Mozambican adolescents' perspectives on the academic procrastination process

Abstract

The current study explored Mozambican adolescents' perspectives of the process of academic procrastination, focusing on three key aspects: Type of tasks where youth usually procrastinate, antecedents, and the perceived consequences. Twenty-four adolescents from a pool of 300 (11th and 12th graders) reported high levels of procrastination and were selected to be interviewed. Data were analysed using content analysis. Overall, the findings showed that perceived lack of content knowledge can be the antecedent of procrastination behaviors, particularly when it comes to homework. These findings may help teachers and school administrators create a better school environment that promotes learning engagement and inhibits procrastination.

Keywords

academic procrastination adolescents homework mathematics perceived consequences procrastination antecedents

Academic procrastination is a common and serious problem in schooling (e.g., Katz, Eilot, & Nevo, 2014; Kim & Seo, 2015). These behaviors are very common among younger students (e.g., Katz et al., 2014), yet the prior research on this topic has been mainly focused on college students (e.g., Ferrari, Keane, Wolf, & Beck, 1998; Wäschle, Allgaier, Lachner, Fink, & Nückles, 2014). Extant research on adolescents' procrastination has examined the relationships between motivational variables (e.g., self-efficacy, intrinsic, and extrinsic motivation) and academic procrastination (e.g., Katz et al., 2014). However, little is known about the process of academic procrastination in high school, especially among students from non-Western cultural backgrounds (Klassen & Kuzucu, 2009; Klassen et al., 2009). The current study aims to explore the perspectives on academic procrastination (i.e., tasks they usually procrastinate on, antecedents, and the perceived consequences) of adolescents from Mozambique. Findings are expected to help inform school-based interventions focused on decreasing academic procrastination and promoting school achievement.

Academic procrastination

Procrastination of academic tasks is a behavior that has been widely reported throughout the last century and examined by researchers using different theoretical frameworks (e.g., self-regulation models; Steel, 2007). The nature of this concept is likely to help understand the relationships between aspects of the individuals' behaviors (e.g., motivation) and performance (Steel, 2007). Academic procrastination is commonly defined as the act of delaying the beginning or the completion of a timely task (Senécal, Julien, & Guay, 2003). Procrastination is also described as a form of motivational dysfunction, and it is expressed similarly across cultures (Klassen & Kuzuku, 2009).

Literature reveals some characteristics that can indicate either current or future procrastination behavior. Wäschle et al. (2014) found that college students with low academic self-efficacy procrastinate often, and they are likely to develop a ‘vicious circle of academic procrastination’ (p. 111). Findings indicated that the more the students postponed assigned work, the more difficulties they faced completing the task. Moreover, authors found that those students were unlikely to complete the subsequent tasks (Wäschle et al., 2014).

Factors contributing to academic procrastination have also received researchers' attention. Ferrari and colleagues (1998) and Orpen (1998), for example, analysed internal (e.g., students' volition and negative emotions) and external (e.g., complexity of the task) antecedents of academic procrastination (Ferrari et al., 1995; Schraw, Wadkins, & Olafson, 2007). Volition antecedents were found to play an important role in one's strength to cope with low interest and lack of pleasure while learning the content (Grunschel, Patrzek, & Fries, 2013). These antecedents also affect one's ability to avoid the negative influences of social distractors (Ferrari et al., 1995). Negative emotions such as stress, frustration, feelings of annoyance, indecision decisions, and task avoidance have been identified as affective antecedents of procrastination (Grunschel, Patrzek, & Fries, 2013; Kliengsiek, Grund, Schmid, & Fries, 2013). Research focused on the external antecedents of procrastination has found that students are more likely to procrastinate their school work when they perceive tasks as important, stressful, and difficult (Pychyl, Lee, Thibodeau, & Blunt, 2000).

Academic procrastination of adolescent students

Orpen (1998) analysed high school students' behaviors and found that academic procrastination was negatively related to academic achievement and academic attitudes. Regarding the latter, the author explained that negative attitudes towards school subjects and study assignments are likely to be associated with non-completion of school tasks (e.g., homework); the latter behavior helps explain students' low achievement. Interestingly, Owens and Newbegin (1997, 2000) examined mathematics grades not as a dependent variable, but as a predictor of academic procrastination. Findings indicated that low grades in mathematics, irrespective to the gender, showed a strong effect on academic procrastination. Owens and Newbegin also found that academic procrastination behaviors increased throughout high school.

The study by Klassen and Kuzucu (2009) added to literature by providing information regarding three aspects of procrastination: The duration of the procrastination behavior, the type of academic tasks where adolescents most often procrastinate, and the nature of the behaviors displayed while procrastinating. Findings indicated that about 80% of the participants reported spending more than an hour a day engaged in academic procrastination behaviors, and more than 40% reported to spent three hours a day on procrastinating school behaviors (e.g., essays, homework and daily study). Boys reported to engage in procrastination behaviors by watching TV, surfing the net, chatting online or playing on the computer. Girls, however, reported that they procrastinate by reading books, newspapers, and magazines. Procrastination behaviors were found to be strongly predicted by low academic self-efficacy and low self-efficacy for self-regulation (see also Klassen et al., 2009). Consistent with those findings, Katz et al. (2014) found negative associations between middle school students' self-efficacy and homework procrastination; both are mediated and moderated by intrinsic motivation to do homework.

