suggest that performance goal orientations play significant roles in both learning performance and in‐game performance, which could benefit the PAVL's in‐game performance, which is a substantial factor in promoting their learning performance via DGBL.

Balancing cognitive complexity and gaming level: Effects of a cognitive complexity-based competition game on EFL students' English vocabulary learning performance, anxiety and behaviors

Digital game-based language learning promotes motivation and enables learners to immerse themselves in learning. However, some gaming elements (e.g., competition and challenge) or learning content (e.g., difficulty levels) may have different influences on different learners, especially those with low self-efficacy or academic achievement, as competitive games may lead to frustration. It is therefore important to take students' cognitive capacities into consideration when designing a competitive learning environment, and to provide them with learning content of appropriate cognitive complexity. In the current study, a game-based situational vocabulary learning system that integrated a cognitive complexity-based competition strategy was developed to provide learners with appropriate tasks. A quasi-experiment was conducted in a high school English course to evaluate the effectiveness of the proposed approach. It was found that, compared to the conventional situational gaming approach, the situational game with the cognitive complexity-based competition strategy significantly improved the participants’ learning performance (in particular, that of the low-achieving students), but it also increased their anxiety. Furthermore, the behavioral analysis showed that the students who learned with the proposed approach accomplished the tasks more smoothly, because the system could take into account players' learning performance and adjust the cognitive complexity of the following tasks through upgrading or downgrading the learners' gaming levels to ensure that individual students learned with tasks at appropriate levels for them. On the other hand, the participants who learned with the conventional game-based learning approach had a greater tendency to fail the game repeatedly. Based on the findings and relevant studies, we also discuss suggestions for future research.

English Central

English Central is an online software program designed to teach various skills of conversation and the basic vocabulary of English. The program is available in 11 different languages, including Chinese, Turkish, Arabic, Spanish, Portuguese, and Korean. Non-native English speakers can use one of these languages to access the website and its various learning materials. According to the program’s homepage (www.englishcentral.com), English Central is a leading provider of online conversation solutions, combining the Internet’s best English videos, a proprietary Intelligent Speech Assessment Technology, an adaptive vocabulary learning system, and live tutors, all of which are delivered seamlessly to computers and mobile devices.
 Users enjoy a welcome lesson, and every topic in the course’s platform contains at least ten units that have comprehensive lessons in conversation. The software also offers different activities for grammar, vocabulary, pronunciation, reading, writing, and speaking. Each activity focuses on a particular sort of conversation arising in everyday life, such as those associated with business engagements, social interactions, travel, academic encounters, and so on. Those who initiate a lesson but then stop prior to its completion can complete the exercise at a later point. The program will mark their placement and remind them where to resume their training.

The effectiveness of using in-game cards as reward

The research team has developed a web-based multiplayer trading card game to allow teachers choosing cards as rewards for students who actively participate in discussions and classroom activities as well as perform well in terms of doing assignments and writing exams or quizzes. In order to verify the effectiveness of the use of in-game cards as rewards, the research team integrated the trading card game into a web-based English vocabulary learning system. Students can receive cards as rewards every time after they use the learning system. A 6-week experiment had been conducted at an elementary school with 172 fifth-grade students. The results showed that boys have higher intention of getting the in-game cards as rewards. The research also showed that the use of the in-game cards as educational rewards not only motivates students to use the vocabulary learning system but also improves their learning outcome. The research result supported the recommended process for teachers to adopt the trading card game in their courses.

学び方が変化するロボットとの共同学習がもたらすLearning by Observingの実現可能性

This paper sought to examine how behavior of a robot can prompt learning by observing in collaborative learning. The robot learns while solving a problem issued by an English vocabulary learning system with a human learner. The learning system presents English words in example sentences and uses a scaffolding function that helps the learner guess the meaning of English words in the example sentence upon a user request. The robot was designed to solve the questions by using scaffolding function and could not answer correctly at beginning. However, the robot change its question-answering method by guessing the meanings of English words in example sentences and improve its accuracy as learning progressed. This behavior of robot can prompt learners to learn by observing in collaborative learning. Ten college students with low level English learned using the English vocabulary learning system with robot for two months and were videoed during that time to see how they learned. We found that learners learned the English vocabulary by using scaffolding function at beginning. However, learners changed their learning method form using scaffolding function to guessing the meanings of English words in English sentences by learning progress. This suggests that robot, which changes the question-solving method to a more effective one and increases its accuracy rate as learning progress, prompts learners to learning by observing in collaborative learning and change their learning method to the more effective one. This learning by observing indicates that learners learn how to guess the meanings of English words in English sentences by observing the robot’s question-solving and speaking. However, the robot does not prompt some learners to learning by observing because they feel lousy that the robot answers the question and improves its accuracy rate, so they ignore what the robot says. Additionally, learners interest in robot decrease when robot performs the same action.

