LEARNING ASSESSMENT AMONG COLLEGE STUDENTS AND ITS RELATION TO CLASSROOM PERFORMANCE

This paper examines the relationship between learning assessment among college students and classroom performance. It explores the different methods of assessment used in higher education settings, their impact on student learning, and how they influence student performance in the classroom. The study suggests that effective assessment practices enhance student engagement, motivation, and understanding of the subject matter, ultimately leading to improved academic performance. The paper concludes by providing recommendations for educators to implement effective assessment strategies in college classrooms

A Development of Student Leadership Characteristic Practice Model at Normal Universities in Hebei Province, China

Student leadership development provides students with opportunities to demonstrate andcultivate their leadership characteristics. In this research, the main purpose was to create a model for the development of student leadership characteristic practice at Normal Universities in Hebei Province of China. It applied both qualitative and quantitative methods. The researcher applied the content analysis about desirable student leadership characteristics in higher education. Skills, knowledge and attitude were crucial components of student leadership development, and the accomplished results of content analysis were validated by twenty-one experts. The researcher utilized survey questionnaires for data collection of 377 students, 243 teachers and 37 top-level administrators. The results ofquestionnaires, combined with interview data collection of 52 market employers of internship together as a reference revealed the areas that need urgent improvements. Student leadership theories and initial findings of first and second objective derived a preliminary model, after the experts’ validation and discussion; the researcher modified the nascent model until it became the final model. In the following step, the period of implementation included three months, which comprised student leadership conferences, local community service outreach, empowering leaders’ camp, co-curricular activities, andevaluation and feedback of student leadership characteristic practice, these called intervention program was developed based on the model. The results of differences between pre-test and post-test, which contained a total of 50 participants, proved that the model was undoubtedly effective with long-term significance. Eventually, the final model and the leadership training offered a potential programmatic option to help develop students as outstanding leaders.

Enhancing Students' Metacognition via AI-Driven Educational Support Systems

As the penetration of digital technology deepens and the demands for educational modernization grow, attention is increasingly being drawn towards the application of artificial intelligence (AI) in the field of education. Especially in educational practice, the optimization of students’ learning experiences and the enhancement of their metacognitive abilities through AI technology have captivated the interest of numerous educators and scholars. Metacognition, which represents a core skill in student self-regulation and self-management, has a significant impact on student learning outcomes and quality. However, current educational support systems primarily rely upon traditional methods of data collection and analysis, which have limitations in terms of real-time responsiveness, granularity, and comprehensiveness. The present research aims to investigate the integration of AI technology with a specific focus on the learning process through educational support systems and the development of a cooperative teaching interaction model. This will ultimately enhance the development of students’ metacognitive abilities more effectively

A sensitivity study of artificial viscosity in a defect-deferred correction method for the coupled Stokes/Darcy model

This paper analyzes the sensitivity of the artificial viscosity in the defect deferred correction method for the non-stationary coupled Stokes/Darcy model. For the defect step and the deferred correction step of the defect deferred correction method, we respectively give the corresponding sensitivity systems related to the change of artificial viscosity. Finite element schemes are devised for computing solutions to the sensitivity systems. Finally, we will verify the theoretical analysis results through numerical experiments. Our results reveal that the solution is sensitive for small values of the artificial viscosity, and when the viscosity/hydraulic conductivity coefficients are small

Construction and Application Practice of the Digital Platform for Red Education of the Young Pioneers of China

The survey found that there is a shortage of red education and extracurricular reading among Chinese primary school students, who play video games and watch cartoons more than watch red inspirational books and movies outside of class, and lack ambitious ideals and learning motivation. To improve this situation, the research group built a digital platform for red education for Chinese children and youth and conducted a one-semester after-school reading comparison experiment among 427 elementary school students in Hangzhou LX Primary School. The post-experimental measurement found that the students in the experimental group enjoyed the “read red books + watch red movies” activity for one hour a day, and their reading time and quantity of red books/films increased significantly, their time spent playing video games and watching cartoons decreased by 46% per day, and their knowledge of Chinese revolutionary history and socialist core values, patriotic consciousness, ideal beliefs, and enthusiasm for learning also improved. Their knowledge of Chinese revolutionary history and core socialist values, patriotic consciousness, ideal beliefs, and enthusiasm for learning have also been greatly improved, and their total scores in the final exams of four courses, namely Chinese, mathematics, moral character, and English, have increased by 12% compared with those before the experiment. In contrast, in the control group, which did not carry out the reading activity and maintained the original learning and living condition, the above post-test indicators did not change significantly from the pre-test. Therefore, the experiment shows that this digital reading model has a positive effect on the cultivation of qualified communist successors, and provides experience and reference for the cultivation and education of Chinese elementary school students