Purpose of the present study

Research analysing the process of adolescents' academic procrastination is still limited (Katz et al., 2014). The topic, however, is particularly important due to its relation with low academic achievement (e.g., Kim & Seo, 2015; Owens & Newbegin, 2000) and school dropout. Moreover, early dropout is related to poor socio-emotional skills, low economic resources, and less promising employment opportunities (e.g., Jimerson, 1999; Klassen, Krawchuk, & Rajani, 2008). All of these problems are present in the Mozambican society (e.g., Fox, Santibañez, Nguyen, & André, 2012). In fact, and despite the recent progress made in the Mozambican educational sector (e.g., the number of primary schools has tripled from 1992 to 2004, see Virtanen and Ehrenpreis, 2007), the overall level of education remains low, especially in rural areas. For example, data from official reports indicate that 60% of school-aged children are likely to leave school without the expected skills in reading, writing, and numeracy (Virtanen & Ehrenpreis, 2007).

The study of academic procrastination in a non-Western context facing severe economical and societal constraints is expected to contribute to the development of the Mozambican students' school success (e.g., Fox et al., 2012). Moreover, despite each African country's own social and economic patterns of development, there are close similarities between their educational systems (Samoff, 1999). For this reason, the findings of this study are likely be useful to educational systems beyond the Mozambican.

To the authors' knowledge, with a few exceptions (e.g., Owens & Newbing, 2000), previous studies on academic procrastination conducted with adolescents did not focus on one school subject. The rationale for this investigation's focus on mathematics is related to the role played by this content in other school subjects (e.g., biology, physics) as well as its association with the development of life and citizenship skills (e.g., Hagger, Sultan, Hardcastle, & Chatzisarantis, 2015). This is particularly important in Mozambique, where teachers often have poor qualifications and students seriously struggle to succeed in mathematics (Vos, Devesse, & Pinto, 2007). Mathematics success in secondary school provides access to vocational or higher education and is likely to be a pathway to high-status careers (e.g., medical doctor, engineer, accountant), and good life conditions (Conselho, 2009). Moreover, Murimo (2013) investigated beliefs and attitudes towards mathematics and found that Mozambican parents recognize the value of mathematics to succeed in other science subjects (e.g., physics, chemistry) and get well paid jobs.

The current study extended prior research conducted with college students by addressing the process of academic procrastination in mathematics among Mozambican high school adolescents. Based on prior studies, data collection and analysis were grounded on three aspects of the procrastination behavior: The tasks students usually put off, the reasons for the procrastination, and the perceived consequences of the procrastination behaviors (Grunschel et al., 2013; Klassen & Kuzucu, 2009; Klingsieck et al., 2013; Schraw et al., 2007). Following Grunschel et al. (2013), the current research was not grounded in a specific theoretical framework to study academic procrastination in-depth and gain new information about the topic under adolescents' perspectives.

Method

Study context and participants

Compulsory education in the Mozambican school system is comprised by primary school (i.e., from 1st grade to 7th grade) and secondary school (i.e., the first cycle comprises 8th up to 10th grade and the second cycle comprises 11th and the 12th grade). The secondary schools registered high rates of school failure (22.3 %), and school dropout ranged between 5.3% (first cycle) and 9.8% (second cycle); these percentages are substantially higher in the 12th grade (40%) (Conselho, 2009). In Mozambique, the secondary schools face severe barriers to education, especially in rural areas; for example, poor infrastructure and little to no provisions for other critical social services (health care), poor teaching qualifications, and lack of school resources (e.g., books, and learning materials) (Conselho, 2009). Moreover, and despite the lack of school resources and poor infrastructures, teachers have to teach large classes. According to national reports of Education in Mozambique, each class has around 70 or more students (Fox et al., 2012), which is a much higher number of students per class than those in most Western countries (25 to 35 students per class) (Eurydice, 2012).

Acknowledging the educational challenges faced by students in the Mozambican secondary school, the current research was conducted at the school level to learn students' perspectives of how they cope with school work and procrastination. To better understand the academic procrastination process, students who reported high academic procrastination behaviors were interviewed (see Grunschel et al., 2013; Klingsieck et al., 2013).

Research was conducted in the outskirts of city of Maputo, at the only high school in the district of Catembe. The school is in a poor rural area of the city with poor school infrastructures, erratic electricity supply (more so during heavy rains), and poorly maintained roads; for example, many students have to walk to school for two hours in each direction.

The school administrator of this high school provided permission to conduct investigations there. All the 903 students enrolled in the final grade levels of high school (11th and 12th grade) were invited to participate, and 684 agreed to participate in the study (response rate of 76%). From this pool, 300 students aged between 16- and 19-years-old (M_age = 17.79; SD = 1.28) were randomly selected, and responded to a questionnaire of academic procrastination (see procedure section). Of these students, 24 (15 girls) were identified as reporting high procrastination behaviors (13 11th graders and 11 12th graders). School records showed that: (1) all 24 students have failed on mathematics at least twice; and (2) 85% of their parents show a low educational attainment (i.e., elementary school). The mathematics teachers of these students (N = 8; 1 female) had 10.7 years of teaching experience in average (SD = 0.79) and their classes had 68 students on average (SD = 3.21).

