Reasons of Academic Procrastination: Self-regulation, Academic Self-efficacy, Life Satisfaction and Demographics Variables

Procedia - Social and Behavioral Sciences 152 ( 2014 ) 188 – 193

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1877-0428 © 2014 The Authors. Published by Elsevier Ltd. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/3.0/).Peer-review under responsibility of the Organizing Committee of the ERPA Congress 2014.doi: 10.1016/j.sbspro.2014.09.179

ScienceDirect

ERPA 2014

Reasons of academic procrastination: self- regulation, academic self-efficacy, life satisfaction and demographics variables

Mehmet Kandemira* aKırıkkale Üniversity, Faculty of Education, Kırıkkale /Turkey

Abstract

The behavior of academic procrastination is quite common among students. Students can not show their real performances in learning processes and they fail because of procrastination behaviors. Determining the reasons of this behavior can decrease students’ behaviors and help them show their performances. In this context, the goal of this research is to determine how the variables of self-regulation, self-efficacy, life satisfaction, hope and other descriptive variables, which are mentioned in the related literature about academic procrastination, explain academic procrastination behavior in the regression model. Descriptive survey model and availability sampling model are used in order to reach this goal. In the research, “Aitken Academic Procrastination Scale”, “Emotional Literacy Scale”, “Academic Self-Efficacy Scale”, “the Satisfaction with Life Scale”, “Hope Scale” and “Information Form” are used in order to gather data. Correlation and hierarchical regression analysis are used in order to analyze the obtained data. At the end of the research, it is found that the regression model predicts academic procrastination. When the results of the research are analyzed, it is seen that the variables that make the highest original contribution to the model are respectively; academic success mean, self-regulation and life satisfaction. When the results of the research are analyzed, it is seen that academic success mean variable, which entered the model in the first step, predicts academic procrastination negatively and meaningfully. © 2014 The Authors. Published by Elsevier Ltd. Selection and peer-review under responsibility of the Organizing Committee of the ERPA Congress 2014.

Keywords:academic procrastination;self-regulation; academic self-efficacy; life satisfaction, hope

1. Introduction

There are some problems in students’ university life that prevent them from overcoming their educational

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E-mail address:[email protected]

© 2014 The Authors. Published by Elsevier Ltd. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/3.0/).Peer-review under responsibility of the Organizing Committee of the ERPA Congress 2014.

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189 Mehmet Kandemir / Procedia - Social and Behavioral Sciences 152 ( 2014 ) 188 – 193

responsibilities. One of these problems that restrain students’ educational potential is academic procrastination behavior. Rothblum, Solomon and Murakami (1986) define this concept as postponing academic duties such as preparing for exams and delaying homework sometimes or constantly. On the other hand, according to Ferrari, Johnson and McCown (1995), academic procrastination behavior is the behavior of avoiding academic duties which cause students have academic failure. Similarly, it can be said that, academic procrastination behavior is to postpone academic duties in a way that that is causes failure, academic unhappiness and stress.There are many studies showing that students who make academic procrastination face with various negative results of this behavior (Burka and Yuen, 1983; Kandemir, 2010). Academic procrastination behavior have negative results such as academic failure (Burka and Yuen, 1983; Ferrari, Johnson and McCown, 1995; Knaus, 1998), falling behind in the class (Rothblum, Solomon and Murakami, 1986), not attending the school and dropping out the school (Knaus, 1998). Besides the studies in the literature about the extensity and results of academic procrastination, there are various significant studies in the literature about the causality of academic procrastination (Farran, 2004; Fritzsche, Young andHickson, 2003; Kandemir, 2010). When the literature is analyzed, it is seen that academic procrastination is related with self-regulation which will be tested as the predictor of it in this research (Faber and Vohs, 2004; Metcalfe and Mischel, 1999; Uzun-Özer, 2010). According to Pintrich and De Groot (1990), cognitive strategies such as controlling and managing the effort given in order to cope with academic duties, repeating what is used for learning and understanding, interpreting and organizing are self-regulation. According to the related literature, it is seen that students who use these strategies make less academic procrastination (Faber and Vohs, 2004). When the literature is analyzed, it can be seen that academic self-efficacy beliefs, which are defined as beliefs about coping with academic duties (Bandura, 1997), is a significant variable that explains academic procrastination (Farran, 2004; Kandemir, 2010; Klassen, Krawchuk and Rajani, 2008). According to these researches, the tendency to postpone decreases when students belief about that they will solve difficult problems increases. It is seen in the related literature that another variable that is included in this research -life satisfaction- is a significant variable of academic procrastination (Binder, 2000; Savithri, 2014). Binder (2000) and Savithri (2014) state that there is a negative correlation between students’ life satisfaction and academic procrastination and life satisfaction have a negative and meaningful effect in predicting academic procrastination. In this research, the variable of hope is also tested in terms of predicting procrastination. Snyder (2002) defines hope as the thought process of an individual besides his goals, his methods to reach these goals and the motive to take action. When the related literature is analyzed, it is seen that the concept of hope has a significant relation with academic procrastination (Alexander and Onwuegbuzie, 2007). When the researches on the issue are analyzed, it is seen that the concept has a negative relation with academic procrastination. As different descriptive variables in the research; academic mean, absence and internet use duration are used. It is seen that there are relations between these variables and academic procrastination. When the results of these researches in the literature are analyzed, it is seen that there is negative relation between academic procrastination and success mean (Owens and Newbegin 1997) and academic procrastination and absence (Solomon and Rothblum, 1984). On the other hand, in the research by Wretschko (2006), it is found that academic procrastination increases when internet use duration increases. In terms of problems, it is seen that there are two basic problems; one of them is that academic procrastination is a common problem among students, while the second is that academic procrastination causes undesired results such as failure, anxiety, failing from courses and low life satisfaction. It is necessary to cope with these problems and overcome obstacles. In order to achieve this, researchers and developers need to have significant and objective information. In this context, the goal of this research is to determine how the variables of self-regulation, self-efficacy, life satisfaction, hope and other descriptive variables, which are mentioned in the related literature about academic procrastination, explain academic procrastination behavior in the regression model.

