• Educational Technology International
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• v.25 no.1
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• pp.27-65
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• 2024

The purpose of this study was to identify differences in learning patterns according to content complexity in video-based learning environments and to derive variables that have an important effect on learning achievement within particular learning contexts. To achieve our aims, we observed and collected data on learners' cognitive processes through perceived affordances, using behavioral logs and eye movements as specific indicators. These two types of reaction data were collected from 67 male and female university students who watched two learning videos classified according to their task complexity through the video learning player. The results showed that when the content complexity level was low, learners tended to navigate using other learners' digital logs, but when it was high, students tended to control the learning process and directly generate their own logs. In addition, using derived prediction models according to the degree of content complexity level, we identified the important variables influencing learning achievement in the low content complexity group as those related to video playback and annotation. In comparison, in the high content complexity group, the important variables were related to active navigation of the learning video. This study tried not only to apply the novel variables in the field of educational technology, but also attempt to provide qualitative observations on the learning process based on a quantitative approach.

• English Language & Literature Teaching
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• v.16 no.1
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• pp.171-188
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• 2009

The purpose of this study was to investigate the role of ongoing feedback from the professor in students' processes of learning and developing writing skills. Specifically, the researcher was concerned with how ongoing feedback affected students' attitudes towards writing because in EFL contexts, motivating students to write is a first step to engage them in a challenging journey of academic writing. 20 freshmen taking a writing course, "Paragraph & Essay Writing", at A university participated in this study and they were asked to complete the questionnaire at the end of the spring semester 2009. The results revealed that receiving ongoing feedback from the professor had a positive influence on affective domain, was helpful to develop learning strategies, and was valuable in learning outcomes. However, they also expressed negative opinions: feeling a burden, focusing on forms, and feeling confused. To reflect their opinions, the following four suggestions were made to create a more effective learning environment: promoting learner autonomy, facilitating individual writing conferences, giving balanced feedback in between form and content, and using judicious feedback through careful streaming.

• MALSORI
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• no.66
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• pp.87-103
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• 2008

We describe a new active learning method in conditional random fields (CRFs) framework for keyphrase extraction. To save elaboration in annotation, we use diversity and representative measure. We select high diversity training candidates by sentence confidence value. We also select high representative candidates by clustering the part-of-speech patterns of contexts. In the experiments using dialog corpus, our method achieves 86.80% and saves 88% training corpus compared with those of supervised method. From the results of experiment, we can see that the proposed method shows improved performance over the previous methods. Additionally, the proposed method can be applied to other applications easily since its implementation is independent on applications.

• Journal of KIISE
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• v.43 no.7
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• pp.781-785
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• 2016

Learning from human behaviors in the real world is essential for human-aware intelligent systems such as smart assistants and autonomous robots. Most of research focuses on correlations between sensory patterns and a label for each activity. However, human activity is a combination of several event contexts and is a narrative story in and of itself. We propose a novel approach of human activity prediction based on event cognition. Egocentric multi-sensor data are collected from an individual's daily life by using a wearable device and smartphone. Event contexts about location, scene and activities are then recognized, and finally the users" daily activities are predicted from a decision rule based on the event contexts. The proposed method has been evaluated on a wearable sensor data collected from the real world over 2 weeks by 2 people. Experimental results showed improved recognition accuracies when using the proposed method comparing to results directly using sensory features.

• Journal of The Korean Association For Science Education
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• v.29 no.4
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• pp.400-413
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• 2009

The purpose of this study was to investigate middle school students' processes of argumentation in science lessons and to compare students' argumentation in different contexts (socioscientific context/scientific context). An argumentation-based teaching-learning strategy was used to enhance quality in students' arguments in science lessons. Data were collected from five lessons by video- and audio-recording eight groups of four students each engaging in argumentation. The quality and frequency of students' argumentation was analyzed using an assessment framework based on the work of Toulmin. The findings showed that: (a) there was improvement in the quality of students' argumentation; (b) there were no differences in the structure of argumentation and percentage of explanatory argumentation components as well as dialogic argumentation components in different argumentation contexts. The results of this study showed that students' argumentation can be enhanced with strategic argumentation teaching-learning.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.2
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• pp.538-561
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• 2020

