Classroom Behavior Research Articles

Academic Ethical Awareness among Undergraduate Nursing Students of a Private University in Nigeria: A Cross-Sectional Descriptive Study.

Academic ethical awareness is a crucial prerequisite for practice, serving as the cornerstone for a professional demeanor in clinical settings and ensuring future adherence to nursing ethics. This study assessed academic ethical awareness as well as its related characteristics among undergraduate Nursing students of a private university in Nigeria. A descriptive cross-sectional research design was utilized. The study was conducted among undergraduate nursing students of a private university in Nigeria. A convenience sample of 158 nursing students from 300 level to 500 level voluntarily participated in this study. Data were collected using the Academic Ethical Awareness Questionnaire and descriptive statistics, mean and standard deviation were employed to analysis the data collected. The mean age of nursing students was 21.1. Majority of the respondents were females, Christians and claimed average financial status with 87%, 94%, and 68%, respectively. Nursing students demonstrated moderate academic ethical awareness (69.5%), a mean score of 3.68 ± 0.81. They knew that revealing patient information in public places of the hospital, disregarding, slandering, or making fun of patients in face-to-face interaction, and having someone else attend class as a substitute were unethical behaviors with mean scores of 3.96, 3.90, 3.88, and 3.88, respectively. Academic ethical awareness was low for submitting cut and paste report, not paying attention in class and being late to class, with mean scores 1.81, 2.05, and 2.80, respectively. Gender, level of study, and satisfaction with Nursing as a course of choice are significant determinant of ethical academic awareness with P value of .018, .005, and .011, respectively. Nursing students assessed demonstrated moderate academic ethical awareness. Improved instruction is required regarding the value of appropriate classroom behavior and emphasis on the implications of plagiarism in practice.

A Mixed-Methods Study of Compassionate Mind Training for Pupils (CMT-Pupils) as a School-Based Wellbeing Intervention

ObjectivesMental health difficulties in children are increasing, especially following transition from elementary to high-school education. In attempts to mitigate risk of these difficulties, proactive wellbeing interventions are becoming increasingly explored in school settings. Recently, Compassionate Mind Training (CMT) has been shown to be well-accepted and efficacious in promoting school staff wellbeing and prosocial behaviours. This paper outlines the impact of CMT as a pupil wellbeing intervention.MethodSixty-seven pupils aged 11–12 took part in either Personal, Social, Health and Economic (PSHE) lessons as usual (n=30), or CMT-Pupils (n=37) as their PSHE lessons, over a 5-week period. A mixed-methods quantitative and qualitative design was utilised to explore implementation and curricula effectiveness across several wellbeing parameters (e.g., anxiety, self-compassion, perfectionism, moods and feelings, self-esteem).ResultsPupils reported positively on their experiences of the CMT-Pupils lessons, content and practices. Quantitative analyses revealed a significant time-by-group interaction effect for anxiety, reflecting differences in anxiety post CMT-Pupils vs. PSHE as usual. No further interactions reached significance. Qualitative analyses revealed benefits of CMT-Pupils for pupil and classroom behaviour, including emotion regulation, kindness to others and feelings of inclusion. Benefits were also found to extend to the class teachers.ConclusionsCMT-pupils could be a promising school-based wellbeing intervention for improving prosocial behaviours, the classroom environment and protecting against deteriorations in child mental health. Larger scale explorations of CMT-Pupils across wider demographics, including investigation of who can deliver the curriculum efficaciously (e.g., teachers vs. external facilitators), are suggested as next steps for investigation.PreregistrationThis study was not preregistered.

Direct and indirect effects of and preferences for feedback during the Good Behavior Game in elementary classes.

The Good Behavior Game (GBG) is an effective procedure for reducing disruptive classroom behavior. Students in three fifth-grade classes selected the rules of the GBG and then experienced the GBG with different forms of feedback for rule violations (vocal and visual, vocal only, visual only, no feedback). Following an initial baseline, the four feedback versions of the GBG and a baseline condition were alternated across sessions in a multielement design. All versions of the GBG substantially reduced disruptive behavior below baseline levels. Additionally, in one of the three classes losing the GBG produced an increase in negative peer interactions immediately following the GBG. Following the multielement comparison, we implemented a group-arrangement concurrent-chains preference assessment in which students selected one of the conditions to experience each day. The most selected condition across all classes was the GBG condition, which included both vocal and visual feedback.

An Intergenerational Comparison of Civility: Nursing Students and Nurse Educators.

