An Application of Entrepreneurship Score Model in College Student Entrepreneurship Education

2013 ◽  
pp. 1099-1106
Author(s):  
Guanxin Yao ◽  
Jing Xu ◽  
Jian Xu
Keyword(s):  
College Student ◽  
Entrepreneurship Education ◽  
Student Entrepreneurship ◽  
Score Model

Student entrepreneurship ecosystems at Australian higher education institutions

2022 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Alex Maritz ◽  
Quan Nguyen ◽  
Sergey Ivanov
Keyword(s):  
Higher Education ◽  
Higher Education Institutions ◽  
Entrepreneurship Education ◽  
University Student ◽  
Content Type ◽  
Student Entrepreneurship ◽  
Start Up ◽  
Entrepreneurship Ecosystems ◽  
Start Ups ◽  
The Impact

PurposeDespite the significance, university student start-ups and student entrepreneurship ecosystems (SEEs) have been subject to little research. This study aims to apply a qualitative emergent enquiry approach to explore best practice SEEs in Australia, complimented by narratives from leading scholars in higher education institutions with the aim of delineating the integrative components of SEEs.Design/methodology/approachAdopting the entrepreneurial ecosystem framework and aligned to the social cognitive theory, this paper explores the components and dynamics of SEEs, contributing to an understanding of how such components can better support the growth, sustainability and success of student start-ups. The authors extend entrepreneurship research on social construction using narrative research.FindingsThe findings provide guidelines for researchers, entrepreneurship scholars and educators, entrepreneurship students, policymakers and practitioners to enhance the impact and success of university student start-ups by adopting a student ecosystem approach.Research limitations/implicationsThe narratives represent a limited number of universities with an opportunity for further research to empirically measure the impact and outcomes of SEEs. The research is exploratory, inherently conceptual and emergent, providing an opportunity for validation of narrative frameworks in future studies.Practical implicationsThe findings may assist university managers to be more aware of their own subconscious preferences to student entrepreneurship and start-up initiatives, which may be useful in refining their impact and offerings regarding a quest toward the entrepreneurial university.Social implicationsFrom social perspectives, the alignment of the components of SEE has the ability to enhance and shift the entrepreneurial mindset of entrepreneurship students, notwithstanding enhancement of intentionality and self-efficacy.Originality/valueThis is the first study of SEEs in Australia, highlighting the importance of the integration of entrepreneurship education programs, entrepreneurship education ecosystems, the entrepreneurial university and specific start-up initiatives such as university accelerators. Furthermore, students may enhance their entrepreneurial mindset by actively engaging in such ecosystems.

scholarly journals Development of Student Entrepreneurship Skills in LKP Kresna Informatika

2020 ◽  
Vol 5 (1) ◽  
pp. 84-91
Author(s):  
Usup Usup ◽  
Supriyono Supriyono ◽  
Hardika Hardika ◽  
Endang Sri Redjeki
Keyword(s):  
Data Collection ◽  
Learning Strategies ◽  
Learning Strategy ◽  
Entrepreneurship Education ◽  
Research Subjects ◽  
Accounting Data ◽  
Student Entrepreneurship ◽  
Special Approach ◽  
Evaluation Of Learning ◽  
Module Development

The purpose of this study is 1) Describe the ideal and feasible model of the allocation of an entrepreneurship education curriculum for learners at a course institution. 2) Describe an ideal and feasible model of an entrepreneurship education learning strategy for learners in a course institution. Qualitative research is also called naturalistic research. Subjects in this study are students and alumi in course programs organized by LKP Kresna Informatika such as English courses courses, computer and office accounting. Data collection techniques in the context of this study have a significant role considering the quality of various types of data obtained at each stage of module development. Observation and documentation, interviews and tests are the data collection techniques used in this research before it will be analyzed. Stages of data analysis pursued after the need for data both secondary and primary when it has been fulfilled which includes; (1) data reduction, (2) display data, and (3) conclusion drawing/verification. The results in the study conclude that to establish entrepreneurial attitude in the courses and training programs conducted by LKP Kresna Informatika include; 1) The prerequisite of one's attitude input and one's entrepreneurial nature in LKP Kresna Informatika includes; discipline, high commitment, honest, reative and Innovative. 2) Design learning strategies in growing and developing entrepreneurship skills of learners in LKP Kresna Informatika through a special approach that is called 4 in 1 or with four stages. 3) Implementation of learning strategies in growing and developing entrepreneurship skills of learners in LKP Kresna Informatika; Identification of Business Opportunities, entrepreneurship learning based on the development of attitudes, knowledge and entrepreneurship skills, Evaluation of Learning Outcomes and Business Assistance and Pioneering.  

