• Communications of Mathematical Education
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• v.37 no.2
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• pp.105-134
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• 2023

The purpose of this study is to explore which performance verbs are used in the achievement standards of the Korean mathematics curriculum and how to improve them. So, first, we analyzed whether there were differences in the performance verbs included in the 2015 revised mathematics curriculum achievement standards by school level. In addition, it was analyzed whether there were differences in the performance verbs included in the mathematics curriculum in Korea and foreign countries. As a result of the analysis, both the frequency and the type of performance verbs included in the achievement standards of the Korean mathematics curriculum decreased as the school level increased. Also, performative verbs such as 'understand' and 'know' were excessively used. Similar tendencies were seen in foreign mathematics curricula, but the frequency and the type of performance verbs were higher than those in Korea, and various performance verbs were used. As a result of the study, it is suggested that performance verbs included in achievement standards need to be improved to improve middle and high school mathematics classes.

• English Language & Literature Teaching
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• v.12 no.4
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• pp.31-68
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• 2006

The present research investigates the acquisition of the English locative alternation by Korean EFL learners, which poses a learnability paradox, taking Pinker's framework of learnability theory as its basis. It addresses two questions (1) how lexical knowledge is represented initially and at different levels of interlanguage development and (2) what kinds of difficulty Korean learners find in the acquisition of English locative verbs and their constructions. Three groups of learners at different proficiency levels with a control group of English native speakers are examined by two instruments: elicited production task and grammaticality judgment task. According to different levels of proficiency, the learners exhibit gradual sensitivity to a change-of-state meaning and obtain complete perception of the meanings of locative verbs (manner-of-motion and change-of-state) and their constructions. Overgeneralization errors are observed in their performance. The errors are due to misinterpretations of particular lexical items in conjunction with the universal linking rules. More fundamental cause of difficulty is accounted for by partial use of learning mechanisms, caused by insufficient L2 input.

• Korean Journal of Cognitive Science
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• v.27 no.4
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• pp.573-597
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• 2016

Recent fMRI and EEG research for neural representations of action concepts insist that processing of action concepts evoke the simulation of sensory-motor information. Moreover, there are several behavioral studies showing that understanding of action verbs or sentences describing actions interfere or facilitate current action performance. However, it is unclear that online interaction between processing of action concepts and current action is based on the simulation of sensory-motor information, or other neural mechanisms. The present research aims to explore the underlying neural mechanism that how the perception of action language influence the performance of current action using high-spacial temporal resolution EEG and multiple source analysis techniques. For this, participants were asked to perform a cued-motor reaction task in which button-pressing hand action and pedal-stepping foot action were required according to the color of the cue, and we presented auditorily action verbs describing the responding actions (i.e., /press/, /step/, /stop/) just before the color cue and examined the interaction effect from the semantic congruency between the action verbs and the current action. Behavioral results revealed consistently a facilitatory effect when action verbs and responding actions were semantically congruent in both button-pressing and pedal-stepping actions, and an inhibitory effect when semantically incongruent in the button-pressing action condition. In the results of EEG source waveform analysis, the semantic congruency effects between action verbs and the responding actions were observed in the Wernicke's area during the perception of action verbs, in the anterior cingulate gyrus and the supplementary motor area (SMA) at the time when the motor-cue was presented, and in the SMA and primary motor cortex (M1) during action execution stage. Based on the current findings, we argue that perceived action verbs evoke the facilitation/inhibition effect by influencing the expectation and preparation stage of following actions rather than the directly activating the particular motor cortex. Finally we discussed the implication on the neural representation of action concepts and methodological limitations of the current research.

• Journal of The Korean Association For Science Education
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• v.40 no.2
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• pp.163-175
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• 2020

The purpose of this study is to propose a method for analyzing suitable achievement standards for the nature of science curriculum. This can be done by introducing various analysis methods, as well as using practical examples to analyze the achievement standards that are the starting point for teaching and learning in the 2015 revised curriculum. In this paper, three methods are shown: ① the method suggested by the Gyeonggido Office of Education, ② the method using understanding verbs of backward design, ③ the method using Bloom's revised taxonomy. In addition, we propose a method to analyze the achievement standards of science curriculum utilizing the characteristics of science curriculum. This method takes advantage of the above three analysis methods. After separating the content and performance verbs, subdividing the performance verbs into the performance verbs of six aspects of understanding and restatement of the achievement standards, the restatement of achievement standards enabled the analysis of in-depth achievement standards by linking to a process-focused assessment plan considering the level of thinking by utilizing the two-dimensional framework of Bloom's revised taxonomy. Through this study, I hope that elementary school teachers will develop meaningful teaching and learning methods that utilize the essence of the subject through in-depth analysis of the achievement standards of science as a subject.