Intergenerational differences in perceptions related to civility among nursing students and nurse educators were explored. A convenience sample of 13 students and 10 educators were interviewed in this descriptive qualitative study. Both groups defined civility as kindness, collaboration, and respect. Educators described civil students as being open to learning, polite, appreciative, and gracious. Students described civil educators as listening without judgment and being supportive and respectful. Educators described uncivil students as being disrespectful and entitled, and improperly using social media. Students described uncivil educators as belittling and impatient, and failing to listening. Respect was the strongest theme for both students and educators. In describing civil acts, students focused on cooperation to accomplish classroom and clinical tasks, whereas educators focused on productive classroom behaviors. More research on intergenerational differences is needed to help nurse educators develop interventions that allow faculty to view civility from a student perspective. [J Nurs Educ. 2024;63(2):86-92.].

Praise as a Gift in the Relationship between Teachers and Their Students

Abstract The term “giving” refers to the altruistic act of offering something to another person for free without expecting anything in return. While prosocial behavior can also be found in very young children, altruistic behavior emerges later, with the moral and cognitive development, also supported by adult praise, that children may receive within the educational relationship. Education, in fact, has the noble purpose of guiding people to a better condition than they are now, through relationships. The aim of this paper is to review the works that have analyzed the effects of praise in the relationship between teacher and student. Experimental studies over the last 50 years have shown that praise is a low-cost strategy that teachers can use to increase adaptive behavior in the classroom and decrease problem behavior. Furthermore, the use of praise improves the classroom climate, as it is a vehicle for positive emotions. Modern neuroscience has now shown how emotions play an important role in learning, including school learning. Therefore, we could consider praise as one of the greatest gifts a teacher can give to their students.

Improved classroom and child outcomes through mental health consultation in New York City subsidized early care and education programs.

This paper describes the evaluation of one year of infant/early childhood mental health consultation (IECMHC) in subsidized early care and education settings provided by the New York City Early Childhood Mental Health Network. The evaluation examined direct and indirect outcomes of IECMHC including (1) improved classroom practices by ECE teachers, and (2) improved social, emotional, and behavioral outcomes among children in the classroom. The study also reviewed child attributes that might have moderated outcomes. An analysis using paired t-tests of pre-and post-assessment data found significant improvements over time in the classroom environment and management practices, as well as in teachers' perceptions of the degree of difficulty presented by children's classroom behaviors. There were significant improvements in protective factors and problem behaviors among the subset of 138 children who received assessments. Improvements were greater for Black/African American children and for all children with pre-assessment scores in the concern range. Males showed greater improvement in protective factors whereas females showed greater improvement in behavioral concerns. IECMHC is a powerful intervention to improve teachers' classroom management and their perceptions of children's behavior and is important in the context of biases that place marginalized groups at risk of punitive actions by teachers and administrators.

Paraprofessional perceptions about and use of behavior strategies in elementary schools

AbstractParaprofessionals are often tasked with implementing behavior management strategies to support the complex needs of students with disruptive behavior disorders. This study examined reported use and effectiveness of common classroom behavior strategies from 86 paraprofessionals working in 36 elementary schools using a mixed method design. Data were from a larger randomized control trial that examined the effects of behavior support coaching on paraprofessional practices and student outcomes. Qualitative analysis highlighted themes related to behavior strategies use, including 94 “other” strategies. Paraprofessionals across conditions reported use of a range of behavior management strategies and were more likely to use consequence‐based than antecedent‐based strategies (χ2 = 381; p < .001; df = 1). Coached paraprofessionals reported greater use of reminding or reinforcing classroom rules and praising for appropriate behavior than controls. No group differences in overall strategy use (χ2 = 1.20; p = .273; df = 1) or overall perceived effectiveness (t = −1.45; p = .149; df = 755) were found. Implications of findings for practice and research are presented.

Implementing and Assessing a Teaching Mode Based on Smart Education in English Literature Teaching

This study addresses the problems in traditional English literature teaching methods for Chinese English majors, proposing a new teaching approach based on smart education concepts to enhance learning effectiveness. An evaluation of a semester-long reform in teaching methods is conducted using a quantitative methodology. The findings reveal significant differences in learning outcomes between the experimental and control classes, suggesting the new model's positive influence on student academic performances. Machine learning algorithms are also used to analyze student classroom behavior, indicating a significant increase in active engagement. In conclusion, students' learning outcomes, as well as engagement, can be substantially improved by integrating smart education techniques into English literature instruction.

The detrimental effects of student-disordered behavior at school: evidence from using the cusp catastrophe.

