Research on optimization strategy and practice of university course management based on machine learning and big data analysis

This manuscript delineates a normative structure for community college students, outlines how this structure varies by student characteristics, and compares this structure to that of a previously established normative structure identified at a 4-year institution. A total of 512 student survey responses on the College Student Behaviors Inventory were collected at a comprehensive community college in the rural Southeast. A series of factor analyses using varimax rotation was applied to identify 23 inviolable norms, 20 admonitory norms, and four laudatory norms, with little variation across student characteristics. Specifically, gender is the only characteristic that yields a significant difference across all patterns of student behavior. We also find the normative structure at a community college to have many similarities to that of a 4-year institution, yet also some differences. The strong number of similarities, however, appears to dispel the suggestion that the diversity in mission and student body characteristics between 2- and 4-year colleges and universities would result in significantly different peer environments. Implications are offered as to how knowledge of such a normative structure may influence policymaking on community college campuses.

The study investigated the characteristic differences among student learning behavior patterns in an online learning situation. Sixty students participated in the work and undertook four months online learning in an e-learning system. The two-stage cluster analysis was designed to explore the identification and classification of student learning behavior patterns. The results found three distinct patterns: Active Participants, Enthusiastic Participants, and Lower Participants. In addition, we found that the preliminary influences of the learning activities and the parent-child learning interaction in online learning situations might be the factors which affect studentpsilas behavior. Finally, this study found no significant difference of learning performance among the various student behavior patterns.

When observing behaviors of special-needs students, on average, typical behaviors of common propensity are observed along with unspecific behaviors. Unlike behaviors that are generally known, information regarding unspecific behaviors is insufficient. For an education or guidance regarding the unspecific behaviors, collection and management of data regarding the unspecific behaviors of special-needs students are needed. In this paper, a consultation management model based on behavior classification of special-needs students using machine learning is proposed. It is a model that provides data to a user by collecting, classifying and managing the behavior data by letting the machine learn the data regarding the unspecific behaviors of special-needs students that are not typical and well known. Since it requires data regarding various behaviors of special-needs students, the data set shall be organized using the behavior pattern data of special-needs students that currently exists, and the data shall be learned by the proposed model. Web-based machine learning model that collects behaviors of special-needs students in real-time is proposed in order to collect the behavior pattern data regarding the unspecific behaviors of special-needs students. The data can be input using the proposed model, and the user can use it through web-browser. The data can be easily input and revised using the proposed model in any environment that the internet can be accessed. The utilization of data analysis result can be enhanced through the use of data list and tools such as a graph through a web-browser, and the accuracy can be enhanced by learning the result that has been acquired by comparing it with previous data by connecting to the database. The test has been performed by arbitrarily applying unspecific behaviors that are not stored in the database, and the forecast model has accurately classified and grouped the input data. Also, it has been verified that it is possible to accurately distinguish and classify the behaviors through the feature data of the behaviors even if there are some errors in the input process. In future, the research of real-time data collection and tailored education index data: the common items need to be organized as a data by recording a class time of special schools or special classes and analyzing the behavior patterns of multiple special-needs students in real-time.

Apartment is a room or several rooms (rooms) that are functioned or designated as a place to live, located in a building that usually has other rooms or rooms and the like. This study attempts to explore and analyze the relationship between residential space patterns and student behavior patterns in Jakarta. The behavioral patterns of students that affect the pattern of vertical residential spaces not only have an impact on the behavior and form of space but also see how student behavior shapes architecture in residential space patterns and architecture shapes student behavior. The purpose of this study is to understand the theory related to the relationship between vertical residential space patterns and student behavior patterns, to understand the characteristics of the relationship between residential space patterns and student behavior, to understand environmental factors for student behavior. The research method taken on the research approach uses a qualitative descriptive method. The data studied and obtained are physical and non-physical data obtained from interviews, observations, and mapping of student behavior patterns in residential spaces of Jakarta apartments. The approach that will be used is the Human Behavior approach to students in apartment housing. From the analysis of behavior patterns carried out, student activities are quite dense, causing the use of furniture according to needs and has ergonomic characteristics.