scholarly journals A Risk Assessment Algorithm for College Student Entrepreneurship Based on Big Data Analysis

Complexity ◽  
2021 ◽  
Vol 2021 ◽  
pp. 1-12
Author(s):  
Chengjun Zhou ◽  
DuanXu Wang
Keyword(s):  
Risk Factors ◽  
Risk Assessment ◽  
Big Data ◽  
Data Analysis ◽  
College Student ◽  
Big Data Analysis ◽  
Technical Support ◽  
Assessment Process ◽  
Student Entrepreneurship ◽  
Study Results

College student entrepreneurship is a complex and dynamic process, in which the potential risks faced by entrepreneurial enterprises are interactive and diverse. The changes in risk assessment for college student entrepreneurship are also dynamic and nonlinear and are affected by many factors, which make the risk assessment process for college student entrepreneurship quite complicated. Big data analysis technology is a new product formed under the background of cloud computing and Internet technology, which has the characteristics of large data scale, multiple data types, and strong data value and provides more technical support for the researches on the risk assessment algorithm for college student entrepreneurship. On the basis of summarizing and analyzing previous research results, this article expounded the research status and significance of the risk assessment algorithm for college student entrepreneurship, elaborated the development background, current status, and future challenges of big data analysis technology, introduced the basic principles of support vector machine (SVM) and hierarchical analytic process, constructed a risk assessment model for college student entrepreneurship based on big data analysis, analyzed the risk factors and assessment indicators of the entrepreneurial model, proposed a risk assessment algorithm for college student entrepreneurship based on big data analysis, performed the discrimination coefficient calculation and comprehensive correlation optimization, and finally conducted a case experiment and its result analysis. The study results show that the risk assessment algorithm for college student entrepreneurship based on big data analysis can effectively realize the comprehensive management of risk factors, make full use of the value of assessment parameter data, and significantly improve the accuracy and efficiency of the risk assessment for college student entrepreneurship, providing more technical support for the researches on the risk assessment algorithm for college student entrepreneurship. The study results of this article provide a reference for further researches on the risk assessment algorithm of college student entrepreneurship based on big data analysis.

scholarly journals Analysis of Factors Affecting Entrepreneurial Interest of Vocational High School Students in Pekanbaru

2018 ◽  
Vol 2 (2) ◽  
pp. 42 ◽  
Author(s):  
Nurmaliza Nurmaliza ◽  
Caska Caska ◽  
Henny Indrawati
Keyword(s):  
High School ◽  
High School Students ◽  
Family Environment ◽  
Entrepreneurship Education ◽  
Simple Random Sampling ◽  
Vocational High School ◽  
School Students ◽  
Factors Affecting ◽  
Student Entrepreneurship ◽  
Analysis Technique

The highest unemployment rate (TPT) in Indonesia is from graduated of Vocational High School (SMK), which is 9.27%. This phenomenon cannot be separated from the low interest of entrepreneurship. SMK graduates are expected to be able to work directly and can open employment area; the fact is far different from expectations. This study aims to analyze the factors that affect student entrepreneurship interest in SMK. The population of this study was 1845 students of class XII SMK Negeri in Pekanbaru City. The sampling method used in this research was Simple Random Sampling so that it obtained 329 students. The data collection used questionnaire with Likert scale that is suitable for exogenous variable (entrepreneurship interest), endogen variable (entrepreneurship education and family environment), and intervening variable (personality). The data analysis technique employed the path analysis method. The results of the analysis show that entrepreneurship education, and family environment have positive and significant influence on entrepreneurship interest through the personality. This shows that interest in entrepreneurship can be enhanced if the quality of entrepreneurship education, family environment and student personality are improved.

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