A System for English Vocabulary Acquisition based on Code-Switching

Vocabulary plays an important part in second language learning and there are many existing techniques to facilitate word acquisition. One of these methods is code-switching, or mixing the vocabulary of two languages in one sentence. In this paper the authors propose an experimental system for computer-assisted English vocabulary learning in context using a code-switching based approach for Japanese learners. First they introduce the CO-MIX system, an English vocabulary teaching system that uses code-switching for vocabulary acquisition. Next, they show how they utilize incidental learning techniques with graded readers to increase language proficiency. The authors present the system architecture, underlying technologies, and evaluate the system's performance through user interaction with both a baseline and the proposed system by using a semantic differential scale. They also perform separate factor analysis of participants' attitudes for both systems, an analysis of users' mistakes and compare users' language tests scores. Finally, the authors discuss the evaluation results and further development of this technology.

Effects of CALL on Self-directed FL Vocabulary Learning

This paper focuses on whether computer technologies could help to create a better learning environment for FL vocabulary learners in China, activating their utilization of various vocabulary learning strategies and thereby enhancing self-directed vocabulary learning (SDVL). A vocabulary learning system called Learning Vocabulary In Domain was developed especially for this research purpose. In the judgmental analysis, students’ satisfaction levels to the vocabulary learning conditions under the computer-based mode and paper-based mode were statistically compared and discussed. As a result, the CALL mode was more favorable to the students during their self-directed learning. The superiority of CALL was further reinforced by the empirical analysis of comparing the students’ vocabulary performances under the two learning modes.

A Learning Environment for English Vocabulary Using Quick Response Codes

AbstractThis study focuses on the process of developing a learning environment that uses tablets and Quick Response (QR) codes to enhance participants' English language vocabulary knowledge. The author employed the concurrent triangulation strategy, a mixed research design. The study was conducted at a private school in Izmir, Turkey during the 2012-2013 academic year. The study sample was determined using the criterion sampling method. The criterion for selection was participants' possession of a mobile device. There were a total of 22 participants including one English teacher in the study, of which 12 were female and 10 male. The students' knowledge of English vocabulary was pretested using the Vocabulary Check List (VCL). During eight classes, participants completed English vocabulary activities using QR codes and tablet PCs. This learning environment integrated digital learning materials and real learning objects using QR codes. After the activities, students' knowledge of English vocabulary was again tested using the VCL, and the participants' opinions about the learning environment were solicited using semi-structured interviews. The research's qualitative data were analyzed using a descriptive analysis. The quantitative data were analyzed using the Wilcoxon signed-rank test and web analysis programs. The study found that the participants' overall rate of completing learning activities was low. The results of the VCL post-test indicated that participants' English language vocabulary knowledge had increases significantly. Participants' opinions regarding the learning environment were analyzed, and it was determined that although they had faced a few problems with the equipment, they experienced a general feeling of curiosity and excitement while using the environment. They found the environment entertaining and reinforcing, stating that learning environments of this kind should be used in other courses, too. The participant teacher stated that although the environment was effective there were a number of time management issues and caused difficulties in classroom management.Keywords: QR Codes * U-Learning * Ubiquitous learning * Learning English * Learning vocabularyIn the present day, English is one of the most important languages spoken, often finding itself as the second language in many countries whose native language is not English. In English language education, a variety of methods, techniques, and technologies are used to develop reading, listening, and speaking skills. As the popularity of using these new technologies increases, it has become increasingly important to provide learners with opportunities to learn English without restrictions of time or location.Language learning is based on vocabulary acquisition. Since students need to know the right words to express their thoughts without difficulty (Huang et al., 2012), considerable research on vocabulary learning has been done. With the development of computers and multimedia environments, a wide range of studies have used multimedia technologies, audio texts, and graphics to support vocabulary learning (Kim & Gilman, 2008; Sun & Dong, 2004). Mobile, wireless, and sensor technologies have been gradually integrated into educational activities, which has led to the establishment of learning environments that include high mobility and context awareness. Researchers have noticed that mobile and wireless technologies, such as multimedia technologies, are popular in language education. Chen and Chung (2008) developed an individualized mobile vocabulary learning system using palmtop computers. Huang et al. (2012) developed a u-learning system for English vocabulary, called UEVL (Ubiquitous English Vocabulary Learning). Laroussi (2004) developed a cyber-classroom called Ubi-Learn based on U-Learning in which he conducted a language course allowing students not only to attend in person or via a distance learning environment, but also to use computers or any mobile device in the class. …

