Nurse educators are interested in reducing student attrition. One approach to decreasing attrition is to expand our understanding of the learning process. Recently, increased attention has been directed toward understanding how the learner processes information (Dansereau, 1985; Weinstein & Underwood, 1985).
In this study, a model of academic achievement among nursing undergraduates was developed and tested. The model focuses on student contributions to academic success as opposed to school effects and teacher effects. The model depicts the possible influence of cognitive, affective, and learning strategy variables on academic achievement. Three cognitive variables (reading ability, language ability, and math ability) and two affective variables (life stress and motivation) are presented as exogenous variables (Figure 1). Each of them is viewed as being directly related to a student's feeling of self-efficacy which, in turn, is directly related to their academic achievement. Reading ability, language ability, and math ability are also seen as directly relating to academic achievement.
In the model, life stress and motivation are also viewed as possible influences on two learning strategy variables: self-monitoring/use of study strategies and concentration/ preparation for class. (The two learning strategy variables were identified by Chacko  in a validation study of the Learning and Study Strategies Inventory [LASSI] with a group of undergraduate nursing students.) In addition, the ability to self-monitor and use study strategies is viewed as affecting one's concentration and preparation for class, which affects one's feelings of self-efficacy (Figure 1).
The model is supported by research findings in several areas. First, cognitive ability is purported to play a role in one's self-efficacy, i.e., one's judgments of one's own capabilities (Bandura, 1982; Schunk, 1983). Furthermore, researchers have shown that cognitive ability is a good predictor of academic achievement (Felts, 1986; Glick, McClelland, & Yang, 1986; Hayes, 1981; Oliver, 1985; Yess, 1980). Therefore, it was hypothesized that cognitive ability is directly related to both feeling of self-efficacy and academic achievement (Figure 1).
Second, several studies have suggested that highly test-anxious students experience cognitive interference, which is a key factor in the lowering of academic performance (Deffenbacher, 1980; Sarason, 1972; Wine, 1980). Other researchers have been concerned with the influence of general academic anxiety on the performance of students, as addressed in self-efficacy theory (Bandura, 1982; Schunk, 1983). Individuals who view themselves inefficacious dwell on their personal deficiencies and imagine potential difficulties, creating stress and concern over failing. On the other hand, individuals who have strong feelings of self-efficacy perform tasks with virtually no anxiety or apprehension, and persist until they succeed (Bandura, 1982). Thus, "the higher the level of perceived self-efficacy, the greater the performance accomplishments" (Bandura, 1982, p. 127). This leads to the hypothesis that feelings of self-efficacy are directly related to academic achievement (Figure 1).
Third, research has shown that life stress has a negative association with academic achievement (de Meuse, 1985; Lloyd, Alexander, Rice, & Greenfield, 1980). According to Davies (1986), stress-related problems of students include poor concentration, persistent worries, panic reactions, and certain minor health problems. For this study, it was hypothesized that life stress is indirectly related to academic achievement by its direct relationship with the ability to self-monitor and use study strategies, with the ability to concentrate and prepare for class, and with feelings of self-efficacy (Figure 1).
Fourth, although motivation, an affective variable, is known to be an important precursor of academic achievement (Davies, 1986; Weinert, 1987), the nature of its influence is not unequivocally understood. In this study, it is proposed that adult students who are highly motivated to complete an educational program of study are likely to use and monitor the study strategies they have learned. In addition, they concentrate on their studies and prepare for class. Lastly, their increased motivation and goal orientation would promote positive feelings of self-efficacy. Thus, it was hypothesized that motivation may indirectly enhance academic achievement by promoting students* self-monitoring and use of study strategies, concentration and preparation for class, and feelings of self-efficacy (Figure 1).
Finally, experts suggest that academically successful students have greater use of study skills such as deep processing and elaborative thinking than students who are less successful academically (Bruch, Pearl, & Giordano, 1986; Dansereau, 1985). However, instructing students in the use of study strategies and self-monitoring does not always lead to increased academic achievement (Naveh-Benjamin, McKeachie, & Lin, 1987; Palmer & Goetz, 1988). This suggests that study strategies and self-monitoring may indirectly affect academic achievement, with other variables intervening. It was hypothesized that the ability to self-monitor and use study strategies may indirectly relate to academic achievement via a direct relationship with concentration and preparation for class, which then relates directly to feelings of self-efficacy. Adult learners who have developed study strategies and self-monitoring skills may be better able to concentrate on their studies and prepare for class than those who have not. In turn, individuals who concentrate and prepare for class, in addition to using study strategies and self-monitoring skills, are likely to experience positive feelings of self-efficacy.
