Evaluation Method of College Students’ English Proficiency Based on Computer Aided Cluster Analysis

ABSTRACT Introduction: The main reason for the decline in college students’ physical fitness and health is the lack of physical exercise, the emphasis on study and the neglect of physical exercise, and the lowering of the physical fitness requirements of college students. Objective: The paper analyzes the status quo and existing problems of college students’ physical fitness and proposes that the school party committee issues policy-based health intervention measures, encourages school physical education teachers to participate in students’ after-school physical exercises, and extensively develops school mass sports activities. Methods: The paper uses a literature method, questionnaire survey, comprehensive evaluation method, etc., to analyze the internal and external factors of college students’ physical decline. Results: Through the practice density test of students in physical education teaching, it is learned that physical education in the first grade can fully develop students’ physical fitness, and the practice density of each class reaches 60%. The practice density of the second-grade optional courses is about 20%, and it cannot achieve the purpose of effective physical exercise. Conclusions: The current teaching content and teaching methods of physical education classes cannot effectively complete physical education tasks. It is necessary to adjust the teaching content further and improve the teaching methods. Level of evidence II; Therapeutic studies - investigation of treatment results.

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Computer Aided Nondestructive Evaluation Method of Welding Residual Stresses by Removing Reinforcement of Weld (Proposal of a New Concept and Its Verification)

Fatigue and Fracture Mechanics: 31st Volume ◽

10.1520/stp14798s ◽

2008 ◽

pp. 128-128-15 ◽

Cited By ~ 1

Author(s):

K Kumagai ◽

H Nakamura ◽

H Kobayashi

Keyword(s):

Residual Stresses ◽

Nondestructive Evaluation ◽

Evaluation Method ◽

Computer Aided

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Study on Vocational College Students Comprehensive Quality Evaluation Index System and Evaluation Method

Information and Business Intelligence - Communications in Computer and Information Science ◽

10.1007/978-3-642-29084-8_44 ◽

2012 ◽

pp. 295-300

Author(s):

Wang Na ◽

Wang Xiao-kun ◽

Wang Hong-hai ◽

Gao Xin ◽

Fan Hai-rong

Keyword(s):

College Students ◽

Index System ◽

Quality Evaluation ◽

Evaluation Method ◽

Evaluation Index System ◽

Evaluation Index ◽

Vocational College

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Irregular sleep and event schedules are associated with poorer self-reported well-being in US college students

SLEEP ◽

10.1093/sleep/zsz300 ◽

2019 ◽

Vol 43 (6) ◽

Cited By ~ 2

Author(s):

Dorothee Fischer ◽

Andrew W McHill ◽

Akane Sano ◽

Rosalind W Picard ◽

Laura K Barger ◽

...

Keyword(s):

College Students ◽

Cluster Analysis ◽

Sleep Duration ◽

Well Being ◽

Early Morning ◽

Time Varying ◽

Clinical Trial Registration ◽

Systematic Relationship ◽

Phase Deviation ◽

Time Varying Covariates

Abstract Study Objectives Sleep regularity, in addition to duration and timing, is predictive of daily variations in well-being. One possible contributor to changes in these sleep dimensions are early morning scheduled events. We applied a composite metric—the Composite Phase Deviation (CPD)—to assess mistiming and irregularity of both sleep and event schedules to examine their relationship with self-reported well-being in US college students. Methods Daily well-being, actigraphy, and timing of sleep and first scheduled events (academic/exercise/other) were collected for approximately 30 days from 223 US college students (37% females) between 2013 and 2016. Participants rated well-being daily upon awakening on five scales: Sleepy–Alert, Sad–Happy, Sluggish–Energetic, Sick–Healthy, and Stressed–Calm. A longitudinal growth model with time-varying covariates was used to assess relationships between sleep variables (i.e. CPDSleep, sleep duration, and midsleep time) and daily and average well-being. Cluster analysis was used to examine relationships between CPD for sleep vs. event schedules. Results CPD for sleep was a significant predictor of average well-being (e.g. Stressed–Calm: b = −6.3, p < 0.01), whereas sleep duration was a significant predictor of daily well-being (Stressed–Calm, b = 1.0, p < 0.001). Although cluster analysis revealed no systematic relationship between CPD for sleep vs. event schedules (i.e. more mistimed/irregular events were not associated with more mistimed/irregular sleep), they interacted upon well-being: the poorest well-being was reported by students for whom both sleep and event schedules were mistimed and irregular. Conclusions Sleep regularity and duration may be risk factors for lower well-being in college students. Stabilizing sleep and/or event schedules may help improve well-being. Clinical Trial Registration NCT02846077.

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