Procedure

Permission to run the study was obtained from the Education District Office, school directors, and parents of the students. One week before the beginning of the study, one member of the research team informed the students about the study in their classroom and delivered the informed consent and authorization letters to their parents. On the day of data collection, only students with signed informed consent and authorization letter from their parents participated in the study. The participation was voluntary, and confidentiality was assured for all enrolled.

Firstly, (see Figure 1), students completed a questionnaire by Rosário et al. (2009) to assess academic procrastination for both daily study and the study for exams (α = 0.74 in the present study). The students (N = 24) of the fourth quartile (i.e., highest scores on the academic procrastination questionnaire) were selected and recruited for individual interviews in a second phase (see Figure 1). The number of students enrolled in the interviews was within the recommended range (20–30) indicated by Warren (2002) and was expected to ensure enough diversity and the saturation of data (e.g., Baker & Edwards, 2012).
Figure 1.
Schematic of procedures of data collection.

The interviews were conducted in Portuguese, the native language of these students, and addressed three key aspects of the process of academic procrastination (Grunschel et al., 2013; Klassen & Kuzucu, 2009; Klingsieck et al., 2013): type of tasks where youth usually procrastinate (i.e., What kind of things do you do when you procrastinate? In what kind of situations do you procrastinate? How often do you procrastinate?), antecedents/reasons (i.e., What are the reasons that lead you to procrastinate?), and consequences (i.e., What are the consequences of your procrastination? What do you think that could help you stop procrastinating?). Before the study began, five students were interviewed to check whether these questions were easily understood. Data from these interviews were not included in results. Students were not familiar with the term ‘procrastination’, so a definition of procrastination according to a Portuguese dictionary was provided in the beginning of the interview, as follows: ‘postpone a task; delay; putting it off until later’.

The 24 interviews were conducted in school after classes and lasted approximately 20 minutes. As the interview was open-ended, the researcher encouraged students to answer using prompt questions (e.g., Can you explain your idea? Can you give me an example? For example, think on a situation that occurred this last week). All interviews were audio recorded and transcribed verbatim.

Data analysis

The QSR International's NVivo 10 software was used to assist with the organization, management, coding, and querying process of the data (e.g., Richards, 2005). The content analysis followed the steps (i.e., pre-analysis, exploration of data, and treatment) described by Bardin (1996). The analysis started with the reading of the verbatim transcriptions to get an overall idea of the data (i.e., pre-analysis). In the coding process (i.e., exploration of data), the number of participants who referred to an idea was used to identify the themes. The identification of categories and subcategories followed a deductive and an inductive iterative process. In the case of the former, all categories and subcategories were organized a priori in a codebook based on the antecedents, behaviors and consequences of academic procrastination identified in the literature (e.g., Grunschel et al., 2013; Klassen & Kuzucu, 2009; Klingsieck et al., 2013; Schraw et al., 2007). For the latter, as the analysis was carried out, new subcategories were added using the participants’ own words (e.g., ‘high domestic chores’, ‘homework non-compliance’). Every time this happened, all the transcriptions were reviewed to check if the coded material fit better in the new subcategories. The NVivo 10 software provided the number of participants in each subcategory and the respective percentages were calculated (i.e., treatment; Bardin, 1996) by the researchers. After 12 interviews with the students and five interviews with the teachers, no new categories or subcategories were identified, therefore it was concluded that the saturation of data had been reached.

The research team conducted methodological procedures to enhance trustworthiness of findings (Lincoln & Guba, 1985). Two members of the research team coded all the material. The two researchers then reviewed all categories and subcategories and discussed the differences found to reach a consensus (e.g., coding ‘technology and social networks’ as one subcategory, given that the subcategories ‘technology’ and ‘social networks’ were highly related). The Kappa value obtained was 0.84, considered as very good according to Landis and Koch (1977). Following literature recommendations, data were used in the original language (Van Nes, Abma, Jonsson, & Deeg, 2010); namely, all data analysis and direct quotations in the manuscript. In the final version of the manuscript, one of the coders, who is Mozambican, translated the direct quotations with the support of an English teacher. Researchers discussed the final version of quotations in English compared to the original and reached total consensus.

Findings

Findings are presented according to the major categories grounded in the literature (e.g., Grunschel et al., 2013; Klassen & Kuzucu, 2009; Klingsieck et al., 2013; Schraw et al., 2007): Academic procrastination behaviors, antecedents and perceived consequences.

Academic procrastination

All students reported that they usually postpone their mathematics homework assignments, and in much lower numbers, students also reported procrastinating in daily study and exam preparation (see Figure 2).
Figure 2.
Graphical model of adolescents' academic procrastination process.

Antecedents of procrastination

Students reported that procrastination of homework may occur due to reasons such as low motivation or interest in mathematics, lack of knowledge or skill, commitment to help the family or do household chores, and the high amount of time spent with the use of technology and social networks (e.g., surfing on Facebook).

Still, the lack of knowledge or skill was the main reasons behind the delay of homework completion. The majority of the students disclosed distress related to their perceived lack of skills in mathematics: ‘I usually don't understand the homework tasks, they are too difficult for me…’ (P₂₃), ‘I was never good at mathematics, I don't have enough knowledge of mathematics to do homework alone, it's too much difficult for me, and I do not have any help at home’ (P₁₃).

