• Journal of Information Processing Systems
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• v.11 no.2
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• pp.165-172
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• 2015

The inactive student rate is becoming a major problem in most open universities worldwide. In Indonesia, roughly 36% of students were found to be inactive, in 2005. Data mining had been successfully employed to solve problems in many domains, such as for educational purposes. We are proposing a method for preventing inactive students by mining knowledge from student record systems with several state of the art ensemble methods, such as Bagging, AdaBoost, Random Subspace, Random Forest, and Rotation Forest. The most influential attributes, as well as demographic attributes (marital status and employment), were successfully obtained which were affecting student of being inactive. The complexity and accuracy of classification techniques were also compared and the experimental results show that Rotation Forest, with decision tree as the base-classifier, denotes the best performance compared to other classifiers.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.12
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• pp.3836-3854
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• 2022

The student group division is benefit for universities to do the student management based on the group profile. With the widespread use of student smart cards on campus, especially where students living in campus residence halls, students' daily activities on campus are recorded with information such as smart card swiping time and location. Therefore, it is feasible to depict the students with the daily activity data and accordingly group students based on objective measuring from their campus behavior with some regular student attributions collected in the management system. However, it is challenge in feature representation due to diverse forms of the student data. To effectively and comprehensively represent students' behaviors for further student group division, we proposed to adopt activity data from student smart cards and student attributes as input data with taking account of activity and attribution relationship types from different perspective. Specially, we propose a novel student group division method based on a multi-view student attribute heterogeneous information network (MSA-HIN). The network nodes in our proposed MSA-HIN represent students with their multi-dimensional attribute information. Meanwhile, the edges are constructed to characterize student different relationships, such as co-major, co-occurrence, and co-borrowing books. Based on the MSA-HIN, embedded representations of students are learned and a deep graph cluster algorithm is applied to divide students into groups. Comparative experiments have been done on a real-life campus dataset collected from a university. The experimental results demonstrate that our method can effectively reveal the variability of student attributes and relationships and accordingly achieves the best clustering results for group division.

• Journal of the Korean Society of Food Culture
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• v.21 no.1
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• pp.57-64
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• 2006

The purpose of this study was to measure the pizza purchasing behavioral characteristics of respondents and importances of factors affecting pizza purchase, to estimate the effects of attributes on pizza restaurant choice, and to predict probability of selecting a particular pizza restaurant. The questionnaire consisted of two parts: The paired experimental profiles, purchasing behavior and importances of factors affecting pizza purchase. This study generated profiles of 16 hypothetical pizza restaurant based on the seven attributes. The profiles comprised 16 discrete sets of variables, each of which had two levels. For this study, researcher randomly selected 150 students of university as respondents. Twenty students did not complete the survey instrument, resulting in a final sample size of 129. All estimations were carried out using frequencies, $X^2$, independent samples t-test, phreg procedure of SAS package. The results are as follows. Some purchasing behavioral characteristics and importances of factors affecting pizza purchase were significantly different by gender. Based on the estimated models developed for male student group and female student group, the Chi-square statistics were significant at p<0.001. The parameter estimate for late delivery time with male student group was highest, and the parameter estimate for price with female student group was highest. The pizza restaurant that charged \20,000, offered 100% discount on eleventh pizza, promised to deliver pizza in 40 mins, usually delivered the pizza as promised time, offered only 1 type of pizza crust, delivered warm pizza, offered the money-back guarantee was favored by each of male student group and female student group. The results from this study suggested that there was an opportunity to increase market share and profit by improving operations so that customers receive discount and money-back guarantee simultaneously, and by reducing price, delivery time.

