Our intuition, and perhaps our experience, suggests that study time should be positively associated with grades. However, the study time-grade association literature has provided inconsistent findings: some researchers have found a positive association, others a negative association, and yet others no association between study time and grades. The present research sought to better understand the nature of the study time-grade association by examining the effects of student, teacher and course characteristics on study time, grades, and the study time-grade association. Results show that study time and grades were inversely associated (r = -.19). Regression analyses indicate that grade inflation was the best predictor of study time; that is, as grade inflation increased study time decreased. Course difficulty was the best predictor of grades; as perceptions of course difficulty increased expected grades decreased. And, course difficulty, grade inflation and student cognitive ability moderated the study time-grade association. Thus, data suggest that the study time-grade association may be spurious. Implications for future research are discussed.
Keywords: study time-grade association, spurious, moderators, motivation, facilitating conditions
The study time-grade literature is scant (Rau & Durand, 2000) and inconsistent (Schuman, Walsh, Olson, & Etheridge, 1985). Early research found a small to moderate positive association between study time and grades (Allen, Lerner, & Hinrichsen, 1972, r = .23; Hinrichsen, 1972, r = .32; Wagstaff & Mahmoudi, 1976, r = .31). More recently, Schuman et al. (1985), in a number of studies conducted from 1973-1984 at the University of Michigan, found that study time was not predictive of grade point average (GPA). Rau and Durand (2000) suggest that the null findings of Schuman et al. (1985) can be attributed to the selectivity of the University of Michigan “that conspires against prediction models” (p. 21). That is, highly selective institutions have very capable student bodies with homogeneously high college GPAs and therefore a restricted range on the criterion. The selectivity hypothesis, however, does not explain the inverse study time-grade association found by Greenwald and Gillmore (1997). Greenwald and Gillmore (1997), in a study of 594 courses across the 1993 - 1994 academic year at the University of Washington, found an inverse association between study time and grades, r = - .15 (p < .005). However, Rau and Durand (2000), with a sample of 252 students at Illinois State University in the spring of 1992, found a positive association between academic ethic and GPA, r = .24. Academic ethic is a broad concept that includes study time, study habits, and academic orientation. Thus, it is not clear whether study time or the other components of the academic ethic are predictive of GPA.
In short, previous research has provided an inconsistent pattern of associations between study time and grades, but little understanding of why these patterns exist. Although sample differences may explain some of the differences in the findings, essentially three explanations have been provided for why the differences exist. One explanation is that study time is, indeed, positively associated with grades; that is, the association is genuine (e.g., Allen et al., 1972; Hinrichsen, 1972; Rau & Durand, 2000; Wagstaff & Mahmoudi, 1976). Schuman et al. (1985) suggest another explanation: “Hours studied may have little effect on grades for the simple reason that most instructors may grade largely on the basis of the material they provide or at least emphasize in lectures” (p. 962). Greenwald and Gillmore (1997) suggest a third explanation: The inverse association between study time and grades can be explained by grade inflation.
Thus, some researchers suggest that the study time-grade association is genuine. Other researchers suggest that the study time-grade association is potentially spurious; that is, there are confounding variables that explain the association (e.g., Greenwald and Gillmore 1997; Schuman et al., 1985). Greenwald and Gillmore (1997) and Schuman et al. (1985), for example, suggest that the study time-grade association is moderated by teacher characteristics. In general, Baron and Kenny (1986) suggest that moderator variables are most likely operating when there is an unexpectedly weak or inconsistent association between a predictor (e.g., study time) and a criterion (e.g., grades) or when an association holds in one setting but not another (e.g., non-selective institutions vs. very selective institutions). The primary goal of the present research is to reexamine the study time-grade association to better understand the nature of this relationship. Central to this examination is an exploration of the predictors of study time and expected grades, as well as the moderators of the study time-grade association.
Rau and Durand (2000) lament that only a few small-scale studies have examined the role students play in their academic work; nonetheless, student characteristics have been acknowledged as the primary determinants of study time and grades. This stands to reason considering the traditional model used to describe the study time-grade association: study time---->grades. Thus, the traditional model is student-centered whereby study time has been conceptualized as antecedent to, and a cause of, grades. Schuman et al. (1985) suggest that there is a widespread and untested assumption that grades reflect study time; that is, academic success is driven by laborious study.
