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Abstract

Drawing from the leadership literature, a new model for advising is proposed. Full range advising encompasses laissez-faire, management by exception, contingent rewards, and transformational behaviors. The relationships between full range advising and advisees' extra effort, satisfaction with the advisor, and advising effectiveness were examined. Four hundred and seven advisee/raters were sampled. Results indicated that contingent rewards and transformational advising behaviors were highly effective as rated by students.

The role and importance of quality advising has received increasing attention in the higher education literature over the past 10 years (Abernathy & Engelland, 2001; Gordon, Habley & Grites, 2008; Light, 2004; Schreiner & Anderson, 2005). Those who have examined advising have expressed important concerns about the lack of scholarship in this area (Creamer, 2000; Nadler & Simerly, 2006; Saving & Keim, 1998). This is in many ways counterintuitive as the advisor-advisee relationship is among the few structures in place to insure students' success during their educational experience and early career preparation (Winston, Miller, Ender, & Grites, 1984). To effectively guide these advising efforts, more focused inquiries testing the advisor-advisee relationship and its outcomes are necessary.

To date, studies examining the advisor-advisee experience tested such variables as student satisfaction (Fielstein & Lammers, 1992), retention (Shields, 1994), trust (Nadler & Simerly, 2006), and morale (Wilder, 1981). Scholars in the academic advising realm have reviewed the treatment of academic advising effectiveness research and concluded that too few studies have tested the relationships between advisor behaviors and student outcomes (Creamer & Scott, 2000)—these relation ships seem the most relevant for guiding best advising practices. Perhaps the closest to meeting this need has been the work of Spicuzza (1992) using a customer service approach to advising. These efforts laid the foundation for more extensive and concise delineation of the advisor-advisee experience drawing from a different field of study.

According to Smith (2002), the academic advising literature describes primarily two types of advising: prescriptive and developmental. Prescriptive advising refers to a style of advising where the advisor primarily tells students what to do. Developmental advising refers to a style of advising where the advisor develops a stronger relationship with the advisee and they decide their roles within this relationship. Research indicates that there is a difference in what students want from advisors and advisors' perceptions of students' needs (Grites & Stockton, 1994). This is illustrated by the fact that most conceptual papers describe the effectiveness of developmental advising over prescriptive advising, but the empirical [End Page 656] evidence for this is not clear (Fielstein, 1989). Additionally, there is confusion regarding the definition of developmental advising (Saving & Keim, 1998). Thus, the advising field needs to step out of this research paradigm and investigate new ways to approach its research and practice. This study draws from the leadership field to propose a new model of advising: we intend to provide a new paradigm of advising where advisors' behaviors are placed in a continuum varying from least effective to most effective.

Literature Review

Student Outcomes

Advising has been linked to many positive stu dent outcomes. The advising quality was related to student satisfaction (Fielstein & Lammers, 1992; Corts, Lounsbury, Saudargas, & Tatum, 2000; Trombley, 1984; Waggenspack & Hensley, 1992), morale (Crockett, 1979), retention (Crockett; Habley, 1982; Pascarella & Terenzini, 1991; Wilder, 1981), persistence (Shields, 1994), academic success (Gordon & Habley, 2000), career selection (Creamer, 2000; McCalla-Wriggins, 2000), and achievement of maximum potential (O'Banion, 1972). In this study we tested extra effort of students, satisfaction with advisor, and students' perceptions of advising effectiveness.

Academic Advising

The advising field is characterized by two dominant models: prescriptive and developmental. The traditional relationship between student and advisor is described as prescriptive (Smith, 2002), characterized by the advisor telling students what to do and students carrying on with the advice. It is assumed that no problems would arise if the students listen and follow up with the advice. This model is hierarchical with the advisor in command of the knowledge and advising sessions—the advisee is passive. Interactions are primarily question-and-answer sessions and are driven by the advisor's interpretation of the student's academic direction (Smith).

