What kind of children do kindergarten teachers prefer? -Typology of the preferred types of children.

The teacher's pets are a common occurrence in the field of education. To investigate the preferences teachers exhibit toward certain children, the study focused on kindergarten teachers and employed a mixed research methodology. Initially, qualitative interviews were conducted with 15 kindergarten teachers to identify specific criteria influencing teacher preferences. Subsequently, A comprehensive model of teacher's pets was developed through a questionnaire survey involving 463 participants. This model encapsulated 32 distinct indicators, categorized into 7 types: children with good appearance (GA), exceptional abilities (OA), commendable conduct (GC), proactive and enthusiastic demeanor (PE), compliant and carefree nature (OC), children from vulnerable groups (VC), and those influenced by their parents (PI). The resulting model demonstrated a sound structure. Not only did it validate existing findings, but it also expanded upon the identified types of teacher's pets. An analysis based on game theory revealed the weighted combinations, highlighting the top three types of teacher's pets: children influenced by parental factors (24.3%), proactive and enthusiastic individuals (15.7%), and obedient, carefree children (14.8%), respectively. Conversely, the representation of vulnerable-concerned children (11.1%) was the lowest among the identified types.

Private Kindergarten Teachers' Intention to Remain: A Comparison Between the Effects of Organizational and Individual Psychological Factors.

The purpose of this study was 2-fold: to validate the Private Kindergarten Teachers' Intention of Remaining (PKTIR) Questionnaire and the Factors of Teachers' Intention of Remaining (FTIR) Questionnaire, and to comparative study to explore the effects of organizational and individual psychological factors in China. A total of 22 experts were recruited to modify and validate both questionnaires. The results showed that both questionnaires had instruments that are reliable and valid. Then, a total of 582 kindergarten teachers were recruited to explore the comparison between the effects of organizational and individual psychological factors. The results from the structural equation model suggested that the influence of individual psychological factors on kindergarten teachers' intention of remaining was greater compared to the organizational factors. Second, among all the factors, the most explanatory are work connections, sense of work gained from it, satisfaction with the salary, and work discard. To our knowledge, this is the first comparative study to explore the effects of organizational and individual psychological factors in China.

Learning Behavior Evaluation Model and Teaching Strategy Innovation by Social Media Network Following Learning Psychology.

With the development of various network technologies and the spread of coronavirus disease 2019, many online learning platforms have been built. However, some of them may negatively impact student learning outcomes. Therefore, this study aims to improve the online learning effect of students by comprehensively evaluating their learning behavior by using deep learning algorithms. On this basis, new teaching strategies are proposed. According to the structured deep network embedding model, a network representation learning algorithm is proposed with the help of auto-encoders under deep learning. This study elaborates the concept and structure of the encoder model and tests its performance. After the node labels and dataset are trained, the applicable parameter λ2 of the model is 0.3. During the teaching process, the model's reliability in distinguishing users is examined. Therefore, this model can be applied to network teaching, is an innovative teaching strategy, and provides a theoretical basis for improving teaching methods.

Exploration of micro-video teaching mode of college students using deep learning and human-computer interaction.

In order to improve the efficiency of teaching and learning in Colleges and Universities (CAUs), this work combines the Browser/Server (B/S) framework with Model View Presenter (MVP) technology to build a college student-oriented micro-video teaching system based on Deep Learning (DL) and Human-Computer Interaction (HCI) technology. Firstly, it makes an in-depth analysis of the problems in the classroom teaching of Chinese CAUs. Three functional modules are designed for the micro-video online teaching platform: video management, user learning, and system management. Then, it uses MVP technology to analyze the use-cases of these three functional modules in detail. Based on this, the micro-video online teaching platform is designed using the B/S framework. The teaching platform interface layer realizes the HCI between the platform and users. The business logic layer responds to the user requests submitted and returns the processing results to the interface layer. Finally, the function test and stress test of each module of the micro-video online teaching platform is carried out. The test results show that the response time of the proposed micro-video teaching platform increases with the number of users. Under the peak concurrent users, the system response time is 6 s, without abnormalities. Meanwhile, the proposed teaching platform has improved students' satisfaction with classroom teaching by nearly 15% and improved the compactness of the college classroom by nearly 12%. When the number of virtual users increases and the number of services increases linearly, the Random Access Memory and Central Processing Unit growth rate is significantly lower than that of the number of services. These outcomes indicate that many system resources are reused, and the system has good scalability, which can meet users' needs for the network video teaching system. The proposed teaching platform provides a new idea for applying DL and HCI technology in researching college students' micro-video teaching mode.

