• Educational Technology International
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• v.17 no.2
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• pp.203-228
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• 2016

This study was designed to determine the factors affecting learner satisfaction and examine the relationships of these factors in mobile learning linked to pre-existing e-learning in universities. In the structural model used, three mobile learning quality factors are the endogenous variables, namely, system quality (SYQ), information quality (INQ) and service quality (SEQ) perceived by students, and learner satisfaction (LS), whereas students' self-efficacy (SE) and experience (EX) in mobile learning are the exogenous variables. The subjects were 900 students who registered for mobile learning courses offered by a private university in Seoul, Korea. The results indicated that SE in mobile learning had positive effects on SYQ, INQ, and SEQ. Furthermore, SE influenced LS when analyzed without quality factors as parameters. Mobile learning EX directly affected INQ, but not SYQ or SEQ. EX likewise had a direct effect on LS when analyzed without quality factors as parameters. Meanwhile, both SYQ and INQ showed a positive effect on LS, but not SEQ. SE and EX affected LS indirectly when SYQ and INQ were used as parameters. This study addresses the importance of increasing SE, EX, SYQ, and INQ to increase LS in mobile learning in universities

• Journal of KIISE:Software and Applications
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• v.30 no.10
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• pp.983-991
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• 2003

The Web-based instruction on the internet provides lots of learners with the related information and knowledge beyond time and space. But in the Web-based instruction, there is a problem that the teaming process statuses for learners can be known only through an exam. This paper introduces a web monitoring method to check whether the learner has some problems in learning process and to be able to find out the students with the problems. In the method this paper proposes a learning time prediction model for predicting the proper next study time intervals based on the learner`s learning times and grades on Previous learning units. This method provides the educator with the learning Process statuses for learners. The Loaming prediction model for web-based monitoring can be used to stimulate learners to take the good teaming processes by sending automatically alerting messages if their real teaming times exceeds on his predicted learning time interval. The results of the estimation through case study on the web-based monitoring to use the teaming time prediction model show that most of on-line learners with Poor teaming process statuses get poor grades. In addition, the results show that learner`s poor habits keep going on without change.

• Journal of The Korean Association For Science Education
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• v.15 no.3
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• pp.284-290
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• 1995

This study examined the effects of the learning cycle model by learner's characteristics such as I.Q., cognitive levels, inquiry skins, cognitive style, activity, reflectiveness. To see the effects of the learning cycle model, nonequivalent control group pretest-posttest multiple treatment designs was used in the study. 99 middle school second-graders(female) were divided into two groups. One group was selected as the experimental group (n=50), the other served at the comparison group(n=49). During the eight-month period, the students in the experimental group were instructed according to the learning cycle model, while the students in the comparison group were instructed according to the traditional instruction methods. Achievement data from science achievement test were analyzed by an ANOVA technique. The results of the study are as follows : 1. Science knowledge achievement. For the lower level students of activity, the learning cycle model is superior to the traditional approaches in science knowledge achievement. 2. Science inquiry skills. For the upper level students of I.Q., cognitive levels, inquiry skills, cognitive style and reflectiveness, the learning cycle model is superior to the traditional approaches in science inquiry skills. 3. Attitudes toward science. For the lower level students of I.Q., cognitive levels, inquiry skills, cognitive style, activity and reflectiveness, the learning cycle model is superior to the traditional approaches in attitudes toward science.

• Journal of Information Technology Services
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• v.7 no.4
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• pp.231-246
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• 2008

This paper suggests an e-learning system model, a goal-driven personalized e-learning system, which increase the effectiveness of learning. An e-learning system following this model makes the learner choose the learning goal. The learner's choice would lead learning. Therefore, the system enables a personalized adaptive learning, which will raise the effectiveness of learning. Moreover, this paper proposes a SCORM standard, which modifies SCORM 2004 that has been insufficient to implement the "goal driven personalized e-learning system." We add a data model representing the goal that motivates learning, and propose a standard for statistics on learning objects usage. We propose each standard for contents model and sequencing information model which are parts of "goal driven personalized e-learning system." We also propose that manifest file should be added for the standard for contents model, and the file which represents the information of hierarchical structure and general learning paths should be added for the standard for sequencing information model. As a result, the system could sequence and search learning objects. We proposed an e-learning system and modified SCORM standards by considering the many factors of adaptive learning. We expect that the system enables us to optimally design personalized e-learning system.

• The Journal of Korean Association of Computer Education
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• v.8 no.6
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• pp.55-63
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• 2005

The purpose of this study is to explore which factors influence the performance of computer practice-education in vocational high schools. We collected 604 response data from total 7 vocational high schools in Seoul City to test empirical analysis using SEM(Structural Equation Modeling) frequently used in social-science area. According to our results, all independent variables(learner's response learner's motivation, learner's attitude, learning contents, intention to learn, learner's ability and learning behavior) were found positively influencing learning performance of students. Based upon them we contributed our research model to combine TRA theory in psychology with Holton theory for academic implications. And also, from the perspective of practical implication, we can expect that our results will provide some useful guidelines for operating effective computer-practice education.