Grades may reflect study time, but study time may also reflect grades. For example, minimal study time met with relatively low grades would suggest that study efforts need to be increased. Conversely, minimal study met with relatively high grades would suggest that there is little need to increase study efforts. It is also possible that study time and grades may be a function of other variables. For example, research suggests that students study more in difficult classes than easy classes, and in classes where teachers are demanding as opposed to lenient (Greenwald & Gillmore, 1997, 1998). Thus students may seek a satisfactory balance between study time and grades, whereby study time and grades may be influenced not only by student characteristics (e.g., cognitive ability), but also course (e.g., difficulty) and teacher charcteristics (e.g., grade inflation and teacher effectiveness). In short, student, course and teacher characteristics are expected to be predictive of study time and grades, and also moderate the study time-grade association. In this article, a moderator will be defined in general terms; that is, a quantitative or qualitative variable that affects the direction and/or strength of an association between an independent and dependent variable (Baron & Kenny, 1986).
Cognitive ability. Cognitive ability (CA) consistently has been recognized as one of the best predictors of academic performance (e.g., Kuncel, Hezlett, & Ones, 2001; Schuman et al., 1985; Wolfe & Johnson, 1995). The relationship between CA and study time, however, is not so obvious, nor is there an abundance of research to support any particular hypothesis. It could be argued that students with a quick mind do not need to study much to get good grades and therefore do not. For example, Rau and Durand (2000) found an inverse association between ACT scores and study time, r = -.21, and concluded that students with quick minds are not necessarily studious, nor do they have to be to be academically successful. Schuman et al. (1985), however, found no association between study time and combined verbal and math SAT scores (TSAT), r = -.03. Again, this lack of association may be due to the highly selective sample at the University of Michigan and the subsequent range restriction on both study time and TSAT. Considering the heterogeneous nature of the students in this study, it is expected that CA will be inversely associated with study time, positively associated with grades, and moderate the study time-grade association.
Student interest and reason for taking a course. As with CA, the relationship between student interest and reason for taking a course and study time has to be inferred from the association between these two variables and grades. Students tend to perform better in courses that interest them than in courses in which they have little interest (Marsh, 1980, 1982). Also, students tend to perform better in courses taken as a major elective or for general interest, as opposed to a general education requirement or as a major requirement (Marsh, 1980, 1982). In general, however, students tend to have more interest in electives, either inside or outside the major, as opposed to major or general education requirements. Thus, it is expected that student interest would be positively associated with study time and grades, and moderate the study time-grade association. Further, it is expected that students would study more in a course taken as an elective than as a requirement.
Course difficulty. Greenwald and Gillmore (1997) found a positive correlation between student study time and the intellectual challenge of a course (r = .36), and between student study time and the amount of effort necessary to succeed in a course (r = .57). Student study time and effort were, however, inversely associated with grades, r = - .15 and r = - .27, respectively. These data suggest that students' study time is positively associated with students' perceptions of course difficulty but inversely associated with academic performance. In short, students tend to study more in difficult classes than easy classes and also expect lower grades in difficult classes than the easy classes (Greenwald & Gillmore, 1997, p. 749). Students who expend considerable effort in a class may do so because they are having difficulty understanding concepts and picking up classroom material; therefore, increased study time may serve as a compensatory mechanism for lack of academic aptitude or preparedness. It is expected that study time and course difficulty will be positively associated, but study time and grades will be inversely associated. Also, it is expected that course difficulty will moderate the study time-grade association.
Grade inflation. Grade inflation and course difficulty are inextricably intertwined. In general, teachers of difficult courses, or courses in which students have to expend considerable effort to earn satisfactory grades, are perceived by students as having stringent grading practices (e.g., Greenwald & Gillmore, 1997). However, teachers of difficult courses can moderate course difficulty by inflating grades. Even in multi-section courses, when the same grading scale is used (e.g., 100 to 90 = A, 89 to 80 = B, etc.), grades can be inflated a number of ways: 1) dropping the lowest exam, 2) providing extra credit, and 3) providing points for attendance and effort. These contextualizing strategies (Horn, 2000) tend to make classes easier and enhance perceptions of grading inflation, while moderating perceptions of course difficulty. When teachers contextualize performance they inflate grades, and students do not need to engage in effortful study to make the grade. Greenwald and Gillmore (1998) suggest that lenient grading practices make it easier to earn satisfactory grades, thereby reducing study behavior, and thereby reducing the amount that students learn (p. 1228). It is expected, therefore, that study time and grading inflation will be inversely associated, grading inflation and grades will be positively associated, and grading inflation will moderate the study time-grade association.
