• Journal of English Language & Literature
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• v.55 no.5
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• pp.885-906
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• 2009

In terms of class, race, or gender, critical literacy takes seriously the problem of inequality and injustice embedded in texts. Texts are considered as tools that are used for maintaining the status quo by constructing and communicating our identities, particularly in relation to others. While reading texts and identifying our roles in society, some feel empowered, and others, marginalized. Thus we need to challenge the characterization and the message included in those texts by asking problem-posing questions. In this paper I have demonstrated how to read and teach four versions of "Snow White" from a critical literacy stance. By the use of problem-posing questions, students are led to discover that one of Grimms' fairy tales, the original version of "Snow White," was written from the perspective of men with power, thus marginalizing women in general, as well as the seven dwarfs. Through a critical analysis of Snow White's personality, the typical theme of fairy tales - good is rewarded while evil is punished - should be challenged. In the animation, Snow White and the Seven Dwarfs, power is given to the marginalized people in the original, the seven dwarfs and women in general. In "Snow Night,"a feminist short story, women in general are empowered while men, who should be judged by their looks, are powerless. "Snow-Drop"reminds us of the original, but challenges stereotypes, prejudices, and the theme inherent in the story. In those three stories many parts from the original are rewritten from the perspectives of the marginalized, but still some people are described prejudicially. So students should be guided to write another story from a new perspective. When those four works were taught with problem-posing questions in a university, this approach proved to be quite successful: most students acknowledged the effectiveness of critical literacy in teaching literary works.

• Journal of the Ergonomics Society of Korea
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• v.35 no.4
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• pp.293-305
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• 2016

Objective: This study aims to measure cognitive load levels by analyzing the EEG of Koreans and foreigners, when they read a Korean text with care selected by level from the grammar and vocabulary aspects, and compare the cognitive load levels through quantitative values. The study results can be utilized as basic data for more scientific approach, when Korean texts or books are developed, and an evaluation method is built, when the foreigners encounter them for learning or an assignment. Background: Based on 2014, the number of the foreign students studying in Korea was 84,801, and they increase annually. Most of them are from Asian region, and they come to Korea to enter a university or a graduate school in Korea. Because those foreign students aim to learn within Universities in Korea, they receive Korean education from their preparation for study in Korea. To enter a university in Korea, they must acquire grade 4 or higher level in the Test of Proficiency in Korean (TOPIK), or they need to complete a certain educational program at each university's affiliated language institution. In such a program, the learners of the Korean language receive Korean education based on texts, except speaking domain, and the comprehension of texts can determine their academic achievements in studying after they enter their desired schools (Jeon, 2004). However, many foreigners, who finish a language course for the short-term, and need to start university study, cannot properly catch up with university classes requiring expertise with the vocabulary and grammar levels learned during the language course. Therefore, reading education, centered on a strategy to understand university textbooks regarded as top level reading texts to the foreigners, is necessary (Kim and Shin, 2015). This study carried out an experiment from a perspective that quantitative data on the readers of the main player of reading education and teaching materials need to be secured to back up the need for reading education for university study learners, and scientifically approach educational design. Namely, this study grasped the difficulty level of reading through the measurement of cognitive loads indicated in the reading activity of each text by dividing the difficulty of a teaching material (book) into eight levels, and the main player of reading into Koreans and foreigners. Method: To identify cognitive loads indicated upon reading Korean texts with care by Koreans and foreigners, this study recruited 16 participants (eight Koreans and eight foreigners). The foreigners were limited to the language course students studying the intermediate level Korean course at university-affiliated language institutions within Seoul Metropolitan Area. To identify cognitive load, as they read a text by level selected from the Korean books (difficulty: eight levels) published by King Sejong Institute (Sejonghakdang.org), the EEG sensor was attached to the frontal love (Fz) and occipital lobe (Oz). After the experiment, this study carried out a questionnaire survey to measure subjective evaluation, and identified the comprehension and difficulty on grammar and words. To find out the effects on schema that may affect text comprehension, this study controlled the Korean texts, and measured EEG and subjective satisfaction. Results: To identify brain's cognitive load, beta band was extracted. As a result, interactions (Fz: p =0.48; Oz: p =0.00) were revealed according to Koreans and foreigners, and difficulty of the text. The cognitive loads of Koreans, the readers whose mother tongue is Korean, were lower in reading Korean texts than those of the foreigners, and the foreigners' cognitive loads became higher gradually according to the difficulty of the texts. From the text four, which is intermediate level in difficulty, remarkable differences started to appear in comparison of the Koreans and foreigners in the beginner's level text. In the subjective evaluation, interactions were revealed according to the Koreans and foreigners and text difficulty (p =0.00), and satisfaction was lower, as the difficulty of the text became higher. Conclusion: When there was background knowledge in reading, namely schema was formed, the comprehension and satisfaction of the texts were higher, although higher levels of vocabulary and grammar were included in the texts than those of the readers. In the case of a text in which the difficulty of grammar was felt high in the subjective evaluation, foreigners' cognitive loads were also high, which shows the result of the loads' going up higher in proportion to the increase of difficulty. This means that the grammar factor functions as a stress factor to the foreigners' reading comprehension. Application: This study quantitatively evaluated the cognitive loads of Koreans and foreigners through EEG, based on readers and the text difficulty, when they read Korean texts. The results of this study can be used for making Korean teaching materials or Korean education content and topic selection for foreigners. If research scope is expanded to reading process using an eye-tracker, the reading education program and evaluation method for foreigners can be developed on the basis of quantitative values.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2022.10a
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• pp.81-83
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• 2022