Most of the female students added that they are expected to do daily chores at home, and some of them said that they are also expected to take care of their little siblings. ‘When I finish school I must hurry because I need to get home quickly to cook for my family’ (P₆).

All students reported that they postpone academic tasks due to their interaction with friends via WhatsApp or Facebook. When asked to further explain, the students said that ‘they are fun’ and ‘a more interesting thing [than studying], because it is just a click away’ (P₉). One of the students said, ‘It is much more fun to chat with our friends than do homework’ (P₃).

Lastly, low motivation or interest in the subject was other reason to postpone the homework (I am simply not interested in math … I always find ways to do other things when I should do math homework, P₁₈).

Consequences of procrastination

All the students reported negative consequences of their procrastination behaviors (e.g., homework non-compliance, lack of knowledge, low achievement, and negative affect). Participants said that to avoid these consequences they frequently copy homework at the last minute from their classmate or attend classes without having the homework completed. Some of the students explained that teachers suspended students who missed homework from class and ask them to complete the homework before returning. Meanwhile in class, teachers check homework on the board and the suspended students miss the opportunity to learn from this feedback. A student who referred to missing homework frequently expressed his despair saying that ‘feel like I’m always missing the boat …’ for ‘not attending class’ (P₃).

As the participants reported, procrastinating regarding school work leads to a negative feedback loop: Miss homework, miss class, and fail homework correction. This loop creates learning gaps and an uneven distribution of knowledge. The students affected by this aftermath expressed discomfort:
I think I'm far behind … I do not understand the contents … I will never learn the topics. (P₂)

On the day of the test, I'm not able to solve the exercises … . (P₆)
As some participants reported, this negative feedback loop promotes low academic achievement (e.g. ‘I don't know how to solve the exercises … I miss homework … I have to leave the classroom and I get a bad grade’, P₄) and feeds procrastination behaviors (e.g. ‘having bad grades in math keeps me procrastinating, and procrastinating is becoming a habit …’, P₂₄). A few students expressed negative affect (e.g., fear, anxiety, frustration) related to their procrastination behaviors (‘I feel bad… [looking anxious] I may fail the school year …’, P₂₁).

Discussion and implications

This study explored adolescents' perspectives on the academic procrastination process (i.e. tasks, antecedents, and consequences of procrastination). The discussion is organized according to each key aspect of academic procrastination.

Academic procrastination

A few participants reported procrastinating in their general daily studies or preparations for exams. This may be due to the fact that students fail to follow study routines (Pychyl, Morin, & Salmon, 2000). Still, all participating students reported procrastinating in their mathematics homework assignments. This finding could be related to the fact that, in the school they are enrolled in, homework is a mandatory school task assigned and monitored daily by teachers. In fact, unlike the students' study behaviors where procrastination may be kept covert (i.e., external control is often lacking and the academic consequences are displaced in time and non-contingent on those procrastination behaviors) (e.g., Klingsieck, 2013; Milgram & Tenne, 2000), homework procrastination is likely to be overt. This may be due to teachers' control on homework completion and the academic consequences of missing homework (e.g., leave class to complete homework outside).

Antecedents of procrastination

Most participants reported the perceived lack of knowledge in mathematics as the main antecedent for the homework procrastination. This is a worrying scenario because mathematics ties in with other important areas of knowledge (e.g., biology, physics) and with the development of life and citizenship skills (e.g., Hagger et al., 2015). Moreover, prior studies have shown that poor mathematics performance is associated with school dropout (Fall & Roberts, 2012). These data merit educators' attention, because lack of knowledge impacts negatively on the use of self-regulated learning (SRL) strategies (Zimmerman, Bandura, & Martinez-Pons, 1992), and is closely related to procrastination (e.g., Wäschle et al., 2014).

Globally, the findings support the need to intervene with students' procrastination behaviors as soon as possible to prevent them from accumulating learning gaps. In general, learning gaps may result in poor SRL, academic failure, and early dropout (see Fall & Roberts, 2012). Students should be helped to diminish their procrastination and become more engaged in their homework. For example, teachers could consider reflecting on the design of the homework assignments. Recent literature highlights that purposeful homework assignments fitted to students' learning needs and level of competence are expected to help them understand the assignments' instrumentality. This helps improve the students' engagement in the task which results in better academic achievement (e.g., Rosário et al., 2015). In class, teachers could also consider emphasizing the importance of asking for help to further exploit the benefits of homework (Du, Xu, & Fan, 2016). Moreover, students would benefit from SRL training. As extant research has shown, there is a negative relationship between procrastination and the use of SRL strategies (e.g., Chu & Choi, 2005; Ferrari, 2001). In fact, students are expected to use SRL strategies in their personal study (e.g., time management, goal setting, note taking) (Núñez, Rosário, Vallejo, & González-Pienda, 2013) but these strategies are seldom taught in class (Rosário, Núñez, Valle, et al., 2013). Therefore, school psychologists, administrators, and educators could consider training the students to use SRL strategies to overcome academic procrastination.