The subjects of this study were 134 first-year nursing students (88% of the total first-year nursing enrollment) enrolled at a midwestern community college during the 1988-1989 academic year. This is a multicampus college and three of the four campuses have a nursing program. The subjects were largely adult learners, with 68% being over age 24 (mean = 29, median = 27). Forty-four percent of the subjects were married, 35% percent were single, and 21% were separated or divorced. It should be noted that single subjects included both students with and without children. Over one third of the subjects worked more than 20 hours each week.
Three instruments were used to measure the cognitive, affective, and learning strategy variables: the ASSET test (ASSET Test Manual, 1986), the Life Experience Survey (LES) (Sarason, Johnson, & Siegel, 1978) and a modified version of the Learning and Study Strategies Inventory (LASSI) (Weinstein, 1987; Chacko, 1989). The dependent variable, academic achievement, was measured by students* grades obtained in an introductory nursing theory course (Human Needs I).
ASSET. The ASSET test (ASSET Technical Manual, 1986) is an advising and planning tool used with students entering 2-year institutions. It measures an individual's verbal ability (language usage and reading skills) and math ability (numerical skills). Reliability and validity measurements were obtained by the test developers from community college students. Reliability coefficients reported in the manual for the scales are 0.87 for the language usage skills, 0.91 for the reading skills, and 0.88 for the numerical skills. Predictive validity was obtained by correlating the students' results with course grades. The correlations between the language usage skills test and the course grades for five related courses ranged from .15 to .30. Correlations between the reading skills test and course grades in 11 related courses ranged from .15 to .42. The numerical skills test was correlated with nine related courses. The correlations ranged from .27 to .42. As one might expect, the lowest correlations were found for courses in which the institutions under study used the test scores for placement, i.e., courses in which student test scores were relatively homogeneous (ASSET Technical Manual, 1986).
LES. The LES (Sarason et al., 1978) measures an individual's life stress. Respondents indicate their perception of 47 Ufe events on a Likert scale ranging from extremely positive ( + 3) to extremely negative ( - 3). The instrument was validated and used with adults in the general population. Sarason et al. report test-retest reliability coefficients obtained from two samples as .19 (ns) and .53 (p<.001) for the positive change score, .56 (p<.001) and .88 (p<.001) for the negative change score, and .63 (p<.001) and .64 (p<.001) for the total change score (Sarason et al., 1978). In the current study, the negative change score was used to measure Ufe stress. Validity was examined by correlating the LES with State- Trait Anxiety Inventory (STAI) and grade point averages. The total and negative change scores of the LES correlated significantly and in a positive direction with the STAI (Spielberger, Gorsuch, & Lushene, 1970). The positive change score was not significantly correlated with either measure. Positive, negative, and total change scores were all found to be negatively correlated with grade point average. The relationship between life change scores and the short form of the Marlowe-Crowne Social Desirability Scale (Strahan & Gerbasi, 1972) was nonsignificant, suggesting that responses to the LES are relatively free from the influence of social desirability response bias (Sarason et al., 1978).
Modified LASSI. The LASSI (Weinstein, Schulte, & Palmer, 1987) is a self-report instrument measuring a student's learning strategy and study skills. According to Weinstein (1987), the instrument provides 10 separate subscales measuring learning strategies of students. The 10 subscaies are: study aids, select main ideas, information processing, self-testing, test strategies, attitude, motivation, concentration, time management, and anxiety. The manual (Weinstein, 1987) reports that coefficient alphas for the 10 LASSI scales ranged from .68 to .86 and the test-retest correlation coefficients ranged from .72 to .85. No information regarding the correlations among the 10 scales is provided in the manual. With regard to validity, the manual states that "the LASSI has been subjected to repeated tests of user validity* (Weinstein, 1987, p. 5). Because of the limited validity data, a validation study of the LASSI with undergraduate nursing students was conducted (Chacko, 1989). The results indicated the presence of 4 rather than 10 subscales for the nursing student sample being studied: self-monitoring/use of study strategies, self-efficacy, concentration/preparation for class, and motivation. Reliability estimates for the four subscales were .86, .88, .91, and .80, respectively.
