Extensive literature exists on the topic of college student retention. Researchers (Astin, 1975; Bean, 1980, 1982; Tinto, 1975, 1993) have studied it from a variety of perspectives, including drop-out, withdrawal, attrition, and retention. Research on student retention in university is significant relevance due to the considerable competition for students among colleges and universities, and the emphasis on the value of higher education (Peltier, Laden & Matranga, 1999). Retention is now viewed as part of the educational process in which behavioural constructs, such as those in Astin’s theory of involvement (1993) and Tinto’s theory of departure (1973), have been developed and examined. Astin, using the theory of involvement, indicates that the more students invest physical and psychological energy to get involved in the academic and social culture of the college, the greater the potential for student success. Tinto’s longitudinal model of institutional departure attributes an individual's decision to continue attending an institution to pre-entry attributes, the student's goals and commitments, academic and social institutional experiences, and academic and social integration.

American and Canadian universities have recognized student retention as a critical issue since the early 1970s (Strommer, 1993). Tinto (1993) reported that more students leave institutions of higher education prior to degree completion than stay. It was projected that of the nearly 2.4 million first-time students who in entered higher education institutions in1993, over 1.5 million will leave without receiving a degree. Of those, 1.1 million will leave higher education altogether without ever completing either a two- or four-year degree program. It was discovered through The College Testing Program (ACT, 1998) that students entering private and public higher education institutions in 1995 experienced dropout rates of 29.9 percent and 32 percent, respectively.

Astin, Tsui, and Avalos (1996) conducted a large-scale study examining degree attainment. They reported the persistence of 75,752 freshmen at 365 baccalaureate-granting institutions from 1985 -1996. Only 39 percent of the students were able to complete a bachelor’s degree within four years of entering college. The results of another study (CSRDE report, 2001) were similar. Over a period of six years, 42 percent of the students dropped out of college. Twenty-one percent left during the first-year, 11 percent in the second year and 10 percent in the third and later years. Evidently, more than half the dropouts did so in their first-year.

Recent studies have found that the length of time that students take to graduate has increased ( Peltier et al., 1999) Peltier et al, found that about one-half of the 1966 first-year students obtained their baccalaureate degrees within four years, compared to one-third of those entering university in 1982. They found that only 28 percent of the 1993-94 first-years graduated within four years, while an additional 30 percent took longer than four years. The eventual degree completion rate for a first-year student is estimated to be 58 percent. From 1993 to 1999, the retention rates improved slightly, from 78 to 80 percent. Institutions with a higher percentage of part-time undergraduate enrollments had lower retention and graduation rates. The graduation rates for the 93-94 cohorts were 66 percent for institutions with less than 10 percent part-time undergraduates, and 39 percent for those with a part-time enrollment higher than 20 percent (CSRDE report, 2001).

In the last decade the information era has impacted higher education and the student population it now serves (Watford, 1995). The academically-skilled, middle-class students have evolved to a more complex mix of academic preparation, age, socioeconomic background, and reasons for enrolling in college (Gordon & Grites, 1984). Researchers (Nagda, Gregerman, Jonides, von Hippel & Lerner, 1998; Braunstein & McGrath, 1997) found that most students including academically-prepared students enter university unprepared for the required level of work and often need assistance to acclimate to the new environment. Accordingly, these students have naïve notions about the scope of undergraduate education, especially about where it should lead and what is expected of them. They go to campus with a different set of needs which must be addressed in university so that they may succeed (Strommer, 1993). Key researchers (Nagda et al., 1998; Astin, 1993; Tinto, 1993) found that student difficulties in identifying with, and connecting to, the academic and social cultures and subcultures within the institution can lead to poor academic performance and eventual withdrawal.

For almost 160 years, first-year students have been a topic of concern for institutions of higher education (Levine, 1991). It was found that first-year programming which deals with the issues of the students impacts academic achievement, academic persistence and graduation for its participants (Levine, 1991; Tinto, 1993). First-year programs range from intensive orientation, developmental course work, advising, counseling and mentoring programs for first-year students (Capolupo, Fuller & Wilson, 1995; Brown, 1995; Strom, 1995, Strommer, 1993). In particular, researchers (Strommer, 1993; Tinto, 1993) realized the critical components of successful first-year programs include academic advising, orientation, support programs, tutoring, supplemental instruction, first-year seminars, skills development programs, mentoring programs, and placement testing.