Of the participants involved, more girls than boys reported procrastinating their school work due to their high involvement in domestic chores. These data are consistent with that of Githua and Mwangi (2003) who found that one of the factors explaining the academic underperformance of girls in Kenya is because they lack time for studying and completing mathematics homework due to their high involvement in domestic chores. Moreover, Taímo (2015) reported that one of the reasons related with the Mozambican girls’ poor school performance and dropout are their families’ high expectations for receiving help with domestic chores (e.g., collecting and cutting firewood, fetching water, cooking, babysitting, and taking care of the elderly). A recent report from UNICEF (2016) on gender inequality indicated that in countries with higher expectations for girls to work, those aged 10- to 14-years-old spend an average of nine hours a week on chores. Following the African values that a child should be raised in a ‘family community’ (Mkhize, 2006, p. 187), this disparity in learning should be addressed by the whole community, because early gender disparities set the ground for inequality and are likely to limit girls’ development opportunities (UNICEF, 2016). Prior investigation has also shown that parents’ support is likely to diminish homework procrastination (Dumont, Trautwein, Nagy, & Nagengast, 2014) and help improve students’ self-regulation strategies, responsibility for academic tasks, and quality of learning (Xu, Benson, Mudrey-Camino, & Steiner, 2010). For these reasons, school psychologists, administrators, and educators could consider working with families to help them value and become more involved in their children's schoolwork (e.g., parents’ involvement in homework management) (Cunha et al., 2015; Xu & Corno, 2003).

Participants also mentioned technology and social networking as a procrastination antecedent; this finding is consistent with literature. Recent work conducted in mathematics showed that middle and high school students reporting higher homework distraction related to technology also reported spending more time on homework (which may be related to procrastination) (see Xu, 2015; Xu, Fan, & Du, 2015). Overall, the use of technology (e.g., online chats and games) as an antecedent of procrastination is increasing among adolescents (e.g., Xu, 2015). To help cope with this distraction, families could consider monitoring their students' usage of technology devices.

The last antecedent reported by the participants is related to lack of motivation and interest to engage in mathematics. Most of the participants mentioned lack of skills in mathematics, which is negatively related to intrinsic motivation and engagement in academic tasks (see Ryan & Deci, 2000). To foster students' motivation to complete homework assignments and avoid procrastination, teachers can try to reflect upon their homework practices and adapt the assignments to match students' level of knowledge; teachers can also stress the instrumentality of doing homework (see Rosário et al., 2015; Xu, 2008).

Consequences of procrastination

As a result of their procrastination behaviors, participants reported that they often miss their homework which frequently results in suspension from the class, and in further procrastination behaviors. Consistent with participants’ perspectives (see Figure 2), literature shows that the more students procrastinate, the more negative emotions they experience (e.g., Kliengsiek et al., 2013), and the lower the likelihood for homework completion (e.g., Xu, 2015), feelings of competence (e.g., Orpen, 1998), and low school grades (e.g., Kim & Seo, 2015). As Figure 2 shows, the lack of knowledge and competence emerges as either an antecedent or a consequence of procrastination. Participants reported they feel ‘stuck’ (P₁₅) in the procrastination ‘cobwebs’ (P₁₈). This aligns with prior findings that describe this ‘vicious circle of procrastination’ (Wäschle et al., 2014, p. 111). Contrary to teachers’ educational intentions, suspension from class deprives students from receiving feedback on their homework which is an important tool to maximize the benefits of homework (e.g., Cooper, 2001). Feedback is critical to help students become more engaged in their learning and improvement towards academic achievement (e.g., Núñez et al., 2015).

Regarding class suspension, a brief examination of the Mozambican school environment may help explain findings. Mozambican teachers, especially in rural areas with schools with poor infrastructures, may find it difficult to manage students' maladaptive homework behaviors or promote SRL strategies in large classes with an average of 70 students (see Fox et al., 2012). A large class can promote behaviors that both reflect and promote students' lack of involvement in class (e.g., high noise level in the class). School administrators may wish to reflect on educational measures to respond to this relevant constraint to teachers' practice because this aspect may be related to many students' educational problems.

In sum, findings add to the literature by proposing a model of adolescents' perspectives on the procrastination process (see Figure 2). Interestingly students' perspectives on academic procrastination are mainly focused on homework procrastination; teachers' behaviors of suspending students from the class do not seem to be helping diminish students' procrastination. Taken together, current findings could be useful for researchers and educational stakeholders to help intervene in academic procrastination.

Limitations and future research

Despite the strengths of the current study, some limitations can be acknowledged. The selectivity of informants (i.e., students with high reported academic procrastination) might be considered a limitation because it may confine the diversity of students’ perspectives (see Bakadorova & Raufelder, 2015). Moreover, because of this methodological selection of participants, gender was not balanced. Future studies could consider exploring the perspectives of boys and girls on the process of academic procrastination. Participants consented to be interviewed; however, interviews were short and in some cases laconic. Despite being concise, there is no evidence that these students gave polite, and socially desirable, answers. On the contrary, students were not distressed in the interviews, and participants voiced independent opinions (e.g., clear critics regarding the teachers ‘norm’ related to the suspension of students from class). For these reasons, present findings are not consistent with those by Jakobsen (2012) in Tanzania, which discouraged the use of interviews with African youth. In the current study, participants’ short statements could be due to their reported high academic procrastination, and low academic achievement. Notwithstanding, future research could consider adding to the interview methodologies likely to help students engagement in data collection (e.g., visual elicitation techniques, see Theron, 2016).