In contrast with prescriptive advising, developmental advising is characterized by the development of the student and advisor relationship in varying degrees. The advisor and the student decide who takes the initiative and the responsibility, who supplies the knowledge and skill, and how the knowledge is obtained and applied. Crookston (1972) stated that these approaches differ from prescriptive advising with regard to abilities, motivation, rewards, maturity, initiative, control, responsibility, learning output, evaluation, and relationship. The developmental model is considered an ongoing process in which advisees are encouraged to share responsibilities for their choices and programs (Fielstein, Scoles, & Webb, 1992). O'Banion (1972) developed a model of academic advising based on a 5-step progression: (a) exploration of life goals, (b) exploration of vocational goals, (c) program choice, (d) course choice, and (e) scheduling course. This model has been criticized because most students actually seek advice in the reverse order (Grites & Stockton, 1994).

Since the first work on developmental advising, the advising literature seems to have expanded substantially. The concept of faculty members as role models, mentors, and friends to students became the mode of thinking (Pardee, 1994). The literature documents that strong, positive relationships between faculty and students prove to be a significant retention variable and a positive influence on the development of students (Ender, 1994).

Winston and Sandor (1984) reported that students preferred developmental advising to prescriptive advising. Conversely, Fielstein (1989) reported that some prescriptive strategies were valued over developmental strategies. Studies started to demonstrate [End Page 657] differences of preference between prescriptive and developmental advising, differences that were attributed to students' characteristics. Andrews, Andrews, Long, and Henton (1987) reported that students with lower grades wanted more personal contact with their advisors. Crockett and Crawford (1989), in comparing Myers-Briggs Type Indicator scores and preference over advising styles, reported that intuitive students preferred developmental over prescriptive advising, while thinking students seemed to prefer prescriptive over developmental advising. Fielstein (1994) argued that enthusiasm for developmental advising may have caused scholars to overlook the benefits of prescriptive advising. Saving and Keim (1998) reported that there is confusion about what developmental advising is, as advisors thought they were using developmental advising, but students disagreed.

Furthermore, developmental advising has not been practiced at the same rate that is supported in the literature (Grites & Stockton, 1994). Many reasons have been given to explain the lack of adoption of developmental advising including: the advisee load is too large for an advisor to meet with students on a regular basis; lack of training in academic advising; each student has a different expectation from the advising experience; lack of faculty incentives; lack of commitment to advising by key administrators and campus leadership; proliferation of part-time faculty, increased out-of-classroom expectations for faculty; and a general depersonalization of the university environment (Pardee, 1994; Strommer, 1994).

These challenges present a need for a new academic advising model. Many scholars critique the advising field because of its two-dimensional approach (Fielstein, 1994; Hemwall & Trachte, 1999; Laff, 1994). Strommer (1994) proposed that instead of continuing the use of the developmental model as the standard of advising, perhaps a new paradigm needs to be developed. Drawing from the leadership field, we propose a new model for advising which considers advisors as leaders for students in their academic programs. Despite this natural application, to the authors' knowledge, no work has been done in this area that applies leadership theory in an academic advising context. This study bridges the educational and leadership field by linking advising and full range leadership.

Full Range Advising

Comparing the leader-follower relationship with the advisor-student relationship, it makes sense to consider ways of capitalizing on what is known in the leadership field to enhance advising. The full range leadership model has been widely studied; it is comprised of three groups of behaviors: (a) laissez-faire, (b) transactional, and (c) transformational. Transformational leadership research has demonstrated consistent, positive relationships between its use and most positive interpersonal and organizational outcomes—including extra effort, satisfaction, and perceived effectiveness (Lowe, Kroeck, & Sivasubramaniam, 1996). These results have been consistent across populations, settings, and contexts (Bass, 1996). It is expected that the same tenants will be true in an advising context.

