Teaching Decisional Capacity Evaluation

Scharrer, Melanie; Peterson, Michael J.

doi:10.1016/j.jagp.2018.01.140

Cited by 3 publications

(3 citation statements)

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“…According to experimental findings, this method's prediction accuracy can reach 94.41 percent, which is about 10.22 percent higher than that of conventional methods. e e system of reference [12] e system of reference [16] is paper system The system of reference [12] The system of reference [16] This paper system Test set e system of reference [12] e system of reference [16] is paper system Computational Intelligence and Neuroscience prediction model can utilise NN's self-learning, self-adaptation, and nonlinear approximation capabilities to calculate the quantitative evaluation while also quantifying the subjective factors in the current evaluation system based on expert ratings. Its calculation efficiency is higher than that of the current evaluation system.…”

Section: Results Analysis and Discussionmentioning

confidence: 99%

“…Bhandari et al used the adaptive and self-learning principles of BPNN (Back propagation neural network) for instructional quality evaluation, and proposed an NN-based instructional quality evaluation model structure and an improved BP network learning algorithm [ 10 ]. Donlan and Byrne pointed out that the introduction of evaluation methods in the teaching of piano group lessons will help teachers to fully understand the whole process of teaching, adjust teaching strategies in time, improve students' self-confidence, and stimulate their inner learning motivation; thus realizing piano learning as soon as possible autonomy and the formation of quality education [ 11 , 12 ]. Capella-Peris et al pointed out that the diversified instructional methods, interactive teaching process, and comprehensive teaching content of piano group lessons in normal normal schools are conducive to cultivating students' keyboard performance application, cooperation, performance, and creativity; Comprehensive quality of music [ 13 ].…”

Section: Related Workmentioning

confidence: 99%

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Prediction Model of Piano Collective Class Teaching and Learning Effect Based on Deep Learning

Zhu

2022

Computational Intelligence and Neuroscience

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This paper proposes a prediction model of piano collective class teaching and learning effect based on DL network in order to realise the precise prediction and evaluation of piano collective class instructional effect and promote the improvement of piano collective class instructional quality. The idea of an instructional assessment index is quantified in this paper using specific data as its input and educational impact as its output. In parallel, several training networks are established to correspond to the first-level evaluation indexes, and the input samples are normalised. Finally, MATLAB performs the empirical research. According to the findings, this method’s prediction accuracy can reach 94.41 percent, which is about 10.22 percent higher than that of conventional methods. This prediction model is somewhat realistic and feasible. When used to predict and assess instructional quality, this method not only eliminates the subjectivity of experts in the evaluation process but also yields satisfactory evaluation outcomes and has a broad range of applications. According to the model’s predictions and evaluation findings in this paper, appropriate teachers can better understand the drawbacks of the collective class model, focus on some important aspects of teaching activities, and then enhance instructional methods and effects.

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Section: Results Analysis and Discussionmentioning

confidence: 99%

Section: Related Workmentioning

confidence: 99%

Prediction Model of Piano Collective Class Teaching and Learning Effect Based on Deep Learning

Zhu

2022

Computational Intelligence and Neuroscience

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“…(ii) However, DL Stufflebeam, Warthin, and Sanders believe that teaching evaluation is "a process of systematically searching and collecting information to assist decision-makers in choosing one of the various feasible ways." is view has won the majority of people [10][11][12].…”

Section: Introductionmentioning

confidence: 99%

The Design of Teaching Evaluation and Organization System Based on the Internet of Things Using Fuzzy Comprehensive Evaluation Software

Guo

2021

Mobile Information Systems

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Educational evaluation is the main method of modern education management and guidance. Through a systematic collection of information and quantitative and qualitative analysis, value judgments can be made on the degree to which education adapts to needs, which can effectively improve the teaching development of applied undergraduate colleges. This article applies the Internet of Things technology to the information collection process of teaching evaluation in applied undergraduate colleges. This paper establishes an Internet of Things architecture to collect information on the impact indicators of the teaching evaluation process and builds a teaching evaluation index system. On this basis, this article combines fuzzy comprehensive evaluation for the quantification and evaluation process of index information. Through comparative analysis, the program can provide an effective way to construct a teaching evaluation system suitable for application-oriented undergraduate colleges. Constructing the research-based undergraduate classroom teaching evaluation index system aims at guiding the transformation of the concept of teaching and learning of teachers and students in research universities, perfecting the teaching and learning methods, improving the quality of teaching and learning, and promoting the common development of teachers and students.

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The Design of Student Comprehensive Education Evaluation System in the Background of Big Data

Zeng,

Maomao,

Zhao

et al. 2024

Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering

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Teaching Decisional Capacity Evaluation

Cited by 3 publications

References 0 publications

Prediction Model of Piano Collective Class Teaching and Learning Effect Based on Deep Learning

Prediction Model of Piano Collective Class Teaching and Learning Effect Based on Deep Learning

The Design of Teaching Evaluation and Organization System Based on the Internet of Things Using Fuzzy Comprehensive Evaluation Software

The Design of Student Comprehensive Education Evaluation System in the Background of Big Data

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