Cognitive Web-based Vocabulary Learning System: The Results of a Pilot Test of Learning Greek as a Second or Foreign Language

In this paper we present cognitive mechanisms (applied and validated at various levels of the protocol stack) for supporting smart applications and services towards users. More specifically, we introduce the results of a pilot test that took place as an application of web-based learning systems. The instance used was the example of linguistics and more specifically the cognitive vocabulary learning system. In the context of this pilot the aim was to test if and how a web-based vocabulary learning system may indeed improve the learning process. More specifically, the focus was put on detecting the student's performance after taking a personalised course and a set of exercises/activities. The learning styles, the vocabulary level of each student and his/her technical background have been taken into consideration in developing the learning material. In the paper we showcase the results of this pilot test, when taking activities fully dependent on the environment. The statistical analysis of the results shows that the final success rate of the students in the exercises referring to the form, the meaning and the use of the vocabulary increases significantly.

Collaborative filtering for expansion of learner’s background knowledge in online language learning: does “top-down” processing improve vocabulary proficiency?

In recent years, collaborative filtering, a recommendation algorithm that incorporates a user’s data such as interest, has received worldwide attention as an advanced learning support system. However, accurate recommendations along with a user’s interest cannot be ideal as an effective learning environment. This study aims to develop and evaluate an online English vocabulary learning system using collaborative filtering that allows learners to learn English vocabulary while expanding their interests. The online learning environment recommends English news articles using information obtained from other users with similar interests. The learner then studies these recommended articles as a method of learning English. The results of a two-month experiment that compared this system to an earlier collaborative filtering system called “GroupLens” reveal that learners who used the collaborative filtering system developed in this study read various news articles and had significantly higher scores on topic-specific vocabulary tests than did those who used the previous system.

Developing and Evaluating an Adaptive Business English Self-Learning System for EFL Vocabulary Learning

This paper developed an adaptive Business English self-learning system for EFL vocabulary learning. The components of word reoccurrence and learner engagement have been built into the system where the amount of unknown word reexposure in various customized texts increases and vocabulary enhancement tasks are added to promote learner engagement with wanted words. To evaluate the system effectiveness on EFL vocabulary learning, the experimental group read system-screened texts with immediate and repeated contacts with individuals’ unknown words and performed vocabulary tasks specific to those unknown words, while the control group read online texts without unknown word reoccurrence and vocabulary practice. After one semester, these two groups were measured by one online vocabulary test, and an online user satisfaction investigation was also administered to the experimental group. The study found that the experimental group reading customized texts to reexpose to previously encountered unknown words in different texts along with doing individualized vocabulary exercises performed significantly better in EFL vocabulary learning than the other group. It was also found that the system was appealing for the learners to show positive attitudes toward the use of the system. The study demonstrated that the constructed adaptive Business English self-learning system could effectively promote vocabulary growth.

Initiating Functional Vocabulary Learning for Mental Retardation Students with Educational Technology Approach

This study developed functional vocabulary learning system for mental retardation students to assist three moderate ones enrolled in special education classes of vocational schools, and discusses the learning effect of the within and extra fading strategies. And the alternative treatment design of the single subject experiment design was adopted to evaluate the effectiveness of the learning system. The teaching strategy adopted photos of physical goods as cues combined with the fading strategy within a stimulus-control process. After experiment, this study has the preliminary result: Stimulus fading strategies can assist functional vocabulary learning in moderate mental retardation students enrolled in special education classes of vocational schools; learning achievement with the extra fading strategy exceeded that with the within fading strategy.

Investigating an intelligent system for vocabulary learning through reading

Investigating an intelligent system for vocabulary learning through reading

Mixed methods in developmental research

Developmental research is widely used in instructional development which tends to use different data collection methods. The research questions of an instructional development study can be looked at from different angles andusing different methods to approach its research questions. This paper presents an analysis of a developmental research study by Ma (2012), which comprised eleven research questions. Ma sstudy developed from Phase One: identifying the target group scurrent vocabulary learning strategies and vocabulary level, to Phase Two: identifying the characteristics of a vocabulary learning system, to Phase Three: designing a vocabulary learning modulefor Chinese EFL learners. Ma used a mixture of qualitative and quantitative methods to give the depth and breadth to the development of her instructional module. Ma's study is distinctively a developmental research employing a mixed methods approach.

英単語学習システムにおける足場かけ使用による学習能力の変化

英単語学習システムにおける足場かけ使用による学習能力の変化