Do Predictors of Health Facility Delivery Among Reproductive-Age Women Differ by Health Insurance Enrollment? A Multi-Level Analysis of Nigeria's Data.

This study aims to compare determinants of health facility delivery for women under a health insurance scheme and those not under a health insurance scheme. Secondary data drawn from the National Demographic and Health Survey was used for the analysis. The characteristics of the women were presented with simple proportions. Binary multilevel logistic regression was used to examine the determinants of health facilities for women who enrolled in health insurance and those who did not. All statistical analyses were set at 5% level of significant level (p = 0.24). The result showed that 2.1% of the women were under a health insurance scheme. Disparity exists in health insurance ownership as a higher proportion of those enrolled in health insurance were those with higher education attainment, in urban parts of the country, and those situated on higher wealth quintiles. There is a significant difference between those with and those without health insurance. It implies that a higher proportion of women who enrolled in health insurance delivered in health facility delivery compared to those who do not. The unique determinants of health facility delivery for women under health insurance were parity and birth order, while unique determinants of health facility delivery for women not enrolled in health schemes were employment status, marriage type, and geopolitical zones. Uniform predictors of health facility delivery for both groups of women were maternal education, household wealth quintiles, autonomy on healthcare, number of antenatal contacts, residential status, community-level poverty, community-level media use, and community-level literacy. Intervention programs designed to improve health facility delivery should expand educational opportunities for women, improve household socioeconomic conditions, target rural women, and encourage women to undertake a minimum of four antenatal contacts.

Future Time Orientation and Learning Engagement Through the Lens of Self-Determination Theory for Freshman: Evidence From Cross-Lagged Analysis.

View of future time orientation is a cognitive construct about future time. This view has its unique work of motivation and effect on academic performance. Previous studies have only explored the influence that future time orientation brings to the learning process at a single time, and most of them focus on cross-sectional studies. To further explore the cross-lagged relationship for freshmen between future time orientation and learning engagement during different periods, AMOS 23.0 was performed for cross-lagged analysis in this study to explore the influence and effect among variables of different periods. This research was based on the theory of self-determination to discover the relationship between future time and learning involvement for freshmen in enrollment and the first summer vacation. In this research, there were 1,000 valid samples in the first stage and 840 valid samples in the second stage for the conduction of descriptive statistics, pair t-test, and cross-lagged analysis. The results show that: (1) for learning engagement, freshmen at the end of the first year have a higher average score than at the beginning of the first year. (2) View of students of future time orientation can affect their learning engagement of the future through self-determination of students. At last, we provide some suggestions as references for institutional research and future research.

Corrigendum: The Relationship Between College Teachers' Frustration Tolerance and Academic Performance.

[This corrects the article DOI: 10.3389/fpsyg.2021.564484.].

The Relationship Between College Teachers' Frustration Tolerance and Academic Performance.

The purpose of this study was twofold: to validate the College Teachers' Academic Frustration Tolerance (CTAFT) Questionnaire and the College Teachers' Academic Performance (CTAP) Questionnaire and to explore the relationship between frustration tolerance and academic performance among college teachers. A total of 25 experts were recruited to modify and validate both questionnaires, and the results showed that the questionnaires had good content validity. Exploratory factor analysis provided further evidence supporting the reliability of the CTAFT and the CTAP, suggesting that the instruments are reliable and valid. Confirmatory factor analysis showed that frustration tolerance affected academic performance, which could best be modeled in the three dimensions of Affect (AF), Preferred Difficulties (PD), and Action (AC). A total of 450 college teachers from each faculty of both universities were then recruited to explore the significant positive correlation between academic frustration tolerance and academic performance. The results from the structural equation model suggested that AC and PD combined significantly predicted academic performance. To our knowledge, this is the first study to explore the relationship between college teachers' academic frustration tolerance and academic performance in China.