Although the implementation of first-year programs is in response to a national concern regarding decreasing rates of retention, national initiatives cannot provide the practical solutions needed to deal with the problem (Colton, Conner, Shultz & Easter, 1999). Tinto (1987, 1993) suggested that successful student retention occurs at the local institutional level since student attrition strongly relates to student-institution interaction after admission rather than individual student characteristics. Accordingly, each institution should examine its unique interaction process (i.e., faculty-student, student-student, student entry characteristics, institution resources, student academic/social expectations, institution academic/social demands) to develop need-based programming that supports and prepares first-year students for the demands of their transition year.

Tinto (1993) identified the use of intrusive interventions for at-risk students that resulted in efficient and positive, academic and retention outcomes. Colton et al. (1999), described a Pennsylvania university’s Student Support Services Freshman Year Program (SSSFYP) as an "intrusive" intervention program. The researchers noted that SSSFYP required the following minimum semester participation: 1) attendance at four meetings with a SSSFYP advisor/counselor 2) participation in a minimum of two SSSFYP sponsored social activities 3) completion of one academic skills workshop 4) attendance at all SSSFYP freshman colloquium sessions (10 weekly 1 hour non-credit sessions in the fall semester) 5) assessment testing and 6) participation in weekly group and/or individual meetings with a student mentor. Further, other researchers (Fidler, 1991; Tinto, 1993, Strom, 1995) found mentor programs to be crucial components of academic support programs.

Using outcome-based research, Colton et al, (1999) conducted a longitudinal evaluation of SSSFYP in order to assess its effectiveness in strengthening student persistence. Demographic background, student satisfaction with programming, academic grade and cumulative point averages, and retention rates were used as criteria for data analysis and program evaluation. Results of participation in the program compared to non participation in the program by students of the same qualifiers showed: a first-year retention rate of 88 percent for the SSSFYP group compared to 54 percent, respectively, a second-year retention rate of 83 percent compared to 33 percent, respectively; and a three-year retention rate of 78 percent compared to 25 percent respectively.

According to Colton et al. (1999), success of intrusive intervention programs demands a critical evaluation of retention needs and the target population of the adapting institutions. The following are intrinsic components for adaptations: the philosophy of intrusive interventions, the fostering of positive faculty/staff-student interactions; the use of a well-designed, comprehensive advisement component, the use of an appropriate colloquium, and the use of extrinsic rewards..

Milem and Berger’s (1997) study examined the relationship between Astin’s theory of involvement and Tinto’s theory of student departure. They concluded that early involvement with other students, as well as with faculty, appears to results in retention. Supporting Tinto (1987), the researchers confirmed that the important factors for student retention are relationships with faculty and positive academic and social experiences during their years on campus.

Pascarella and Smart (1991) concluded that athletic participation also had a direct effect on social involvement, and a marginally significant effect on bachelor’s degree attainment and social self-esteem. Similarly, Daly and Breegle (1989) found that graduates in one institution had a higher participation rate in extracurricular activities than dropouts. Both studies support Astin’s (1993) theory of involvement which was discussed earlier in this review.

Tucker (1999) revisited Tinto’s (1987) theory of departure rendering the deductive process inadequate in retention studies. Because of the dynamics of group departure it is difficult to infer from quantitative evidence. According to Tucker and Tinto research into transitions, this directly relates to the students’ need to feel a sense of belonging. These initiatives may involve mailings to incoming students, visiting high schools, establishing a one-on-one help line, or providing adequate and readily available psychological, academic, and peer counseling. "Vision" and "Sense of Community" were found by Tucker (1999) to have the most substantial effect on transition. Vision was noted to be the image that students hold of the future, while sense of community included any phenomena that make students feel a sense of belonging in the new educational environment.

