• Asia Pacific Journal of Corpus Research
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• v.2 no.1
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• pp.35-45
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• 2021

With the wide spread of the Common European Framework of Reference (CEFR) scales, many studies attempt to apply them in routine teaching and rater training, while more evidence regarding criterial features at different CEFR levels are still urgently needed. The current study aims to explore complexity features that distinguish and predict CEFR proficiency levels in oral performance. Using a quantitative/corpus-based approach, this research analyzed lexical and syntactic complexity features over 80 transcriptions (includes A1, A2, B1 CEFR levels, and native speakers), based on an interview test, Standard Speaking Test (SST). ANOVA and correlation analysis were conducted to exclude insignificant complexity indices before the discriminant analysis. In the result, distinctive differences in complexity between CEFR speaking levels were observed, and with a combination of six major complexity features as predictors, 78.8% of the oral transcriptions were classified into the appropriate CEFR proficiency levels. It further confirms the possibility of predicting CEFR level of L2 learners based on their objective linguistic features. This study can be helpful as an empirical reference in language pedagogy, especially for L2 learners' self-assessment and teachers' prediction of students' proficiency levels. Also, it offers implications for the validation of the rating criteria, and improvement of rating system.

• Nuclear Engineering and Technology
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• v.54 no.11
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• pp.4170-4180
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• 2022

The task complexity (TACOM) measure was previously developed to quantify the complexity of proceduralized tasks conducted by nuclear power plant operators. Following the development of the TACOM measure, its appropriateness has been validated by investigating the relationship between TACOM scores and three kinds of human performance data, namely response times, human error probabilities, and subjective workload scores. However, the information reflected in quantified TACOM scores is still insufficient to determine the levels of complexity of proceduralized tasks for human reliability analysis (HRA) applications. In this regard, the objective of this study is to suggest criteria for determining the levels of task complexity based on logistic regression between human error occurrences in digitalized main control rooms and TACOM scores. Analysis results confirmed that the likelihood of human error occurrence according to the TACOM score is secured. This result strongly implies that the TACOM measure can be used to identify the levels of task complexity, which could be applicable to various research domains including HRA.

• Archives of design research
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• v.14 no.1
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• pp.111-118
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• 2001

The primary purpose of this research is to identify effects of the complexity levels of visual factors on user's communication in the web-sites. In this study, six complexity levels of visual factors were manipulated with four items(graphics, moving graphics, size and links) to test communication effects. As a result, user's communication was influenced by the complexity of illustration. This result shows that web sites with moderate levels of illustration complexity are more preferred than with complex or simple levels of visual complexity.

• Phonetics and Speech Sciences
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• v.5 no.1
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• pp.39-46
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• 2013

This study examined the effects of phonetic complexity and articulatory severity on Percentage of Correct Consonant (PCC) and speech intelligibility in adults with dysarthria. Speech samples of thirty-two words from APAC (Assessment of Phonology and Articulation of Children) were collected from 38 dysarthric speakers with one of two different levels of articulatory severities (mild or mild-moderate). A PCC and speech intelligibility score was calculated by the 4 levels of phonetic complexity. Two-way mixed ANOVA analysis revealed: (1) the group with mild severity showed significantly higher PCC and speech intelligibility scores than the mild-moderate articulatory severity group, (2) PCC at the phonetic complexity level 4 was significantly lower than those at the other levels and (3) an interaction effect of articulatory severity and phonetic complexity was observed only on the PCC. Pearson correlation analysis demonstrated the degree of correlation between PCC and speech intelligibility varied depending on the level of articulatory severity and phonetic complexity. The clinical implications of the findings were discussed.

• Journal of information and communication convergence engineering
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• v.4 no.1
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• pp.23-27
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• 2006

The discipline of software performance is very broad; it influences all aspects of the software development lifecycle, including architecture, design, deployment, integration, management, evolution and servicing. Thus, the complexity of software is an important aspect of development and maintenance activities. Much research has been dedicated to defining different software measures that capture what software complexity is. In most cases, the description of complexity is given to humans in forms of numbers. These quantitative measures reflect human-seen complexity with different levels of success. Software complexity growth has been recognized to be beyond human control. In this paper, we have focused our discussion on the increasing software complexity and the issue with the problems being faced in managing this complexity. This increasing complexity in turn affects the software productivity, which is declining with increase in its complexity.