Teacher effectiveness. There is a large literature that suggests that effective teachers increase student learning (see The American Psychologist, November 1997 issue). It is suggested that effective teachers are organized, articulate and fair, and have a comprehensive knowledge of the subject they teach. Moreover, effective teachers are persuasive, able to heighten students' interest in the subject matter, set high standards, and motivate students to attain these standards (Friedrich & Douglass, 1998; Wright, 2001). It is expected, therefore, that effective teachers will induce study behavior and academic performance; that is, students' ratings of teacher effectiveness should be positively associated with study time and grades, and teacher effectiveness should moderate the study time-grade association.
In summary, the primary purpose of this paper is to better understand the nature of the study time-grade association. This purpose will be realized through 1) an examination of predictors of study time and grades and 2) the potential moderating effects of student, teacher and course characteristics on the study time-grade association. As part of this exploration, the variables study time and grades will realized as both independent and dependent variables. Further, study time will be operationalized as self-reported study time and grades will be operationalized as students' expected grades.
It is also expected that one or more of the following variables may moderate the study time-grade association: cognitive ability, student interest, reason for taking a course, course difficulty, grade inflation, teacher effectiveness.
Participants were 194 students enrolled in 5 sections of Introductory Psychology at a mid-size northeastern state college. Four instructors taught the 5 sections; one instructor taught two sections. Data were collected at two times during the semester, the first day (time 1) and the fifteenth week (time 2). Seventy-two percent of the students (N = 140) provided data at both time 1 and time 2. Students provided the last four digits of their social security number so that data from time 1 and time 2 could be matched.
Precourse Measure (Time 1). The precourse measure assessed the reason students are taking Introductory Psychology, their interest in the course, and their academic aptitude.
Reason. Students were asked, “What is your reason for taking this course?” They were given the following options from which to choose: major course requirement, general education requirement, elective for major, elective for minor, general interest.
Precourse Interest (PCI). Student interest was assessed with the following statement, “My level of interest in this course can be best described as:” 7 (Extremely Interested), 4 (Average Interest), 1 (Not at all Interested).
Student Cognitive Ability (CA). Student academic aptitude was measured with the Wonderlic, a 50-item paper and pencil test of cognitive ability (see Wonderlic & Associates, 1992). Scores can range from 0 to 50. The mean for college freshmen is 24 with a standard deviation of 6.4 (see Wonderlic & Associates, 1992). The mean for this sample was 22.57 with a standard deviation of 5.01. The 95% confidence interval about the mean was 21.92 to 23.59. The reliability and validity of the Wonderlic is well documented. Dodrill (1983), for example, found the longitudinal reliability to be .94. The Wonderlic correlates very highly with the Wechsler full-scale (r = .92); thus demonstrating its construct validity (e.g., Dodrill, 1981, 1983; Dodrill & Warner, 1988).
End-of-Course Measure (Time 2). Students were asked to respond to 6 statements that assessed study time, perceptions of course difficulty, teacher effectiveness, student expected grade, student deserved grade, and grade inflation.
(1) Self-Reported Study Time (SRST). Students were asked “to estimate, on average, the number of hours per week they spent studying for this course, outside of class, this includes reading, reviewing notes, writing papers, doing assignments and any other course related work” (e.g, Greenwald & Gillmore, 1997). Students were asked to write in their responses.
(2) Course Difficulty (CD). Students were asked to assess the difficulty of the class with the following question: “Compared to all other college courses you have taken, how would you rate the difficulty of this class.” Ratings were made on a 7 (Extremely Difficult), 4 (Average Difficulty) and 1 (Not at All Difficult) scale.
(3) Teacher Effectiveness Ratings (TER). Students were asked to rate the effectiveness of the teacher with the following statement: “Overall, how would you rate the quality of your instruction, as it contributed to your learning” (from the Student Instructional Report II, item # 40). Ratings were made on a 7 (Very Effective) to 1 (Very Ineffective) scale.
(4) Student Expected Grade (SEG). Students' grades were operationalized as students' expected grades. Students were asked to indicate the grade they expected to receive in the course by choosing from one of 12 mutually exclusive options. Students at this institution are assigned a grade that ranges from A to F, with corresponding pluses and minuses, excepting A+, F+ and F-.