These subscales were used in the current study as measures of affective and learning strategy variables. The self-monitoring/use of study strategies subscale (18 items) measures the techniques used by individuals for processing incoming information as well as their assessment of the effectiveness of these techniques. One item is, "I make simple charts, diagrams, or tables to summarize material in my courses." Seif-efficacy measures one's perception of academic competence and one's worry regarding academic performance, including test anxiety. "When I begin an examination I feel pretty confident that I will do well" is one example of the 19 items that comprise this subscale. The concentration/preparation for class subscale (22 items) measures an individual's ability to focus on academic tasks and to use time management principles for completing class assignments and preparing for examinations. A sample item is as follows, "My mind wanders a lot when I study" (reverse coded). The motivation subscale consists of 16 items and measures an individual's interest in learning as well as one's diligence in studying in order to succeed academically. One example of an item is, "When work is difficult I either give up or study only the easy parts" (reverse coded).
Academic achievement. Final grades obtained by the subjects in the first nursing theory course, Human Needs I, were used as an indicator of the dependent variable, academic achievement. The subjects' course grades were computed as follows: first, the subject's percentage correct was computed for each of the seven exams in the course; next, the percentage scores were multiplied by the assigned weight for the exam, reflecting the emphasis of that unit in the course; and finally, the weighted scores were summed to obtain the subject's final grade in the course. Because the course is taught by different instructors on different campuses using the same examination blueprints, each subject's course grade was converted to a Z score within his or her class.
After consent was obtained, the LES and LASSI instruments were administered to subjects during the fall 1988 semester, and ASSET scores were obtained from the subjects' file records. At the end of the semester, the subjects' grades in Human Needs I were obtained.
The relationships among the variables are presented in Table 1. Because a significant relationship between life stress and self-monitoring/use of study strategies did not exist, this pathway in the model was deleted. The remaining 14 pathways were retained in the model since they were not incompatible with the bivariate correlations. Correlations among exogenous variables can also be seen in Table 1.
Intel-correlations of Variables
Means, Standard Deviations, and Ranges of Subjects' Scores on Variables
Path analysis was used for testing the model. Multiple regressions were computed using as criterion variables each of the four endogenous variables shown in the model: academic achievement, se If- efficacy, concentration/ preparation for class, and self-monitoring/use of study strategies. In each case, variables specified as being directly related to the criterion constituted the predictor variable set. Additional multiple regressions were conducted to determine if any paths not described in the a priori model were significant. The significance criterion for retaining a path coefficient wasp<.05. Due to the presence of missing data on some variables, the path analysis was conducted on the 95 subjects for whom there were no missing data.
The mean, standard deviation, and range of the subjects' scores for each of the variables are reported in Table 2. Figure 2 portrays the results of the path analysis. Eleven of the 14 pathways remaining in the model following the preliminary analysis were supported by the path analysis. No unspecified path was significant.
As hypothesized, both dimensions of verbal ability were found to be directly related to academic achievement. In addition, the hypothesis that self-efficacy is directly related to academic achievement was supported by the analysis. No other variables were found to have direct effects on achievement.
Four of the six variables hypothesized to be directly related to self-efficacy were supported by the path analysis. The four variables consisted of language ability, math ability, motivation, and concentration/preparation for class. In addition, as expected, self-monitoring/use of study strategies was not found to be directly related to self-efficacy.
Students' life stress, motivation, and self-monitoring/ use of study strategies were found to be directly related to their concentration and preparation for class. No other variable in the model was found to have a direct effect on concentration/preparation for class. Motivation was the only variable directly related to students' self-monitoring and use of study strategies.
The path analysis did not confirm three of the proposed pathways. First, math ability was not directly related to one's academic achievement. Second, an individual's reading ability was not found to have a direct effect on one's feelings of self-efficacy. Third, life stress was not found to have a significant direct relationship with one's self-efficacy and academic anxiety.
As can be seen in Figure 2, almost half of the variance in academic achievement was accounted for. Reading ability and language ability accounted for 38% of the variance in academic achievement. Self-efficacy was found to account for an additional 8% of the variance in academic achievement. The residual coefficients indicate that the model does not explain a considerable portion of the variance in these variables (Figure 2). The direct, indirect, and total effects of the variables are reported in Table 3.
The model presented in this paper depicts relationships among cognitive variables, affective variables, learning strategy variables, and academic achievement for students in a 2-year nursing program. As expected, support was found for the hypothesis that reading ability and language ability are directly related to academic achievement. Many researchers have found that cognitive ability is a strong predictor of academic achievement (Felts, 1986; Click, McClelland, & Yang, 1986; Hayes, 1981; Oliver, 1985; Yess, 1980). Logically, current achievement is influenced by previous achievement. The current finding supports the appropriateness of developing guidelines for the use of the ASSETs reading ability and language ability tests for academic counseling with students in a 2-year nursing program. Such guidelines would assist academic counselors in assessing students' preparedness for entering the nursing program. If students were found academically unprepared in the reading and language areas to enter the program, they could be advised to participate in developmental studies to obtain the necessary skills. Assuring that subjects are appropriately prepared for the nursing program would promote feelings of self-efficacy as well as academic success.
