Table of Contents
- Introduction
- 1. Objectives of Research
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- 2. Hypothesis
- 3. Data collection and Analysis techniques
- 4. Procedure
- 5. Measurements
- 6. Results
- Exploratory Data Analyses
- 7. Discussion
- 8. Limitations and Suggestions for Future Research
- Implications
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Introduction
The previous review of the literature shows that inefficient usage of time causes stress. A survey carried at University of Bolton evaluates the psychological status of 1000 undergraduate students. The results are alarming, showing that more than half of the university students are suffering from various severities of depression, anxiety and psychological problems that were due to improper Time Management. Students remark that they are always stressful concerning their study matter, future career, examination stress and managing time. Significantly, stress relationship with quality of sleep occurs in the students. A recent research emphasizes that students with daytime dysfunction in campus and sleep disturbances lacks Time Management skills, and they complain high intensity of stress. Improper Time Management correlates to poor quality of sleep, and poor sleep results negative consequences in academic growth. (Britton, 1991)
1. Objectives of Research
Time management sleep quality and stress correlates with each other, and each of the factor affects student performance. The objective of this research is to explore the possible priority so as to tackle and prevent the problem. Further, this research will try to explore a relationship of Time Management with stress and sleep quality and suggests suitable measures.
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2. Hypothesis
Overall, by review of the previous literature and previous observations, four hypotheses seem to appear in this study: hypothesis one shows time management disposition positively relates with students’ academic performance. Hypothesis two states perceived stress negatively correlate with academic growth. Hypothesis three states, quality of sleep negatively correlates with academic achievement and hypothesis number four, time management character is a negative forecaster of stress. (Adams, 1997)
3. Data collection and Analysis techniques
By adopting convenience and snowball method of sampling, 110 full time undergraduate psychology students from University of Bolton involves in the present research. Fifty three (48.6%) and 37 out of 110 (32%) are third year and second year undergraduate psychology students of Bolton University. The remaining 20 of them (19.4%) are part time psychology students. The students age from 18 to 26 years old. The majority of students are 21 years old (33.7%) and 22 years old (25.6%). The mean age works out to be 22.66 years old. Fifty Nine (53.3%) are female while 49 (45.8%) of them are male and two’s gender is missing (approximately 1%). Forty three (38.4%) and 22 (21.3%) out of 110 students achieved a cumulative grade point average of 2.51 to 2.98 and 3.00 to 3.38 respectively. (Adams, 1999)
4. Procedure
First of all, approval from the University Institutional Board is necessary before starting the data collection. Besides data collection, data and consent forms are anonymous and strictly confidential so as to protect the identity of students. Distribution of questionnaires takes place during break time and class sessions. Eighty four students were able to complete questionnaires and returned them in time. The remaining students join the survey by snowball sampling and these students also approach other students who are full time psychology students. In this research, students have to answer four sets of questionnaires. To ensure that students understand all those questions properly, this study implements Pittsburgh Sleep Quality Index. Time Management Disposition Inventory and Perceived Stress scales.
The procedure starts with distribution of approximately 175 questionnaires to psychology undergraduate students of Bolton University. One hundred and eleven questionnaires received from students show a response rate of 65.5%. Moreover, Shahani (1993) recommends that the minimum numbers of students in a research for running multiple regressions should be 16 cases for each forecaster. The present research involves three predictors, which implies that this research requires minimum 45 cases and fulfills the criteria obligations.
After collecting data, coding and feeding into a statistics software program begins by entering Statistical Package for the Social Sciences. With the help of SPSS then relevant statistics, correlation, descriptive statistics, multiple regression and linear regression starts for analysis of the data. Besides, all tests comply carrying a 94% confidential interval.
5. Measurements
The measurements that include in the present research are TMDI Inventory, academic performance, Pittsburgh Sleep Quality Index, Perceived Stress Scale, and academic performance. TMDI applies in the present research. TMDI calculates time management in three domains, such as the time value, time control and time efficacy. Students need to response a six point Likert scale (1 = not agreed at all to 6 = fully agree). Cronbach’s alpha for TMDI is .62 to 86 and retest dependability is .72 to .82, which shows that the measure is from medium to highly dependable.