In general, it would be useful to investigate the graphical model of students' academic procrastination process (see Figure 2) in other cultures, domains, and school levels (e.g., elementary and middle school). Finally, the current study showed that the students' involvement in domestic chores is an important procrastination antecedent, so future studies could interview parents to further understand these behaviors. Moreover, in the current study, students reported that their suspension from the class contributes to reinforcing one of the antecedents of their procrastination (i.e. lack of knowledge). A prior study with college students found that teachers' characteristics (e.g., flexibility to deadlines) may be an antecedent to academic procrastination (Schraw et al., 2007). To acquire a broad picture of the procrastination process of Mozambican adolescents, their teachers could also be interviewed.

Finally, these findings could help decision makers implement policies aiming to increase the quality of the education in Mozambique (e.g., improve schools' infrastructures, the teachers' qualifications and hire school psychologists to work in the schools). School psychologists help students struggling with a variety of problems, such as procrastination behaviors, that hinder their successful learning. These professionals could organize school-based programs to promote SRL and work with teachers on their approaches to teaching to help improve students learning outcomes (Núñez et al., 2013; Rosário, Núñez, Ferrando et al., 2013).

Footnotes

Author's Note

Celso Fulano and Jennifer Cunha contributed equally in the authorship and should be listed as co-first authors.

Acknowledgements

Authors would like to thank Sofia Kirkman and Priya Kabaria for the English editing of the manuscript.

Declaration of Conflicting Interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This work was supported by Portuguese Foundation for Science and Technology and the Portuguese Ministry of Science (UID/PSI/01662/2013).

Author biographies

Celso Fulano finished his PhD in the Escola de Psicologia at Universidade do Minho, Portugal. He is an Assistant Professor at the Universidade Pedagógica, Moçambique and a research fellow of Camões - Instituto da Cooperação e da Língua , IP. His major research interests include academic procrastination and self-regulated learning of Mozambican students.

Jennifer Cunha is finishing her PhD in the Escola de Psicologia at Universidade do Minho, Portugal. Her major research interests include self-regulated learning, homework, parental homework involvement, and students' and teachers' conceptions of feedback.

José Carlos Núñez is full Professor in the Departamento de Psicologia at Universidade de Oviedo, Spain. He is the Director of the Department of Psychology and one of the Editors of Psicothema. His research interests include approaches to learning and learning strategies among secondary and university students.

Beatriz Pereira is a Graduate Student in the Educational Psychology Program at the Universidade do Minho. Her major research interests include self-regulated learning and school achievement of marginalized children.

Pedro Rosário is Associate Professor with tenure in the Escola de Psicologia at Universidade do Minho, Portugal. His research interests include students' self-regulation of their learning and procrastination. He runs projects to enhance self-regulation in Portugal, Brazil and Chile. He is the Director of the Research Centre (CiPsi) at the Escola de Psicologia.

References

Bakadorova

Raufelder

(2015) Perception of teachers and peers during adolescence: Does school self-concept matter? Results of a qualitative study. Learning and Individual Differences 43: 218–225. doi: 10.1016/j.lindif.2015.08.035.

Baker, S. E., & Edwards, R (2012). N. C. R. M. How many qualitative interviews is enough? National Center for Research Methods. Retrieved from http://eprints.ncrm.ac.uk/2273/.

Bardin

(1996) The content analysis, Paris: PUF.

Chu

A. H. C.

Choi

J. N.

(2005) Rethinking procrastination: Positive effects of ‘active’ procrastination behavior on attitudes and performance. The Journal of Social Psychology 145: 245–264. doi: 10.3200/SOCP.145.3.245-264.

Conselho, D. M. (2009). Estratégia do Ensino Secundário Geral 2009–2015 [General Higher Education Strategy 2009–2015].

Cooper

(2001) The battle over homework: Common ground for administrators, teachers, and parents, (2nd ed.). Thousand Oaks, CA: SAGE.

Cunha

Rosário

Macedo

Nunes

A. R.

Fuentes

Pinto

Suárez

(2015) Parents' conceptions of their homework involvement in elementary school. Psicothema 27: 159–165. doi: 10.7334/psicothema2014.210.

Fan

(2016) Investigating factors that influence students' help seeking in math homework: A multilevel analysis. Learning and Individual Differences 48: 29–35. doi: 10.1016/j.lindif.2016.03.002.

Dumont

Trautwein

Nagy

Nagengast

(2014) Quality of parental homework involvement: Predictors and reciprocal relations with academic functioning in the reading domain. Journal of Educational Psychology 106: 144–161. doi: 10.1037/a0034100.

10.

Eurydice (2012) key data nn education in Europe, Bruxelas: EACEA/Eurydice.. doi: 10.2797/81131.

11.

Fall

A. M.

Roberts

(2012) High school dropouts: Interactions between social context, self-perceptions, school engagement, and student dropout. Journal of Adolescence 35(4): 787–798. doi: 10.1016/j.adolescence.2011.11.004.

12.

Ferrari

J. R.

(2001) Procrastination as self-regulation failure of performance: Effects of cognitive load, self-awareness, and time limits on ‘working best under pressure’. European Journal of Personality 15(5): 391–406. doi: 10.1002/per.413.

13.

Ferrari

J. R.

Keane

S. M.

Wolfe

R. N.

Beck

B. L.

(1998) The antecedents and consequences of academic excuse-making: Examining individual differences in procrastination. Research in Higher Education 39(2): 199–215.

