Predicting the Variables That Determine University (Re-)Entrance as a Career Development Using Support Vector Machines with Recursive Feature Elimination: The Case of South Korea
Abstract
:1. Introduction
2. Theoretical Background
2.1. University (Re-)Entrance as Career Development of Korean High-School Graduates
2.2. Career Development from an Ecological Perspective
2.3. SVM-RFE in Educational Fields
- (1)
- Survival analysis (time-to-event analysis): Once you have a model through survival analysis on your data, you can answer the following questions.
- What is the probability that a patient diagnosed with blood cancer will survive for more than 3 years?
- −
- Survival probability S(t)
- How long should I wait to catch a taxi?
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- Median t time
- I have 100 job seekers. How many people get a job after one year?
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- 100 × S(t) persons
- (1)
- Survival analysis applications: Survival analysis applications are frequently used in the following medicines, but the same technique can be used in marketing and engineering (reliability).
- Establishing a business plan
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- Establishing a strategy by identifying the characteristics of customers with a long remaining period without departure
- Lifetime Value (LTV) Forecast
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- Responding to customers in line with LTV values
- Effective customers
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- Predict whether customers will be valid until a certain point in time
- Campaign evaluation
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- Monitoring campaign effectiveness according to customer churn rate (survival rate)
- Industry-specific survival analysis
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- Retail: The time it takes for customers to purchase fresh food to purchase non-fresh food
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- Manufacturing: Machine parts lifetime
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- Public: The time it takes for an important social event to occur
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- Catalog mail order: time to next order
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- Home mortgage: the time it takes to repay your home mortgage
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- Insurance: Time to extinguish insurance policy rights
3. Methods
4. Evaluation Results
5. Discussion and Conclusions
Author Contributions
Funding
Acknowledgments
Conflicts of Interest
References
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System | Examples |
---|---|
individual systems | gender roles, religious beliefs, and intrapsychic processes |
microsystems | family, siblings, teachers, peers, and schools where each student belongs |
mesosystems | interaction between parents, siblings, teachers, and peers |
exosystems | extended family, community resources, school board, organization neighborhoods, mass media, and parents’ work environments where each student belongs |
macrosystems | social, cultural, historical influences, broad ideology, and laws and customs |
chronosystems | changes in environment over time |
Variable Ranking | No.1 Why Are You Preparing for the Entrance Exam again? | No. 2 If You Enter University again, Why Do You Choose Your Major? | ||||
---|---|---|---|---|---|---|
Re-admitted group | Class variable (Weight) | The university’s social awareness was low | 37.04 | Class variable (Weight) | My talent and aptitude | 48.15 |
I didn’t like the former university | 25.93 | My hope | 37.04 | |||
Parent’s recommendation | 0 | Parent’s recommendation | 0 | |||
Newly admitted group | Class variable (Weight) | CAST score was low | 46.44 | Class variable (Weight) | My hope | 44.76 |
Rejected by all the colleges that I applied for | 23.03 | My talent and aptitude | 41.39 | |||
Parents’ recommendation | 0 | Parents’ recommendation | 1 |
Variable | What Is the Main Reason for Preparing for College Entrance again? | |
---|---|---|
Re-admitted and newly admitted group | Class variable | Association with class variables mentioned in Table 2 (Weight) |
Rejected by all the colleges that I applied for | Newly admitted Group’s Variable Ranking No.1 (23.03%) | |
The former university’s social awareness was low | Re-admitted Group’s Variable Ranking No.1 (37.04%) | |
CAST score was lower than expected | Newly admitted Group’s Variable Ranking No.1 (46.44%) | |
I didn’t like my major of the former university | Re-admitted Group’s Variable Ranking No.2 (37.04%) Newly admitted Group’s Variable Ranking No.2 (41.39%) | |
Parent’s recommendation | Newly admitted Group’s Variable Ranking No.1 (6%) Newly admitted Group’s Variable Ranking No.2 (1%) |
Variable | What Is the Main Reason for Preparing for College Entrance? | |
---|---|---|
Both the employed and unemployed | Class variable | Association with class variables mentioned in Table 2 (Weight) |
To overcome academic restrictions | Re-admitted Group’s Feature Ranking No.1 The prior university’s recognition was low (37.04%) | |
To improve professionalism | Re-admitted Group’s Feature Ranking No.2 My talent and aptitude (48.15%) Newly Admitted Group’s Feature Ranking No.2 My talent and aptitude (41.39%) | |
To increase pay | Re-admitted Group’s Feature Ranking No.2 My talent and aptitude (48.15%) Newly Admitted Group’s Feature Ranking No.2 My talent and aptitude (41.39%) | |
For promotion | Re-admitted Group’s Feature Ranking No.2 My talent and aptitude (48.15%) Newly Admitted Group’s Feature Ranking No.2 My talent and aptitude (41.39%) | |
Only the unemployed | Recommendations from acquaintances | Newly Admitted Group’s Feature Ranking No.1 Parents’ recommendation (6%) Newly Admitted Group’s Feature Ranking No.2 Parents’ recommendation (1%) |
For pure academic exploration | Re-admitted Group’s Feature Ranking No.2 My hope (37.04%) Newly Admitted Group’s Feature Ranking No.2 My hope (44.76%) |
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Park, T.; Kim, C. Predicting the Variables That Determine University (Re-)Entrance as a Career Development Using Support Vector Machines with Recursive Feature Elimination: The Case of South Korea. Sustainability 2020, 12, 7365. https://doi.org/10.3390/su12187365
Park T, Kim C. Predicting the Variables That Determine University (Re-)Entrance as a Career Development Using Support Vector Machines with Recursive Feature Elimination: The Case of South Korea. Sustainability. 2020; 12(18):7365. https://doi.org/10.3390/su12187365
Chicago/Turabian StylePark, Taejung, and Chayoung Kim. 2020. "Predicting the Variables That Determine University (Re-)Entrance as a Career Development Using Support Vector Machines with Recursive Feature Elimination: The Case of South Korea" Sustainability 12, no. 18: 7365. https://doi.org/10.3390/su12187365