Psychology is a contemporary science. Listed below are several recent papers. For the first part of this assignment, choose

Investigating grit and its relations with college students’ self-regulated learning and academic achievement

Christopher A. Wolters & Maryam Hussain

Received: 9 May 2014 /Accepted: 4 November 2014 /Published online: 18 November 2014 # Springer Science+Business Media New York 2014

Abstract We investigated grit and its relations with students’ self-regulated learning (SRL) and academic achievement. An ethnically diverse sample of 213 college students completed an online self-report survey that included the Grit Short scale (Duckworth and Quinn Journal of Personality Assessment, 91(2), 166–174, 2009), seven indicators of SRL and their past and present academic achievement. Results indicated that one aspect of grit, perseverance of effort, was a consistent and adaptive predictor for all indicators of SRL including value, self-efficacy, cognitive, metacognitive, motivational, time and study environment management strategies, and procrastination. A second aspect of grit, consistency of interest, was associated only with the latter two facets of SRL. Perseverance of effort predicted achievement before, but not after, accounting for SRL; hence, students’ engagement in SRL may serve as a mediating pathway through which this aspect of grit is associated with improved academic outcomes. In contrast, consistency of interest showed no relation to achievement. Implications of the findings for additional research and instruction are discussed.

Keywords Grit . Self-regulated learning . Motivation . Strategies . Procrastination .

Achievement . Postsecondary

Over the past 25 years, self-regulated learning (SRL) has emerged as a major framework used to understand, evaluate, and improve students’ functioning within academic contexts (Schunk and Zimmerman 2008). Individual differences characterized by many as more stable or trait- like, including personality, intelligence, and achievement motives, also have been investigated repeatedly as an important influence on students’ academic functioning (Diseth, and Kobbeltvedt 2010; Komarraju et al. 2009; Richardson et al. 2012). Studies integrating these two perspectives indicate that accounting for both SRL and more stable individual differences may provide for a better understanding of students’ academic performance than either one does alone (Bidjerano and Dai 2007; De Feyter et al. 2012; Eilam et al. 2009; Richardson and

Metacognition Learning (2015) 10:293–311 DOI 10.1007/s11409-014-9128-9

C. A. Wolters (*) Department of Educational Studies, Dennis Learning Center, 250 Younkin, The Ohio State University, Columbus, OH 43201-2333, USA e-mail: [email protected]

M. Hussain Department of Educational Psychology, University of Houston, Houston, TX 77204, USA

Abraham 2009). In the present study, we advance this area of research by investigating the relation of grit, SRL and academic achievement. Although grit is considered distinct from other personal traits and has proven useful for explaining academic outcomes (Duckworth and Quinn 2009; Maddi et al. 2012; Strayhorn 2013), the relation of grit and SRL has not yet been investigated. The present study addresses this gap by exploring whether grit can be used to predict seven indicators of college students’ engagement in SRL, and whether grit and SRL together can be used to understand students’ academic achievement.

Grit

Grit is defined as a person’s trait-level perseverance and passion for long-term goals (Duckworth et al. 2007). As such, grit has been conceived as a stable characteristic or disposition of the individual that, similar to traditional personality traits, influences his/her attitudes and behavior across diverse contexts (Duckworth and Quinn 2009; Kleiman et al. 2013; Reed et al. 2013). Compared to their less gritty peers, individuals with higher levels of grit are expected to exhibit greater persistence in the pursuit of their goals despite setbacks, distractions, or other forms of interference. Within educational contexts, grit is portrayed as a potentially important influence on outcomes such as students’ engagement, achievement level, retention and probability of graduation (Duckworth and Quinn 2009; Maddi et al. 2012; Strayhorn 2013).

Although still quite limited, the research examining grit indicates that it can be measured reliably and that it is empirically distinct from other trait-like individual differences. In particular, Duckworth and colleagues (2007) developed an initial self-report measure of grit and provided some evidence that it was different than traditional personality constructs such as conscientiousness. Although analyses with adults suggested that it consisted of two related dimensions, these researchers examined grit using a single 12-item scale. Based on samples from several distinct populations, these researchers showed that this broad indicator of grit was related positively to educational attainment, college grades, self-control, retention within a rigorous military training program, and adolescents’ performance in a competitive national spelling bee.