Moreover, the internal uniformity of TMDI is .69, and it corresponds well with TMQ and TMB recommending that TMDI possess both concurrent and internal validity. Therefore, for evaluating stress in students Perceived Stress Scale (PSS) is a widely popular method. It uses a 6-point Likert scale (0 = never and 5 = remarkably often) point out unpredictable, uncontrollable, and excessive loading in the previous month. The Perceived Stress Scale is reliable and valid scale.
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Perceived Stress Scale remarkably correlates with Events and Life Score and depressive symptoms in three student samples. From the same student samples, the Cronbach alphas of 15-item, PSS is .85 and .86. Furthermore, among the general population of student, the consistency of PSS is .76.
Sleep quality. The present research employs the Pittsburgh Sleep Quality Index to evaluate sleep quality during the past month. Such studies usually adopt PSQI to examine subjective sleep quality, and its purpose is to differentiate between healthy and poor sleep.
It is a self designed questionnaire which contains seven domains: perceived sleep latency, sleep quality, sleep hours, sleep efficacy, disturbed sleep, use of medication, and daytime un-alertness. The sum of these scores of seven domains is the global score. PSQI implements four-point Likert scale for each of the seven fields, with a global score that ranges from 0-20. Higher global PSQI score depicts poor sleep quality while lower score reflects better sleep quality. The PSQI proved to be trustworthy. The internal consistency is 0.82 and test retest reliability is 0.84.
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Academic performance. For measuring students’ academic performance and avoiding missing data, students need to report the series of GPA instead of the number. According to the range of cumulative grade point average, academic performance classify into five categories (fail = below 3.00, pass = 3.00 to 3.19, third class = 3.20 to 3.49, second lower class = 3.50 to 3.99, second upper class = 4.00 to 4.39 and first class = 4.40 to 5.00).
Besides, in order to get interval, scale variables for running regression analysis, students class changes to dummy variables with yes coded as 1 and no coded as 0. For example, students with first class code as 1. If not, they code as 0.
6. Results
The present research adopts descriptive statistics. Kendall’s tau-b and Spearman correlation, Pearson, Mann-Whitney U test, and regression evaluates the connectivity among time management, sleep quality, stress and academic output among students in Bolton University. The results divide into five sections: results of the reliability and validity tests of each measurement, descriptive statistics, exploratory data analyses, data screening, and hypotheses testing. (Macan, 1990)
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The validity and reliability of measurements correspond to the findings from the past studies, TMDI, PSS, and PQSI shows highly valid and reliable. The Cronbach’s alpha for PSS, TMDI, and PSQI show .83, .89 and .84 respectively in this research. It explains that data are highly reliable. Besides, Cronbach’s alphas relation to every few sub-constructs of TMDI such as the value of time, control time, and the time efficiency are .88, .89 and .78 respectively, which shows that TMDI holds the oblique validity of each and every few sub-constructs (when items and questions relates with each other and then these questions and items measure the same construct, it derives the convergent validity). On the other side, the Cronbach’s alpha relation with three sub constructs of TMDI is only .62, which demonstrates the discriminate proof, or a case of divergent validity for three sub-constructs of TMDI.
Exploratory Data Analyses
This research also explores the difference with respect to gender on academics and the connectivity between age, academic output and year of study. Since, questionnaire ask the students to rate their current, cumulative grade point average as a first class, second upper and etc, therefore, this study views these data as ordinary data. Mann-Whitney U test is useful to compare the gender difference on academic performance. Mann-Whitney U test is useful to deal with data, when there is no disturbance in dependent variable, and the samples are independent corresponds to independent sample t-test. (Campbell, 1992)
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Usually, t-tests deal with dependent variables and their classification is on the basis of interval or scale data. The results show that there is no key difference in gender on students academic output.
Determination of the relationship between academic performance and age and academic performance and year of study is by conducting Kendall’s tau-b analysis method of correlation (as this test finds the relationship between two ordinal data). The results depict a powerful negative relationship between academic performance and age. It shows that older students have their lower GPA.
