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XinXiu Yang – International Journal of Information and Communication Technology Education, 2024
The objective of this work is to predict the employment rate of students based on the information in the SSM (student status management) in colleges and universities. Firstly, the relevant content of SSM is introduced. Secondly, the BP (Back Propagation) neural network, the LM (Levenberg Marquardt) algorithm, and the BR (Bayesian Regularization)…
Descriptors: Prediction, Employment Patterns, College Students, Algorithms
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Broda, Michael D.; Bogenschutz, Matthew; Dinora, Parthenia; Prohn, Seb M.; Lineberry, Sarah; Ross, Erica – American Journal on Intellectual and Developmental Disabilities, 2021
In this article, we demonstrate the potential of machine learning approaches as inductive analytic tools for expanding our current evidence base for policy making and practice that affects people with intellectual and developmental disabilities (IDD). Using data from the National Core Indicators In-Person Survey (NCI-IPS), a nationally validated…
Descriptors: Artificial Intelligence, Prediction, Employment Patterns, Day Programs
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Doll, Jessica L. – Management Teaching Review, 2022
Workforce planning is prevalent and recognized as a good strategic practice in many organizations. However, business students may have little experience with workforce planning or workforce analytics. The purpose of this article is to present a workforce planning exercise for use in a face-to-face or online classroom setting. In this exercise,…
Descriptors: Labor Force Development, Strategic Planning, Business Administration Education, Human Resources