Adding to this research, Duckworth and Quinn (2009) developed a shorter 8-item self- report survey based on a subset of the original grit items. Re-evaluation of data from the participants in Duckworth et al. (2007) with this smaller set of items as well as an additional sample of adults indicated that grit was best modeled as two first-order latent factors that also loaded on to one second-order latent factor. One of the first-order factors, titled consistency of interest, reflected participants’ reported tendency to adhere to particular goals over longer periods of time. The second first-order latent factor, termed perseverance of effort, represented participants’ reported tendency to sustain the time and energy necessary for accomplishing long term tasks even in the face of distractions. Despite the distinction between these factors, Duckworth and Quinn utilized a single 8-item indicator of grit in several additional studies with adolescents, military cadets and adults. Overall, Duckworth and Quinn replicated many of the earlier findings from Duckworth et al. (2007) including the independence of grit from aspects of personality, and its positive relation to academic success, retention within a rigorous military training program, and ranking in a national spelling bee. They also found that the single short measure of grit was relatively stable across the span of one year among adolescents.

Recent contributions from other researchers tend to confirm the view of grit as a potentially important influence on aspects of individual’s persistence and performance, including within

294 C.A. Wolters, M. Hussain

academic contexts. Maddi et al. (2012), for instance, found that a singular indicator of grit was a strong predictor of retention and performance in sample of military cadets. Higher levels of a general measure of grit have also been linked to increased intensity of exercise (Reed et al. 2013) and reduced suicide ideation (Kleiman et al. 2013). In a sample of high school students, MacCann and Roberts (2010) found that both dimensions of grit, but especially the persever- ance of effort, were positively correlated with life satisfaction, multiple aspects of conscien- tiousness and teacher’s rating of social behavior, but not to grades or academic readiness. Finally, Strayhorn (2013) found that an overall indicator of grit was a positive predictor of self- reported grades among African-American males attending a university with a predominantly White student population. In this study, grit was a stronger predictor of college grades than high school GPA and other standardized college entrance exams.

Summing across this work, grit appears to represent a compound personal characteristic that is associated with students’ tendency to be successful within achievement contexts. The evidence linking grit specifically to students’ academic achievement, however, is still very limited and somewhat inconsistent. For instance, the two studies that examined the relation of grit with students’ course grades produced conflicting results (MacCann and Roberts 2010; Strayhorn 2013). Further, the pathways through which this impact may be realized have not yet been examined. In particular, the possibility that grit is associated with increased engage- ment in SRL has not been investigated.

Self-regulated learning

SRL is understood generally to be the process through which students take an active, purposeful role in managing motivational, cognitive and behavioral aspects of their own learning (Pintrich 2004; Zimmerman 2000). This management is accomplished through students’ engagement of various sub-processes that include goal setting, activation of relevant prior knowledge, progress monitoring, engagement and regulation of learning strategies, and reflection (Pintrich 2004; Winne and Hadwin 1998). Across these various sub-processes, two consistently critical components of SRL reflect students’ motivation and their engagement and use of different cognitive and regulatory strategies.

Motivation

SRL is an effortful process that involves the activation and use of substantial cognitive and metacognitive resources. Hence, motivation is viewed as an important facet of what it takes to engage in SRL (Pintrich and Zusho 2002; Winne and Hadwin 2008; Zimmerman and Schunk 2008). The forms of motivation that have been incorporated into models of SRL are diverse with no clear hegemony (Schunk and Zimmerman 2008). For instance, models of SRL have highlighted the roles of goal setting, achievement goals, interest, value, perceived self-efficacy and attributions (Pintrich and Zusho 2002; Winne and Hadwin 2008). The focus in this study is on two aspects of achievement motivation, perceived self-efficacy and value, which consis- tently have been used within models of SRL (Pintrich and Zusho 2002; Zimmerman 2000). Self-efficacy, defined as students’ beliefs about whether they are capable of successfully reaching particular learning goals, has been intricately linked to their goal setting, choice and effort within academic contexts (Linnenbrink and Pintrich 2003; Pajares 1996; Zimmerman 2000). As well, students who report higher levels of self-efficacy have been found to exhibit increased use of the cognitive and metacognitive strategies central to SRL. Even when examined outside the framework of SRL, self-efficacy has proven to be an

Grit and self-regulated learning 295

important predictor of success, retention, and performance within college student populations (Richardson et al. 2012; Robbins et al. 2004).

Students’ value for the material they are learning is also a key form of motivation within many models of SRL (Pintrich and Zusho 2007; Wigfield and Cambria 2010). Value is a multi- dimensional construct that can incorporate students’ personal interest, importance, usefulness, and aspects of situational interest (Wigfield and Eccles 2000). In general, students who perceive the materials or skills they are learning as useful, interesting, important or enjoyable are more likely to engage the regulatory strategies necessary for SRL and evidence higher academic achievement (Pintrich and Zusho 2007; Wigfield and Cambria 2010).

