Novel evaluation approach for extracurricular sports lifestyle of college students

2020 ◽  
pp. 002072092092851
Author(s):  
Pingping Zhang ◽  
Jiyun Cai ◽  
Lining Xing
Keyword(s):  
College Students ◽  
Extracurricular Activities ◽  
University Education ◽  
Concordance Index ◽  
Evaluation Approach ◽  
Electre Method ◽  
Classroom Education ◽  
Credibility Index ◽  
Evaluation Matrix

Good extracurricular activities can optimize the quality of education, fetch up with classroom education and teach them what they cannot learn from it, is conducive to improve students’ comprehensive quality, to complete the task and achieve the goal of university education. For this reason, this paper proposes an extracurricular sports lifestyle evaluation to college students via an improved ELECTRE method. In the proposed method, three indexes – concordance index, non-concordance index and credibility index – are defined first. Based on these indexes, the preference evaluation matrix is constructed, and consistent credibility, non-consistent credibility and net credibility are computed second. Third, it was sorted for the quality of all alternatives according to the value of group net credibility. In general, the greater the value of the group net credibility of a project, the better the project is. Simulation experiments suggest that this proposed method is feasible and valid. Extracurricular activities for college students take a very important part of university education, and it models their characters, opens up their minds, adventure spirits, strengthens their social connections, improve their comprehensive quality and their personal positive socialization.

scholarly journals College Students’ Sleep Habits and Their Perceptions Regarding Its Effects on Quality of Life

2018 ◽  
Vol 3 (2) ◽  
pp. 7 ◽  
Author(s):  
Megan L. Herrmann ◽  
Anthena K. Palmer ◽  
Morgan F. Sechrist ◽  
Sam Abraham
Keyword(s):  
Quality Of Life ◽  
College Students ◽  
Extracurricular Activities ◽  
Sleep Problems ◽  
The United States ◽  
Poor Sleep ◽  
Significant Finding ◽  
Sleep Habits ◽  
Spring Semester

Objective: Poor sleep in college students can attribute to poor academic performance. Poor sleep is detrimental to health; however, adequate sleep is not often seen as a priority. The objective of the study was to better understand college students’ sleep habits and determine their perceptions regarding the effects of these sleep habits on quality of life.Methodology: A quantitative, cross-sectional approach with a descriptive design was appropriate for this study. Participants were 122 students, in a Christian college with a population of about 2000 in the mid-western region of the United States. The survey instrument was developed with 6 demographic items and 19 statements using a 4-point Likert-type scale. Data collection occurred in the hallway of the library on two days in the spring semester of 2016.Results: Regarding sleep habits, the average college student keeps their sleep and study spaces separate, they wake up at a regular time every day, they do use technology, such as a cell phone, TV/radio, computer, or iPad before going to sleep, and they have a sleep environment that is quiet and calming. A significant finding was that students did not think extracurricular activities (anything outside of class) negatively affected their sleep. Conclusions: A large percentage of students use technology before bed, which places them at a higher risk for negative quality of life. Students admit to experiencing irregularity in their sleep patterns (M=3.59, on a 4-point scale); however, most participants did not agree that caffeine consumption (M=2.15), extracurricular activities (M=2.25), or daytime naps (M=2.16) contributed to sleep problems.

The Effects of Exercise Commitment Facilitated by Service Quality of Smartphone Exercise Applications on Continued Exercise Intention

2019 ◽  
Vol 118 (1) ◽  
pp. 14-19
Author(s):  
Boo-Gil Seok ◽  
Hyun-Suk Park
Keyword(s):  
College Students ◽  
Factor Analysis ◽  
Regression Analysis ◽  
Statistical Analysis ◽  
Correlation Analysis ◽  
Service Quality ◽  
Frequency Analysis ◽  
Primary Data ◽  
Exercise Intention

Background/Objectives: The purpose of this study is to examine the effects of exercise commitment facilitated by service quality of smartphone exercise Apps on continued exercise intention and provide primary data for developing and/or improving smartphone exercise Apps. Methods/Statistical analysis: A questionnaire survey was conducted amongst college students who have experiences in using exercise App(s) and regularly exercise. The questionnaire is composed of four parts asking about service quality, exercise commitment, continued exercise intention, which were measured with a 5-point Likert Scale, and demographics. Frequency analysis, factor analysis, correlation analysis, and regression analysis were carried out to analyze the obtained data with PASW 18.0.

Pollutants in Organic Chemistry and Medicinal Chemistry Education Laboratory. Experimental and Machine Learning Studies

2020 ◽  
Vol 20 (9) ◽  
pp. 720-730
Author(s):  
Iker Montes-Bageneta ◽  
Urtzi Akesolo ◽  
Sara López ◽  
Maria Merino ◽  
Eneritz Anakabe ◽  
...  
Keyword(s):  
Organic Chemistry ◽  
Machine Learning ◽  
Chemistry Education ◽  
Organic Waste ◽  
Computational Modelling ◽  
University Education ◽  
Academic Factors ◽  
Academic Year ◽  
Statistical Analysis Software

Aims: Computational modelling may help us to detect the more important factors governing this process in order to optimize it. Background: The generation of hazardous organic waste in teaching and research laboratories poses a big problem that universities have to manage. Methods: In this work, we report on the experimental measurement of waste generation on the chemical education laboratories within our department. We measured the waste generated in the teaching laboratories of the Organic Chemistry Department II (UPV/EHU), in the second semester of the 2017/2018 academic year. Likewise, to know the anthropogenic and social factors related to the generation of waste, a questionnaire has been utilized. We focused on all students of Experimentation in Organic Chemistry (EOC) and Organic Chemistry II (OC2) subjects. It helped us to know their prior knowledge about waste, awareness of the problem of separate organic waste and the correct use of the containers. These results, together with the volumetric data, have been analyzed with statistical analysis software. We obtained two Perturbation-Theory Machine Learning (PTML) models including chemical, operational, and academic factors. The dataset analyzed included 6050 cases of laboratory practices vs. practices of reference. Results: These models predict the values of acetone waste with R2 = 0.88 and non-halogenated waste with R2 = 0.91. Conclusion: This work opens a new gate to the implementation of more sustainable techniques and a circular economy with the aim of improving the quality of university education processes.

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