Work integrated learning (WIL), most in the form of co-operative (co-op) partnerships or workplace placements/internships, has been incorporated into many undergraduate programs in universities around the world. In this express report, we share a recent trial of a new WIL model for a bachelor's IT degree in data science and big data processing technology experimented at our University (Inner Mongolia Agricultural University, IMAU) in China. This new model involves three entities, an institution as IMAU (Part A), an industry-certification training agency (Part B), and a cloud computing enterprise (Part C). Our experiment was initiated in September 2018 with the first intake of about 120 undergraduate students and completed in July 2022 over four years of full-time study. The initial results show that the three-way WIL initiative produced more than 60 employment-ready and industry-certified professionals for ICT enterprises and service providers specialized in data science and big data processing technology. The industry-standard certification training and the four-month industry placement in a top 500 ICT enterprise in the world significantly improved both the hands-on skills required by the ICT industry and the employment opportunities for the graduates.
Citation: Gaifang Dong. Successes and lessons from a trial of the three-way university-enterprise cooperation program on data science and big data processing technology in China[J]. STEM Education, 2022, 2(4): 293-302. doi: 10.3934/steme.2022018
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[2] | Simone Göttlich, Oliver Kolb, Sebastian Kühn . Optimization for a special class of traffic flow models: Combinatorial and continuous approaches. Networks and Heterogeneous Media, 2014, 9(2): 315-334. doi: 10.3934/nhm.2014.9.315 |
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[8] | Mauro Garavello . A review of conservation laws on networks. Networks and Heterogeneous Media, 2010, 5(3): 565-581. doi: 10.3934/nhm.2010.5.565 |
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Work integrated learning (WIL), most in the form of co-operative (co-op) partnerships or workplace placements/internships, has been incorporated into many undergraduate programs in universities around the world. In this express report, we share a recent trial of a new WIL model for a bachelor's IT degree in data science and big data processing technology experimented at our University (Inner Mongolia Agricultural University, IMAU) in China. This new model involves three entities, an institution as IMAU (Part A), an industry-certification training agency (Part B), and a cloud computing enterprise (Part C). Our experiment was initiated in September 2018 with the first intake of about 120 undergraduate students and completed in July 2022 over four years of full-time study. The initial results show that the three-way WIL initiative produced more than 60 employment-ready and industry-certified professionals for ICT enterprises and service providers specialized in data science and big data processing technology. The industry-standard certification training and the four-month industry placement in a top 500 ICT enterprise in the world significantly improved both the hands-on skills required by the ICT industry and the employment opportunities for the graduates.
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1. | C. D'Apice, R. Manzo, B. Piccoli, Numerical Schemes for the Optimal Input Flow of a Supply Chain, 2013, 51, 0036-1429, 2634, 10.1137/120889721 | |
2. | Mauro Garavello, Benedetto Piccoli, Time-varying Riemann solvers for conservation laws on networks, 2009, 247, 00220396, 447, 10.1016/j.jde.2008.12.017 | |
3. | Simone Göttlich, Stephan Martin, Thorsten Sickenberger, Time-continuous production networks with random breakdowns, 2011, 6, 1556-181X, 695, 10.3934/nhm.2011.6.695 | |
4. | S. Göttlich, M. Herty, C. Ringhofer, U. Ziegler, Production systems with limited repair capacity, 2012, 61, 0233-1934, 915, 10.1080/02331934.2011.615395 | |