(5) Student Deserved Grade (SDG). Students also were asked to indicate the grade they believed they deserved by, again, choosing from one of 12 mutually exclusive options, as noted above.
(6) Grade Inflation (GI). Grading inflation was operationalized as the difference between students' expected grade and the grade students believed they deserved. The operationalization of grade inflation was derived from Lichtenstein, Fischhoff, & Phillips (1982) and Landrum (1999). Lichtenstein et al. (1982) have consistently shown that students think that they know more than they know. And Landrum (1999) found that students believed they deserved better grades (A or B) than they had earned (C), even after they acknowledged the mediocrity of their work. Together these two pieces of research suggest that students have an inflated and unwarranted sense of knowing and entitlement. Further, these data are consistent with The UCLA Higher Education Research Institute's Freshman Survey (2000) that suggests students are spending less time studying yet expecting higher grades. Faculty who conform to inflated expectations of the students inflate grades (Landrum, 1999). Thus an expected-deserved grade difference that is positive suggests that students expect a grade that is higher than the grade they believe they deserve. The positive difference is an indication of grading inflation.
Five sections of an Introductory Psychology class were recruited to participate in this study. Student participation was sought at the beginning of the first day of class, and prior to students receiving the course syllabi. Students were told that data would be gathered at two times during the semester: the first day of class (time 1) and during the 15th week of class (time 2). Students were also informed that the study would require approximately 15 to 20 minutes of their time, at each administration. All students agreed to participate.
Let us assume an H0 that suggests there is no association between study time and grades, and an alternative hypothesis, H1, that suggests an association exists. Power is the probability of being right in rejecting H0 given that H1 is true (Hays, 1988). Power was computed, using a sample size of 140, an estimated effect size of r = .25 and p for a two-tailed test equal to .05, to be .84 (Howell, 1997). Thus the probability of rejecting the hypothesis of no association between study time and grades, given an association exists, is .84.
Reason for taking a course was not included in any analysis because 82% of the students took Introductory Psychology as a general education requirement and another 9% as a major requirement; hence, only 9% of the students took the course as an elective. Thus meaningful analysis with this variable were precluded.
Hypotheses 1-5 were tested using zero-order correlations. Table 1 provides the intercorrelations of the study variables.
Hypothesis 1. Cognitive ability (CA) was inversely associated with self-reported study time (SRST) (r = -.23, p < .01) and positively associated with student expected grades (SEG) (r = .28, p < .001), thus confirming Hypothesis 1.
Hypothesis 2. As predicted, student precourse interest (PCI) was positively associated with SRST, r = .14, p = .048 (one-tailed test).
Hypothesis 3. As hypothesized, course difficulty (CD) was positively associated with study time, r = .14, p = .048 (one-tailed test); SRST and SEG were inversely associated, r = - .19, p < .05; further, students expected lower grades as their perceptions of course difficulty increased, r = -.39, p < .001; and, perceptions of course difficulty were inversely associated with cognitive ability, r = -.21, p = .013.
Hypothesis 4. SRST and grade inflation (GI) were inversely associated, r = -.35, p < .001; that is, students studied less when they expected higher grades than they believed they deserved. GI and SEG were positively associated, r = .35, p < .001, thus confirming Hypothesis 4.
Hypothesis 5. As predicted, teacher effectiveness ratings (TER) were positively associated with study time, r = .21, p = .014; However, TER were not, as predicted, positively associated with SEG, r = .10, ns.
The zero-order correlations suggest that grade inflation may be the best predictor of study time, r = -.35, p < .001. Course difficulty may be the best predictor of expected grade, r = -.39, p < .001. Regression analysis will examine these possibilities, as well as moderator effects.
What variables best predict study time and expected grade?
Stepwise regression analyses were computed to identify the best predictors of study time. Potential predictors of study time were PCI, CA, CD, SEG, TER, and GI. The F-to-enter a predictor was set at 3.00; the F-to-remove a predictor was set at 2.00 (Pedhazur, 1997). Table 2 provides the regression results. GI was the best (accounted for the most variance) predictor of study time: GI accounted for 12% of the variance in study time. TER provided 5% incremental validity and CA provided 2% incremental validity. No other variables were predictive of study time.
Table 2 also provides the results of the stepwise regression analysis that identified the best predictors of student expected grade (SEG). Potential predictors of student expected grades were SRST, PCI, CA, CD, TER, and GI. CD was the best predictor of SEG: CD accounted for 15% of the variance in SEG. GI accounted for 8% of the variance in SEG; CA and TER each provided 3% incremental validity. No other variables were predictive of student expected grades.