Strategy use

From its inception, the activation and effective use of strategies that promote learning, understanding and achievement has been a hallmark of what it means to engage in SRL (Pintrich 2004; Winne and Hadwin 1998; Zimmerman 2000). Although cognitive and metacognitive learning strategies have been examined most commonly, researchers recognize that other types of strategies are also critical to successful SRL (Pintrich 2004; Wolters 2003a). Consistent with this view, we assess four distinct types of strategies that reflect adaptive aspects of SRL including cognitive, metacognitive, motivational, and time and study environ- ment management.

Generally, cognitive strategies are understood to include different tactics that students use to facilitate the encoding and storage of the material they are supposed to learn (Weinstein et al. 2011). For instance, cognitive strategies include efforts to rehearse, elaborate, or organize material one is trying to learn. Closely linked to these, metacognitive strategies include students’ efforts to plan, select, monitor, evaluate and, when necessary, modify or regulate their use of learning strategies (Pintrich et al. 2000). Motivational regulation strategies represent students’ efforts to control their own level of motivation or motivational processing (Wolters 2003a). This type of strategy, including self-consequating, self-talk about goals, and making learning tasks more enjoyable, are thought to be particularly important when students are facing obstacles to their continued engagement and effort on academic tasks (Wolters 1998, 2003a). Time management and control of the learning environment also represent important self-regulatory skills (Pintrich 2004; Zimmerman et al. 1994). These more behavioral strate- gies reflect students’ efforts to control when and where they study including the use of planners, to-do lists, and well-organized study spaces.

Overall, there is compelling evidence that the use of SRL strategies is associated positively with students’ achievement within academic contexts. The evidence for this connection is strongest for students’ use of cognitive and metacognitive strategies (Pintrich and Zusho 2007). Research also shows that college students have a repertoire of motivational regulation strategies and that use of these strategies is associated with increased effort, persistence, and academic performance (Schwinger et al. 2009; Wolters 1998). Although not always conducted using a SRL framework, there is also ample research showing that students who report greater time management tend to get better grades (Claessens et al. 2007; Kitsantas et al. 2008; Macan et al. 1990).

Procrastination

We investigate procrastination as a reflection of students’ ability to effectively self-regulate their learning. Procrastination can be defined as students’ delay of tasks or decisions that are necessary and will eventually be completed (Steel 2007). Although studied through many

296 C.A. Wolters, M. Hussain

theoretical perspectives, procrastination repeatedly has been portrayed as a failure of effective self-regulation (Steel 2007; Wolters 2003b). Consistent with this view, procrastination by students within academic settings has been associated with lowered academic performance (Schouwenburg et al. 2004). Procrastination also has been linked to maladaptive outcomes such as reduced sense of well-being, depression, stress and fatigue (Schraw et al. 2007; Steel 2007). At the same time, studies have consistently found that procrastination is prevalent among college student populations with some estimates indicating that over 75 % of students reporting that they procrastinate regularly (Ferrari et al. 2007; Schraw, et al. 2007; Steel 2007).

Grit and self-regulated learning

According to Pintrich (2004), one assumption consistent within most models of SRL is that SRL processes serve as a mediator between students’ personal and background characteristics and their performance within particular contexts. Dispositions, personality traits, or other stable individual differences such as grit are, therefore, commonly viewed as precursors or potential influences on the attitudes, beliefs, cognitive processes, and behaviors that embody SRL (Bidjerano and Dai 2007; Eilam et al. 2009; Komarraju et al. 2009). In line with this assumption, one would expect that aspects of grit could be used to explain college students’ motivation and use of strategies emblematic of SRL. Up to this point, however, no published empirical research has investigated these theoretical links directly. Duckworth et al. (2010) did find that grit was a positive predictor of the deliberate and more effortful forms of practice reported by contestants preparing for a national spelling bee. This study, however, did not assess any of the specific strategies used during the practice time and was focused on early adolescents engaged in an extra-curricular activity. The overall goal of the present study was to address this major gap in prior research by examining the relations between aspects of grit and college students’ SRL as represented by measures of their value, self-efficacy, reported use of four types of learning strategies, and procrastination.