5. | Felix Bestehorn, Christoph Hansknecht, Christian Kirches, Paul Manns, 2019, A switching cost aware rounding method for relaxations of mixed-integer optimal control problems, 978-1-7281-1398-2, 7134, 10.1109/CDC40024.2019.9030063 | |
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7. | Felix Bestehorn, Christoph Hansknecht, Christian Kirches, Paul Manns, Switching Cost Aware Rounding for Relaxations of Mixed-Integer Optimal Control Problems: The 2-D Case, 2022, 6, 2475-1456, 548, 10.1109/LCSYS.2021.3082989 | |
8. | Simone Göttlich, Patrick Schindler, Optimal inflow control of production systems with finite buffers, 2015, 20, 1553-524X, 107, 10.3934/dcdsb.2015.20.107 | |
9. | Khaled A.A.A. Othman, Thomas Meurer, Demand Tracking Control in Manufacturing Systems, 2020, 53, 24058963, 11219, 10.1016/j.ifacol.2020.12.334 | |
10. | Simone Göttlich, Michael Herty, Optimal control for supply network models: Mixed integer programming, 2007, 7, 16177061, 2060051, 10.1002/pamm.200700618 | |
11. | Alfredo Cutolo, Benedetto Piccoli, Luigi Rarità, An Upwind-Euler Scheme for an ODE-PDE Model of Supply Chains, 2011, 33, 1064-8275, 1669, 10.1137/090767479 | |
12. | Ciro D'Apice, Peter I. Kogut, Rosanna Manzo, On Approximation of Entropy Solutions for One System of Nonlinear Hyperbolic Conservation Laws with Impulse Source Terms, 2010, 2010, 1687-5249, 1, 10.1155/2010/982369 | |
13. | Michael N. Jung, Christian Kirches, Sebastian Sager, Susanne Sass, Computational Approaches for Mixed Integer Optimal Control Problems with Indicator Constraints, 2018, 46, 2305-221X, 1023, 10.1007/s10013-018-0313-z | |
14. | Khaled A.A.A. Othman, Thomas Meurer, Optimal Boundary Control for the Backlog Problem in Production Systems, 2022, 55, 24058963, 511, 10.1016/j.ifacol.2022.09.146 | |
15. | Tanmay Sarkar, A numerical study on a nonlinear conservation law model pertaining to manufacturing system, 2016, 47, 0019-5588, 655, 10.1007/s13226-016-0199-y | |
16. | Agnes Dittel, Simone Göttlich, Ute Ziegler, Optimal design of capacitated production networks, 2011, 12, 1389-4420, 583, 10.1007/s11081-010-9123-1 | |
17. | A. Fügenschuh, S. Göttlich, M. Herty, C. Kirchner, A. Martin, Efficient reformulation and solution of a nonlinear PDE-controlled flow network model, 2009, 85, 0010-485X, 245, 10.1007/s00607-009-0038-7 | |
18. | A. Fügenschuh, S. Göttlich, M. Herty, A. Klar, A. Martin, A Discrete Optimization Approach to Large Scale Supply Networks Based on Partial Differential Equations, 2008, 30, 1064-8275, 1490, 10.1137/060663799 | |
19. | Oliver Kolb, Simone Göttlich, A continuous buffer allocation model using stochastic processes, 2015, 242, 03772217, 865, 10.1016/j.ejor.2014.10.065 | |
20. | Ciro D'Apice, Peter I. Kogut, Rosanna Manzo, On relaxation of state constrained optimal control problem for a PDE-ODE model of supply chains, 2014, 9, 1556-181X, 501, 10.3934/nhm.2014.9.501 | |
21. | Simone Göttlich, Michael Herty, Claus Kirchner, Optimal control for supply network models: adjoint calculus, 2007, 7, 16177061, 2060053, 10.1002/pamm.200700624 | |
22. | Simone Göttlich, Axel Klar, 2013, Chapter 8, 978-3-642-32159-7, 395, 10.1007/978-3-642-32160-3_8 | |
23. | Ingenuin Gasser, Martin Rybicki, Winnifried Wollner, Optimal control of the temperature in a catalytic converter, 2014, 67, 08981221, 1521, 10.1016/j.camwa.2014.02.006 | |
24. | Simone Göttlich, Sebastian Kühn, Jan Peter Ohst, Stefan Ruzika, Markus Thiemann, Evacuation dynamics influenced by spreading hazardous material, 2011, 6, 1556-181X, 443, 10.3934/nhm.2011.6.443 | |
25. | P. Degond, C. Ringhofer, Stochastic Dynamics of Long Supply Chains with Random Breakdowns, 2007, 68, 0036-1399, 59, 10.1137/060674302 | |
26. | S. Göttlich, S. Kühn, J. A. Schwarz, R. Stolletz, Approximations of time-dependent unreliable flow lines with finite buffers, 2016, 83, 1432-2994, 295, 10.1007/s00186-015-0529-6 | |
27. | Simone Göttlich, Oliver Kolb, Sebastian Kühn, Optimization for a special class of traffic flow models: Combinatorial and continuous approaches, 2014, 9, 1556-181X, 315, 10.3934/nhm.2014.9.315 | |
28. | Sebastian Sager, 2012, Chapter 22, 978-1-4614-1926-6, 631, 10.1007/978-1-4614-1927-3_22 |
Overall structure of 3UECP