Barbuto, Story, Fritz, and Schinstock (2008) argued that advisors who use more transformational behaviors are likely to bring about increases in positive student outcomes. Leaders operate across three groups (laissez-faire, transactional, and transformational), but operate decidedly more in one of the groups, and consequently, exhibit the associated behaviors. Laissez-faire (hands-off leadership) is best characterized as non-transacting. Followers of laissez-faire leaders perceive their leaders are ineffective at their jobs (Bass & Riggio, 2006). Transactional [End Page 658] behaviors include: passive management by exception (leader deals with problems after they occur); active management by exception (leader allows followers little latitude); and contingent rewards (leader creates clear mutual expectations and exchanges). Followers of transactional leaders have reported inconsistent relationships with positive organizational outcomes. Contingent rewards behaviors are normally associated positively to most positive organizational outcomes, while active and passive management by exception behaviors are associated with negative organizational outcomes (Lowe et al., 1996). Transformational behaviors include: individualized consideration (leader is considerate of followers); intellectual stimulation (leader encourages independent thought); inspirational motivation (leader excites followers about the future); and idealized influence (leader acts as role model). Followers of transformational leaders feel trust, admiration, respect, and loyalty towards the leader, are motivated to perform extra-role behaviors, are highly satisfied, and perceive that the organization they work for is highly effective (Lowe et al.). Full range leadership construct is applied to academic advising with similar tenants and expectations evident in the literature (Barbuto et al.).

Full Range Advising Behaviors

Laissez-faire is characterized by avoidance of decisions and abstaining from interventions (Bass, 1985). Laissez-faire advising would feature an inaccessible advisor who makes students sense that they are on their own. Lowe et al. (1996) reported from their meta-analysis consistent negative outcomes associated with leaders' use of laissez-faire behaviors. Similarly, we expect students of a laissez-faire advisor to experience increased frustration resulting from the advisor's apathetic response and unavailability, which result in decreased levels of perceived advisor effectiveness, student satisfaction, and student extra effort.

H1: Laissez-faire advising will be negatively correlated with advisees' ratings of advisor effectiveness, satisfaction, and extra effort.

Passive management by exception is characterized by standards creation and limited awareness of deviations until corrections are necessary (Bass, 1985). The profile of passive management by exception advisors involves reaction only after students make mistakes. This form of advising may result in students' frustration with the lack of guidance and shared information.

Active management by exception is characterized by rule enforcement, error correction, and proactive deviation inspection (Bass, 1985). The profile of an active management by exception advisor includes searching for mistakes, enforcing university rules, and then correcting problems. This style of advising may result in increased students' frustration rooted in the advisors' insistence on enforcing rules and regulations and identifying mistakes. Lowe et al. (1996) reported consistent negative outcomes associated with leaders' use of passive and active management by exception. It is expected that these results will be similar under the advising context.

H2: Passive and active management by exception advising will be negatively correlated with advisees' ratings of advisor effectiveness, satisfaction, and extra effort.

The use of contingent rewards is characterized by clarification of desired outcomes and exchanges for rewards and recognitions for meeting these expectations (Bass, 1985). The profile of a contingent rewards advisor involves recognition (praise, feedback) of students who achieve desired outcomes. This form of advising may result in students' achievement of the expected outcome, but not greater performance than was expected. Lowe at al. (1996) reported [End Page 659] consistent positive outcomes associated with leaders' use of contingent rewards behaviors. It is expected the same will hold true under the academic advising context.

H3: Contingent rewards advising will be positively correlated with advisees' ratings of advisor effectiveness, satisfaction, and extra effort.

Individualized consideration is characterized by personal attention to subordinates. Each subordinate is treated differently in accordance to his or her needs and abilities (Bass, 1985). The profile of an individualized consideration advisor includes development of a customized program around each student's needs and professional aspirations. Furthermore, demonstrated value of the individual student's needs, empathy, and encouragement of continuous improvement would characterize an advisor's individualized consideration behavior. This approach to advising may result in students' willingness to develop.

Intellectual stimulation is characterized by a highlighted importance of the intellect, encouragement of the imagination, and challenges to the status quo. The profile of an intellectual stimulation advisor includes creation of an environment where students can question assumptions and consider new and innovative ways to solve problems. This form of advising would result in students' willingness to think for themselves.

Inspirational motivation is characterized by a visualization of an attractive, attainable future and alignment of individual and organizational needs (Bass, 1985). The profile of an inspirational motivation advisor includes communication of a desirable future state or vision to the student. The advisor selects this vision as a backdrop for rationale in important matters. This form of advising may result in students' willingness to excel.