Conjugate phase retrieval in a complex shift-invariant space

The conjugate phase retrieval problem concerns the determination of a complex-valued function, up to a unimodular constant and conjugation, from its magnitude observations. It can also be considered as a conjugate phaseless sampling and reconstruction problem in an infinite dimensional space. In this paper, we first characterize the conjugate phase retrieval from the point evaluations in a shift-invariant space $\mathcal S(\phi)$, where the generator $\phi$ is a compactly supported real-valued function. If the generator $\phi$ has some spanning property, we also show that a conjugate phase retrievable function in $\mathcal S(\phi)$ can be reconstructed from its phaseless samples taken on a discrete set with finite sampling density. With additional phaseless measurements on the function derivative, for the B-spline generator $B_N$ of order $N\ge 3$ which does not have the spanning property, we find sets $\Gamma$ and $\Gamma'\subset (0,1)$ of cardinalities $2N-1$ and $2N-5$ respectively, such that a conjugate phase retrievable function $f$ in the spline space $\mathcal B_N$ can be determined from its phaseless Hermite samples $|f(\gamma)|, \gamma\in\Gamma+\Z$, and $|f'(\gamma)|, \gamma'\in\Gamma'+\Z$. An algorithm is proposed for the conjugate phase retrieval of piecewise polynomials from the Hermite samples. Our results provide illustrative examples of real conjugate phase retrievable frames for the complex finite dimensional space \C^N

The Impact of Psychological Factors on the Asymmetry of Stock Market Volatility in China—An Empirical Study Based on EGARCH Model

The asymmetry of stock market volatility has existed for a long time. Most of the early scholars’ research on this phenomenon is based on the assumption of efficient market. In recent years, with the development and deepening of behavioral finance theory, psychological factors have been added to the research process as an important variable to better explain the asymmetry of stock market volatility. Therefore, on the basis of this analysis, this paper uses the basic theories of overconfidence, disposal effect, herding effect and framing effect of behavioral finance to analyze the impact of different psychological conditions on stock market volatility. This paper collects all the closing price data of the Shanghai and Shenzhen 300 index, and processes the logarithmic rate of return, then introduces the proxy variable turnover rate of psychological factors into the mean equation of EGARCH model, establishes a modified EGARCH model, and obtains the empirical results that psychological factors do have an impact on the asymmetry of volatility in China’s stock market. It is concluded that: first, there is asymmetry of volatility in China’s stock market, Investors will respond significantly more to bad news than to good news. Second, when investors are hit by bad news, their expectations for the future become worse, which will increase the turnover rate and finally obtain a lower yield; When investors are hit by good news, their expectations for the future become better, which will reduce the turnover rate and finally obtain a higher yield. Finally, according to these two conclusions, positive and feasible suggestions are given

Simultaneously encoding movement and sEMG-based stiffness for robotic skill learning

Transferring human stiffness regulation strategies to robots enables them to effectively and efficiently acquire adaptive impedance control policies to deal with uncertainties during the accomplishment of physical contact tasks in an unstructured environment. In this work, we develop such a physical human-robot interaction (pHRI) system which allows robots to learn variable impedance skills from human demonstrations. Specifically, the biological signals, i.e., surface electromyography (sEMG) are utilized for the extraction of human arm stiffness features during the task demonstration. The estimated human arm stiffness is then mapped into a robot impedance controller. The dynamics of both movement and stiffness are simultaneously modeled by using a model combining the hidden semi-Markov model (HSMM) and the Gaussian mixture regression (GMR). More importantly, the correlation between the movement information and the stiffness information is encoded in a systematic manner. This approach enables capturing uncertainties over time and space and allows the robot to satisfy both position and stiffness requirements in a task with modulation of the impedance controller. The experimental study validated the proposed approach