Despite the lack of studies examining grit and SRL directly, research investigating similar trait-like individual differences supports the need to investigate these relations. Based on the five-factor model of personality, for instance, greater conscientiousness among college stu- dents tends to be associated with higher levels of academic motivation and especially self- efficacy or perceived competence (De Feyter et al. 2012; Komarraju et al. 2009; Richardson and Abraham 2009). As well, college students who are more conscientious also tend to report increased use of some learning strategies typical of SRL (Bidjerano and Dai 2007). Given its association with attributes such as diligence, dependability, organization, punctuality, careful- ness and self-control, conscientiousness also has been linked to lower levels of procrastination (vanEerde 2004). Although not found in every case (Trautwein et al. 2009), several studies have concluded that the influence of conscientiousness and other personality traits on students’ achievement is mediated by their motivation and use of regulatory strategies (Bidjerano and Dai 2007; De Feyter et al. 2012; Eilam et al. 2009; Richardson and Abraham 2009).

Achievement motives represent another type of trait or stable disposition that has been used to understand students’ academic functioning (Bartels et al. 2010; Diseth and Martinsen 2003). Motives linked to wanting to achieve success and to avoid failure both have been used to explain more context specific aspects of students’ motivation, especially their achievement goals (Bartels et al. 2010; Chen et al. 2009; Conroy and Elliot 2004; Elliot and Church 1997; Elliot and McGregor 2001; Elliot and Murayama 2008; Michou et al. 2013). Likewise, approach motives have been associated positively with self-reported engagement and the use of deep, metacognitive or other adaptive types of strategies emblematic of SRL (Bartels and

Grit and self-regulated learning 297

Magun-Jackson 2009; Bartels et al. 2010; Diseth and Kobbeltvedt 2010; Diseth and Martinsen 2003; Michou et al. 2013). In contrast, fear of failure or other avoidance motives have been associated with performance-avoidance goals and test anxiety, along with decreased use of adaptive strategies (Bartels et al. 2010), increased use of surface strategies (Diseth and Kobbeltvedt 2010; Diseth and Martinsen 2003), and increased levels of self-handicapping, procrastination, and other indicators of poor self-regulation (Chen et al. 2009). Finally, studies also show that the relations of achievement motives to students’ academic performance may be mediated by more situational forms of motivation and engagement (Diseth and Kobbeltvedt 2010; Diseth and Martinsen 2003; Elliot and Church 1997; Elliot and Murayama 2008).

Research questions

In sum, individual differences similar to grit have been linked to several indicators of students’ SRL such as their motivation, use of learning strategies, and procrastination. Research investi- gating these relations with regard to grit, however, is absent. We address this gap in prior work via four related research questions. One, is grit related to college students’ value and self-efficacy? Given its basic conceptual definition as well as past research with conscientiousness and achievement motives, we expected that grit would be associated positively with both of these adaptive motivational beliefs and attitudes. Two, is grit related to more strategic aspects of students’ SRL including their use of different regulatory strategies and level of academic procrastination? We expected that grit would be a positive predictor of students’ use of regulatory strategies and negatively associated with their self-reported procrastination. Three, is grit related to college students’ academic achievement? Although the evidence of this connection is not entirely consistent, we anticipated that grittier students would tend to get better grades. Finally, do the motivational and strategic aspects of SRL mediate the relation between grit and students’ academic performance? Given findings with other types of individual differences, we expected that aspects of SRL may also mediate any relation between grit and students’ grades.

Method

Participants

The 213 participants for this study came from a large and diverse public university. The students were primarily female (n=188, 88 %), and self-reported their race/ethnicity as African-American (n=45, 21 %), Asian/Pacific Islander (n=53, 25 %), Hispanic (n=62, 29 %), White (n=43, 20 %), or Other (n=10, 5 %). The academic rank reported by the participants included freshman (n=28, 13 %), sophomore (n=51, 24 %), junior (n=74, 35 %), and seniors or post-baccalaureate (n=60, 28 %).

Procedures

Participants were recruited through a subject pool associated with multiple undergraduate psychology and educational psychology courses. Students in these courses had access to an electronic list with short descriptions for the studies that could be used to satisfy requirements for participation in research. Students who elected to volunteer for the present study clicked on a link that took them first to a consent document and, if approved, to the actual survey. Surveys were completed during the final two weeks of the autumn semester before the final exam period.

298 C.A. Wolters, M. Hussain

Measures

The primary instrument was an online self-report survey with a total of 136 items. Only data from 78 items related to demographics, grit, achievement motivation, strategy use, procrasti- nation and academic performance were used in the present study. Other than the demographics and performance sections, all items used Likert-styled items with a response scale ranging from 1 (not at all true of me) to 5 (very true of me).

