Affordances and constraints of mathematics-specific observation frameworks and general elements of teaching quality

Litke, Erica; Boston, Melissa D.; Walkowiak, Temple A.

doi:10.1016/j.stueduc.2020.100956

Cited by 21 publications

(14 citation statements)

References 55 publications

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“…According to the principle of weight determination, with reference to the weight setting data of other higher vocational colleges, the weights of primary indicators and secondary indicators are determined through expert discussion by using an expert opinion method and investigation and analysis method, and the sum of the weights of indicators at the same level is 1. The value of teaching quality evaluation is simulated using a BP neural network in this paper [22][23][24][25]. The primary index evaluation value is used as the input value, and the secondary index evaluation value is turned into the primary index evaluation value.…”

Section: Evaluation Algorithm Of Network Ideological Andmentioning

confidence: 99%

Analyzing the Network Evaluation Model in Mobile Learning Environment to Monitor Different Capabilities of Students

2022

Wireless Communications and Mobile Computing

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In light of the current ideological and political teaching quality’s poor impact, this paper proposes the construction and research method of a network ideological and political teaching quality evaluation model from the perspective of school-enterprise cooperation, optimises the network ideological and political teaching model using the Internet technology, constructs the teaching quality evaluation index and algorithm, and realizes the optimization of the ideopolitical teaching model. Finally, it is confirmed by experiments. According to the viewpoint of school endeavor collaboration, the organization’s philosophical and political quality evaluation model has higher practicability during the time spent in commonsense application and completely meets the examination prerequisites.

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Section: Evaluation Algorithm Of Network Ideological Andmentioning

confidence: 99%

Analyzing the Network Evaluation Model in Mobile Learning Environment to Monitor Different Capabilities of Students

2022

Wireless Communications and Mobile Computing

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“…Physical education is different from cultural courses. Physical skills and sports intelligence account for a large proportion of physical education, so it is necessary to evaluate physical education teaching and sports skills, but physical education also has the function of educating people, and it can also reveal many principles and philosophies of life, so the evaluation of humanistic thought and sports culture in physical education teaching is also indispensable [18][19][20]. is requires a more comprehensive, objective, and reasonable method to be applied to the evaluation of physical education teaching quality.…”

Section: Introductionmentioning

confidence: 99%

Evaluation Method of Physical Education Teaching and Training Quality Based on Deep Learning

Wang

Yang

Xing

2022

Computational Intelligence and Neuroscience

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To solve the problems of great difficulty and low accuracy in the evaluation of physical education teaching results, an evaluation method of physical education teaching and training quality based on deep learning is proposed. The evaluation index system is constructed based on the teaching content, teaching attitude, teaching content, teaching method, and teaching effects that affect the teaching quality. After the influence factors of each index are quantified, the resolution coefficient of the index is dynamically taken, the index correlation relationship based on weight is established, and the score distribution and score progress are taken as the evaluation results. The test results show that the correlation coefficient between the evaluation result of the design method and the actual results is 0.9430, and the evaluation accuracy is 94.73%.

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“…The data to be clustered are not labeled with its category in advance and can be generated by a mixed model. Its main idea is to divide data into several classes or clusters to maximize the similarity of data objects within clusters and minimize the similarity of data objects between clusters [ 9 ]. The clustering algorithm can be selected by the data type of field attributes in the database and the characteristics of objects operated by clustering.…”

Section: Introductionmentioning

confidence: 99%

“…e data to be clustered are not labeled with its category in advance and can be generated by a mixed model. Its main idea is to divide data into several classes or clusters to maximize the similarity of data objects within clusters and minimize the similarity of data objects between clusters [9].…”

Section: Introductionmentioning

confidence: 99%

Data Analysis of Educational Evaluation Using K-Means Clustering Method

Liu

2022

Computational Intelligence and Neuroscience

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It is thought to be an effective technique to handle the problem of educational data explosion and lack of information by identifying potential relationships between data and directing decision-makers through the extraction, transformation, analysis, and modeling of educational data. Based on this, this research constructs a data analysis model for education evaluation using the K-means clustering technique in DM. The weight of each index of students’ comprehensive quality is calculated using AHP, and the value of the weight is used to determine whether the index is the important feature of analysis system mining. Improved sampling technology is used to deal with the representation of large-scale data sets; a sample partition clustering technique is proposed as a general framework. The best accuracy of this method, according to experimental data, is 95.6 percent, which is 12.1 percent greater than Mi cluster algorithm and 6.8 percent higher than DRCluster algorithm. The K-means clustering analysis technology is used to analyze students’ comprehensive evaluation data in this paper, with the goal of determining the regularity of data implication, accurately diagnosing learning problems, and providing the foundation for developing effective student management strategies.

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Affordances and constraints of mathematics-specific observation frameworks and general elements of teaching quality

Cited by 21 publications

References 55 publications

Analyzing the Network Evaluation Model in Mobile Learning Environment to Monitor Different Capabilities of Students

Analyzing the Network Evaluation Model in Mobile Learning Environment to Monitor Different Capabilities of Students

Evaluation Method of Physical Education Teaching and Training Quality Based on Deep Learning

Data Analysis of Educational Evaluation Using K-Means Clustering Method

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