7. Discussion
Concerning the hypotheses obtained from review of literature, the results of the present research supports hypotheses four; however, it do not agree with hypotheses one to three. Besides, the results support the initial model of time management, quality of sleep and perceived stress. A combined impact of time management and stress appears to be the significant predictor of quality of sleep. Besides, hypotheses testing in case of exploratory testing show a powerful relationship between academic performance and age. While analyzing the exploratory data, there is no key difference between academic performance and gender, and no powerful correlation between academic performance and year of study. After the results of exploratory analysis, there is a necessity to discuss the results of hypotheses analyses. While examining hypotheses one to three, there are no key relationships between time management disposition, sleep quality, perceived stress and academic attainment which are considerably significant. The explanation of these contradictory results can be due to the limitations of this research.
8. Limitations and Suggestions for Future Research
As seen above from the results, this research only requires students to rate their current, cumulative grade point average, which is the obstacle in the analysis. For future researches, researchers should ask students for the accurate cumulative grade point average with three decimal points or try to cut down the ranges in a smaller piece the future. Further, this study do not account for error variances, as such it cannot explain how much error variances are influencing the analyses. The study recommends implementing structure equation modeling for conducting future analyses. It is possible to establish the model with error variances by the researcher by adopting structure equation modeling. Moreover, he can explain how to fit the model simply by observing different model fit indexes. Secondly, this research adopts convenience sampling, which is a non probability sample method. It is much better implementing probability sampling method as it confirms representativeness. There are numerous kinds of probability sampling method: systematic, simple random, multistage sampling and stratified. However, most of time, it is not possible to implement them. For example, the simple relationship between systematic and random sampling methods is difficult to implement. It is difficult to obtain the whole list of students studying in Bolton University. Researcher can look for alternative measures; can adopt stratified sampling, which is multistage sampling and probability sampling method. In the initial stage of stratified sampling, a selection of sample takes place from a wide range of predetermined areas. For example, this study aims to examine the effectiveness of Time Management in university students, a sample might be graded by the university or year of study or even main subject and so forth. In the next stage, it is possible to choose a sample selection at random within those areas. Lastly, it is not possible to conclude causal relationship in this study. The research at Bolton University recommends future studies to conduct a longitudinal study on this topic to expose the causal relationship. (Walker, 1980)
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Implications
This research based on the above findings discusses the numerous implications for university students and practitioners appearing due to poor Time Management resulting in stress and sleep disorder. Firstly, practitioners such as psychologists and counselors can devise time management and stress management seminars for university students. These seminars and programs can inspire and educate students with better time management skills as well as stress management skill. It will further make them free from negative effects of poor sleep quality that are occurring due to poor Time Management. The results show that combination of Time Management with Stress Management improves the quality of sleep. Therefore, practitioners should not neglect including Time Management in stress management programs, and try to grasp the cause of stress, which is improper Time Management. However, if there is a lack of time in implementing both programs, the first priority should be the stress management. As by anticipating the gravity of perceived stress, it is extremely much larger than time management regulation. This recommends that perceived stress is more closely connected to quality of sleep. Alternatively, psychologists can blend the two aspects of the training program and deliver it to university students. For Bolton University students, the findings provide them to set out for a better life. The findings of this research can assist them to acknowledge the relationship among time management, stress and quality of sleep. By understanding the linkage of stress and sleep quality with Time Management, university students should learn to manage usage of time by disciplining themselves and learning will automatically show how to manage time and stress.
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Improper Time Management directly correlates with stress and sleep quality and improvement in time and stress management would undoubtedly benefit Bolton University students. It will further save them negative effects of poor time management, poor quality of sleep and higher level of stress. By learning these basic techniques, they can improve their academic performance. In other words, students will become both physiologically and psychologically healthy lifestyle and after their graduation; they can become an asset to the society. (Kleijn, 1994)
The present research aims to examine the relationships between time management, academic performance, stress and quality of sleep. The results show that both time management and stress are key indicators of sleep quality. Moreover, instead of individual effect, the best forecaster of sleep quality is the joint effect of time management and stress. On the other side, these three constructs do not accurately relate to academic performance