Recommender Systems (RecSys) have a major role in e-commerce for recommending products, which they may like for every user and thus improve their business aspects. Although many types of RecSyss are there in the research field, the state of the art RecSys has focused on finding the user similarity based on sequence (e.g. purchase history, movie-watching history) analyzing and prediction techniques like Recurrent Neural Network in Deep learning. That is RecSys has considered as a sequence prediction problem. However, evaluation of similarities among the customers is challenging while considering temporal aspects, context and multi-component ratings of the item-records in the customer sequences. For addressing this issue, we are proposing a Deep Learning based model which learns customer similarity directly from the sequence to sequence similarity as well as item to item similarity by considering all features of the item, contexts, and rating components using Dynamic Temporal Warping(DTW) distance measure for dynamic temporal matching and 2D-GRU (Two Dimensional-Gated Recurrent Unit) architecture. This will overcome the limitation of non-linearity in the time dimension while measuring the similarity, and the find patterns more accurately and speedily from temporal and spatial contexts. Experiment on the real world movie data set LDOS-CoMoDa demonstrates the efficacy and promising utility of the proposed personalized RecSys architecture.

• Journal of The Korean Association of Information Education
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• v.6 no.1
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• pp.64-74
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• 2002

The purpose of this paper is to review the importance of situated cognition and the features of MOO(Multi-user Object Oriented)environments for effective foreign language learning. Learning foreign languages is beyond simply recalling for the vocabularies or expression usages of targeted languages. As much the same as children naturally acquire their mother languages among active and social interactions with other surrounding people, foreign languages should be told in the circumstances and contexts for authentic applications of foreign languages. The MOO, one of the virtual realities with spatial metaphors on the text basis, has been gaining high attentions from educational fields, thanks to the strong functions of social contexts and learner interactions. This paper approaches the features of MOO as foreign language learning environments, in terms of activity, context and interaction.

• The Journal of the Korea Contents Association
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• v.18 no.5
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• pp.123-130
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• 2018

The present study aims to investigate how Korean EFL learners' views of form-focused instruction, integrated and isolated FFI (form-focused instruction), are related to their beliefs about grammar and attention and how different these relationships are between high and low proficiency levels and between males and females in Korean college contexts. The findings indicated the participants' strong preference for integrated FFI, which was significantly correlated with two factors, attention in English class and English proficiency. On the other hand, the isolated FFI was strongly correlated with their beliefs about grammar learning, that is, independent learning of grammar and importance of learning grammar rules. In conclusion, the integrated FFI was associated with students' proficiency and attention, while the isolated FFI was related to their views of grammar learning. In conclusion, it is suggested that we need to use integrated FFI in Korean EFL contexts considering students' levels of proficiency and attention.

• The Journal of the Convergence on Culture Technology
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• v.7 no.3
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• pp.591-598
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• 2021

It's possible to get the word-vector by the statistical SVD or deep-learning CBOW and LSTM methods and theses ones learn the contexts of forward/backward words or the sequence of following words. It's used to analyze the poems by Ki Hyung-do with similar words recommended by the word-vector showing the core images of the poetry. It seems at first sight that the words don't go well with the images but they express the similar style described by the reference words once you look close the contexts of the specific poems. The word-vector can analogize the words having the same relations with the ones between the representative words for the core images of the poems. Therefore you can analyze the poems in depth and in variety with the similarity and analogy operations by the word-vector estimated with the statistical SVD or deep-learning CBOW and LSTM methods.

• English Language & Literature Teaching
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• v.18 no.3
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• pp.1-24
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• 2012

It has long been shown that Korean EFL students have not practiced extensive reading in school curriculum. Their vocabulary knowledge is limited and a tool for measuring text readability for them has hardly been developed and used. The study aimed to check the current situations on the above issues and develop a reading framework appropriate for extensive reading within the national English curriculum, including the Readability Formula in Korean EFL contexts (KRF). The study consists of four steps. The study does a survey to check the current Korean EFL situations on the issues, suggests a new vocabulary learning size, develops a readability formula as a tool for measuring text difficulty based on the newly suggested vocabulary size, and finally validates the formula with various kinds of English books, including the primary and secondary school English textbooks. It is expected that this study will provide a model for the vocabulary size and the readability index for extensive reading in EFL contexts.