Data mining (DM) approaches have been applied in the field of Educational Data Mining (EDM) to obtain the important insights about student preferences and behaviors. By using a variety of strategies to increase the effectiveness of e-learning environments, the design aims to enhance learning processes by forecasting the traits of students. Academic data can be used to study trends in student behavior using a selection of DM, such as grouping, classification, and forecasting. This study presents a novel approach to learning behaviors prediction in the Chaotic-Tuned Shuffled Frog Leaping Optimized Random Forest (CSFLO-RF). The CSFLO technique, which accelerates the global convergence of the traditional SFLO technique, improves the accuracy of RF categorization in the suggested methodology. The K-Means Clustering (KMC) methodology uses the student behavior patterns recorded in the log record to group learners into specific categories based on their e-learning system usage. The generated clusters were allocated multiple learning styles based on the framework for learning styles. Following that, the specified behaviors were employed as input for the proposed CSFLO-RF classification to evaluate the degree to predict the students’ learning behavior. According to the results of the suggested technique, which is implemented to utilize the Weka platform, the CSFLO-RF approach yielded more successful outcomes than other existing strategies.

Recent studies of student problem-solving behavior have shown stable behavior patterns within student groups. In this work, we study patterns of student behavior in a richer self-organized practice context where student worked with a combination of problems to solve and worked examples to study. We model student behavior in the form of vectors of micro-patterns and examine student behavior stability in various ways via these vectors. To discover and examine global behavior patterns associated with groups of students, we cluster students according to their behavior patterns and evaluate these clusters in accordance with student performance.

The use of school security measures has increased over the last two decades. Yet prior research suggests school security measures have a deterrent effect on student misbehavior. Existing studies often focus on school-level comparisons in security as opposed to examining how students within a given school differ in their interaction with security measures (i.e., within-school differences). To address this gap in the literature, the current study estimates the association between individual students' engagement with security and multiple forms of maladaptive student behavior in school. In particular, this study is guided by two research questions: 1) What is the relationship between students' engagement with school security measures and their engagement in problem behaviors; and, 2) To what extent do the relationships between engagement with security and student behavior problems differ by student race and ethnicity? Longitudinal data were collected from students at two separate time points in one academic year (N=359) across eight schools in one urban school district. Using a series of models to examine how students' engagement with school security measures is related to their perpetration of student behavior, findings highlight negative associations between engagement with school security and non-serious violent and weapons-related crime. While the school security change score and students' engagement in problem behaviors was no different for Black students than it was for students who were non-Black or non-Hispanic, the negative association between engagement with security and behavior indicated a stronger deterrent effect for Hispanic students. Findings suggest that engagement with school security should be examined at the within-school level and with consideration that racial and ethnic differences might vary from student to student within any given school. Moreover, long-term programming goals should be established when developing process for securing schools with emphasis on how security measures might influence individual students differently within the school setting.

Youth's social relationships at school and at home have been shown to predict a wide variety of school outcomes, such as behavior at school and academic performance. Specifically, relationships with teachers, parents, and peers have all been shown to affect student performance. The current study utilized data collected from 848 Latino middle school students to examine direct and indirect linkages of students' relationships with teachers, parents, and friends with student outcomes. Structural equation models revealed that teacher support was associated with both student behavior and satisfaction with school and was indirectly associated with time spent on homework and grades. Parental support, friend support, friends' school behavior, and parental monitoring of educational issues were directly associated with student reports of teacher support and were indirectly linked to school behavior and satisfaction. Friend behavior at school also showed a significant direct association with student behavior, and parental education monitoring directly predicted student satisfaction with school. Directions for future research and implications for school policy and programming are discussed.

The current research on the study of school climates is described, and implications of this research for counselor role are indicated. This research has examined the nature of educational climates and environments, as well as the relationship of various environments to student achievement, attitudes, and behaviors. The research provides information about the nature of school environments as they are affected by staff characteristics and behaviors and student peer group characteristics. This research indicates that schools do have quite different climates which are supportive of diverse types of student and staff behavior. It appears that the adjustment and success of an individual student may well be a function of (a) the type of climate of the school he attends, and (b) the extent to which the school climate is supportive of his individual needs. After an extensive review of nine methodologies for studying school climate, possible applications of these research findings by the counselor are described.

The development of information technology has made the management of students more systematic in colleges and universities. Student behavior information, such as grade information, trajectory information, competition information, and diversified student behavior information makes college management cumbersome. The application of big data technology can mine student behavior information and realize the construction smart campus. In this regard, this paper designs a student behavior analysis system, and uses the Kmeans algorithm to perform cluster analysis on the data of student behavior characteristics, which provide quantitative data support for the evaluation of scholarships and bursaries and the identification of poor students in the process of student management. The system is used to analyze student behavior, saving a lot of labor costs and providing scientific decision-making suggestions for student management.