Understanding research trends is necessary to select research topics and explore related works. Most researchers search representative keywords of interesting domains or technologies to understand research trends. However some conferences in artificial intelligence or data mining fields recently publish hundreds to thousands of papers for each year. It makes difficult for researchers to understand research trend of interesting domains. In our paper, we propose an automatic technology keyphrase extraction method to support researcher to understand research trend for each conference or journal. Keyphrase extraction that extracts important terms or phrases from a text, is a fundamental technology for a natural language processing such as summarization or searching, etc. Previous keyphrase extraction technologies based on pretrained language model extract keyphrases from long texts so performances are degraded in short texts like titles of papers. In this paper, we propose a techonolgy keyphrase extraction model that is robust in short text and considers the importance of the word.

• The Journal of Korean Association of Computer Education
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• v.19 no.2
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• pp.99-114
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• 2016

The transient information effect occurs when long and complex transient information disappear before the learner has time to adequately process it or link it with new information. This study aimed to explore the impact of the transient information effect on multimedia learning efficiency within the cognitive load perspective and how segmentation and pacing of instructional materials interact with the transient information effect. The results revealed that the visualonly instruction(a diagram with long and complex texts) was more efficient than the audiovisual instruction(a diagram with long and complex spoken texts). The overall results suggested that using long and complex spoken texts with a diagram can have a negative impact on learning unless the transient information effect are reduced through segmentation and learner-paced instructions.

• Journal of Convergence for Information Technology
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• v.8 no.3
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• pp.145-152
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• 2018

This study aims to investigate the effects of literary texts as a teaching tool to enhance college students' English communicative competence both in linguistic aspects and affective ones. The control group used only the course book as study material, whereas the target group read four short stories along with it and engaged in a series of follow-up tasks. To measure their English competence, the researcher had both groups take a pre-test and a post-test, compared the results, and analyzed the data using SPSS. The study indicates that though the target students' post-test scores increased, the result failed in reaching a significant level. Nevertheless, reading and discussing literature facilitated the target students' affective aspects of communication. This article points out some other limitations of utilizing literary texts in language teaching and suggests the need for further research to deal with the issues.

• Journal of Popular Narrative
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• v.25 no.4
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• pp.397-428
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• 2019

Fantasy emerges from the cracks and crevices of rational reality. Italo Calvino says, "Fantasy is possible when the reader stays at a certain distance without falling into the text." Fantasy does not form farthest from reality. It comes from the confusion between reality and fiction. In short, fantasy does not exist on the contrary of reality, but on the boundary of reality. Reality and fantasy are also structurally intertwined. We can't distinguish the reality from fantasy clearly. In fact, in this case, the reader or audience is confused about whether what I see is real or not. Todorov calls this case "hesitation." Hesitation is a key element of fantasy. Two texts that expressed "hesitation" are Kim Young-ha's short novel Vampire (1997) and Wes Anderson's film The Grand Budapest Hotel (2014). On the surface, these two texts seem to have nothing to do with narrative structural similarities. And both also arouse readers' and audiences' interest by letting confuse reality to fantasy. In Kim Young-ha's Vampire, we can look at the process of confusion of reality called "narrative infection" when a text is read to the reader. In the movie The Grand Budapest Hotel, we can find a strategy to make an unreal story feel like a fact in history. And we can also find a process in which the success stories of alienated characters become reality through 'solidarity' in the film. This paper is a study of how fantasy creates "reality", makes readers feel fantasy, and how it spreads through these two texts.