14.

Fox

Santibañez

Nguyen

André

(2012) Education reform in Mozambique: Lessons and challenges, World Bank Publications.

15.

Githua

B. N.

Mwangi

J. G.

(2003) Students' mathematics self-concept and motivation to learn mathematics: Relationship and gender differences among Kenya's secondary-school students in Nairobi and Rift Valley provinces. International Journal of Educational Development 23(5): 487–499. doi: 10.1016/S0738-0593(03)00025-7.

16.

Grunschel

Patrzek

Fries

(2013) Exploring different types of academic delayers: A latent profile analysis. Learning and Individual Differences 23: 225–233. doi: org/10.1016/j.lindif.2012.09.014.

17.

Hagger

M. S.

Sultan

Hardcastle

S. J.

Chatzisarantis

N. L.

(2015) Perceived autonomy support and autonomous motivation toward mathematics activities in educational and out-of-school contexts is related to mathematics homework behavior and attainment. Contemporary Educational Psychology 41: 111–123. doi: org/10.1016/j.cedpsych.2014.12.002.

18.

Jakobsen

(2012) Focus groups and methodological rigour outside the minority world: Making the method work to its strengths in Tanzania. Qualitative Research 12(2): 111–130. doi: 10.1177/1468794111416145.

19.

Jimerson

S. R.

(1999) On the failure of failure: Examining the association between early grade retention and education and employment outcomes during late adolescence. Journal of School Psychology 37(3): 243–272. doi: 10.1016/S0022-4405(99)00005-9.

20.

Katz

Eilot

Nevo

(2014) ‘I'll do it later’: Type of motivation, self-efficacy and homework procrastination. Motivation and Emotion 38(1): 111–119. doi: 10.1007/s11031-013-9366-1.

21.

Kim

K. R.

Seo

E. H.

(2015) The relationship between procrastination and academic performance: A meta-analysis. Personality and Individuals Differences 82: 26–33. doi: 10.1016/j.paid.2015.02.038.

22.

Klassen

R. M.

Kuzucu

(2009) Academic procrastination and motivation of adolescents in Turkey. Educational Psychology 29(1): 69–81. doi: 10.1080/01443410802478622.

23.

Klassen

R. M.

Ang

R. P.

Chong

W. H.

Krawchuk

L. L.

Huan

V. S.

Wong

I. Y. F.

Yeo

L. S.

(2009) A cross-cultural study of adolescent procrastination. Journal of Research on Adolescence 19: 799–811.

24.

Klassen

R. M.

Krawchuk

L. L.

Rajani

(2008) Academic procrastination of undergraduates: Low self-efficacy to self-regulate predicts higher levels of procrastination. Contemporary Educational Psychology 33(4): 915–931. doi: 10.1016/j.cedpsych.2007.07.001.

25.

Klingsieck

K. B.

(2013) Procrastination: When good things don't come to those who wait. European Psychologist 18(1): 24–34. doi: 10.1027/1016-9040/a000138.

26.

Klingsieck

K. B.

Grund

Schmid

Fries

(2013) Why students procrastinate: A qualitative approach. Journal of College Student Development 54(4): 397–412.

27.

Landis

J. R.

Koch

G. G.

(1977) The measurement of observer agreement for categorical data. Biometrics 33: 159–174.

28.

Lincoln

Y. S.

Guba

E. G.

(1985) Naturalistic inquiry, Beverly Hills, CA: SAGE.

29.

Milgram

N. A.

Tenne

(2000) Personality correlates of decisional and task avoidant procrastination. European Journal of Personality 14(2): 141–156.

30.

Mkhize

(2006) African traditions and the social, economic and moral dimensions of fatherhood. In: Richter

Morrell

(eds) Baba: Men and fatherhood in South Africa, Cape Town: HSRC Press, pp. 183–198.

31.

Murimo

A. E.

(2013) The influence of gender, parents and background factors on Grade 7 students' beliefs and attitudes towards mathematics in Mozambique. Perspectives in Education 31(2): 74–82.

32.

Núñez

Rosário

Vallejo

González-Pienda

(2013) A longitudinal assessment of the effectiveness of a school-based mentoring program in middle school. Contemporary Educational Psychology 38: 11–21. doi: org/10.1016/j.cedpsych.2012.10.002.

33.

Núñez

Suárez

Rosário

Vallejo

Cerezo

Valle

(2015) Teachers' feedback on homework, homework-related behaviors, and academic achievement. The Journal of Educational Research 108(3): 204–216. doi: 10.1080/00220671.2013.878298.

34.

Orpen

(1998) The causes and consequences of academic procrastination: A research note. Westminster Studies in Education 21(1): 73–75. doi: 10.1080/0140672980210107.

35.

Owens

A. M.

Newbegin

(1997) Procrastination in high school achievement: A causal structural model. Journal of Social Behavior and Personality 12(4): 869–887.

36.

Owens

A. M.

Newbegin

(2000) Academic procrastination of adolescents in English and mathematics: Gender and personality variations. Journal of Social Behavior and Personality 15(5): 111.

37.

Pychyl

T. A.

Lee

J. M.

Thibodeau

Blunt

(2000) Five days of emotion: An experience sampling study of undergraduate student procrastination. Journal of Social Behavior and Personality 15: 239–254.