2. Methods

This research, in which students’ academic procrastination behaviors are predicted with self-regulation, self-efficacy, life satisfaction, hope and other descriptive variables in regression model, has a descriptive survey model. The research group of this research is made of a total of 619 students; 450 female and 169 male students from


different faculties of Kırıkkale University. 155 1st grade students, 169 2nd grade students, 210 3rd grade students and 85 4th grade students participated in this research.

2.1. Data Collection Tools

Aitken Academic Procrastination Scale: The scale is developed by Aitken (1982) in order to evaluate student tendencies in terms of postponing academic duties. The scale is adapted to Turkish by Balkıs (2007); Emotional Literacy Scale: The scale’s goal is to determine university students’ emotional literacy scale levels and it is developed by Palancı, Kandemir, Dündar and Özpolat (2014);Academic Self-Efficacy Scale: The scale is developed by Kandemir and Özbay (2012);The Satisfaction with Life Scale: The scale is developed by Diener, Emmons, Larsen and Griffin (1985) and it evaluates general life satisfaction. Pavot and Diener (2009) state that it is free to use the scale and there is no need for permission. The scale was previously translated to Turkish by Köker (1991); Hope Scale: The scale is developed by Snyder et al. (1991) in order to evaluate the hope levels of individuals. The scale is adapted to Turkish by Akman and Korkut (1993); Information Form: The form is created in order to obtain information about students’ sex, grades, academic means, absence and internet use level.

3. Findings

Hierarchical regression analysis is used in order to determine the prediction level of academic procrastination behaviour in terms of self-regulation, self-satisfaction, life satisfaction, hope and other descriptive variables. Correlation efficacy among related variables is analyzed before making hierarchical regression analysis.

Table 1: Correlation Values Among Variables

Variables 1 2 3 4 5 6 7 8

Procrastination (1) 1

Self Regulation (2) -.21** 1

Self efficacy (3) -.11** .60** 1

Life Satisfaction (4) -.23** .26** .26** 1

Hope (5) -.12** .09* -.09* -.13** 1 Absence (6) .19** -.15** -.10* -.14** -.10* 1

Internet use (7) .18** -.10* .10* -.10* -.10* .10* 1

Mean (8) -.26** .13** .10* .08 .12* -.10* -.11* 1 *p<.05, ** p<.01

At the end of the correlation analysis, it is seen that there are meaningful relations between the variables about

academic procrastination. It is found that academic procrastination is related with self regulation r=-.21, p<01; with academic self-efficacy r=-.11, p<01; with life satisfaction r=-.23, p<01; with hope r=-.12, p<01; with absence r=.19, p<01; with internet use r= .18, p<01 and with academic success mean r=-.26, p<01. It is also found that there are meaningful relations among other variables’ correlation coefficients.

When Table 2 is analyzed, it is seen that three hypothesis test models, which are tested with hierarchical regression analysis, predict academic procrastination together. In the first step, academic success mean, internet use level and absence are included in the model while self-regulation, academic self-efficacy are included in the second step and life satisfaction and hope are included in the third and last step. It is seen that all of the three steps that are tested in the model make meaningful contribution. It is determined that the original contribution of the first step is meaningful in the model (R² =.16, F (3/405) =19.20, p< .01). It is found that academic success make contribution at β=-.24, p< .01 level; internet use level make contribution at β=.17, p< .01 level and absence make contribution at β=.15, p< .05 level to the model. It is also found that the original contribution of the second step is meaningful in the model (R² =.18, F (2/403) =17.22, p< .01). It is seen that in this step, academic success make negative contribution to the model while internet use level and absence make positive contribution to the model. It is also determined that


