• Journal of the Korea Society of Computer and Information
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• v.28 no.5
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• pp.189-196
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• 2023

This study aims to show that "Computer-assisted language learning (CALL)" and "Mobile-based language learning (MALL)" actually influence education, deviating from the traditional "drill and practice" method in foreign language education and learning due to the development of information and communication technology (IT). Specifically, for first-year college students who have relatively poor English skills and do not feel enough motivation for English learning, I will produce educational video content using multimedia authoring tools and upload it to the e-learning system. Video content is configured to be accessed and utilized through various media such as computers, smartphones, tablets, laptops, etc. Ultimately, an exploration of educational value behind the utilization of IT devices in English language Teaching(ELT) and the Second Language Acquisition (SLA) theory behind effective instructional use of such technology are presented. That is to say, the effectiveness of language learning using information and communication technology (IT) is introduced. The article closes by suggesting how to use computers and mobile media for 'Flipped Learning'.

• Journal of Digital Convergence
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• v.15 no.5
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• pp.345-351
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• 2017

The international status of the Korean language has been elevated as the demand for studying the language among foreign students has grown sharply over the past few years. Unfortunately, foreign students face difficulties in learning the language, conflicts are also deepening between Korean and foreign students. Using Erin Sander's design research spiral, this paper investigates foreigners' Korean language learning experiences, identify the main cognitive and affective factors influencing their learning process. Research findings collected with the design analysis revealed needs and insights that offer opportunities relevant specifically for the conception, design and development of new products and services related to Korean language learning.

• Language and Information
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• v.7 no.1
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• pp.87-99
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• 2003

This paper investigates the role of input frequency in the acquisition of verb argument structures based on distributional information of a corpus of utterances derived from the English CHILDES database (MacWhinney 1993). It has been widely accepted that children successfully learn verb argument structures by innate language mechanisms, such as linking rules which connect verb meanings and its syntactic structures. In contrast, an approach to language acquisition called “statistical language learning” has currently claimed that children could succeed in acquiring syntactic structures in the absence of innate language mechanisms, making use of distributional properties of the input. In this paper, I evaluate the feasibility of the statistical learning in acquiring verb argument structures, based on distributional information about locative verbs in parental input. The naturalistic data allow us to investigate to what extent the statistical learning approach can and cannot help children succeed in learning the syntax of locative verbs. Based on the results of English database analysis, I show that there is rich statistical information for learning the syntactic possibilities of locative verbs in parental input, despite some limitations in the statistical learning approach.

• Journal of Korean language education
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• v.29 no.4
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• pp.65-92
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• 2018

This study explored how a particular social media can be used to supplement elementary-level Korean language course in the US public university. The researchers administered a survey measuring students' patterns and habits of social media use. Based on the survey results, researchers designed six different types of learning materials and uploaded them regularly to Instagram throughout the semester. At the end of the semester, a survey was conducted to find out students' satisfactory level. From the 44 students' responses, the study found out that using Instagram 1) is more accessible to students than any other learning management system, 2) is fun and students are willing to participate, 3) increased the target language exposure and authentic language use, 4) increased interaction between teachers, students and even other native speakers, and 5) is helpful to improve listening and other language skills. The study closes with the suggestion for further experimental studies.

• Educational Technology International
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• v.14 no.1
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• pp.41-53
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• 2013

On the basis of two premises and embodied cognition theory, the vibration tactile learning is proposed as an effective method for foreign language learning. The premises are: the real nature of language is sound and the source of sound is vibration. According to embodied cognition theory, cognition is inherently connected to bodily sensation rather than metaphysical and independent. As a result, the vibration tactile learning is: people are able to learn foreign language better by listening to sound and experiencing its vibration through touch rather than solely listening to sound. The effectiveness of vibration tactile learning is tested with two instructional media theories: media comparison and media attribute. For the comparison, an experiment is conducted with control and experimental groups. The attributes of vibration tactile media are investigated in points of relationships with the learning process. The experiment results indicate a small effect on the increased mean score. Three kinds of relationships are found between the media attribute and learning process: enforced stimulus, facilitated pronunciation, and assimilation of resonance to sound patterns through touch. Finally, this paper proposes a new theoretical development for instructional media research: an embodied cognition based media research and development.