What is the relationship between study time and expected grades when potential moderators are controlled?
Stepwise regression analyses were computed with study time as the predictor and expected grades as the criterion. Given the weak association between study time and grades study time (r = -.19), the F-to-enter/remove criteria were relaxed so that study time would remain in the equation when moderator variables were entered; hence, the association between study and grades could be examined after controlling for the potential moderators. Table 3 provides the results of these analyses. Course difficulty, grade inflation and cognitive ability moderated the study time-grade association, rendering it non-significant; no other variables affected the study time-grade association.
On average, how much time did students spend studying for Introductory Psychology and what grade did they expect to receive? On average, students studied 3.01 (SD = 2.59) hours per week (outside of class). For a 3-semester hour course, the Carnegie Foundation benchmark is 6 hours of study per week outside the class (National Survey of Student Engagement, 2000). Thus, on average, students in this sample studied 50% less than what is recommended by the Carnegie Foundation. Table 4 provides more insight regarding study time, expected grade, and academic aptitude. Fifty-two percent of the students studied 2 hours or less per week; 82% studied 4 hours or less per week. Students' average expected grade, however, was a B. Students with the highest academic aptitude studied the least but expected the highest grades; conversely, students with the lowest academic aptitude studied the most but expected the lowest grades.
The primary purpose of this study was to reexamine the study time-grade association to better understand the nature of this relationship. Previous research has provided mixed results and explanations for the existence of a particular empirical outcome. Traditionally, it has been assumed that study time is predictive of grades; that is, study time is a primary determinant of academic success. Schuman et al. (1985), however, suggested that the study time-grade association is an untested assumption, and that hours studied may have little effect on grades because teachers' grading practices may moderate the study-time grade association. Greenwald and Gillmore (1997) also suggested that teachers' grading practices might help to explain the study-time grade association. Thus, common to previous research were explanations that suggested student and teacher characteristics affected the study time-grade association. The results of this study suggest that course (course difficulty), teacher (grade inflation) and student (cognitive ability) characteristics moderated the study-time grade association: these variables reduced the study-grade association to zero. Hence, the inconsistent findings of previous research may be due to the spurious nature of the study time- grade association. Future research should seek to replicate this finding.
The nature of the study time-grade association can be better understood by examining the predictors of study time and grades. The best predictors of study time were grade inflation, students' perceptions of teacher effectiveness and student cognitive ability. Combined, these three variables explained approximately 19% of the variance in study time: grading inflation 12%, teacher effectiveness 5% and academic aptitude 2%. Prior student interest in the course and course difficulty did not explain additional variance. Thus, teacher characteristics were the primary determinants of student study time. Teachers who inflated grades reduced student study time (e.g., Greenwald and Gillmore, 1997, 1998). Teachers rated effective by students induced study time (e.g., Friedrich & Douglass, 1998). And, high aptitude students studied less than low aptitude students did (e.g., Rau & Durand, 2000).
The best predictors of expected grade were course difficulty, grade inflation, cognitive ability and perceptions of teacher effectiveness. Combined, these four variables explained 29% of the variance in expected grade: course difficulty 15%, grade inflation 8%, cognitive ability 3%, and perceptions of teacher effectiveness 3%. Thus, course difficulty was the best predictor of expected grade. When a course was perceived as difficult, students expected lower grades; when teachers inflated grades students expected higher grades; students high in cognitive ability expected higher grades than students low in cognitive ability; and students expected higher grades when they perceived the teacher as effective. Moreover, ratings of teacher effectiveness and grade inflation were independent variables.
Teacher effectiveness ratings and cognitive ability also help us to better understand study time and expected grade. Students who rated teachers favorably studied more and expected higher grades than students who rated teachers unfavorably. As explained above, however, 82% of the students studied 33% less than what is recommended by the Carnegie Foundation; thus, students in this sample did not engage in considerable study time, despite the predictive nature of teacher effectiveness. In other words, teacher effectiveness plays a relatively minor role in inducing study time and enhancing academic performance.