The failure to find a direct relationship between subjects' math ability and academic achievement was unexpected. Math ability was indirectly related to academic achievement via its direct effect on one's feelings of self-efficacy. Although unanticipated, this finding was consistent with the view that many nursing students perceive themselves as having poor math skills, leading to increased academic anxiety and negative feelings of self-efficacy. Furthermore, the finding that math ability was directly related only to self-efficacy and not to academic achievement may be due to the way math ability was measured in this study. The numerical scale of the ASSET is mainly composed of elementary arithmetic skills. It does not include the advanced math skills of algebra used for drug calculations and problemsolving in the nursing curriculum. Further research should examine if the ASSETs elementary algebra test would assist in determining students' preparedness for the nursing program.
An unusual finding was the direct relationship between one's feelings of self-efficacy and the language, but not the reading, component of verbal ability. One possible explanation is that students may have viewed themselves as having sufficient reading skills for the reading and comprehension of textbooks, but some may have been unsure of possessing the communication skills needed for working with clients and other health team members. This uncertainty could have resulted in decreased feelings of self-efficacy. Further research is needed to explore this view.
The path analysis supports the view that life stress may have a negative relationship with academic achievement (de Mueu.se, 1965; Lloyd et al., 1980) via its direct relationship with one's concentration and preparation for class; however, the strength of this relationship was almost negligible. For this population of primarily adult learners, a more appropriate variable might have been the ability to react to and cope with life stress. Individuals' degree of life stress does not necessarily correspond with their ability to cope with this stress. Further study in this area is needed.
Motivation has been viewed as a strong influencing factor on academic achievement, but the exact nature of its influence is not known. The proposed model suggested that motivation influences one's ability to self-monitor and use study strategies, one's concentration and preparation for class, and one's feelings of self-efficacy. The results of the path analyses supported these relationships. In addition, they are in harmony with the views of McCombs (1988) and Covington (1983) who contend that motivation helps individuals allocate attention and effort to academic tasks. The results are also compatible with the contention that increased motivation produces increased feelings of self-efficacy. These findings indicate the importance of assessing students' motivation to reach their educational goals, as well as providing a nursing curriculum that maintains or enhances students' motivation. In addition, educators should assess if the lack of student motivation results from the nature of the nursing curriculum or from personal characteristics of students.
Regarding the two learning strategy variables, the path analysis revealed that students1 use of study strategies and self-monitoring was directly related to their concentration and preparation for class, which related to their feelings of self-efficacy. The use of study strategies and self-monitoring skills allows individuals to devote time and effort to desired learning goals. When a highly motivated adult student concentrates and spends considerable time on learning educational material, it is logical that increased feelings of self-efficacy would result. This suggests the importance of educators' assessing whether or not students possess these skills. If students are deficient in these areas, educators can assist in finding resources to help them obtain skills for studying, selfmonitoring, concentrating, and preparing for class.
Recent research has demonstrated that instructing individuals in the use of learning strategies is one way to influence the manner in which individuals process new information and skills (Biggs, 1984; Dansereau et al., 1984; McCombs, 1988; Miller, Alway, & McKinley, 1987; Nisbet & Shucksmith, 1986; Weinstein & Underwood, 1985). However, the mere possession of these skills will not guarantee academic achievement. The use of skills for studying, self-monitoring, concentrating, and preparing for class may need to be promoted through motivation or encouragement.
A limitation of this study is the use of self-report instruments to measure all independent variables with the exception of reading ability, language ability, and math ability. Self-report measures are more likely to reflect subjects' perceptions than their actual behaviors. Cautious interpretations of causality are warranted due to the small sample size. Further research is needed to explore these relationships with other samples of nursing students and with students from other disciplines.
These findings support the view that the academic achievement of students results from a complex process of learning. Superior academic achievement may be related to students' superior cognitive ability; to decreased life stress; to high motivation; to positive feelings of selfefficacy; and to the ability to study, concentrate, and prepare for class. Although most of these factors are related to academic achievement separately, it may be the combination that more precisely distinguishes the effective learner from the less effective learner.
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Intel-correlations of Variables
Means, Standard Deviations, and Ranges of Subjects' Scores on Variables