Everyday discrimination, negative emotions, and academic achievement in Filipino secondary school students: Cross-sectional and cross-lagged panel investigations

Everyday Discrimination and Sleep Among Migrant and Non-migrant Filipinos: Longitudinal Analyses from the Health of Philippine Emigrants Study (HoPES)

This study aimed to (1) identify differences in sleep patterns between Filipino migrants and non-migrants across 2 years and (2) explore the impact of discrimination trajectories on sleep trajectories. The Health of Philippine Emigrants Study (HoPES) consisted of a migrant (n = 832) and non-migrant cohort (n = 805), with baseline data collected in the Philippines. Both cohorts were followed longitudinally, with the non-migrants followed in the Philippines and the migrant cohort followed to the United States. Sleep duration, quality, and difficulty were assessed with the National Institutes of Health Patient-Reported Outcomes Information System (PROMIS) inventory, and discrimination was measured with an adapted version of the Everyday Discrimination scale. Migrants reported a faster decline in sleep duration (- 12 min a year) but higher sleep quality than non-migrants over 2 years. Migrants who reported high initial levels of everyday discrimination also reported faster declines in sleep duration and a slower decline in sleep difficulty. Further, migrants who reported stable (versus declining) levels of discrimination over 2 years reported a faster decline in sleep quality. These results speak to the complexity of immigrant health patterns and long-term associations between discrimination and sleep processes.

The Impact of EFL Students' Emotioncy Level on Their Motivation and Academic Achievement: A Theoretical Conceptual Analysis

Recently, teachers' and language learners' emotional status has received special attention among researchers. They argued that learners' emotioncy level might affect every aspect of language teaching process; therefore, the present study reviewed the impact of EFL students' emotioncy level on their motivation and academic achievement. Reviewing the literature revealed that there are different classifications for learners' emotioncy level. However, studies showed that the most prominent classification of learners' feeling is positive or negative. No matter positive or negative, the main responsibility of teachers in these situations is finding an appropriate way to control these feeling. The paper concludes with some pedagogical implications to control emotioncy in the classroom.

School violence negative effect on student academic performance: a multilevel analysis

The relative roles of school context and individual student factors are of special interest to educators in measuring academic performance. Little is known about the effect of school violence on a student's academic performance and well-being. The aims of this study were to examine the effects of three types of school violence (direct violence, discrimination, and cyberbullying) on students' academic performance in standardized tests of mathematics, reading and history, and to identify individual student factors that contribute to reducing the negative effect of exposure to violence at school. We used 10th grade Chilean student data from the representative cross-sectional test of the Education Quality Measurement System (SIMCE in Spanish) from 2015. Multilevel linear models, adjusted for gender, incorporated other school and environmental contextual factors, as well as individual student factors. The results show that school violence in its three forms had a negative effect on academic performance. Student self-efficacy, educational expectations and satisfaction with interpersonal relations with their teachers, were important in reducing the negative effect of exposure to violence. The implications for the school are discussed.

Subjective well-being and academic performance among middle schoolers: A two-wave longitudinal study

INTRODUCTION

Previous studies have suggested that present subjective well-being promotes students' academic achievement. However, adolescents' subjective well-being tends to be future-oriented; for example, when adolescents think about the future, they have hopeful expectations, feel energized, or confused. Therefore, this 14-month follow-up study conducted in China aimed to establish the longitudinal relationships between present- and future-oriented well-being and academic achievement.

METHODS

Using two waves of data, this longitudinal study explored the bidirectional relationships between present- and future-oriented well-being and academic achievement among 189 Chinese middle school students (102 girls, 82 boys, 5 unknown) whose mean age was 13.76 at Time 1 and 14.78 at Time 2. The Adolescent Well-being Scale, which has six dimensions (present life satisfaction, present positive affect, present negative affect, hopeful future expectations, positive affect toward future life, and negative affect toward future life) was administered to all students at Time1 and Time 2, and academic scores were collected two weeks later. Structural equation modeling was used to analyze the data.

RESULTS

Cross-lagged analyses revealed that present life satisfaction, present positive affect, and positive affect toward future life at Time 1 were positively correlated with academic achievement at Time 2.

CONCLUSIONS

These findings suggest that both present- and future-oriented well-being are associated with later academic achievement. Teachers and parents should cultivate students' well-being by targeting not only present life satisfaction and positive affect but also positive feelings toward the future.

Academic Emotion Classification and Recognition Method for Large-scale Online Learning Environment-Based on A-CNN and LSTM-ATT Deep Learning Pipeline Method

Subjective well-being is a comprehensive psychological indicator for measuring quality of life. Studies have found that emotional measurement methods and measurement accuracy are important for well-being-related research. Academic emotion is an emotion description in the field of education. The subjective well-being of learners in an online learning environment can be studied by analyzing academic emotions. However, in a large-scale online learning environment, it is extremely challenging to classify learners’ academic emotions quickly and accurately for specific comment aspects. This study used literature analysis and data pre-analysis to build a dimensional classification system of academic emotion aspects for students’ comments in an online learning environment, as well as to develop an aspect-oriented academic emotion automatic recognition method, including an aspect-oriented convolutional neural network (A-CNN) and an academic emotion classification algorithm based on the long short-term memory with attention mechanism (LSTM-ATT) and the attention mechanism. The experiments showed that this model can provide quick and effective identification. The A-CNN model accuracy on the test set was 89%, and the LSTM-ATT model accuracy on the test set was 71%. This research provides a new method for the measurement of large-scale online academic emotions, as well as support for research related to students’ well-being in online learning environments.