Pub Date : 2023-09-30DOI: 10.17154/kjal.2023.9.39.3.35
Jonghyun Lee
This study applied sentiment analysis to Ibsen’s “A Doll’s House” to investigate the potential of deep learning-based sentiment analysis in examining the underlying structure of modern drama and to explore optimal strategies for its practical application. Our exploration results underscore the potential of sentiment analysis as a methodology for analysis in literary studies. We utilized three distinct measures to process sentiment scores: mean sentiment scores, moving average sentiment curves, and cumulative sentiment curves. Each of these measures consistently resonated with the play’s themes and content, thereby underscoring their relevance in literary studies. Specifically, mean sentiment scores proved beneficial in encapsulating the overall sentiment profiles of the characters. Moving average sentiment curves excelled in tracing the dynamic fluctuations of sentiment throughout the narrative. Lastly, cumulative sentiment curves offered a comprehensive perspective of sentiment trends across the play. Despite these encouraging findings, the study also highlights the necessity for more refined and context-specific models and techniques for a more accurate and detailed sentiment analysis in literature.
{"title":"Sentiment Analysis on Ibsen’s “A Doll’s House”","authors":"Jonghyun Lee","doi":"10.17154/kjal.2023.9.39.3.35","DOIUrl":"https://doi.org/10.17154/kjal.2023.9.39.3.35","url":null,"abstract":"This study applied sentiment analysis to Ibsen’s “A Doll’s House” to investigate the potential of deep learning-based sentiment analysis in examining the underlying structure of modern drama and to explore optimal strategies for its practical application. Our exploration results underscore the potential of sentiment analysis as a methodology for analysis in literary studies. We utilized three distinct measures to process sentiment scores: mean sentiment scores, moving average sentiment curves, and cumulative sentiment curves. Each of these measures consistently resonated with the play’s themes and content, thereby underscoring their relevance in literary studies. Specifically, mean sentiment scores proved beneficial in encapsulating the overall sentiment profiles of the characters. Moving average sentiment curves excelled in tracing the dynamic fluctuations of sentiment throughout the narrative. Lastly, cumulative sentiment curves offered a comprehensive perspective of sentiment trends across the play. Despite these encouraging findings, the study also highlights the necessity for more refined and context-specific models and techniques for a more accurate and detailed sentiment analysis in literature.","PeriodicalId":114013,"journal":{"name":"Korean Journal of Applied Linguistics","volume":"07 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-09-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135039147","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-09-30DOI: 10.17154/kjal.2023.9.39.3.3
Seungjoo Kim, Josephine Mijin Lee
This study aimed to assess the efficacy of AI chatbots in facilitating meaning negotiation for a group of 40 Grade 1 middle school students in Korea. The experimental group used a voice-enabled ChatGPT, while the control group engaged in peer interactions. The results showed that the ChatGPT group exhibited higher instances of negotiation and speaking turns compared to the peer group. Both groups predominantly utilized the T-I-R-RR routine, with the ChatGPT group, in addition, employing a confirmation and reconfirmation phase. Notably, ChatGPT
{"title":"The Effect of Voice-enabled ChatGPT on Negotiation of Meaning of Korean EFL Learners","authors":"Seungjoo Kim, Josephine Mijin Lee","doi":"10.17154/kjal.2023.9.39.3.3","DOIUrl":"https://doi.org/10.17154/kjal.2023.9.39.3.3","url":null,"abstract":"This study aimed to assess the efficacy of AI chatbots in facilitating meaning negotiation for a group of 40 Grade 1 middle school students in Korea. The experimental group used a voice-enabled ChatGPT, while the control group engaged in peer interactions. The results showed that the ChatGPT group exhibited higher instances of negotiation and speaking turns compared to the peer group. Both groups predominantly utilized the T-I-R-RR routine, with the ChatGPT group, in addition, employing a confirmation and reconfirmation phase. Notably, ChatGPT","PeriodicalId":114013,"journal":{"name":"Korean Journal of Applied Linguistics","volume":"33 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-09-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135039480","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-09-30DOI: 10.17154/kjal.2023.9.39.3.57
Euhee Kim, Keonwoo Koo
The relations between words in natural language are governed by hierarchical structures rather than linear ordering. In recent years, artificial neural network-based language models (LMs) have demonstrated impressive achievements in tasks related to sentence processing. These models benefit from pre-training, which helps enhance their performance. However, our comprehension of the precise syntactic knowledge acquired by these models during sentence processing remains somewhat restricted. This paper examines whether the L2-textbook Seq2Seq (Sequence-to-Sequence) language model processes or transforms sentences based on a syntactic hierarchical inductive bias or a linear inductive bias through transformation tasks. We replicate several previous experiments and explore our model’s capacity to exhibit human-like behavior. Our experiments provide evidence that, in transformation tasks, our pre-trained L2-textbook LSTM-based Seq2Seq model performed based on the linear rule rather than hierarchical rule. In essence, our model showcased a linear inductive bias, consistent with the Scratch-Seq2Seq model.