The purpose of the present study is to examine the potentially complex relationship between disordered behavior at school and students' engagement with reading activities given that they enjoy reading. Of particular interest is the role of disordered behavior which we believe moderated the relationship between liking reading and reading engagement. Participants were 2,420 fourth graders who participated in the 2021 PIRLS study from Saudi Arabia and were selected using stratified random sampling from 117 schools in the Kingdom. Data were analyzed using linear and nonlinear means such as the linear model, the logistic model, and the cusp catastrophe. Results pointed to the superiority of the cusp catastrophe towards predicting student engagement in reading by highlighting the splitting role of students' disruptive classroom behavior. It was evident that exceeding a critical upward level in disruptive classroom behavior was associated with unpredictable and sudden changes in reading engagement. It is concluded that the application of non-linear means may be conducive to understanding complex educational phenomena.

Portrait of Indonesian and Pakistan EFL Students’ Engagement in Online Classroom Based on Neuroscience Approach

The integration of neuroscience principles in online teaching can enhance student engagement and create a more engaging and brain-friendly learning experience. This study aims to portray the comparation of Indonesian and Pakistan EFL students’ behaviour, cognitive and emotional engagement in online classroom based on neuroscience approach. The participants in this research were students from Indonesian and Pakistan EFL students. The purposive sampling was used to select the participants who were taking from students of STKIP PGRI Jombang of English language education students from Indonesia and students of Government College Peshawar, Pakistan. This study employed a mixed case study by using a quantitative and qualitative data. The instruments of this study were close- ended and open-ended questionnaires. close-ended questionnaire. The quantitative data was analyzed by using descriptive statistics and the qualitative data was analyzed by thematic analysis. The findings showed that online learning in Indonesia and Pakistan shown to have positive levels of behavioral, cognitive and emotional engagement. The most positive engagement from both Indonesia and Pakistan students was behavioral engagement. Then, students’ cognitive engagement was more positive than emotional engagement. Then the finding also showed that the students engagement in Pakistan students was high positive level than Indonesia students.

Research on the Influence of PE Teaching Reform Based on Behavioral Psychology on College Students' Mental Health

Behavioral psychology is an important branch of psychological research, which mainly studies the relationship between human psychological performance and behavioral development. The main research direction of behavioral psychology is to study the relationship between human behavior development and psychology. In education, we can intervene the development of education through the study of students' behavior psychology to achieve the role of promoting students' development. At present, in modern education, we can improve Canadian education and teaching through the study of students' behavior psychology. Physical education in Colleges and universities has always been an important subject of modern quality education, which plays a role in promoting students' physical and mental health, thinking ability and innovation ability. However, in recent years, more and more college students have been affected by learning pressure, development factors and adverse interpersonal communication. Students' mental health problems have become increasingly serious, affecting the development of higher education in China. Therefore, based on the relevant theories of behavioral psychology, this paper studies the students' physical education classroom behavior, and puts forward some suggestions on reforming college physical education, so as to promote college physical education and help students shape a positive and healthy psychology. The strategies of physical education reform in Colleges and universities include innovating teaching contents, improving teaching methods, improving teachers' comprehensive quality and carrying out physical psychology teaching. The purpose is to continuously improve teaching conditions and promote students' healthy and scientific development through the research on College Students' behavioral psychology.

Examining the Classroom Impact of the Bounce Back Trauma Intervention: Implications for Selecting Progress Monitoring Tools

Limited research has examined the impact of Bounce Back (BB), a trauma-focused intervention for elementary-age students, on student academic engagement and daily classroom behavior. This study utilized both ongoing direct and indirect measures of student functioning to evaluate student progress and inform the implementation of BB. Participants were six U.S. students (four male and two female). We employed an AB single-subject design across cases with follow-up, and we collected data via the Direct Behavior Rating–Single Item Scale (DBR-SIS). We also employed a quasi-experimental pretest–posttest design using the Strengths and Difficulties Questionnaire (SDQ), Social, Academic, and Emotional Behavior Risk Screener (SAEBRS), and mySAEBRS across raters before/after intervention implementation. We found either direct or indirect assessment could be used to monitor intervention effectiveness for youth who presented with some internalizing and externalizing problems, whereas indirect measures (i.e., rating scales) showed the primary effect for youth with solely internalizing problems, and direct assessment (i.e., DBR-SIS) showed the primary effect for youth with predominantly externalizing behaviors. Selecting progress-monitoring tools based on presenting concerns is important to adequately monitor the effectiveness of school-based mental health interventions. Implications for practice are discussed.