• Journal of the Ergonomics Society of Korea
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• v.32 no.1
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• pp.59-68
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• 2013

Objective: The purpose of this paper is to introduce a task complexity model combining task design aspects and complexity dimensions and to explain an approach to identifying and organizing task complexity factors based on the model. Background: Task complexity is a critical concept in describing and predicting human performance in complex systems such as nuclear power plants(NPPs). In order to understand the nature of task complexity, task complexity factors need to be identified and organized in a systematic manner. Although several methods have been suggested for identifying and organizing task complexity factors, it is rare to find an analytical approach based on a theoretically sound model. Method: This study regarded a task as a system to be designed. Three levels of design ion, which are functional, behavioral, and structural level of a task, characterize the design aspects of a task. The behavioral aspect is further classified into five cognitive processing activity types(information collection, information analysis, decision and action selection, action implementation, and action feedback). The complexity dimensions describe a task complexity from different perspectives that are size, variety, and order/organization. Combining the design aspects and complexity dimensions of a task, we developed a model from which meaningful task complexity factors can be identified and organized in an analytic way. Results: A model consisting of two facets, each of which is respectively concerned with design aspects and complexity dimensions, were proposed. Additionally, twenty-one task complexity factors were identified and organized based on the model. Conclusion: The model and approach introduced in this paper can be effectively used for examining human performance and human-system interface design issues in NPPs. Application: The model and approach introduced in this paper could be used for several human factors problems, including task allocation and design of information aiding, in NPPs and extended to other types of complex systems such as air traffic control systems as well.

• Journal of Digital Convergence
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• v.15 no.8
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• pp.127-135
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• 2017

Consumers tend to feel concern about disclosure of personal information and, at the same time, to avoid inconvenience of procedural complexity caused by the privacy protections. The purpose of current paper is to investigate relationships between opt-in procedural complexity and shopping behavior using smart phones, moderating by the amount of visual attentions using eyetrackers. Therefore, we created a virtual mobile Web-site in which the complexity of opt-in procedures in our experiment is manipulated and measured. Also, we measured the dwell-time of area of interest using SMI-RED 250 instrument for tracking the real eye movement. Results indicated that the levels of procedural complexity are related to repurchase, indicating a moderating effect of the amount of visual attentions. Finally, we discussed several theoretical and practical implications of management for mobile commerce.

• 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.

• Korean Institute of Interior Design Journal
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• v.15 no.3 s.56
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• pp.173-183
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• 2006

Design is inseparably related to aesthetics. In spite of that, it is difficult to explain the precise aesthetic variables that affect the aesthetic value of space or environment. Therefore, this study intended to find the relationships between aesthetic variables by perceptual and affective judgement for space design with focus on complexity and preference variables. The research found low level of 'arousing' as well as high levels of affective dimension variables 'pleasant' and 'relaxing' evoked high preference. High preference also appeared in space design cases with high unity, order, and clarity with low contrast and complexity, which are variables of perceptual dimension. Complexity, one variables of preference by Kaplan, is in an inverse proportion to space preference. Thus, space design with high complexity has high level of 'exciting' and 'arousing' affective responses and relatively low level of 'relaxing' response. Additionally, it was confirmed that the most importantly influential factor on complexity was diverse components rather than visual richness and ornamentation.

• Asia pacific journal of information systems
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• v.15 no.3
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• pp.41-64
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• 2005

The effects of information quality and the importance of information have been reported in the information Systems(IS) literature. However, little has been learned about the impact of data quality(DQ) on decision performance. Recognizing with this problem, this study explores the effects of contextual DQ on decision performance. To examine them, a laboratory experiment was conducted. Based on two levels of contextual DQ and two levels of task complexity, this study had a $2{\times}2$ factorial design. The dependent variables used to measure the outcomes of decision performance were problem-solving accuracy and time. The results demonstrated that the effects of contextual DQ on decision performance were significant. The findings suggest that decision makers can expect to improve their decision performance by enhancing contextual DQ. This research not only extends a body of research examining the effects of factors that can be tied to human decision-making performance, but also provides empirical evidence to validate and extend DeLone and McLean's IS success model.