38.

Pychyl

T. A.

Morin

R. W.

Salmon

B. R.

(2000) Procrastination and the planning fallacy: An examination of the study habits of university students. Journal of Social Behavior and Personality 15: 135–150.

39.

Richards

(2005) Handling qualitative data: A practical guide, London: SAGE.

40.

Rosário

Costa

Núñez

J. C.

González-Pienda

J. A.

Solano

Valle

(2009) Academic Procrastination: Associations with personal, school, and family variables. Spanish Journal of Psychology 12(1): 118–127.

41.

Rosário

Núñez

J. C.

Ferrando

Paiva

Lourenço

Cerezo

Valle

(2013) The relationship between approaches to teaching and approaches to studying: A two-level structural equation model for biology achievement in high school. Metacognition and Learning 8: 44–77. doi: 10.1007/s11409-013-9095-6.

42.

Rosário

Núñez

J. C.

Vallejo

Cunha

Nunes

Mourão

Pinto

(2015) Does homework design matter? The role of homework's purpose in student mathematics achievement. Contemporary Educational Psychology 43: 10–24. doi: 10.1016/j.cedpsych.2015.08.001.

43.

Rosário

Núñez

Valle

González-Pienda

Lourenço

(2013) Grade level, study time, and grade retention and their effects on motivation, self-regulated learning strategies, and mathematics achievement: A structural equation model. European Journal of Psychology of Education 28: 1311–1331. doi: 10.1007/s10212-012-0167-9.

44.

Ryan

Deci

E. L.

(2000) Intrinsic and extrinsic motivations: Classic definitions and new directions. Contemporary Educational Psychology 25: 54–67. doi: 10.1006/ceps.1999.1020.

45.

Samoff

(1999) Education sector analysis in Africa: Limited national control and even less national ownership. International Journal of Educational Development 19: 249–272. doi: 10.1016/S0738-0593(99)00028-0.

46.

Schraw

Wadkins

Olafson

(2007) Doing the things we do: A grounded theory of academic procrastination. Journal of Educational Psychology 99(1): 12–25. doi: 10.1037/0022-0663.99.1.12.

47.

Senécal, C., Julien, E., & Guay, F. (2003). Role conflict and academic procrastination: A self-determination perspective. European Journal of Social Psychology, 33, 135–145.

48.

Steel

(2007) The nature of procrastination: A meta-analytic and theoretical review of quintessential self-regulatory failure. Psychological Bulletin 133(1): 65–94.

49.

Taímo, N. V. (2015). Keeping Girls in School: Building the capacity of the women and education association in Mozambique. Oxfam Novib.

50.

Theron, L. (2016). Researching resilience: lessons learned from working with rural, Sesotho-speaking South African young people. Qualitative Research, 1–18. doi: 10.1177/1468794116652451.

51.

UNICEF (2016) Harnessing the power of data for girls: Taking stock and looking ahead to 2030, New York: UNICEF.

52.

Van Nes

Abma

Jonsson

Deeg

(2010) Language differences in qualitative research: Is meaning lost in translation?. European Journal of Ageing 7(4): 313–316. doi: 10.1007/s10433-010-0168-y.

53.

Virtanen, P., & Ehrenpreis, D. (2007). Growth, poverty and inequality in Mozambique (No. 10). International Policy Centre for Inclusive Growth.

54.

Vos

Devesse

T. G.

Pinto

A. A. R.

(2007) Designing mathematics lessons in Mozambique: Starting from authentic resources. African Journal of Research in Mathematics, Science and Technology Education 11(2): 51–66. doi: 10.1080/10288457.2007.10740621.

55.

Warren

C. A. B.

(2002) ‘Qualitative Interviewing’. In: Gubrium

J. F.

Holstein

J. A.

(eds) Handbook of interview research: Context and method, Thousand Oaks, CA: SAGE.

56.

Wäschle

Allgaier

Lachner

Fink

Nückles

(2014) Procrastination and self-efficacy: Tracing vicious and virtuous circles in self-regulated learning. Learning and Instruction 29: 103–114.

57.

(2008) Models of secondary school students' interest in homework: A multilevel analysis. American Educational Research Journal 45(4): 1180–1205. doi:10.3102/0002831208323276.

58.

(2015) Investigating factors that influence conventional distraction and tech-related distraction in math homework. Computers and Education 81: 304–314. doi:10.1016/j.compedu.2014.10.024.

59.

Corno

(2003) Family help and homework management reported by middle school students. The Elementary School Journal 103(5): 503–517.

60.

Fan

(2015) Homework distraction scale confirming the factor structure with middle school students. Journal of Psychoeducational Assessment. 1–15. doi: 10.1177/0734282915620900.

61.

Benson

S. N. K.

Mudrey-Camino

Steiner

R. P.

(2010) The relationship between parental involvement, self-regulated learning, and reading achievement of fifth graders: A path analysis using the ECLS-K database. Social Psychology of Education 13(2): 237–269. doi: 10.1007/s11218-009-9104-4.

62.

Zimmerman

B. J.

Bandura

Martinez-Pons

(1992) Self-motivation for academic attainment: The role of self-efficacy beliefs and personal goal setting. American Education Research Journal 29: 663–676.