• Journal of Korea Multimedia Society
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• v.24 no.1
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• pp.117-124
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• 2021

Korean education in China began at Peking University in the 1950s. At present, The Korean language education in China has made remarkable progress in many aspects such as scale, scope, level and achievement. In addition, with the increasingly frequent economic and cultural exchanges or cooperation between China and South Korea and the increasing trend of internationalization, the prosperity of Korean wave culture and the sound development of China-South Korea relations, the country's demand for Korean language talents is increasing day by day. However, with the rise of Korean education in China in recent years, some hidden problems also surfaced. In this paper, the Korean language proficiency test(TOPIK) is used to evaluate the Korean language proficiency of Korean learners, and Chinese juniors are used to evaluate the Korean language proficiency. In addition, a questionnaire survey was conducted to analyze the learning media of Chinese Korean learners at the present stage, and the relationship between learning media and learning outcomes was concluded. At the same time, deficiencies and problems existed in Korean education in colleges and universities were proposed and their own ideas were put forward.

• KIPS Transactions on Software and Data Engineering
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• v.11 no.8
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• pp.325-330
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• 2022

This paper conducts the collection and experiment of datasets for deep learning research on sign language such as sign language recognition, sign language translation, and sign language segmentation for Korean sign language. There exist difficulties for deep learning research of sign language. First, it is difficult to recognize sign languages since they contain multiple modalities including hand movements, hand directions, and facial expressions. Second, it is the absence of training data to conduct deep learning research. Currently, KETI dataset is the only known dataset for Korean sign language for deep learning. Sign language datasets for deep learning research are classified into two categories: Isolated sign language and Continuous sign language. Although several foreign sign language datasets have been collected over time. they are also insufficient for deep learning research of sign language. Therefore, we attempted to collect a large-scale Korean sign language dataset and evaluate it using a baseline model named TSPNet which has the performance of SOTA in the field of sign language translation. The collected dataset consists of a total of 11,402 image and text. Our experimental result with the baseline model using the dataset shows BLEU-4 score 3.63, which would be used as a basic performance of a baseline model for Korean sign language dataset. We hope that our experience of collecting Korean sign language dataset helps facilitate further research directions on Korean sign language.

• Research in Mathematical Education
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• v.17 no.3
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• pp.169-180
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• 2013

Communicating about mathematics is an essential component in learning mathematics and is a key standard for successful learning in a mathematics classroom using stories and storytelling as a catalyst to mathematics instruction. This, however, can make learning math for students with language deficiencies since they are working toward mastering both basic language proficiency as well as the specialized language needed for mathematics. This is a particular concern because the number of students of multicultural families is rapidly increasing. In this paper, we discuss the challenges and complexities of language-deficient students learning math in a classroom where communication is a key standard for successful learning, and suggest implications for teaching, by presenting an USA elementrny teacher's scaffolding to make reading and solving word problems less intimidating for her language learner students as well as native speaking students.

• Electronics and Telecommunications Trends
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• v.35 no.3
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• pp.9-19
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• 2020

Recently, a technique for applying a deep learning language model pretrained from a large corpus to fine-tuning for each application task has been widely used as a language processing technology. The pretrained language model shows higher performance and satisfactory generalization performance than existing methods. This paper introduces the major research trends related to deep learning pretrained language models in the field of language processing. We describe in detail the motivations, models, learning methods, and results of the BERT language model that had significant influence on subsequent studies. Subsequently, we introduce the results of language model studies after BERT, focusing on SpanBERT, RoBERTa, ALBERT, BART, and ELECTRA. Finally, we introduce the KorBERT pretrained language model, which shows satisfactory performance in Korean language. In addition, we introduce techniques on how to apply the pretrained language model to Korean (agglutinative) language, which consists of a combination of content and functional morphemes, unlike English (refractive) language whose endings change depending on the application.

• Journal of the Korea Society of Computer and Information
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• v.29 no.9
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• pp.69-77
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• 2024

This study evaluates the performance of second language acquisition models learning Korean and English using the GPT-2-Small model, analyzing the impact of various training conditions on performance. Four training conditions were used: monolingual learning, sequential learning, sequential-interleaved learning, and sequential-EWC learning. The model was trained using datasets from the National Institute of Korean Language and English from BabyLM Challenge, with performance measured through PPL and BLiMP metrics. Results showed that monolingual learning had the best performance with a PPL of 16.2 and BLiMP accuracy of 73.7%. In contrast, sequential-EWC learning had the highest PPL of 41.9 and the lowest BLiMP accuracy of 66.3%(p < 0.05). Monolingual learning proved most effective for optimizing model performance. The EWC regularization in sequential-EWC learning degraded performance by limiting weight updates, hindering new language learning. This research improves understanding of language modeling and contributes to cognitive similarity in AI language learning.