self regulation, which is included in the model in the second step, make (β=-.22, p< .01) contribution to the model while academic self-efficacy belief in the same step doesn’t make meaningful contribution to the model (β=-.02, p > .05). It is seen that original contribution of the third step is meaningful in the model (R² =.23, F (2/401) =17.43, p< .01). Life satisfaction, which is included in the model in the third step, make original contribution at β=-.22, p< .01 level while hope level make contribution at β=-.14, p< .05 level. When the results of the research are analyzed, it is seen that the variables that make the highest original contribution to the model are respectively; academic success mean, self-regulation and life satisfaction. When the results of the research are analyzed, it is seen that academic success mean variable, which entered the model in the first step, predicts academic procrastination negatively and meaningfully. In other words, decrease in academic success increases academic procrastination behavior. When the related literature is analyzed, it is seen that there is no causality study that support this result. But there are some researches showing that there is a negative relation between academic procrastination and success (Knaus, 1998; Owens and Newbegin 1997). Academic success is a concept that has relation with academic procrastination motivation variable (Ames, 1992; Kandemir, 2010). Students that are academically unsuccessful may be losing learning motivation in time. In this case, students who lose academic motivation may be increasing academic procrastination behavior. At the end of the research, it is determined that increase in the level of internet use increases academic procrastination behavior. It is found that there are studies that support this result in the related literature (Wretschko, 2006). As a result of problematic internet use, students want to be on internet constantly and they lose control (Young, 2004). This situation may cause students make procrastination by preventing coping with academic duties which require continuity, responsibility and order. It is determined that absence which entered the model in the first step explains academic procrastination behavior positively. It is found that there are researches in the related literature which support this result (Solomon and Rothblum, 1984). In the research by Solomon and Rothblum (1984) they found that there is a relation between academic procrastination and absence. When students’ absence behavior increases, they may ignore academic responsibilities. It is seen that self regulation which entered the research model in the second step, negatively and strongly predicts academic procrastination. ıt is seen that the related literature supports this result of the research (Faber and Vohs, 2004; Metcalfe and Mischel, 1999; Uzun-Özer, 2010). In the research by Park and Sperling (2012) it is seen that self-regulation is a strong predictor of university students’ academic procrastination behaviors. Controlling and managing the effort of coping with academic duties and using strategies in order to learn and understand may ease organizing academic duties. Students may approach to academic duties rather than avoiding them if they can organize these duties. There are a limited number of researches in the literature which support this result of this research (Aydoğan and Özbay, 2011). Aydoğan and Özbay (2011) made a study on students preparing for university exam and obtained similar results. In this research, it is seen that there is a negative and meaningful relation between academic self efficacy and academic procrastination (r=-.11). But it is possible to say that this is not a predictive relation in the regression model. Including stronger variables that predict academic procrastination in the model (self-regulation, life satisfaction, success etc.) may have decreased self-efficacy’s influence power. It is found that life satisfaction, which entered the research model in the third step, negatively and strongly predicts academic procrastination. In other words, increase in life satisfaction level decreases academic procrastination behavior. It is seen that there are studies in the literature which support this result (Binder, 2000; Savithri, 2014). These researchers found that when students are satisfied with their life, namely when they are happy, academic procrastination behaviors decrease. Satisfaction with life or happiness may ease taking the responsibility of academic duties. Students that are happy may have positive views about everything in their life including academic duties. This situation may motivate students in coping with academic duties. It is seen that hope variable, which entered the model in the third step, have a negative and meaningful effect on predicting academic procrastination. This result is supported by the related literature (Alexander and Onwuegbuzie, 2007; Özer and Altun, 2011). Özer and Altun (2011) made a research and used canonical correlation technique. At the end of this research, they determined that hope variable negatively affects academic procrastination. Hope shortly means having goals for future. Using goals as motivation tools in order to cope with academic responsibilities may get students closer to these responsibilities instead of avoiding them.


Table 2: Results of regression analysis about predicting academic procrastination

Model Predictors B SD df t P R R² ΔR² F

Constant 14.38 1.28 3/405 11.22 .00 .35 .16 .12 19.20 1 Mean -2.03 .39 -.24 -5.18 .00 Internet use .79 .23 .17 3.55 .00 Absence .09 .03 .15 3.26 .01 Constant 21.16 1.86 2/403 11.40 .00 .42 .18 .17 17.22 Mean -1.87 .38 -.23 -4.89 .00 Internet use .70 .22 .15 3.18 .02 2 Absence .07 .03 .12 2.65 .08 Self regulation -2.13 .59 -.22 -3.64 .00 Self efficacy -.09 .29 -.02 -.29 .76 Constant 29.07 2.85 2/ 401 10.19 .00 .48 .23 .22 17.43 Mean -1.79 .37 -.21 -4.82 .00 Internet use .63 .21 .13 2.96 .03 Absence .06 .03 .11 2.36 .02 3 Self regulation -1.79 .57 -.18 -3.13 .02 Self efficacy .07 .29 .01 .23 .82 Life satisfaction -.67 .14 -.22 -4.73 .00 Hope -4.35 1.41 -.14 -3.08 .02

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Reasons of Academic Procrastination: Self-regulation, Academic Self-efficacy, Life Satisfaction and Demographics Variables