• Journal of the Korean Institute of Intelligent Systems
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• v.16 no.1
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• pp.124-129
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• 2006

This parer presents a method of ranking translation word selection for Korean verbs based on lexical knowledge contained in a bilingual Korean-English dictionary and WordNet that are easily obtainable knowledge resources. We focus on deciding which translation of the target word is the most appropriate using the measure of semantic relatedness through the 45 extended relations between possible translations of target word and some indicative clue words that play a role of predicate-arguments in source language text. In order to reduce the weight of application of possibly unwanted senses, we rank the possible word senses for each translation word by measuring semantic similarity between the translation word and its near synonyms. We report an average accuracy of $51\%$ with ten Korean ambiguous verbs. The evaluation suggests that our approach outperforms the default baseline performance and previous works.

• The Journal of Korean Association of Computer Education
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• v.5 no.2
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• pp.11-19
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• 2002

In this paper, we present a simple statistical method for performing word sense disambiguation(WSD), specially for Korean transitive verbs, based on a supervised learning algorithm. This approach combines a set of indicators based on syntactic relations between surrounding words and an ambiguous verb. Experiments with 10 Korean verbs show that accuracy performance of our WSD method using indicators based on syntactic relations is 27% higher than the baseline performance. Moreover, our method using weighting mechanism based on each indicator type is 12% higher than a method which uses only an unordered set of surrounding words in the context.

• Journal of the Korean earth science society
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• v.34 no.7
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• pp.711-726
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• 2013

The purpose of this study was to investigate how congruently the learning objectives of Earth Science I textbooks match the 2009 revised Earth Science curriculum. For this purpose, we classified the learning objectives of curriculum and textbooks were into three factors including ability, cross-cutting concepts, and behavioral verbs. The text data were analyzed using the semantic network analysis method. The results are as follows. The learning objectives of textbooks with regard to ability factors mainly emphasized the cognitive and affective domain. In addition, the ability of inquiry performance was emphasized in the learning objective of the curriculum. The textbooks used various sub-frame of cross-cutting concepts in comparison with the curriculum. Both textbooks and curriculum used the term 'comprehension' the most as behavioral verbs. However, most behavioral verbs just remained at the level of cognitive system.

• Journal of Information Processing Systems
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• v.7 no.3
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• pp.459-472
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• 2011

The vast number of biomedical literature is an important source of biomedical interaction information discovery. However, it is complicated to obtain interaction information from them because most of them are not easily readable by machine. In this paper, we present a method for extracting biomedical interaction information assuming that the biomedical Named Entities (NEs) are already identified. The proposed method labels all possible pairs of given biomedical NEs as INTERACTION or NO-INTERACTION by using a Maximum Entropy (ME) classifier. The features used for the classifier are obtained by applying various NLP techniques such as POS tagging, base phrase recognition, parsing and predicate-argument recognition. Especially, specific verb predicates (activate, inhibit, diminish and etc.) and their biomedical NE arguments are very useful features for identifying interactive NE pairs. Based on this, we devised a twostep method: 1) an interaction verb extraction step to find biomedically salient verbs, and 2) an argument relation identification step to generate partial predicate-argument structures between extracted interaction verbs and their NE arguments. In the experiments, we analyzed how much each applied NLP technique improves the performance. The proposed method can be completely improved by more than 2% compared to the baseline method. The use of external contextual features, which are obtained from outside of NEs, is crucial for the performance improvement. We also compare the performance of the proposed method against the co-occurrence-based and the rule-based methods. The result demonstrates that the proposed method considerably improves the performance.

• The KIPS Transactions:PartB
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• v.18B no.4
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• pp.241-248
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• 2011

Homographs can have multiple senses. In order to understand the meaning of a sentence, it is necessary to identify which sense isused for each word in the sentence. Previous researches on this problem heavily relied on the word co-occurrence information. However, we noticed that in case of verbs, information about subordinating cases of verbs can be utilized to further improve the performance of word sense disambiguation. Different senses require different sets of subordinating cases. In this paper, we propose the verb sense disambiguation using subordinating case information. The case information acquire postposition features in Standard Korean Dictionary. Our experiment on 12 high-frequency verb homographs shows that adding case information can improve the performance of word sense disambiguation by 1.34%, from 97.3% to 98.7%. The amount of improvement may seem marginal, we think it is meaningful because the error ratio reduced to less than a half, from 2.7% to 1.3%.

• Journal of KIISE:Software and Applications
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• v.37 no.12
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• pp.946-950
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• 2010

Many sentiment categorization systems based on machine learning methods use morphological analyzers in order to extract linguistic features from sentences. However, the morphological analyzers do not generally perform well in a customer review domain because online customer reviews include many spacing errors and spelling errors. These low performances of the underlying systems lead to performance decreases of the sentiment categorization systems. To resolve this problem, we propose a feature extraction method based on simple longest matching of Eojeol (a Korean spacing unit) and phoneme patterns. The two kinds of patterns are automatically constructed from a large amount of POS (part-of-speech) tagged corpus. Eojeol patterns consist of Eojeols including content words such as nouns and verbs. Phoneme patterns consist of leading consonant and vowel pairs of predicate words such as verbs and adjectives because spelling errors seldom occur in leading consonants and vowels. To evaluate the proposed method, we implemented a sentiment categorization system using a SVM (Support Vector Machine) as a machine learner. In the experiment with Korean customer reviews, the sentiment categorization system using the proposed method outperformed that using a morphological analyzer as a feature extractor.