Students' Learning Characteristics, Perceptions of Small-Group University Teaching, and Understanding Through a "Meeting of Minds"

Understanding, Investigating, and promoting deep learning in language education: A survey on chinese college students' deep learning in the online EFL teaching context

This study aims to (1) develop and validate the four-dimension model hypothesis of deep learning to better understand deep learning in language education; (2) investigate and promote deep learning by conducting a survey involving 533 college students in the online learning English as a foreign language (EFL) teaching context in China. Concretely, this study initially synthesized theoretical insights from deep learning in the education domain and related theories in the second language acquisition and thus proposed the four-dimension model hypothesis of deep learning involving the motivation of deep learning, the engagement of deep learning, the strategy of deep learning, and the directional competence of deep learning. This study subsequently undertook a questionnaire survey utilizing a standardized instrument to confirm the model hypothesis and further investigate the current status and salient differences in students' deep learning in online EFL teaching. Exploratory factor analysis (EFA), confirmation factor analysis (CFA), and Pearson's correlation test validated a positively correlated four-dimension model of deep learning with high composite reliability and good convergent validity. Moreover, the descriptive and inferential statistics revealed that the level of students' deep learning marginally reached the median, with the lowest mean of directional competence and the highest mean of motivation; students manifested more instructional motives, neglect of deploying skilled-based cognitive strategies, and deficiency of language application skills, etc.; there existed some significant differences between deep learning and four sub-dimensions across the grade, English proficiency, EFL course, and vision groups. Eventually, this study proffered primary reasons and five appropriate strategies to scaffold and promote students' deep learning in online EFL teaching. Hopefully, this study will be a pioneering effort to clear away the theoretical muddle of deep learning construct in language education and be illuminating to further improve effectiveness in the online EFL teaching context.

Defense Styles, Academic Procrastination, Psychological Wellbeing, and Approaches to Learning: A Person-Oriented Approach

ABSTRACT

This study investigates the relationships among defense styles, academic procrastination, psychological well-being, and approaches to learning. The questionnaires Defense Style Questionnaire-88, Procrastination Assessment Scale Questionnaire, Flourishing Scale, and HowULearn are used to measure the aforementioned variables, respectively. Social science students (N = 628) take part in the study. A hierarchical cluster analysis is used for clustering students into homogeneous groups. Three groups of students are identified: "psychologically stable and adaptive" (n = 285), "immature and unstable at risk" (n = 134), and "defensively dissonant" (n = 209) students. A decision tree model is used with the grade point average (GPA) score as an outcome variable to further examine interactions between the three clusters and the years of study on GPA. "Psychologically stable and adaptive" students report the highest GPA. Our findings bridge mental health variables with learning shedding light on our understanding of the use of defense styles when it comes to learning.

Students' Entire Deep Learning Personality Model and Perceived Teachers' Emotional Support

In recent years, deep learning as the requirement of higher education for students has attracted the attention of many scholars, and previous studies focused on defining deep learning as the deep processing of knowledge of the brain, however, in the process of knowledge processing, the brain not only involves the deep processing of information but also participates in learning consciously and emotionally. Therefore, this research proposed a four-factor model hypothesis for deep learning that includes deep learning investment, deep cognitive-emotional experience, deep information processing, and deep learning meta-cognitive. In addition, the research proposed teachers’ emotional support perceived by students has an effect on the four factors of deep learning. Through SPSS 26 and AMOS 24, this research has verified the four-factor model of deep learning applying exploratory factor analysis (EFA) and confirmatory factor analysis (CFA) and verified that the perceived teacher emotional support has an impact on the four factors of students’ deep learning using the SEM.