Improving the quality of teaching by utilising written student feedback: A streamlined process

Hujala, Maija; Knutas, Antti; Hynninen, Timo; Arminen, Heli

doi:10.1016/j.compedu.2020.103965

Cited by 47 publications

(34 citation statements)

References 63 publications

(124 reference statements)

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“…When the temperature is high, the new solution may be accepted, which is almost random. With the decrease in temperature, more and more people tend to choose a better solution [18][19][20].…”

Section: Optimization Of Evaluation Weight Based On Simulatedmentioning

confidence: 99%

Research on Teaching Quality Evaluation Model of Physical Education Based on Simulated Annealing Algorithm

Duan

Hou

2021

Mobile Information Systems

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One of the most significant components of the teaching department is the evaluation of teaching quality. The traditional teaching quality evaluation model has the problems of low weight calculation accuracy and long evaluation time. With the development of educational informatization, modern information processing technology can be used to effectively evaluate teachers’ teaching quality. In this article, a physical education teaching quality evaluation model based on the simulated annealing algorithm is proposed. An evaluation index system is established based on the construction principles of the evaluation index system followed by the construction of a judgment matrix to calculate the weight of the evaluation index. The simulated annealing algorithm is employed to effectively optimize the weight of the evaluation index and improve the evaluation accuracy. In addition, the analytic hierarchy process (AHP) is used to test the consistency of the judgment matrix, and the weight ranking results of the evaluation indexes are obtained to complete the teaching quality evaluation of physical education. The experimental results show that the performance of the proposed model in terms of evaluation weight calculation accuracy and evaluation calculation time is higher than that of the existing models. Therefore, the proposed model can better meet the requirements of physical education teaching quality evaluation.

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Section: Optimization Of Evaluation Weight Based On Simulatedmentioning

confidence: 99%

Research on Teaching Quality Evaluation Model of Physical Education Based on Simulated Annealing Algorithm

Duan

Hou

2021

Mobile Information Systems

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“…e study on the impact and mechanism of the green innovation performance on companies is distinct for most researchers in Germany and overseas from that of traditional innovation performance on companies. Scott [1] thinks, for instance, that corporations must also consider demand-side issues in addition to typical R&D operations. ese include market demand, environmental guidelines, and pressure on business innovation performance in the same industry.…”

Section: Green Innovation Performancementioning

confidence: 99%

Big Data-IoT: An Analysis of Multidimensional Proximity Implications on Green Innovation Performance—An Empirical Study of the Data from the Chinese Power Industry

Xiao

Jian-bang

Luo

et al. 2021

Mobile Information Systems

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With the global energy crisis and environmental degradation getting more rigorous, an essential approach is required to attain introverted development through structural optimization, autonomous invention, and technological innovation system. It is an important way to include energy conservation, emission reductions, and the implementation of a low-carbon mode in the power industry, which is a highly polluting sector of the national economy. This article is based on the State Intellectual Property Office of China’s patent search and analysis database. We choose the number of green patents jointly submitted for innovative topics in the power industry from 2016 to 2020. The negative binomial regression is constructed from the standpoint of multidimensional closeness by employing Gephi visual analysis, Ucinet, and the Stata 15 regional model. Furthermore, we investigate the impact of geographical closeness, technological closeness, and institutional closeness, as well as their interaction, on the green innovation performance of inventive organizations in China’s power industry. According to the findings of the study, geographical and institutional closeness have an important influence in increasing the green innovation performance. The suggested model applies to the power sector, and technological closeness has an inverted U-shaped association with green innovation performance in the power business. Furthermore, the model output at inference time is just a collection of successive parameters that improve the interaction of the closeness of innovation subjects to the green innovation performance of the power industry, all of which are represented as complementary effects.

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“…At present, the main method of evaluating mathematics teaching in domestic colleges and universities is the evaluation of students' performance. Under the new situation, the method of teaching reform must break through the traditional one-size-fits-all teaching evaluation method [10]. For example, in the assessment of students, it is necessary to add some practical skills exercises, which will make the assessment space wider, so that students can apply the knowledge content they have learned through practice and think to answer.…”

Section: Effectively Reform the Current Teaching Evaluation Andmentioning

confidence: 99%

Quality Evaluation Method of a Mathematics Teaching Model Reform Based on an Improved Genetic Algorithm

Yang

2021

Scientific Programming

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The poor comprehensiveness of the evaluation indexes of quality evaluation methods for the traditional college mathematics teaching model reform results in low accuracy of the evaluation outcomes. In this paper, aiming at this problem, a quality evaluation method for the college mathematics teaching model reform, based on the genetic algorithm, is proposed. The simulated annealing algorithm uses the weighted comprehensive objective evaluation multiobjective optimization effect that can effectively improve the accuracy of the evaluation results. In the training process, the gradient descent back-propagation training method is used to obtain new weights for the quality evaluation of college mathematics teaching mode reforms and to score various indicators and evaluate the indicators. The mean value of the outcomes is the result of mathematics teaching quality evaluation. The experimental results show that the training error of the convolutional network of the proposed method is significantly small. Based on the genetic algorithm that improves the convolutional network training process, the obtained quality evaluation outcomes are higher in accuracy, better in goodness of fitness function, and considerably lower than other state-of-the-art methods. We observed that the improved genetic algorithm has a more than 90% goodness of fit and the error is significantly lower, that is, 0.01 to 0.04, than the classical genetic algorithm.

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Improving the quality of teaching by utilising written student feedback: A streamlined process

Cited by 47 publications

References 63 publications

Research on Teaching Quality Evaluation Model of Physical Education Based on Simulated Annealing Algorithm

Research on Teaching Quality Evaluation Model of Physical Education Based on Simulated Annealing Algorithm

Big Data-IoT: An Analysis of Multidimensional Proximity Implications on Green Innovation Performance—An Empirical Study of the Data from the Chinese Power Industry

Quality Evaluation Method of a Mathematics Teaching Model Reform Based on an Improved Genetic Algorithm

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