• Journal of The Korean Association For Science Education
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• v.22 no.2
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• pp.398-409
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• 2002

The purpose of this study was to investigate the validity, reliability and practicality of a concept map as an assessment tool in the context of biology concept learning. Forty undergraduate students participated in concept mapping, and the maps were scored by preservice science teachers, using one of three different scoring methods, that is, concept map scoring methods developed by Burry-Stock, Novak & Gowin and McClure & Bell. Two scorers were assigned to each scoring method. As far as the validity of the assessment methods was concerned, two of the three methods were found to be very valid, while Burry-Stock's scoring method was shown little valid. As far as the internal consistency of the methods was concerned, considerably high consistencies were shown between every pair of scorers, judging from high correlation coefficients between the pair of scorers for each scoring method. It took from 1.13 minutes to 3.70 minutes to assess a map at the average. It showed that concept mapping could be used in school classrooms with the limited resources of time and people. These findings suggest that the concept mapping can be an appropriate tool for assessing biology concept understandings.

• Journal of the Korea Society of Computer and Information
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• v.14 no.6
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• pp.99-106
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• 2009

Over recent decades, concept mapping has been used as a valuable Learning and Teaching tool. A number of studies have shown a positive impact on student learning. One of the disadvantages of this technique has been that assessing them or providing feedback to students is time consuming. We aim here to introduce ways of reducing the complexity of using concept map techniques in online activities. Several types of scoring methods for the concept map based assessment have been developed. In this paper, we describe the development of an automatic assessment system that implements those techniques. We contribute a design that uses semantic web technologies for both the management and the scoring of the concept maps.

• Journal of The Korean Association For Science Education
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• v.36 no.3
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• pp.389-397
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• 2016

This study aims to test the efficacy of English-based automated computer scoring models and machine translation to score Korean college students' written responses on natural selection concept items. To this end, I collected 128 pre-service biology teachers' written responses on four-item instrument (total 512 written responses). The machine translation software (i.e., Google Translate) translated both original responses and spell-corrected responses. The presence/absence of five scientific ideas and three $na{\ddot{i}}ve$ ideas in both translated responses were judged by the automated computer scoring models (i.e., EvoGrader). The computer-scored results (4096 predictions) were compared with expert-scored results. The results illustrated that no significant differences in both average scores and statistical results using average scores was found between the computer-scored result and experts-scored result. The Pearson correlation coefficients of composite scores for each student between computer scoring and experts scoring were 0.848 for scientific ideas and 0.776 for $na{\ddot{i}}ve$ ideas. The inter-rater reliability indices (Cohen kappa) between computer scoring and experts scoring for linguistically simple concepts (e.g., variation, competition, and limited resources) were over 0.8. These findings reveal that the English-based automated computer scoring models and machine translation can be a promising method in scoring Korean college students' written responses on natural selection concept items.

• Journal of KIISE
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• v.41 no.11
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• pp.911-920
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• 2014

In this paper, we introduce an automatic scoring system for middle-school level writing test based on using machine learning techniques. We discuss overall process and features for building an automatic English writing scoring system. A "concept answer" which represents an abstract meaning of text is newly introduced in order to evaluate the elaboration of a student's answer. In this work, multiple machine learning algorithms are adopted for scoring English writings. We suggest a decision process "optimal combination" which optimally combines multiple outputs of machine learning algorithms and generates a final single output in order to improve the performance of the automatic scoring. By experiments with actual test data, we evaluate the performance of overall automated English writing scoring system.

• The Journal of the Korea Contents Association
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• v.4 no.3
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• pp.115-123
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• 2004

This study suggests the output of the fingerprint doorlock design development through the structured methodology of concept selection in the process of design development, after characterizing the doorlock product itself. All of the early phases of product development are very important on eventual product success. Concept selection is the process of evaluating concepts with respect to customer needs and other criteria, comparing the relative strength and weaknesses of the concepts, and selecting one or more concepts for further investigation or development. To obtain the ideal concept o( new product, this work used a two-stage concept selection methodology which consist of concept screening and concept scoring. As a result, this study represents the fixed design rendering for mass production.

• The Korean Journal of Applied Statistics
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• v.10 no.2
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• pp.275-291
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• 1997

In the case that an abstract concept was measured indirectly by using its indicators, many researcher have obtained its score by using the simple mean, the first principal component, or the first factor, etc. In this paper, an scoring method named as the representative component scoring system was suggested as an alternative and its validity and applicability were studied.

• Journal of Digital Convergence
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• v.15 no.12
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• pp.349-358
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• 2017

This study was done to identify the relationship between emotional intelligence, critical thinking disposition professional self-concept and problem solving skills of nursing students. Subjects were 212 associate nursing students associate nursing students(3rd and 4th grade) in Korea. The data were collected using self -report questionnaire from February 20 to March 30, 2017. Data were analyzed by frequencies, t-test, ANOVA, Pearson's correlation using SPSS Win 18.0. The score for emotional intelligence was 3.59, critical thinking disposition scoring 3.47, professional Self-Concept scoring 3.45 and problem solving skills scoring 3.45. Problem solving skills were significantly strong positive correlation with emotional intelligence(r=.68, p<.001), critical thinking disposition(r=.77, p<.001), Professional Self-Concept(r=.66, p<.001) in nursing students. Emotional intelligence, critical thinking disposition and professional self-concept explained 65.1% of total variance of problem solving skills of nursing students. Therefore, To increase problem solving skills of nursing students, it is necessary to develop and test the program for increase emotional intelligence, critical thinking disposition and professional self-concept of nursing students.

• Journal of the Korean Operations Research and Management Science Society
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• v.13 no.2
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• pp.1-8
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• 1988

This study suggests on optimal process when decision maker is confronted with expert's biased information under the situation that the bias is caused mainly by the difference of their interest. In order to make honest transmission of expert's probabilistic information, the concept of expert use and scoring rule to provide expert with an incentive is used in this paper. And expected regret concept is introduced to evaluate the value of expert's information. A simple example is also shown.

• Journal of KIISE
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• v.42 no.12
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• pp.1522-1534
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• 2015

This work presents a new method that can predict, without the use of training data, whether an input essay is written on a given topic. ConceptNet is a common-sense knowledge base that is generated automatically from sentences that are extracted from a variety of document types. An essay prompt is the topic that an essay should be written about. The method that is proposed in this paper uses ConceptNet and an essay prompt to decide whether or not an input essay is off-topic. We introduce a way to find the shortest path between two nodes on ConceptNet, as well as a way to calculate the semantic similarity between two nodes. Not only an essay prompt but also a student's essay can be represented by concept nodes in ConceptNet. The semantic similarity between the concepts that represent an essay prompt and the other concepts that represent a student's essay can be used for a calculation to rank "on-topicness" ; if a low ranking is derived, an essay is regarded as off-topic. We used eight different essay prompts and a student-essay collection for the performance evaluation, whereby our proposed method shows a performance that is better than those of the previous studies. As ConceptNet enables the conduction of a simple text inference, our new method looks very promising with respect to the design of an essay prompt for which a simple inference is required.

• Proceedings of the Korean Society for Quality Management Conference
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• 2006.04a
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• pp.182-187
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• 2006

The learning, which is an extended concept from the concept of continuos improvement and replace it, has become a very important core concept in Malcom Baldridge National Quality Award these days. The most potent core value among 11 core values is 'organizational and personal learning' Embedded learning in the organization is also a critical part to get a high score in approach scoring criteria for 6 categories except results category. But the concept of learning is often overlooked for the people who have interests in MB award or TQM. This paper review and analyze the concept of learning which has appeared In MB criteria since it's first appearance.