{"title":"Investigating a Hierarchical Inductive Bias in L2-textbook Seq2Seq Language Model","authors":"Euhee Kim, Keonwoo Koo","doi":"10.17154/kjal.2023.9.39.3.57","DOIUrl":"https://doi.org/10.17154/kjal.2023.9.39.3.57","url":null,"abstract":"The relations between words in natural language are governed by hierarchical structures rather than linear ordering. In recent years, artificial neural network-based language models (LMs) have demonstrated impressive achievements in tasks related to sentence processing. These models benefit from pre-training, which helps enhance their performance. However, our comprehension of the precise syntactic knowledge acquired by these models during sentence processing remains somewhat restricted. This paper examines whether the L2-textbook Seq2Seq (Sequence-to-Sequence) language model processes or transforms sentences based on a syntactic hierarchical inductive bias or a linear inductive bias through transformation tasks. We replicate several previous experiments and explore our model’s capacity to exhibit human-like behavior. Our experiments provide evidence that, in transformation tasks, our pre-trained L2-textbook LSTM-based Seq2Seq model performed based on the linear rule rather than hierarchical rule. In essence, our model showcased a linear inductive bias, consistent with the Scratch-Seq2Seq model.","PeriodicalId":114013,"journal":{"name":"Korean Journal of Applied Linguistics","volume":"60 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-09-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135039457","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-09-30DOI: 10.17154/kjal.2023.9.39.3.71
Young-Joo Lee
The role of raters in performance-based assessment is crucial, but due to the interactions between raters and rating criteria, rater-induced errors often interfere with the accurate evaluations of examinees’ performances. Based on the hypothesis (Eckes, 2012) that severity bias is combined with higher criterion importance and leniency bias is aligned with lower criterion importance, this study investigates the relationship between perceived criterion importance and scoring behavior by employing hierarchical clustering and a Many-facet Rasch analysis. In a survey, 30 in-service secondary Korean English teachers indicated their perceived criterion importance and rated thirty English essays from Yonsei English Learner’s Corpus (YELC). The results of the survey responses and the measures from the MFRM interaction analysis between participants and the rating criteria were applied respectively to form two rater types: cognitive raters types (CRTs), based on criterion perception and operational rater types (ORTs), based on criterion-related bias. The comparison of these two rater types and the analysis of individual rater’s criterion importance rating together with their criterion-related bias measures showed that the hypothesized link between rater criterion perception and rating behavior only existed in content. The findings of the study will provide valuable information for rater training and Korean English teachers evaluating writing performances.
{"title":"Effects of Korean Secondary English Teachers’ Perceived Criterion Importance on Scoring Behavior in L2 Writing Assessment","authors":"Young-Joo Lee","doi":"10.17154/kjal.2023.9.39.3.71","DOIUrl":"https://doi.org/10.17154/kjal.2023.9.39.3.71","url":null,"abstract":"The role of raters in performance-based assessment is crucial, but due to the interactions between raters and rating criteria, rater-induced errors often interfere with the accurate evaluations of examinees’ performances. Based on the hypothesis (Eckes, 2012) that severity bias is combined with higher criterion importance and leniency bias is aligned with lower criterion importance, this study investigates the relationship between perceived criterion importance and scoring behavior by employing hierarchical clustering and a Many-facet Rasch analysis. In a survey, 30 in-service secondary Korean English teachers indicated their perceived criterion importance and rated thirty English essays from Yonsei English Learner’s Corpus (YELC). The results of the survey responses and the measures from the MFRM interaction analysis between participants and the rating criteria were applied respectively to form two rater types: cognitive raters types (CRTs), based on criterion perception and operational rater types (ORTs), based on criterion-related bias. The comparison of these two rater types and the analysis of individual rater’s criterion importance rating together with their criterion-related bias measures showed that the hypothesized link between rater criterion perception and rating behavior only existed in content. The findings of the study will provide valuable information for rater training and Korean English teachers evaluating writing performances.","PeriodicalId":114013,"journal":{"name":"Korean Journal of Applied Linguistics","volume":"45 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-09-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135039318","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-09-30DOI: 10.17154/kjal.2023.9.39.3.103
Sang-su Na, Beomjin Kim
This study developed a method to assess the text level automatically regarding syntactic complexity. The new method was developed by improving the method of measuring the syntactic complexity of large-scale texts with various types. We implemented a Korean sentence syntactic complexity assessment model based on the deep learning models, especially the Korean BERT models. In particular, the KcBERT-based model, fine-tuned through the “National Institute of Korean Language Dependency-Parsed Corpus (v.2.0)”, showed excellent performance with an accuracy of 0.949. This model is expected to contribute to establishing an integrated model to assess the text level as the sub-factor model. By segmenting the text assessment model by factors, it could overcome the limitations of the existing research using unexplainable deep learning models to provide a direction for more sophisticated educational treatment.
