Online Blending Learning Model of School-Enterprise Cooperation and Course Certificate Integration During the COVID-19 Epidemic

Liu, Shihua; Zhang, Hao; Ye, Zhanxiang; Wu, Gang

doi:10.11648/j.sjedu.20200802.16

Cited by 6 publications

(6 citation statements)

References 2 publications

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“…Pure digital training required a complete self-directedness of participants and showed strength in terms of time and cost but had the lowest effectiveness. Blending the advantages of digital and offline could enhance learning effectiveness ( Mantyla, 2001 ) and under today’s digital transformation, advancing traditional methods by technology-based learning (e.g., Driscoll, 2002 ; Graham, 2006 ) might be a suitable way of talent development (i.e., Liu et al, 2020 ).…”

Section: Discussionmentioning

confidence: 99%

“…Blended learning combines traditional methods with technology-based learning and avoids the demerits of offline and online learning (e.g., Driscoll, 2002 ; Graham, 2006 ). At present, the terms blended learning and hybrid learning are interchangeably used ( Watson, 2008 ; Graham, 2009 ) and are regarded as one of the most suitable modes for training in the digital era ( Liu et al, 2020 ). Consequently, technology-blended learning could lead to best practices for businesses ( Singh and Reed, 2001 ; Driscoll, 2002 ) since the learners’ cognitive process and the training/teaching strategy might change ( Liu et al, 2020 ).…”

Section: Theoretical Backgroundmentioning

confidence: 99%

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Innovating workplace learning: Training methodology analysis based on content, instructional design, programmed learning, and recommendation framework

Kim

2022

Front. Psychol.

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The quality of sales processes is crucial in automotive and directly related to the firm’s competitive advantage and financial success. Sales training is the most prevalent intervention to guarantee quality and productivity. Extant literature has attempted to measure training effectiveness adequately, and the Context, Input, Process, and Product evaluation (CIPP) model has been a popular approach. This study endeavored to advance current literature and suggest a novel effectiveness framework, Content, Instructional design, Programmed learning, and Recommendation (CIP-R). The framework was applied to examine three different methodologies—traditional, pure digital, and hybrid training—collecting 583 instances from the automotive sales training conducted from 2019 to 2020 in South Korea. The findings advocate the importance of human elements, the role of efficacy, and self-determination in generating learning transferability, leading to performance in the digital age.

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Section: Discussionmentioning

confidence: 99%

Section: Theoretical Backgroundmentioning

confidence: 99%

Innovating workplace learning: Training methodology analysis based on content, instructional design, programmed learning, and recommendation framework

Kim

2022

Front. Psychol.

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“…As is shown in Figure 2, transition, planning, attracting, developing, and retaining are common aspects of talent training or the talent management model. In the case of development, the talent onboarding training process is considered the first and foremost priority that needs to be incorporated into this scenario (Liu et al, 2020). The development of workforce planning relies on broader organizational strategy and management.…”

Section: Talent Management Modelmentioning

confidence: 99%

A Case Study of Talent Training: Based on the Cooperation Between University and Enterprise

Tang¹,

Liu²,

Lian³

et al. 2022

Proceedings of the 2022 2nd International Conference on Enterprise Management and Economic Development (ICEMED 2022)

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Talent training is considered one of the most important in this scenario that is beneficial for enhancing the competitive advantage of students and teaching staff. Good cooperation between universities and enterprises can increase learning and thinking ability to face increasingly severe employment pressure and social demand. This study selected the talent training model from the school of Business Administration of Guangzhou Institute of Science and Technology as the primary sample. This training model is also called "Innovation Class" that is designed to train professional headhunters under the new university-enterprise cooperation policy. We took the contrast method, questionnaire survey, and data analysis to explore a suitable way for private undergraduate universities to build a talent training mode and cultivate classified innovation as well as application.

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“…Liu et al [15] used the Bridge-in, Objective/Outcome, Pre-assessment, Participatory learning, Post-assessment, and Summary (BOPPPS) method as a base to develop their own blended learning approach. They combined BOPPPS to provide interactive, live, and online assignments; online videos for self-study and mind-map summaries; and consolidation exercises via Q&A tests.…”

Section: During the Epidemicmentioning

confidence: 99%

Using Artificial Intelligence to Predict Class Loyalty and Plagiarism in Students in an Online Blended Programming Course during the COVID-19 Pandemic

Chien

et al. 2021

Electronics

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During the COVID-19 epidemic, most programming courses were revised to distance learning. However, many problems occurred, such as students pretending to be actively learning while actually being absent and students engaging in plagiarism. In most existing systems, obtaining status updates on the progress of a student’s learning is hard. In this paper, we first define the term “class loyalty”, which means that a student studies hard and is willing to learn without using any tricks. Then, we propose a novel method combined with the parsing trees of program codes and the fuzzy membership function to detect plagiarism. Additionally, the fuzzy membership functions combined with a convolution neural network (CNN) are used to predict which students obtain high scores and high class loyalty. Two hundred and twenty-six students were involved in the experiments. The dataset was randomly separated into the training datasets and the test datasets for twenty runs. The average accuracies of the experiment in predicting which students obtain high scores using the fuzzy membership function combined with a CNN and using the duration and number of actions are 93.34% and 92.62%. The average accuracies of the experiment in predicting which students have high class loyalty are 95.00% and 92.74%. Both experiments show that our proposed method not only can detect plagiarism but also can be used to detect which students are diligent.

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Online Blending Learning Model of School-Enterprise Cooperation and Course Certificate Integration During the COVID-19 Epidemic

Cited by 6 publications

References 2 publications

Innovating workplace learning: Training methodology analysis based on content, instructional design, programmed learning, and recommendation framework

Innovating workplace learning: Training methodology analysis based on content, instructional design, programmed learning, and recommendation framework

A Case Study of Talent Training: Based on the Cooperation Between University and Enterprise

Using Artificial Intelligence to Predict Class Loyalty and Plagiarism in Students in an Online Blended Programming Course during the COVID-19 Pandemic

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