Cognitive ability was also predictive of study time and expected grade. Students high in cognitive ability studied less and expected higher grades than students low in cognitive ability. Further, the data suggest that students attempt to compensate for a lack of cognitive ability by studying more. Students who studied the most, nine hours or more per week, had the lowest cognitive ability scores (N = 7, M = 17.57, SD = 2.82) and expected the lowest grade, C (2.19). Students who studied the least, 0 hours, had the highest cognitive ability scores (N = 6, M = 25.33, SD = 7.74) but expected a grade of B (3.23). More generally, there is an inverse linear trend between study time and cognitive ability. This finding is consistent with Rau and Durand (2000) who also found an inverse association between student effort and academic aptitude.
In summary, the results of this study suggest the study time-grade association may be spurious and that course difficulty, grade inflation, teacher effectiveness, and student cognitive ability help us to better understand both study time and grades. Further, this study sheds light on the pervasive findings of student disengagement and grade inflation in higher education (e.g., Beaver, 1997; Juola, 1980; Landrum, 1999; McSpirit & Jones, 1999). Perhaps the contradictory findings of previous study time-grade association literature are not contradictory; rather, they may reflect real changes over time in how student performance is determined; that is, teachers may be changing their behaviors in how they grades students (i.e., inflating grades). McSpirit and Jones (1999), for example, suggest that “students have been graduating with consistently higher grade point averages since 1983” (p. 2). Levine (1994) suggests that between 1969 and 1993 the number of A's given to students has quadrupled while the number of C's has dropped by two-thirds. Moreover, McSpirit and Jones (1999) found that the rate of grade inflation was higher for low aptitude students than other aptitude subgroups; and, today colleges are represented by an inordinate number of ill-prepared students (Beaver, 1997). Beaver (1997) suggests that, because of the intense competition for students, no more than 15% of the nation's colleges can be considered selective; hence, most colleges accept most of the students that apply. Thus, the changing study time-grade associations, from 1972-1992, may reflect real changes in teachers' behaviors over time, whereby teachers have tried to accommodate changing student demographics and the competitive nature of higher education by inflating grades. There was a time when student effort and aptitude were the primary determinants of academic performance; this study suggests that may no longer be the case.
In the present study, study time is a central variable of interest. Further, study time is a behavior from which motivation can be inferred; that is, study time can be considered a motivational variable. Thus one way future research could explore factors related to the study time-grade association is to use motivation theory as a guiding framework. Weiner (1990), writing on the history of motivation in education, suggested that motivation is a work-related concept. More recently, Pinder (1998) offered this definition: Work motivation can be defined as “a set of energetic forces that originate both within as well as beyond an individual's being, to initiate work-related behavior, and to determine its form, direction, intensity, and duration (p. 11). Simply, motivation can be thought of as how hard students are willing to work to make the grade, given their ability and the influences of environmental factors. Hence, from a motivational framework, the study time-grade association could be conceptualized as follows: Grades are a function of ability X motivation X facilitating conditions. Facilitating conditions are environmental factors and opportunities that facilitate or retard behavior, (and ultimately performance) (e.g., Hinkley & McInerney, 1998). In this study, environmental factors were grade inflation, course difficulty, and teacher effectiveness. Future research could consider other environmental factors (e.g., peers and academic culture), the interface between environmental factors and motivational elements, and the effects on the study time-grade association.
Goal setting (Locke & Latham, 1990) and expectancy theory (Van Eerde & Thierry, 1996; Vroom, 1964) are two related motivational theories, supported by empirical research, that may help us to better understand the study time-grade association in the context of environmental factors. Expectancy theory, for example, suggests that if students do not value high grades they will not be motivated to achieve high grades, even if they believe they have the ability to earn high grades and they believe their efforts will result in high grades. Similarly, students who are in college for the primary purpose of being credentialled would probably have little interest in extending considerable effort on academic pursuits; that is, these students would be relatively indifferent to grades. Goal setting would suggest a similar outcome. In other words, if the student's goal is simply to graduate, then a 2.0 GPA will suffice. But consider students who plan to pursue medical school or a doctoral degree, for example. Will they engage in considerable study, even if they can make the grade with minimal effort? If students believe that there is little or no relationship between effort and performance, then there will be little pressure on the student to exert considerable effort to obtain the desired grade. Under these circumstances, will students who value education, high grades, and have higher educational goals, engage in considerable study time? What facilitating conditions will have the greatest influence on student academic goals and values, motivation, study behavior and grades: grade inflation, course difficulty, teacher effectiveness, peers, academic cultural, parental influences? As one reviewer of this paper suggested, future research should consider goal setting, elements of expectancy theory, and environmental factors as moderators of the study-time grade association.
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