• The KIPS Transactions:PartB
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• v.8B no.6
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• pp.595-600
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• 2001

Recently, WBI model which is based on web has been proposed in the part of the new activity model of teaching-learning. The demand for the customized coursewares which is required from the learners is increased, the needs of the efficient and automated education agents in the web-based instruction are recognized. But many education systems that had been studied recently did not service fluently the courses which learners had been wanting and could not provide the way for the learners to study the learning weakness which is observed in the continuous feedback of the course. In this paper we propose design of multi-agent system for course scheduling of learner-oriented using weakness analysis algorithm. First, proposed system monitors learner's behaviors constantly, evaluates them, and calculates his accomplishment. From this accomplishment, the multi-agent schedules the suitable course for the learner. The learner achieves an active and complete learning from the repeated and suitable course.

• Asia Pacific Journal of Corpus Research
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• v.5 no.1
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• pp.23-36
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• 2024

This research centers on the Taiwan Eye-Movement Corpus of Spanish (TECS), a specially created corpus comprising eye-tracking data from Chinese-speaking learners of Spanish as a third language in Taiwan. Its primary purpose is to explore the broad utility of TECS in understanding language learning processes, particularly the initial stages of language learning. Constructing this corpus involves gathering data on eye-tracking, reading comprehension, and language proficiency to develop a machine-learning model that predicts learner behaviors, and subsequently undergoes a predictability test for validation. The focus is on examining attention in input processing and their relationship to language learning outcomes. The TECS eye-tracking data consists of indicators derived from eye movement recordings while reading Spanish sentences with temporal references. These indicators are obtained from eye movement experiments focusing on tense verbal inflections and temporal adverbs. Chinese expresses tense using aspect markers, lexical references, and contextual cues, differing significantly from inflectional languages like Spanish. Chinese-speaking learners of Spanish face particular challenges in learning verbal morphology and tenses. The data from eye movement experiments were structured into feature vectors, with learner behaviors serving as class labels. After categorizing the collected data, we used two types of machine learning methods for classification and regression: Random Forests and the k-nearest neighbors algorithm (KNN). By leveraging these algorithms, we predicted learner behaviors and conducted performance evaluations to enhance our understanding of the nexus between learner behaviors and language learning process. Future research may further enrich TECS by gathering data from subsequent eye-movement experiments, specifically targeting various Spanish tenses and temporal lexical references during text reading. These endeavors promise to broaden and refine the corpus, advancing our understanding of language processing.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.17 no.3
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• pp.364-372
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• 2016

This study examined the multi-phrased effects and outcomes of adult female learners who participated in lifelong learning activities, as well as the proposed structural relationships among the five latent variables. Questions established to achieve the purpose of the study are as follow: What effects do the learner's characteristics, lifelong education institutions, learning flow, and learning satisfaction have on the learning come? The participants of the survey numbered 632, but 54 respondents who were unreliable or did not complete their survey were excluded. A total of 578 cases were analyzed for this research. The structural relationships among the five latent variables-learner's characteristics, lifelong education institutions, learning flow and learning satisfaction, and learning outcome of the adult female learners-AMOS 18.0 program were also used for structural analysis. The major findings of this research are as follows. First, the model fitness showed that the hypothetical model provided a reasonable fit to the data ${\chi}^2=224.267$ (df=69, p<.001), RMSEA=.062, TLI=.943, RFI=.920, CFI=.957, IFI=.957, NFI=.939. Second, the learner's characteristics ( =.218, p<.001) and lifelong education institutions ( =.301, p<.001) have a direct effect on the learning outcomes. The learning flow ( =-.149 p=.541) does not have a direct effect on the learning outcome. Learning satisfaction ( =.405 p<.001) have a direct effect on the learning outcome. To put findings above together, in respect to adult female learners' performances, the learning outcomes are influenced directly by the learner characteristics, conditions of the lifelong education institutions, and learning satisfaction, whereas satisfaction indirectly affects the learners' learning outcome.

• Journal of The Korean Association of Information Education
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• v.21 no.5
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• pp.583-593
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• 2017

In order to overcome the difficulties of programming education for beginners, various research strategies such as UMC(Use-Modify-Create), design based learning, discovery learning and play learning are applied. In this study, we developed a HVC(History-VR Coding-Collaboration) learning strategy model for the improvement of learner's computational thinking. The HVC model is composed of a combination module of block type. We developed a 12th session storytelling - based virtual reality programming curriculum. As a result, HVC model and SW education program showed significant difference in improvement of learner's computational thinking.

• The Journal of Korean Association of Computer Education
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• v.6 no.1
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• pp.65-77
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• 2003

This paper presents a model for supporting the adaptive interaction between the computer and the learner. To design an adaptive interaction model, the strategy to support the adaptive interaction in the web-based educational system was established. And then. the necessary components for executing each strategy were selected. Also. the logical relations among the components were verified. To verify the effectiveness of the proposed adaptive interaction model, we applied the existing web-based courseware and the new courseware using the adaptive interaction models to two groups respectively, and then measured the performance of each group. Experimental results reveal that the adaptive interaction model actually has positive effects on the learning activities of the learner.