Idealized influence is characterized by persistence in pursuit of objectives, confidence in the vision, and a strong sense of purpose and trust (Bass, 1985). The profile of an idealized influence advisor includes demonstration of a passion for student development and a true commitment to cause positive influences in the lives of the students. This form of advising results in students' trust and emulation of positive behaviors. Taken together, these four dimensions comprise transformational advising. Lowe et al. (1996) reported consistent strong positive outcomes associated with leaders' use of transformational behaviors. This is also expected when applied to the academic advising context.

H4: Transformational advising will be positively correlated with advisees' ratings of advisor effectiveness, satisfaction, and extra effort.

Method

Subjects

The student population used for this sample consisted of 1,017 students from a land-grant university in the Midwest U.S. Responses were received from 40% of the students (N = 407) who were solicited by their advisors to anonymously complete an online questionnaire. Women made up 69% of the advisees (281). Out of the complete sample, 75% (305) were earning a bachelor's degree, 13% (53) were earning a master's degree, and 2% (8) were earning a doctoral degree. Among the fields of study, 25% (103) of the students were majoring in social sciences: 12% (50) in elementary education, 7% (29) in middle level education, and 6% (24) in family and consumer sciences; 22% (89) were majoring in life sciences: 8% (31) in biochemistry, 5% (20) in biological sciences engineering, 5% (19) in biology, and 5% (19) in entomology; the remaining 53% (216) were in programs across 43 majors. [End Page 660]

Procedure

Data were collected from an intact group of advisors as part of a semester-long transformational advising training seminar. Advisors were asked to complete the adapted version of Bass and Avolio's (1995) self-rated Multifactor Leadership Questionnaire (MLQ) on line. Each advisor was asked to distribute the link to the online student survey to the entire advisee roster. Advisors were asked not to select or deselect advisees for participation to avoid potential response bias. Data were collected from multiple levels (self and other) consistent with transformational leader ship research recommendations (Yammarino & Bass, 1990). Instruments were coded to protect the identities of raters; however, advisors' names were kept on a separate coding sheet for interpretation and feedback as part of the advising development initiative. All instruments were processed electronically using Survey Monkey, which generated the data set automatically. Participants and their raters were provided letters detailing their participation and rights, which included the right to withdraw at any time during the research process—consistent with Institute of Review Board for research of human subjects; none of the participants asked to withdraw from the study. Because the advisors had preregistered for the workshop, the response rate is less relevant; however, 37 of the eligible 50 advisors who signed up participated in the study. This high participation rate (74%) indicates that participants were keenly interested in the information; however, because of the small number of advisors participating, for the purpose of this study only data collected from students were analyzed.

Instruments

Full Range Advisor Behavior.

Advisor behaviors were measured using an adapted version of Bass and Avolio's (1995) MLQ Form 5X Short. The MLQ was originally developed and validated to measure transactional and transformational leadership behaviors (Bass, 1985). It has been updated periodically the 1995 version was adapted for this project to measure advising behaviors. The MLQ has been used in hundreds of studies with varied populations and has consistently been found to be both reliable and valid for predicting positive organizational and interpersonal outcomes in followers (Lowe et al., 1996). The items from the MLQ were reworded for the advising context; for example: "The person I am rating fails to interfere until problems become serious" was modified to "My advisor fails to interfere until advising problems become serious." The four scales used to measure transformational advising were (a) idealized influence ("My advisor talks about his/her most important values and beliefs"; α = .80), (b) inspirational motivation ("My advisor talks optimistically about my future"; α = .89), (c) intellectual stimulation ("My advisor reexamines assumptions to question whether they are appropriate"; α = .81), and (d) individualized consideration ("My advisor spends time teaching and coaching me"; α = .87). The three scales measuring transactional advising were (a) contingent rewards ("My advisor provides me with assistance in exchange for my efforts"; α = .79), (b) active management by exception ("My advisor focus attention on irregularities, mistakes, exceptions, and deviations from standards"; α = .79), and (c) passive management by exception ("My advisor fails to interfere until advising problems become serious"; α = .64). Laissez-faire was measured by four questions of the MLQ ("My advisor avoids getting involved when important advising issues arise"; α = .58).