{"title":"Implementation of Deep Learning Model-based Korean Sentence Syntactic Complexity Assessment Model","authors":"Sang-su Na, Beomjin Kim","doi":"10.17154/kjal.2023.9.39.3.103","DOIUrl":"https://doi.org/10.17154/kjal.2023.9.39.3.103","url":null,"abstract":"This study developed a method to assess the text level automatically regarding syntactic complexity. The new method was developed by improving the method of measuring the syntactic complexity of large-scale texts with various types. We implemented a Korean sentence syntactic complexity assessment model based on the deep learning models, especially the Korean BERT models. In particular, the KcBERT-based model, fine-tuned through the “National Institute of Korean Language Dependency-Parsed Corpus (v.2.0)”, showed excellent performance with an accuracy of 0.949. This model is expected to contribute to establishing an integrated model to assess the text level as the sub-factor model. By segmenting the text assessment model by factors, it could overcome the limitations of the existing research using unexplainable deep learning models to provide a direction for more sophisticated educational treatment.","PeriodicalId":114013,"journal":{"name":"Korean Journal of Applied Linguistics","volume":"76 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-09-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135039148","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-06-30DOI: 10.17154/kjal.2023.6.39.2.81
M. Ko, Kyung A. Lee
{"title":"University English Speaking Program Evaluation and Improvement","authors":"M. Ko, Kyung A. Lee","doi":"10.17154/kjal.2023.6.39.2.81","DOIUrl":"https://doi.org/10.17154/kjal.2023.6.39.2.81","url":null,"abstract":"","PeriodicalId":114013,"journal":{"name":"Korean Journal of Applied Linguistics","volume":"256 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-06-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123096071","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-06-30DOI: 10.17154/kjal.2023.6.39.2.35
Myeongeun Son
{"title":"The Development of Writing in 5th and 6th Graders of Elementary School through Comparison with 2015 English Curriculum: A Corpus-based Analysis","authors":"Myeongeun Son","doi":"10.17154/kjal.2023.6.39.2.35","DOIUrl":"https://doi.org/10.17154/kjal.2023.6.39.2.35","url":null,"abstract":"","PeriodicalId":114013,"journal":{"name":"Korean Journal of Applied Linguistics","volume":"39 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-06-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126247651","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-06-30DOI: 10.17154/kjal.2023.6.39.2.3
Won-kie Kim
{"title":"How can Artificial Intelligence be Employed for Semantic Prosody Analysis?","authors":"Won-kie Kim","doi":"10.17154/kjal.2023.6.39.2.3","DOIUrl":"https://doi.org/10.17154/kjal.2023.6.39.2.3","url":null,"abstract":"","PeriodicalId":114013,"journal":{"name":"Korean Journal of Applied Linguistics","volume":"23 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-06-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132908775","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-06-30DOI: 10.17154/kjal.2023.6.39.2.55
Jae-Eun Park
{"title":"Visualization of Objects in Mobile Messenger Conversations","authors":"Jae-Eun Park","doi":"10.17154/kjal.2023.6.39.2.55","DOIUrl":"https://doi.org/10.17154/kjal.2023.6.39.2.55","url":null,"abstract":"","PeriodicalId":114013,"journal":{"name":"Korean Journal of Applied Linguistics","volume":"13 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-06-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131982796","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-03-31DOI: 10.17154/kjal.2023.3.39.1.3
{"title":"L1 Transfer in the Acquisition of Word Order in the Adjective-Added Korean Classifier Phrases by L1-Chinese and L1-Russian Children","authors":"","doi":"10.17154/kjal.2023.3.39.1.3","DOIUrl":"https://doi.org/10.17154/kjal.2023.3.39.1.3","url":null,"abstract":"","PeriodicalId":114013,"journal":{"name":"Korean Journal of Applied Linguistics","volume":"418 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-03-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116708032","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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