• Journal of Internet Computing and Services
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• v.20 no.2
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• pp.93-100
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• 2019

Recently, in various business fields, companies are concentrating on providing chatbot services to various environments by adding artificial intelligence to existing messenger platforms. Organizations in the field of job placement also require chatbot services to improve the quality of employment counseling services and to solve the problem of agent management. A text-based general chatbot classifies input user sentences into learned sentences and provides appropriate answers to users. Recently, user sentences inputted to chatbots are inputted as short texts due to the activation of social network services. Therefore, performance improvement of short text classification can contribute to improvement of chatbot service performance. In this paper, we propose T-EBOW (Translation-Extended Bag Of Words), which is a method to add translation information as well as concept information of existing researches in order to strengthen the short text classification for employment chatbot. The performance evaluation results of the T-EBOW applied to the machine learning classification model are superior to those of the conventional method.

• Journal of the Korean BIBLIA Society for library and Information Science
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• v.27 no.1
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• pp.237-261
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• 2016

This study analyzed readers' responses of children of families with immigration background on children's literature that describes similar life experiences with the readers, based on Brooks & Browne's Culturally Situated Reader Response Theory. Six children between 10 and 16 met the researcher three times each, and read along four different texts about multiculturalism in Korea. The texts include On the Road Together, a picture book, and three short stories in The Black Egg. Participating children showed various ethnic identities - identity as a Korean; identity as a foreigner; identity between a Korean and a foreigner; identity as a child of a multicultural (bicultural) family. The children empathized with the characters or showed their frustrations against racism portrayed in the texts. The four texts used in this study worked as a mirror that reflects each child's own self, and further allowed the children to contemplate their own identities and speak out about their deepest thoughts and feelings. The children were dissatisfied with the main characters' powerlessness and depressing endings of the stories. They wanted the characters with immigration background to be positive and bright, and expected stories about peaceful relationship between children of families with immigration background and children with non-immigration background.

• Proceedings of the Korea Information Processing Society Conference
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• 2018.05a
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• pp.331-334
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• 2018

비정형 데이터의 대표적인 형태 중 하나인 텍스트 데이터 기계학습은 다양한 산업군에서 활용되고 있다. NOTAM 은 하루에 수 천개씩 생성되는 항공전문으로써 현재는 사람의 수작업으로 분석하고 있다. 기계학습을 통해 업무 효율성을 기대할 수 있는 반면, 축약어가 혼재된 단문이라는 데이터의 특성상 일반적인 분석에 어려움이 있다. 본 연구에서는, 데이터의 크기가 크지 않고, 축약어가 혼재되어 있으며, 문장의 길이가 매우 짧은 문서들을 군집화하는 방법을 제안한다. 주제를 기준으로 문서를 분류하는 LDA 와, 단어를 k 차원의 벡터공간에 표현하는 Word2Vec 를 활용하여 잡음이 포함된 단문 데이터에서도 효율적으로 문서를 군집화 할 수 있다.

• Journal of information and communication convergence engineering
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• v.21 no.1
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• pp.9-16
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• 2023

The natural language on social network platforms has a certain front-to-back dependency in structure, and the direct conversion of Chinese text into a vector makes the dimensionality very high, thereby resulting in the low accuracy of existing text classification methods. To this end, this study establishes a deep learning model that combines a big data ultra-deep convolutional neural network (UDCNN) and long short-term memory network (LSTM). The deep structure of UDCNN is used to extract the features of text vector classification. The LSTM stores historical information to extract the context dependency of long texts, and word embedding is introduced to convert the text into low-dimensional vectors. Experiments are conducted on the social network platforms Sogou corpus and the University HowNet Chinese corpus. The research results show that compared with CNN + rand, LSTM, and other models, the neural network deep learning hybrid model can effectively improve the accuracy of text classification.