Stegman (1969) conducted a study at Southwest Missouri State College using experimental living area activities. The study was designed to improve the retention ratio of college freshman. The objectives included identifying potential dropout students and assigning them to an empathic graduate assistant living in the residence hall. The assistant was assigned with the responsibility of encouraging the potential dropout to stay in college. Stegman found that the personal attention and assistance given to the experimental subjects may have been instrumental in accounting for a significant (beyond 95% confidence) rise in retention as compared to their control counterparts.

Thompson, Samiratedu, and Rafter (1993) studied the influence of residing on-campus, as compared to residing off-campus, on academic performance, progress, and retention. The researchers noted that students living on campus showed significantly higher performance, greater progress, and a higher return rate than those residing off campus. Blimling (1989) reported that when other differences are controlled, the academic performance of residence-hall students and students living at home with parents did not differ significantly. The researcher further indicated that students living in residence halls perform better academically than those living off-campus, the difference being the presence of organized mentoring and social integration.

Tinto (1996) pointed out that retention programs have had limited impact. More recently, Tinto(1998) noted that the educational community is not adjusting academic or organizational processes to enhance student retention. Student retention in college is related to a complex set of factors, including student involvement, ethnicity, gender, and age, as well as place of residence (Peltier et al, 1999). Women have generally higher rates of graduation than men while older students have many barriers to overcome that are not common among traditional age students. Retention appears to a key issue for first-year students faced with societies higher education demands.

Researchers (Erkut & Moros, 1984; Thomas, 1982) have noted that social learning theory (Bandura, 1965) or social cognitive theory (Bandura, 1986) provides a theoretical foundation for mentoring. Bandura’s Social learning theory focuses on cognitive concepts, the way children and adults operate on their social experiences and how these cognitions then influence behaviour and development. Bandura introduced the notion of modeling or vicarious learning as a form of social learning. In 1986, Bandura renamed is Social Learning Theory to Social Cognitive Theory, with the introduction of concepts including self-efficacy (which was discussed in the previous section) and the idea that there can be a significant temporal variation in time lapse between cause and effect. The Social Cognitive theory defines human behaviour as a triadic, dynamic, and reciprocal interaction of personal factors, behaviour, and the environment (1986).

Jones (1989) suggested that the Social Cognitive theory determines the mind as an active force that constructs one’s reality, selectively encodes information, performs behaviour on the basis of values and expectations, and imposes structure on its own actions. Through feedback and reciprocity, a person’s own reality is formed by the interaction of the environment (including other people, mentors) and one’s cognitions. Also, cognitions change over time as a function of maturation and experience (McCormack Brown, 1998). Therefore, through an understanding of the process involved in one’s construction, human behaviour can be understood, predicted, and changed.

Bandura (1989) further noted that humans are able to model observed behaviour through cognitive processes. Symbols provide the mechanism that allows for cognitive problem solving and foresighted action. Observational learning allows one to develop a concept of how a new behaviour is formed without actually performing the behaviour. Also, the observer is most likely to attend to, and model, behaviours of people that are most like themselves and those that they associate with the most. Bandura (1986) believed that modeling was an important way of teaching people overt behaviour and also one of the most powerful means of transmitting values, attitudes, and patterns of thought and behaviour. Further, the theorist believed people could learn not only by imitating the overt behaviour of others, but also observing how others were affected by situations that occurred in their lives. Reciprocally, the vicarious success experience of others provides incentives for individuals to undertake challenges. Bandura, also noted that expectations of behavioural outcomes, more so than actual outcomes, influence the likelihood that a behaviour will be performed again. While social learning theory describes the role of modeling in learning, it does not deal with other aspects of mentoring such as professional or emotional support (Jacobi, 1991).

The transition from the industrial era to the information era has profound implications for educational systems. Well-paying industrial and manufacturing jobs demanding minimal cognitive skills are rapidly shrinking (Jacobi, 1991). Communication and critical thinking skills are required to fulfill the more complex occupational roles and demands of contemporary life. Students must be taught how to educate themselves to become adaptable, proficient learners. Bandura has noted that "the hope and future of individuals and their societies reside in their capacities for self-renewal" (p.213).