Outcomes.

Outcomes were measured with Bass and Avolio's (1995) MLQ Form 5X Short, which was adapted for an advising context. The three subscales included (a) advisor [End Page 661] effectiveness ("My advisor is effective in meeting my school-related needs"; α = .89), (b) advisees' extra effort ("My advisor gets me to do more than I am expected to do"; α = .86), and (c) satisfaction with advisor ("My advisor uses advising methods that are satisfying to me"; α = .87).

All subscales were measured on a 5-point, Likert-type scale from 0 (not at all) to 4 (frequently, if not always).

Analysis

Results of this study were analyzed using SPSS-PC. Analysis of the MLQ of student raters' reports began by calculating the subscales of laissez-faire, passive management by exception, active management by exception, contingent rewards, intellectual stimulation, inspirational motivation, individualized consideration, and idealized influence. Simple statistics and correlations were calculated (p < .05) to interpret the data and test the hypothesized relationships. Hierarchical linear model was used to test the best predictive model for the significant findings.

Results

Simple statistics were calculated and provided for all variables tested in this study. Advisors as a group seem to exhibit the highest degree of idealized influence (M = 28.90, SD = 5.35) among the 8 full range of advising behaviors tested. Among the transformational advising behaviors the lowest observed was intellectual stimulation (M = 15.03, SD = 3.60). The lowest observed advising behavior was laissez-faire (M = 5.43, SD = 2.11); however, the reliability estimate was too low to interpret this result. Generally, the transactional advising behaviors were the lowest observed behaviors across the population of academic advisors. Complete means and standard deviations are calculated and reported in Table 1.

Several significant relationships emerged from this analysis. Complete correlation analysis was calculated and reported. As mentioned, the laissez-faire subscale did not achieve an acceptable reliability estimate, so the correlational results for it were not interpreted. A significant negative relationship was found between passive management by exception with advisees' ratings of extra effort (r = -.37, p < .01), satisfaction (r = -.49, p < .01), and advisor effective ness (r = -.51, p < .01; H2). A positive significant relationship was found between active management by exception with advisees' ratings of extra effort (r = .13, p < .05; H2). No significant relationship was found between advisees' ratings of satisfaction with active management by exception. A significant negative relationship was found between active management by exception with advisees' ratings of advisor effectiveness (r = -.11, p < .05; H2). As hypothesized, a significant positive relationship was found between contingent rewards and advisees' ratings of extra effort (r = .75, p < .01), satisfaction (r = .72, p < .01), and advisor effectiveness (r = .80, p < .01; H3). Idealized influence shared a positive significant relationship with extra effort (r = .79, p < .01), satisfaction (r = .70, p < .01), and advisor effectiveness (r = .78, p < .01; H4). A positive significant relationship was found between inspirational motivation with advisees' ratings of extra effort (r = .75, p < .01), satisfaction (r = .80, p < .01), and advisor effectiveness (r = .84, p < .01; H4). Intellectual stimulation shared a positive significant relationship between advisees' ratings of extra effort (r = .75, p < .01), satisfaction (r = .68, p < .01), and advisor effectiveness (r = .73, p < .01; H4). A positive significant relationship was found between individualized consideration and advisees' ratings of extra effort (r = .83, p < .01), satisfaction (r = .81, p < .01), and advisor effectiveness (r = .88, p < .01; H4). [End Page 662]

Table 1. Descriptive Statistics, Reliabilities, and Intercorrelations
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Table 1.

Descriptive Statistics, Reliabilities, and Intercorrelations

[End Page 663]

Table 2. Summary of Hierarchical Regression Analysis for Variables Predicting Effectiveness (N = 407)
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Table 2.