Youth dress, influenced by commercialism, impacts students' attitudes and behaviors in public schools. This article reports quantitative data and qualitative data on Black educators' views on student dress and behavior, including the use of uniforms. Findings indicate that educators support the use of school uniforms because they believe that uniforms reduced the risk of both psychological harm and school related problems. Younger students (sixth graders) agreed with the educators while the older students disagreed. These findings generally reflect the views of many educators who are grappling with effective strategies to reduce dress-related problems among youth in public schools. Children and adolescents are socialized around dress across several settings such as the family, school, marketplace, workplace, and others. Research has been conducted on dress socialization and its influence on children's development and has identified many dress-related challenges and problems within these various contexts (LaPoint, Alleyne, Lee, & Mitchell, 2003). Many public schools, especially at the elementary and middle school levels, have begun to implement student uniforms in an effort to promote student health and safety (Lopez, 2003). Very little empirical research exists on the effectiveness of school uniforms on student achievement and social competence. Moreover, little research exists in educators' views on the nature of dress-related problems at school, especially the views of educators of color (LaPoint et al., 2003). This article reports qualitative and quantitative data on Black educators' views on dress and behavior in a public middle school in a large Northeastern city. It is part of a larger study on youth dress and behavior and includes data collected from students (LaPoint et al., 2003). The article includes a literature review, a description of the study including the sample and methods, analysis and findings, and implications for further research, policies, and programs relating to the use of uniforms in public schools. LITERATURE REVIEW While literature on student dress and behavior in public schools often cites educators' views on youth dress and behavior in public schools, it is often anecdotal (LaPoint et al., 2003). The literature generally focuses on educators' (e.g., teachers, administrators, staff) views of challenges of youth dress to classroom and school behaviors and the solutions to theses challenges, including the use of uniforms (King, Walker, & Minor, 2002; King, 1998; LaPoint et al., 2003; Lopez, 2003; Mitchell & Knechtle, 2003). Research and reports are inconclusive about the positive impact of uniforms on various academic and academic-related behaviors (Brunsma & Rockquemore, 1998; LaPoint et al., 2003). Moreover, some research indicates mixed support for the use of uniforms in public schools (National Association of Elementary School Principals, 1998) even though the federal government issued guidelines encouraging the use of uniforms in public schools (U.S. Department of Education, 1996). Finally, the literature, generally does not relate commercialism influences on youth dress in schools to broader commercialism influences in other settings (LaPoint & Alleyne, 2001; LaPoint et al., 2003). The present study provides empirical data, both quantitative and qualitative, on educators' views on the use student uniforms in one public middle school. It also provides data on educators' views about commercial influences on students' attitudes and dress in the school and other socialization settings. THE RESEARCH STUDY The study used two approaches to obtain educators' views on student dress and behavior in a public middle school in a northeastern U.S. city. The first was a survey that examined Black educators' attitudes toward dress and behavior among students. These data were compared with the data obtained from all students in the school (grades 6, 7, and 8). …

With the advancement of Internet information technology, the rapid development of the Internet celebrity economy has had an important impact on the consumption behaviour of college students. The online live broadcast platform caters more to the consumer psychology of college students. College students are more susceptible to its influence and blind consumption occurs. Combining the characteristics of live broadcast platforms in the Internet celebrity economy and the characteristics of college students' consumption psychology and behaviour, this paper selects four variables of media brand, highlights show, interaction & promotion and interest groups as the starting point, uses structural equation model(SEM), and uses AMOS software to carry out structural equation analysis. This paper analyses the influence of the "Internet celebrity economy" marketing model on the actual consumption behaviour of college students. The results show that highlights show and media brands will promote the actual consumption behaviour of college students, while interaction & promotion and interest groups have no significant impact on the consumption behaviour of sample college students. This paper further analyses the reasons for the formation of this situation, and provides reference and suggestions for guiding college students to establish a reasonable consumption view.