• School Mathematics
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• v.10 no.2
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• pp.259-277
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• 2008

Conventional assessments only provide a single summary score that indicates the overall performance level or achievement level of a student in a single learning area. For assessments to be more effective, test should provide useful diagnostic information in addition to single overall scores. Cognitive diagnosis modeling provides useful information by estimating individual knowledge states by assessing whether an examinee has mastered specific attributes measured by the test(Embretson, 1990; DiBello, Stout, & Rousses, 1995; Tatsuoka, 1995). Attributes are skills or cognitive processes that are required to perform correctly on a particular item. By the results of this study, students, parents, and teachers would be able to see where a student stands with respect to mastering the attributes. Such information could be used to guide the learner and teacher toward areas requiring more study. By being able to assess where they stand in regard to the attributes that compose an item, students can plan a more effective learning path to be desired proficiency levels. It would be very helpful to the examinee if score reports can provide the scale scores as well as the skill profiles. While the scale scores are believed to provide students' math ability by reporting only one score point, the skill profiles can offer a skill level of strong, weak or mixed for each student for each skill.

• Korean journal of medical education
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• v.30 no.4
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• pp.339-346
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• 2018

Purpose: The purpose of this study was to examine whether non-cognitive student attributes such as learning style and personality type affected academic performance in a flipped learning classroom of a pre-dental undergraduate science course. Methods: 'Biodiversity and Global Environment,' a 15-week, 3-credit course, was designed as a flipped class in Seoul National University School of Dentistry in 2017. Second-year pre-dental students were required to enroll in the course and to engage in online learning and in-class discussion. The Kolb's Learning Style Inventory and the Myers-Briggs Type Indicator were conducted to measure non-cognitive student factors. Independent samples t-test and multivariate regression analyses were used to examine the relationships between self-rated measurements and academic achievement. Results: More than half of the students enrolled in the flipped science course had an assimilator learning style (50%), followed by convergers (24%), accommodators (16%), and divergers (10%), and their personality types were dominated by the introverted, sensing, thinking, and judging types, respectively. Examining group differences using the t-test demonstrated a significant relationship between the diverger group and higher academic success. In particular, the multivariate regression analysis indicated that both thinking types and female students performed better in discussion than feeling types and male students. Conclusion: To operate the flipped learning classroom more effectively in medical and dental education, the instructor should carefully develop and apply a more tailored facilitation and relevant assessment by considering student learning styles and personality types.

• Journal of Information Science Theory and Practice
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• v.8 no.2
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• pp.32-44
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• 2020

This study attempts to draw the implications of student satisfaction with fieldwork courses in the library and information science (LIS) program in South Korea by determining the level of satisfaction experienced by students with practicums at a library and information service agency. LIS students with fieldwork experience were surveyed to assess their satisfaction and the factors affecting their satisfaction. Results from a multiple regression analysis revealed that from among factors of practicum settings, major-related attributes, and general attributes of respondents, "satisfaction with majors" and "interpersonal relationships" had a significant effect on satisfaction with practicums. Examining the six components of satisfaction with the course revealed that "practicum program" and "practicum setting" had a significant relationship with overall satisfaction. A selective intervention program to improve satisfaction with the course needs to be developed based on factors influencing overall satisfaction, focusing on "interpersonal relationship" and "satisfaction with majors.

• Journal of Distribution Science
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• v.14 no.2
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• pp.47-56
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• 2016