Design of Intelligent Interactive Teaching System for College English Based on Streamlined Bilinear Attention Networks

Abstract Intelligent methods such as deep learning provide an innovative optimization path for English teaching in colleges and universities. In this paper, the attention mechanism is based on traditional CNN. Embedded attention and multilayer convolutional feature fusion are used to complete the design of streamlined bilinear attention networks. The streamlined bilinear attention network is used to obtain the characteristics of students’ classroom behavior in the process of English teaching, combine the characteristics of students’ classroom behavior and computer programming language to design and implement the intelligent interactive teaching system of English in colleges and universities, and test and apply the analysis of the intelligent interactive teaching system of English. The results show that in the query performance test report, even though the number of requests issued in the test is 2,000, the error rate is always kept at 0, the throughput is 39.8, and the response time is kept at 95~1144s, which indicates that this system can meet the performance requirements with a moderate number of users. In the application analysis, the total score of the teaching method of English Intelligent Interactive Teaching System (mean=94.62) is higher than that of the traditional English teaching method (mean=89.65), which indicates that the teaching method of English Intelligent Interactive Teaching System is more capable of improving the interaction and communication ability of the students in English teaching. The system constructed in this study can meet the diverse needs of students and contribute to the quality improvement of English teaching in colleges and universities.

Research on Deep Learning Technology to Enhance the Efficiency of Teaching Interaction in College English Classrooms

Abstract Accompanied by the significant progress of deep learning in various fields, target detection, an important branch in the field of deep learning, is gradually being applied in educational scenarios. In this paper, using the GCT-YOLOv5 algorithm and the Lasso-LARs algorithm, we studied how to improve the interactive efficiency of college English classroom teaching Research first combines the YOLOv5 model with the GCT unit, constructs the GCT-YOLOv5 target detection model for students’ classroom behaviors, and compares it with Fast-RCNN, SSD, YOLOv3, YOLOv4, and YOLOv5 in the public dataset and the student classroom behavior dataset for comparison experiments, respectively. Then, the LASSO-LARS algorithm is used to construct the classroom behavior scoring model, adjust classroom teaching interactions according to the scoring results, and analyze the effect of the adjustment. On the classroom behavior dataset, the GCT-YOLOv5 model is 98.81%, second only to Fast-RCNN, and improves 0.65% relative to the original model YOLOv5. Its inference time compared to YOLOv5 inference time increased by only 0.13h, shorter than other models. The GCT-YOLOv5 model in this paper has better applicability and timeliness in general. Teaching interaction adjustment based on the results of classroom behavior analysis can improve students’ classroom performance as well as their academic performance, i.e., enhance the efficiency of teaching interaction and provide a way of thinking about how to monitor learners’ learning status in a smart classroom.

Analysis of Teachers’ Classroom Behavior in Relation to their Demographic Characteristics at University Level

Analysis of Teachers’ Classroom Behavior in Relation to their Demographic Characteristics at University Level

A Diversified Teaching Model of Business English in Multimodal Perspective

Abstract Traditional business English pedagogy has predominantly relied on an unimodal teaching approach, which often fails to satisfy the demands of contemporary talent development. Addressing this inadequacy, this study advocates for the establishment of a diversified teaching model from a multimodal perspective. Furthermore, it introduces a comprehensive evaluation framework designed to assess the efficacy of various business English teaching methodologies. This evaluation model employs the K-means clustering algorithm for data segmentation, utilizes both positive and negative indicators for constructing metrics, and integrates the fuzzy comprehensive evaluation method with gray system theory for robust analysis. The research was conducted at AB University, where experimental and control groups were established to critically assess the effectiveness of the diversified teaching approaches. Results indicate that the experimental group’s average business English score was 53.1, which is significantly higher by 10.94 points than that of the control group (P<0.01). Moreover, notable differences were observed in students’ classroom behaviors, including course engagement, responsiveness to teachers, and learning attitudes, all showing highly significant improvements in the experimental group (P<0.01). Similarly, in terms of teaching quality, the experimental group significantly outperformed the control group across the dimensions of content design, lecture delivery, and overall teaching impact (P<0.01). This study not only underscores the effectiveness of the proposed diversified business English teaching model but also provides a theoretical and empirical foundation for its evaluation.