Background and Aim: Vocational high schools play a crucial role in cultivating technical and skilled talents. However, managing student behavior and fostering a positive learning environment remain significant challenges due to the unique characteristics of vocational students, such as lower academic foundations and weaker self-discipline. Traditional class management methods often fall short in addressing these issues. The 7S management method, originating from industrial management practices, has recently gained attention in educational settings. This study aims to explore the application of the 7S management method in vocational high school class management and its impact on student behavior and class environment. Materials and Methods: This study employed a quasi-experimental design, selecting one class from a vocational high school as the experimental group. Data were collected through systematic observation, questionnaires, and semi-structured interviews. The 7S management method was implemented over a semester, during which changes in classroom environment, student behavior, and learning attitudes were monitored. To analyze the collected data, both quantitative and qualitative analysis methods were used. Quantitative data from the questionnaires were analyzed using descriptive statistics to summarize key trends, followed by inferential statistics, such as paired t-tests, to assess significant changes before and after the implementation of the 7S method. Qualitative data from observations and interviews were analyzed using thematic analysis, where recurring themes and patterns were identified and coded. This mixed-methods approach allowed for a comprehensive evaluation of the impact of the 7S method on the class environment and student behavior. Results: The implementation of the 7S management method led to significant improvements in class cleanliness, student organization, and overall classroom discipline. Students reported increased satisfaction with the learning environment and a greater sense of responsibility. Qualitative data from interviews indicated that both teachers and students perceived positive changes in class cohesion and learning atmosphere. Conclusion: The 7S management method is an effective tool for enhancing class management in vocational high schools. It not only improves the physical environment but also fosters positive behavioral changes and a stronger sense of community among students. Future research should focus on long-term effects and broader implementation strategies.

The aim of this paper is to describe the consumer behaviour and everyday lifestyle patterns of Hungarian university and college students. The results are gained from an international survey, carried out by the Department of Environmental Economics and Technology at the Corvinus University of Budapest, supported by the Norwegian Financial Mechanism. As background literature, characteristics of the consumer society and the development of sustainable consumption as a concept are interpreted in the paper. The empirical analysis aims to describe the most important clusters of students, based on the factors of their consumer behaviour, environmental activism and pro-environmental everyday habits. Our results identify two extreme clusters which most significantly differ from each other: the environmental activists and the indifferent group. However, a third cluster has the most modest consumer behaviour, namely the group which considers product features, energy consumption and the behaviour of producers. They sp...

With the rapid advancement of the internet and mobile technology, the global e-commerce industry is experiencing unprecedented growth. As the largest e-commerce market in the world, China has made significant progress in e-commerce infrastructure, payment methods, and logistics systems in recent years. However, international students in China may face challenges and opportunities in the online shopping environment that differ from those in their home countries. As a unique consumer group, the online shopping behavior of international students is influenced not only by personal characteristics, technology acceptance, and other factors but also by their cultural backgrounds. This study aims to explore the behavior patterns of international students in China’s online shopping environment, particularly how online shopping perceptions, cultural differences, and purchase intentions jointly influence their online shopping behavior. Through a questionnaire survey, this research selects foreign students from Chongqing and Chengdu as subjects, establishing an empirical model covering e-commerce perception factors, cross-cultural adaptation characteristics, consumption decision tendencies, and cross-border online shopping behavior. The study systematically analyzes the interactive effects of multiple factors on international students' online consumption behavior. The introduction chapter outlines the research's value and practical significance, clarifies the academic objectives and research approach, and summarizes the innovative dimensions and academic breakthroughs of this study. The theoretical foundation chapter integrates consumer decision-making mechanisms, rational behavior frameworks, technology adoption models, risk perception theories, and cross-cultural adaptation theories, constructing a multi-dimensional academic analysis framework. The model construction chapter clearly defines the observed and latent variables in the empirical study, establishes a quantifiable indicator system, and deduces a series of testable hypotheses based on theoretical reasoning. In the research implementation section, the focus is on data collection standards and quality control processes, detailing the dimensional division and scale selection criteria for the questionnaire design, as well as sampling strategies and the effective response rate of the questionnaires. The data analysis module uses statistical software to systematically process the sample data, conducting internal consistency tests, structural validity verification, multicollinearity diagnostics, and hierarchical regression analysis, ultimately completing the empirical validation of the research hypotheses. The core objective of this study is to explore the consumption characteristics of foreign students on Chinese e-commerce platforms, with a focus on how online consumption perception dimensions (including perceptions of shopping convenience, ease of use, transaction risks, and platform trust) influence actual purchasing behavior through the mediation of purchase intentions. The study also examines the moderating effects of cross-cultural dimensions (involving individual value orientations, class cognition differences, and risk aversion tendencies) in the consumption decision-making chain, providing empirical evidence for optimizing international user service experiences on cross-border e-commerce platforms. Through in-depth data analysis and hypothesis testing, this research aims to provide targeted marketing strategy recommendations for e-commerce platforms, helping them better understand and serve this important international consumer group, thus promoting the development of cross-border e-commerce.