An Evaluation Model for the Cultivation and Improvement of the Innovation Ability of College Students

Wang, Kechuang; Yan, Chuankui

doi:10.3991/ijet.v15i17.16735

Cited by 6 publications

(3 citation statements)

References 24 publications

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“…According to the actual case study, the current sports professional academics and teachers in the scientific research and innovation ability are the shortcomings, and they indicate the direction to promote the teachers and students of sports academic research and innovation ability to improve. Literature [14] designed a framework for judging the level and development of students' innovation ability, and empirical analysis methods were used to corroborate the feasibility of the proposed assessment framework. Literature [15] designed an analytical framework based on grey system theory and hierarchical Analysis to understand the logic of the teacher-student collocation teaching model to develop students' knowledge innovation ability and gave some constructive optimization solutions to provide some ideas for the development of students' knowledge innovation ability.…”

Section: Introductionmentioning

confidence: 99%

Quality Innovation Cultivation Strategy for College Students in the Internet Era Oriented on the Cultivation of Innovative Ability

Zhou,

2024

Applied Mathematics and Nonlinear Sciences

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Addressing the imperative of cultivating innovation and learning quality in 21st-century college education, this research proposes a strategic CTDE model to enhance college students’ innovative capacities. By implementing a personalized information mining technique, we have established a sophisticated user profile model that strategically distributes learning resources geared towards innovation. The methodology integrates factor analysis with K-means clustering for a customized learning experience. A targeted survey reveals notable achievements: a standout innovation ability score of 3.92 for an individual student and a class-wide enhancement, with improvements ranging from 14% to 21% after detailed work evaluations. These findings affirm the CTDE model’s efficacy in fostering student innovation and quality learning.

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Section: Introductionmentioning

confidence: 99%

Quality Innovation Cultivation Strategy for College Students in the Internet Era Oriented on the Cultivation of Innovative Ability

Zhou,

2024

Applied Mathematics and Nonlinear Sciences

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“…In order to provide guidance to learners in making learning decisions, a necessary work is to thoroughly analyze and research the changing laws of learners' learning behavior [1][2][3][4][5][6][7][8][9]. This research involves professional knowledge of psychology, pedagogy, sociology, and other disciplines, through descriptive statistics on the learning behavior of different groups, it can be found that individuals in learning groups have a few similarities in terms of the regularity of learning time, requirement for learning resources, and requirement for tutoring and accompanying [10][11][12][13][14][15][16][17].…”

Section: Introductionmentioning

confidence: 99%

College Students' Learning Decision-Making Based on Group Learning Behavior

Li¹,

Chen²,

Li³

2022

Int. J. Emerg. Technol. Learn.

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In learning groups, individuals have a few similarities in terms of the regularity of learning time, requirement for learning resources, and requirement for tutoring and accompanying. Analyzing the differences and connections of the learning behavior of different groups is helpful for generating more effective, targeted, and comprehensive learning decisions, however, existing studies are not extensive or deep enough in analyzing the learning behavior of different type learning groups. For this reason, this paper attempts to explore a learning decision-making model based on the influence of group learning behavior. At first, this paper made use of the advantages of Q-learning to improve the conventional behavior tree model, constructed a new model and used it to research the group learning behavior; then, this paper combined decision-making idea with the game model, and adopted a complex network structure to explore the evolution law of group learning decision-making based on multiple games. At last, this paper used experimental results to prove the effectiveness of the constructed model.

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“…e specific steps of the algorithm were given. Wang and Yan [30] proposed an extension model for evaluating students' ability cultivation and improvement: the problem was clearly defined as the evaluation of the cultivation and improvement of college students' innovation ability, an evaluation model was established to train and enhance that ability, the workflow of the model was explained, and the evaluation algorithm was designed in detail.…”

Section: Introductionmentioning

confidence: 99%

Design and Implementation of University Students Scientific Research Ability Evaluation System Based on Neural Network

Yin

Zhang

et al. 2022

Scientific Programming

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At present, many colleges attach more and more importance to the cultivation of scientific research ability of college students. However, there is no unified standard to effectively measure the cultivation effect. The current performance inference method cannot comprehensively evaluate the scientific research ability of college students. Few scholars have directly analyzed the college students’ scientific research ability from the internal and external influencing factors. Therefore, this paper tries to design and implement a neural network analysis system for scientific research ability evaluation of college students. After surveying the status quo of scientific research ability evaluation of college students in northern China’s Hebei Province, a hierarchical evaluation index system was constructed for college students’ scientific research ability, referring to the existing evaluation index systems, and the weights were designed for the evaluation indices. Next, the backpropagation (BP) neural network was optimized by chaotic sine-cosine grasshopper optimization algorithm (CSCGOA) and used to establish a neural network analysis system for scientific research ability evaluation of college students. The proposed system was proved effective through experiments. The relevant results effectively enhance the scientific level and accuracy of the evaluation of college students’ scientific research ability, improve the cultivation of college students, and provide a scientific basis for colleges to understand the scientific research ability of their students.

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An Evaluation Model for the Cultivation and Improvement of the Innovation Ability of College Students

Cited by 6 publications

References 24 publications

Quality Innovation Cultivation Strategy for College Students in the Internet Era Oriented on the Cultivation of Innovative Ability

Quality Innovation Cultivation Strategy for College Students in the Internet Era Oriented on the Cultivation of Innovative Ability

College Students' Learning Decision-Making Based on Group Learning Behavior

Design and Implementation of University Students Scientific Research Ability Evaluation System Based on Neural Network

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