Research on the Informatization Strategy and Practical Effect of Chinese Traditional Culture Education

Abstract The development of curriculum culture is a profound reflection on the evolution of school curriculum in the present era. The article proposes a Retina Student network to detect students’ classroom behaviors and then incorporates the implementation of a classroom behavior coding system using computer vision. Based on this, we established a student detection dataset for the classroom attention recognition task, utilizing the Retina Studen student detection algorithm to achieve optimal recognition accuracy of 0.92 and 0.93, and recall of 0.91 and 0.94 for both gaze and non-gaze states. Then, the visualization information of students’ learning behaviors was targeted, and the classroom status was discussed. The experimental results demonstrate that this paper’s algorithm outperforms other algorithms in identifying student learning behaviors. Finally, through the coding analysis of the teaching video of the cultural education smart classroom, we found that students’ behaviors in the calligraphy, painting, and opera smart classroom are rich, and the traditional way of “explaining-questioning-answering-feedback” is still the main behavior in the classroom.

A Study on the Integration and Practice of Integrated Transfer Learning Strategies in Japanese Language Teaching and Learning

Abstract Addressing the prevalent issue of inefficiency in Japanese language learning, this study focuses on innovating classroom teaching methodologies for the Japanese language. Initially, the research employs a stochastic gradient descent algorithm to enhance the performance of a transfer learning algorithm, aiming to accurately identify student behaviors within the Japanese language classroom. Subsequently, these behaviors are quantified into integration weights using a predefined integration strategy. Behaviors demonstrating significant similarities are consolidated and analyzed to yield the results of the student behavior identification process. Furthermore, this behavior recognition approach is seamlessly incorporated into Japanese language pedagogy to develop a refined model for teaching, thereby potentially increasing the efficacy of language acquisition. Using this paper’s algorithm to identify students’ classroom behaviors and correlate them with their grades, it is found that when the number of positive behaviors in the classroom is higher, the student’s academic performance is also higher (r=0.9986, p=0.001<0.05). The average percentage of students’ attentive listening behaviors could reach 52.24% after the intervention, as determined by behavioral recognition results in the Japanese language teaching classroom. The behavior recognition algorithm in this paper provides an effective method for analyzing and intervening in students’ behavior in the classroom, and the teaching model constructed based on the algorithm offers a reference way to improve the effectiveness of Japanese language teaching.

Exploration and Practice of English Civics Teaching Design in Colleges and Universities Based on Big Data Analysis

Abstract This study explored the cutting-edge methodology of integrating curricular Civics into teaching specialized disciplines in higher education, an essential trend for the future development of higher education. By applying data-mining algorithms, the article constructs a big-data analysis framework from the dimensions of students’ classroom behavior and performance. The fuzzy C-mean clustering algorithm was optimized using the cuckoo algorithm to effectively classify the characteristics of students’ behavior in the Civics classroom, and the attention-based hybrid encoder-decoder model was used to accurately predict students’ grades. After establishing a complete analytical framework, an innovative college English Civics teaching model was developed following the ASSURE teaching model. It was applied and analyzed for its effect in actual teaching. The study results show that, after the implementation of the English Civics and Politics course based on the ASSURE model, the average grade of the students increased by about 0.5 points. The grades were distributed between 80 and 95 points, significantly different from the pre-test grades (P<0.05). The prediction error was controlled to be less than ±2 points, which indicates that the teaching model had a significant teaching effect. This study not only improves English learning performance but also promotes the improvement of students’ performance in Civics, showing the great potential and value of integrating Civics curriculum into professional teaching.

Research on Building a New Mode of Civic and Political Education by Image Recognition Technology for Popularizing Socialist Core Values

Abstract Given the current state of ideological education in colleges and universities, we propose leveraging image recognition technology to foster innovation and digital advancement in this mode of education. The weighted average method is used to greyscale the video images of students’ classrooms, and after binarizing the images using the OTSU algorithm, interference factors are avoided by denoising and angle correction. We combine the motion history image (MHI) and HOG features to create a new feature that depicts Civics classroom behavior. The SVM classifier then performs the classification of classroom behavior, ultimately constructing the Civics classroom behavior recognition model based on HOC+MHII+SVM. This paper’s model and research data are combined to conduct an example analysis of Civics education in colleges and universities. It can be concluded from the analysis that, in the case of simultaneously adopting SVM for recognition and classification, it is found that HOC+MHI feature fusion has a more significant effect on classroom behavior recognition than FPN+Multi-layer CBAM, and the difference of its various indexes is maintained within the range of 0.01~0.08. In addition, the experimental group has a significant difference relationship in the four dimensions of demonstrating the concept of honor and shame, the concept of national development, the value of development, and the value of society, P<0.05. This study provides theoretical references for research on the innovation of the ideological and political education model and is conducive to the promotion of cultivating the formation of students’ socialist core values.