Grit Participants completed the eight-item Grit Short scale (Duckworth and Quinn 2009). In line with Duckworth and Quinn, a confirmatory factor analysis with the current sample indicated that a measurement model with two first-order latent factors fit the data well (χ2

(19, N=213) =20.04, p=.392; RMSEA=.02 (90 % confidence interval [CI]=.00, .06), CFI=.997). In contrast, alternative models that reflected all items in one general factor (χ2

(20, N=213) =125.756, p<.001; RMSEA=.16 (90 % CI=.13, .19), CFI=.645) or that included a second order general factor (χ2 (36, N=213) =333.81, p<.001; RMSEA=.20 (90 % CI=.18, .22), CFI=.000) did not fit the data well. Given these findings and consistent with prior work with this scale (Duckworth and Quinn 2009), we constructed separate scales representing the two first order factors based on the mean of the relevant items. Perseverance of effort reflected students’ self-reported tendency to sustain the time and energy necessary for accomplishing long-term tasks. Consistency of interest represented students’ self-reported tendency to stick with particular goals over longer periods of time. Items for these scales included “I finish whatever I begin.” (Perseverance of effort), and “I often set a goal but later choose to pursue a different one” (Consistency of effort, reverse coded). Coefficient alphas for each of the scales, as well as all those described below are presented in Table 1.

Motivation Motivation was measured using 11 items modified to assess students’ beliefs and attitudes regarding school or learning in general rather than a specific course (Pintrich et al. 1993; Wolters 2003b). Six items represented value, or the extent that students perceived coursework as useful, interesting, and important. Five items reflected self-efficacy, or how confident students felt about their ability to learn and successfully complete their coursework.

Strategy use and procrastination Using modified items from Pintrich et al. (1993) and Wolters (2003b; Wolters and Benzon 2013) to refer to learning or coursework in general, four types of self-regulatory strategies were assessed. Cognitive strategies measured participants’ reported use of rehearsal, elaboration and organization strategies to complete academic tasks (9 items). Metacognitive strategies measured participants’ reported use of techniques for planning, monitoring, and managing their learning strategies (9 items). Time and study environment management reflected the extent to which students believed they used effective strategies for academic scheduling and regulating where they studied (8 items). Motivational strategies measured participants’ reported use of strategies for managing their level of motivation and their effort at particular academic tasks (14 items). Finally, procrastination was assessed by adapting the 12 items from the Pure Procrastination Scale (Steel 2010) to refer to academic contexts. These items measured students’ reported tendency to delay making decisions, begin tasks, or miss deadlines for their academic work. As shown in Table 1, all of the motivation, strategy use, and procrastination scales had moderate to high levels of internal consistency.

Academic performance Prior achievement was based on a single item on which students reported their cumulative high school grade point average (HSGPA). Although not ideal, self- reported grade point average is a widely used measure of academic performance and has

Grit and self-regulated learning 299

T ab

le 1

M ea n s, st an da rd

de vi at io n s, an d bi v ar ia te co rr el at io ns

fo r gr it , se lf -r eg ul at ed

le ar ni ng , an d ac h ie v em

en t va ri ab le s

1 2

3 4

5 6

7 8

9 10

11

1 . C on si st en cy

of in te re st

–

2 . P er se ve ra nc e of

ef fo rt

.1 2

–

3 . V al u e

.0 3

.3 8

–

4 . S el f- ef fi ca cy

.0 3

.4 1

.5 7

–

5 . C og ni ti ve

st ra te gi es

.0 7

.4 5

.4 4

.4 6

–

6. M et ac og ni ti ve

st ra te gi es

.0 8

.5 1

.4 4

.4 4

.8 3

–

7. M ot iv at io na l st ra te gi es

.0 4

.5 1

.5 0

.4 2

.6 9

.7 1

–

8 . T im

e &

st ud y en vi ro nm

en t m an ag em

en t st ra te gi es

.2 7

.5 5

.4 2

.3 2

.6 1

.6 5

.6 1

–

9. P ro cr as ti na ti on

−. 36

−. 49

−. 28

−. 23

−. 3 5

−. 4 1

−. 3 9

−. 6 7

–

1 0.