Summary of Hierarchical Regression Analysis for Variables Predicting Effectiveness (N = 407)

To test the best predictive model for the significant findings, the transformational behaviors were entered in three stepwise hierarchical models. Intellectual stimulation, inspirational motivation, and individualized consideration explained 81% of the variance in students' ratings of advisor effectiveness. Although idealized influence shared a significant relationship with students' ratings of advisor effectiveness, it did not contribute significantly beyond what was explained by the other three behaviors (see Table 2). Intellectual stimulation, inspirational motivation, and individualized consideration explained 81% of the variance

Table 3. Summary of Hierarchical Regression Analysis for Variables Predicting Extra-Effort (N = 407)
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Table 3.

Summary of Hierarchical Regression Analysis for Variables Predicting Extra-Effort (N = 407)

[End Page 664]

in students' ratings of extra effort. Inspirational motivation shared a significant relationship with ratings of extra effort, but it did not contribute significantly beyond what was explained by the other three behaviors (see Table 3). All four transformational behaviors entered together were able to explain 76% of the variance in satisfaction with advisor (see Table 4).

Tolerance and variance inflation factor (VIF) statistics revealed that multicollinearity was not a problem for this research. A tolerance value that is less than .10 and a VIF value above 10.0 show evidence of collinearity (Field, 2005). In the three regressions, values of the tolerance statistic for the independent variables ranged from .24 and .71. Values from the VIF ranged from 1.0 to 4.1.

A summary of hypotheses and results is assembled to illustrate the consistent relationships found between full range advising behaviors and extra effort, satisfaction, and perceived effectiveness (see Table 5). Taken together, all of the transformational advising hypotheses were supported with relationships ranging from .68 to .88. Contingent rewards and management by exception also performed in this study as hypothesized—although active management by exception hypotheses were only partially supported.

Discussion

This work developed and tested a framework of full range advising with several significant results. Simple statistics revealed that among the transformational advising behaviors idealized influence was the most observed behavior. This indicates that advisors are able

Table 4. Summary of Hierarchical Regression Analysis for Variables Predicting Satisfaction (N = 407)
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Table 4.

Summary of Hierarchical Regression Analysis for Variables Predicting Satisfaction (N = 407)

[End Page 665]

Table 5. Summary of Hypotheses and Results
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Table 5.

Summary of Hypotheses and Results

to express a dedication to students and garner respect—and perhaps admiration—from advisees. This would seem to bode well for fostering a productive and engaging advisor-advisee relationship. Also noteworthy was that the lowest observed transformational advising behavior was intellectual stimulation. Although this was still observed at greater frequency than the transactional behaviors, its place as lowest among the transformational advising behaviors raises some concerns. Advisors may be offering answers when opportunities may [End Page 666] exist for engaging students' intellect to find the answers or explore the possibilities. The lower mean, compared to the other transformational advising behaviors, indicates that advisors are not naturally doing this as much as the other behaviors—such as idealized influence, individualized consideration, and inspirational motivation.

A negative significant relationship between passive management by exception and three positive outcomes (advisor effectiveness, advisee's extra effort, and satisfaction with advisor) indicated that advisors who do not give directions to students and wait for students to make mistakes before intervening are viewed as less effective across the three outcomes studied. Thus, advisors should avoid displaying passive management by exception behaviors to increase their advising effectiveness. This result is consistent with findings of the meta-analysis by Lowe et al. (1996) on transactional and transformational leadership behaviors.

A negative significant relationship emerged between active management by exception and advisor effectiveness and satisfaction with advisor. A significant positive relationship was found between active management by exception and advisees' reports of extra effort. These results indicated that advisors who search for mistakes, enforce university rules, and monitor for deviations are viewed as able to exert extra effort in students; however, these students feel that the experience is less effective and less satisfying. If advisors value student satisfaction, they should minimize their active management by exception behaviors.

A positive significant relationship was found between contingent rewards advising across all three positive advising outcomes. These results indicated that students view advisors positively when expectations are clarified and rewards are based on meeting these expectations. Past leadership studies showed that followers are less likely to exceed expectations in contingent rewards exchanges (Lowe et al., 1996). Academic students will also meet, but not likely exceed, expectations in a contingent rewards advising system.