Purpose - The purpose of this study is to investigate the difference in the degree of significance and satisfaction perceived by college students and ordinary consumers on the HMR product attributes. Comparison of the difference on HMR product attributes between ordinary consumers and college students who belong to the current and future consumption groups of HMR will provide information for clear marketing strategies and PR on target consumers from the aspects of companies. Also, overall difference on HMR was investigated through IPA(importance-performance analysis) on significance and satisfaction with each product attribute. This result will provide information to food companies that produce or supply HMR products to be supplemented and improved. Finally, IPA was conducted between groups on product attribute to find which difference exists between groups. This result is also expected to provide crucial information to companies as suggested in the first purpose. Research design, data, and methodology - The procedure of analysis is as follows. First, independent sample t-test was conducted on the significance and satisfaction on HMR product attributes. Second, with using IPA, the significance and satisfaction on HMR product attributes of the respondents were checked to investigate marketing strategy direction on overall HRM products. Third, the difference between generations was verified using IPA on the college student and consumer groups. According to this result, the direction of marketing strategy on HRM products was to be proposed to food companies. Results - It was known that consumers consider HMR product attributes statistically and significantly such as nutrient content(nutrition), country of origin, brand, main raw material, packaging, and awareness of manufacturer. They keep after purchase more importantly than college students who considered only volume and price than consumers. In comparison with the difference in satisfaction on HMR product attributes, the college student group was more satisfied than ordinary consumers only in flavor, condition of food additives, and volume. Also, HMR related food companies must maintain taste, cooking method, manufacturing date, expiration date, and safety on current products continuously. Finally, as a result of analysis from the groups, the attributes such as cooking method, manufacturing date, expiration date, and safety were considered significantly with high achievement by the two groups. It was known that college students considered food texture to be important, but consumers considered storage method to be important after purchasing it. Conclusions - There is necessity to differentiate effectiveness of products when releasing HMR products subject to consumers and college students. The result will give great assistance to the improvement of companies, produce or supply HMR products. It will also provide entry strategies on target groups of companies that are planning for entry. The factors that consumers commonly considered not to be significant were brand, package form(appearance), cooking time, and sale(purchase) location, which were found in the comparison with the groups that awareness about manufacturers and storage method after purchase corresponded to college students and that distribution route corresponded to ordinary consumers.

• Korean journal of food and cookery science
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• v.19 no.3
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• pp.363-373
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• 2003

The purpose of this study was to identify university students' attitude to the foodservice attributes in their contribution to the selection or a fast food restaurant. Among 300 subjects, 214 were used in the analysis. The frequencies, Descriptives, ANOVA and t-test were used for the statistical analyses in this study. The findings from this study were as follows: firstly, there were no significant differences in the importance (or salience) of the foodservice attributes between the three different types of fast food restaurant. Secondly, there were no significant differences in the foodservice attributes between the means of the importance and salience for each of the selected fast food restaurants. Thirdly, there were no significant differences in the foodservice attributes in determining between the three types of fast food restaurant. Fourthly, there were no significant differences for the foodservice attributes between the mean importance (or salience) and universal mean for each of the selected fast food restaurants. Finally, the results of this study could provide some insight into the type of marketing strategies that may be successfully used by marketers who manage fast food restaurants.

• International Journal of Computer Science & Network Security
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• v.21 no.2
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• pp.188-192
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• 2021

In this paper, we apply data mining techniques and machine learning algorithms using R software, which is used to predict, here we applied a regression model to test some factor on the dataset for which we assumed that it effects student performance. Model was built on an existing dataset which contains many factors and the final grades. The factors tested are the attention to higher education, absences, study time, parent's education level, parent's jobs, and the number of failures in the past. The result shows that only study time and absences can affect the students' performance. Prediction of student academic performance helps instructors develop a good understanding of how well or how poorly the students in their classes will perform, so instructors can take proactive measures to improve student learning. This paper also focuses on how the prediction algorithm can be used to identify the most important attributes in a student's data.

• Korean journal of food and cookery science
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• v.19 no.3
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• pp.390-395
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• 2003

The purposes of this study were to identify the attributes of food and service quality, to examine the levels of satisfaction and plate wastes leftover in school meals and to determine the relationship between student satisfaction and plate wastes. A questionnaire was administrated to 1000 elementary students. The respondents comprised of 505 boys and 494 girls. The satisfaction score with the food service quality was rated as 'average', with a score of 3.06 out of 5. The quality attributes of the food service were categorized into three aspects, which included food, service and hygiene. The satisfaction scores for the food- and hygiene-related factors were 3.20 and 3.24, respectively. However, the aspect of service was rated at 2.74, indicating a low level of satisfaction. The intake rates of soup, kimchi, fish and vegetables were lower than those of other types of foods. Two groups, a no-leftovers group and a leftovers group, were classified based on whether students ate all or left foods. The satisfaction scores for the school food service attributes between the two groups revealed that the no-leftovers group was more highly satisfied with the food service quality than the leftovers group (p＜0.001).