Policy Planning in Higher Technical Education

Soni, Sanjay; Chorasia, B.K.

doi:10.4018/ijsda.2017070105

Cited by 8 publications

(3 citation statements)

References 15 publications

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“…So, developing and transition countries are particularly challenged in a highly competitive world economy because their systems are not adequately developed for the creation and use of competent technical manpower available. Converting the challenges into opportunities depend on the rapidity with which they adapt to the changing environment (Soni & Chorasia, 2017). Hence, there is a need for systems structure or approach due to global corporate development with multinational organizations in borderless economies and that is proposed and discussed below as the Cultural Legal Oriented Value Embedded (CLOVE) Framework.…”

Section: Approach Structure and Theory Critiquementioning

confidence: 99%

Innovative Systems Structure for Real Corporate Governance

Baporikar

2022

International Journal of System Dynamics Applications

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All around the world, trends of globalization and industrialization have been experienced both in the development of large corporations and conglomerates. These larges firms contribute enormously to the socio-economic development of countries. Adopting a systematic literature review method with in-depth content analysis, the paper explores the concept of corporate governance holistically from systems lens and proposes an innovative systems structure-based framework namely Cultural Legal Oriented Value Embedded (CLOVE) for corporate governance to enable better decision making. In this paper, the structure proposed refers to components of culture, legal, orientation, value embeddedness that may be internal or external to the firm and these components are those, which will have a role in undertaking effective corporate governance and wealth creation for shareholders and the firm.

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Section: Approach Structure and Theory Critiquementioning

confidence: 99%

Innovative Systems Structure for Real Corporate Governance

Baporikar

2022

International Journal of System Dynamics Applications

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“…Al-Kadeem et al (2017) studied the how the work system changes in an industry. Soni & Chorasia (2017) studied various policies related to training in higher sectors. Pradhan (2017) gave a model for minimizing the risk in any project.…”

Section: Related Workmentioning

confidence: 99%

Enhancing Behavioral Dependency for Effective Computing in Software

Bura

Choudhary

2021

International Journal of System Dynamics Applications

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Software plays an important role in effective computing and communication of any services. It become crucial to identify some critical parts of the software that can lead to enhanced computing and increases efficiency of the software. Dependency plays a significant role in finding relationship amongst classes and predicting change prone classes. This paper aims to enhance Behavioral Dependency by defining 6 types of dependencies amongst classes. These are (i) direct behavioral dependency (ii) indirect behavioral dependency (iii) internal behavioral dependency (iv) external behavioral dependency (v) indirect internal behavioral dependency and (vi) Indirect External Behavioral Dependency. Evaluating these dependencies, gives accurate results for the prediction of change prone classes. Further, paper compares proposed approach with existing methods.

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“…The authors provided a comprehensive classification of existing domains of imbalanced learning. Soni et al (2017) computed the quality of higher technical Institute by using various attributes like placements, faculty strength, student's satisfaction, faculty satisfaction, etc. The authors constructed a dynamic model for policy planning to attain optimum quality in higher technical education system.…”

Section: Introductionmentioning

confidence: 99%

Significance of Non-Academic Parameters for Predicting Student Performance Using Ensemble Learning Techniques

Aggarwal¹,

Mittal

Bali³

2021

International Journal of System Dynamics Applications

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The academic institutions are focusing more on improving the performance of students using various data mining techniques. Prediction models are designed to predict the performance of students at a very early stage so that preventive measures can be taken beforehand. Various parameters (academic as well as non-academic) are considered to predict the student performance using different classifiers. Normally, academic parameters are given more weightage in predicting the academic performance of a student. This paper compares the two models: one built using academic parameters only and another using both academic and non-academic (demographic) parameters. The primary data set of students has been taken from a technical college in India, which consists of data of 6,807 students containing attributes. Synthetic minority oversampling technique filter is applied to deal with the skewed data set. The models are built using eight classification algorithms that are then compared to find the parameters that help to give the most appropriate model to classify a student based on his performance.

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Policy Planning in Higher Technical Education

Cited by 8 publications

References 15 publications

Innovative Systems Structure for Real Corporate Governance

Innovative Systems Structure for Real Corporate Governance

Enhancing Behavioral Dependency for Effective Computing in Software

Significance of Non-Academic Parameters for Predicting Student Performance Using Ensemble Learning Techniques

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