A positive significant relationship was found between transformational advising and the three positive outcomes studied (advisor effectiveness, advisee's extra effort, and satisfaction with advisor). These results indicated that advisors who give personal attention to students, value each student's individual needs, and encourage the students ' continuous improvement were viewed as more effective across all student outcomes tested. Advisors should use individualized consideration if they desire increased extra effort, increased satisfaction, and increased advising effectiveness. Advisors who encourage imagination and challenge assumptions are also viewed by students as more effective. Advisors should increase the use of intellectual stimulation behaviors if the quality of academic advising is a priority. The results also indicated that advisors who communicate an appealing future for students and use this vision to shape advising strategies are viewed by students as more effective. Advisors should increase the use of inspirational motivation if they seek optimal levels of extra effort, student satisfaction, and students' perception of advisor effectiveness. Results indicated that advisors' demonstration of commitment to student development related to students' extra effort, satisfaction, and advisor effectiveness ratings. Advisors should increase their use of idealize influence to achieve greater levels of these positive outcomes.

The model of full range advising was able to explain 76% to 81% of the variance in the three positive outcomes measured. Research in full range leadership also reported higher correlations with single-method designs than when multiple source data were used (Lowe et al., 1996). [End Page 667]

Limitations and Future Research

Single-method variance increased the strength of the correlations reported in this study. Two of the subscales had weak reliability estimates: passive management by exception and laissez-faire. The results for laissez-faire advising behaviors were not interpreted; however, the MLQ traditionally has reported very good reliability estimates across all subscales. Perhaps the change in the context created this weaker reliability; therefore, scholars should be cautious in interpreting results from these two subscales. On the other hand, previous data from the leadership field strongly support the results found (for a meta-analysis, see Lowe et al., 1996). To address these concerns, larger or cumulative advisor samples may be useful to test advising philosophies against the positive outcomes measured in this work. Some refinements to the contextually derived measure of full range advising are necessary to improve psychometrics and confidence in the data representation. Objective measures of performance should be used to capture impact of transformational advising on students.

Future research may also consider gender differences for both advisors and advisees and how these may impact relationships between advising styles and student outcomes. Class standing and its moderating effect on these relationships may also be analyzed and studied in future work. Future researchers are encouraged to test full range advising across many academic settings and contexts. Other positive outcome variables such as student retention, number of major changes, perceptions of career preparedness, successful degree completion, student graduating GPA, and overall good will towards the university should be studied and reported to further generalize the impact of transformational advising on the student experience

Practical Implications

This study revealed several strong relationships between academic advisors' behaviors and positive student outcomes. Based on these results advisors may conscientiously increase their use of positive transformational advising behaviors and resist or avoid specifically passive and active management by exception behaviors that have been shown to relate in lower ratings of extra effort, satisfaction, and advisor effectiveness. Research in the leadership field has consistently demonstrated relationships between transformational behaviors and the three positive outcomes studied. The results of this study strongly support prior ones, which were conducted in organizational contexts. The full range model appears to have application in the educational context.

Conclusion

This work tested an application of transactional and transformational leadership principles in an advising context. A student sample assessed their advisors' behaviors towards them as well as extensive outcomes. The results of this work were consistent with prior studies in other contexts and are highly relevant to the academic advising field. Greater attention to the role and effectiveness of advising present countless opportunities for further inquiry. [End Page 668]

John E. Barbuto

John E. Barbuto, Jr. is Associate Professor of Management at California State University Fullerton;

Joana S. Story

Joana S. Story is an Assistant Professor of Management at NOVA School of Business and Economics in Lisbon;

Susan M. Fritz

Susan M. Fritz is Vice President, University of Nebraska-Lincoln;

Jack L. Schinstock

Jack L. Schinstock is Professor of Biological Systems Engineering, University of Nebraska-Lincoln.

Correspondence concerning this article should be addressed to John E. Barbuto, Jr., Associate Professor and Director of the Center for Leadership, Mihaylo College of Business and Economics, California State University FULLERTON, RM 5357c Mihaylo Hall, Fullerton, CA 92831; jbarbuto@fullerton.edu

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Additional Information

ISSN
1543-3382
Print ISSN
0897-5264
Pages
656-670
Launched on MUSE
2011-11-23
Open Access
No
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