P ri or

ac hi ev em

en t

−. 12

.0 9

.1 1

.1 9

.1 1

.0 9

.0 9

.0 9

−. 10

–

11 . C ur re nt

ac hi ev em

en t

.1 0

.2 9

.2 0

.2 6

.2 2

.2 4

.2 4

.4 1

−. 41

.2 8

–

A lp ha

.7 4

.6 4

.8 4

.8 7

.8 0

.8 3

.9 0

.7 7

.9 2

– –

n 21 3

21 3

21 3

2 13

2 13

2 13

2 13

21 3

21 3

21 3

21 1

M 2. 84

3. 50

3. 78

3. 79

3. 5 3

3. 5 1

3. 6 1

3. 3 4

2 .9 4

6 .3 2

3. 34

S D

0. 57

0. 72

0. 78

0. 75

0. 6 8

0. 7 2

0. 7 5

0. 7 1

0 .9 0

2 .1 5

0. 48

N o te : r≥

.2 0,

p < .0 1 ; r≥

.2 4 , p < .0 01

300 C.A. Wolters, M. Hussain

shown a high correlation with actual grade point average (Caskie et al. 2014; Kuncel et al. 2005). Simple mean imputations were used to replace the missing observations for nine students who did not respond or indicated that they did not know their HSGPA. The eight response options for this item were based on 0.25 GPA increments from 8 (4.00–3.76) to 1 (2.00 or below). Current achievement was based on three separate items on which students reported the number of courses they were currently taking in which they expected to earn 1) an A, 2) a B or C, and 3) a D or lower. Responses to these items were combined to create one five- level variable with higher scores representing better expected grades in the courses they were taking the semester the survey was completed. Students with the top score (i.e., a 5) reported that they expected to receive an “A” in all of their courses. Students with scores of 4 and lower reported that they were expecting an increasingly larger number of B and C, or D and lower grades.

Results

Results are divided into two sections. First, we present descriptive information and bivariate correlations among the major variables. Second, we discuss findings from three sets of multiple regressions.

Descriptives and correlations

The means and standard deviations for the grit, SRL and achievement variables are presented in Table 1. The mean for perseverance of effort appeared somewhat higher (M=3.5) when compared to the mean for consistency of interest (M=2.84). Consistent with previous studies using similar scales with college populations (Wolters 2003b), all of the means for the SRL variables fell near the middle of the response scale.

The bivariate correlations among the grit, SRL and achievement measures are also pre- sented in Table 1. Most noteworthy among these results is the low correlation between the two aspects of grit, as well as the distinctive pattern of relations each had with the SRL and achievement measures. Perseverance of effort was positively correlated with both value and self-efficacy, as well as with each of the …

INVITED EDITORIAL: Let's Do It Again: A Call for Replications in Psi Chi J o u rn a l o f Psychological Research J o h n E. E d lu n d R o c h e s te r In s titu te o fT e c h n o lo g y

S c ie n c e is said to b e su ffe rin g fro m a crisis o f r e p li c a b i li t y ( I o a n n i d is , 2 0 0 5 ). T h is crisis o c c u rs w h e n s c ie n tific s tu d ie s fail

to b e s u p p o r te d by s u b s e q u e n t re s e a r c h . T h e challenges posed by th e replication crisis address the fundam ental n atu re o f science an d the p ublic’s u n d e r s t a n d i n g o f it. N u m e r o u s c o n t r i b u t i n g reasons for th e rep licatio n crisis have b e e n n o ted in c lu d in g d a ta fa lsific a tio n (S te e n , 2 0 1 1 ), th e pressures o f ten u re an d p ro m o tio n (Varian, 1998), questionabl

---

---

Who We Are

We are a professional custom writing website. If you have searched a question and bumped into our website just know you are in the right place to get help in your coursework.

Do you handle any type of coursework?

Yes. We have posted over our previous orders to display our experience. Since we have done this question before, we can also do it for you. To make sure we do it perfectly, please fill our Order Form. Filling the order form correctly will assist our team in referencing, specifications and future communication.

Is it hard to Place an Order?

1. Click on the “Place order tab at the top menu or “Order Now” icon at the bottom and a new page will appear with an order form to be filled.

2. Fill in your paper’s requirements in the "PAPER INFORMATION" section and click “PRICE CALCULATION” at the bottom to calculate your order price.

3. Fill in your paper’s academic level, deadline and the required number of pages from the drop-down menus.

4. Click “FINAL STEP” to enter your registration details and get an account with us for record keeping and then, click on “PROCEED TO CHECKOUT” at the bottom of the page.

5. From there, the payment sections will show, follow the guided payment process and your order will be available for our writing team to work on it.

Need this assignment or any other paper?

Click here and claim 25% off
Discount code SAVE25