Bandura (1997) further noted that efficacy beliefs are intimately involved in the cultivation of cognitive competencies. These mediators include cognitive, motivational, affective, and selective processes. Bandura found three ways in which efficacy beliefs operate as contributors to the development of cognitive competencies governing academic achievement: student’s beliefs in their efficacy to master different academic subjects; teachers’ beliefs in their personal efficacy to motivate and promote learning in their students; and faculties’ collective sense of efficacy that their students can accomplish significant academic progress.

Bouffard-Bouchard, Parent, and Larivee (1991) corroborated Collins (1982) finding that students with stronger belief in their efficacy were able to solve more problems, rework those in which they failed, and work more accurately than children of equal ability with less self-efficacy. Bouffard-Bouchard (1990) further connected the causal contribution of efficacy beliefs to cognitive functioning in a study where high or low efficacy beliefs were instilled in students compared with fictitious peer norms irrespective of their actual performance. Students whose sense of efficacy was raised set higher aspirations for themselves, demonstrated greater strategic flexibility problem-solving, achieved higher intellectual performances, and provided more accurate evaluation of their performances than those with lower self.

Schunk (1996) used an informative experimental paradigm that enhanced our understanding of factors that affect perceived cognitive efficacy and its impact on scholastic performance. The researcher’s subjects presented severe deficits in mathematical and language skills. The participants followed a self-directed learning program of basic principles and practices applied to mathematical problems. This was supplemented with instructional social influences that can affect their beliefs of their cognitive efficacy. The influences included modeling of cognitive operations, instruction in higher order strategies, and the use of different forms of performance feedback, self appraisal of capabilities, and positive incentives and aspirational goals as further motivators. In this paradigm, the researcher was able to remove ambiguity about the source and direction of causation through experimental variation in the design of the study. The acquisition of cognitive sub-skills showed the researcher that the contribution of efficacy beliefs to academic performance was more important than the contribution of acquired skills.

Schunk (1996) found that although efficacy beliefs are influenced by acquisition of cognitive skills, it is not a reflective concept. Accordingly, several factors may account for the predictive superiority of efficacy belief over acquired skills. Subjects vary in how they interpret, store, and recall their successes and failures. They evaluate social influences that contribute to efficacy beliefs independently of skills. Academic performances are the products of cognitive capabilities applied through motivational and other self-regulatory skills. Schunk concluded that perceived self-efficacy is a better predictor of intellectual performance than skills alone. Bandura and Schunk (1981) noted that perceived efficacy impacts directly on academic performance by affecting quality of thinking and effective use of acquired skills, and indirectly by heightening persistence in the search for solutions. The motivational link was convincingly demonstrated when efficacy beliefs were altered by arbitrary means without changing skills. Other researchers (Brown & Inouye, 1978; Lyman, Prentice-Dunn, Wilson, & Bonfilio, 1984) confirmed that individuals with high efficacy were persisters in trying to solve intractable or insoluble intellectual problems.

Further, researchers (Pajares, Urdan, & Dixon, 1995; Pajares & Kranzler, 1995; Pajares & Miller, 1994) found that efficacy beliefs play an influential mediating role in academic achievement. These factors included level of cognitive ability, prior educational preparation and attainment, gender, and attitudes toward academic activities. The researchers concluded that the more these factors altered efficacy beliefs, the greater the impact they had on academic achievement.

Bandura (1991) acknowledged the need for sustained involvement in activities to develop cognitive competencies. Enduring self-motivation is achieved through personal challenges that create a sense of efficacy and self-satisfaction in performance accomplishments. Apparently, proximal or short- term goals serve as cognitive motivators and effective vehicles for developing a sense of personal efficacy. Self-motivation is sustained by combining long-range goals that set the course of one’s endeavours with a series of tangible sub-goals that guide and sustain efforts along the way. According to Bandura, these sub-goals provide positive indicators of success that verify this sense of personal efficacy. An earlier study by Bandura and Schunk (1981) showed that students who motivated themselves with proximal sub-goals made rapid progress, achieved substantial mastery of mathematic operations and developed a sense of mathematical efficacy, while distal goals had no demonstrable effects.

Schunk and Rice (1989) demonstrated that the benefits of goal-setting to cognitive development are replicable across different academic domains and types of goals. Schunk (1996) further concluded that the progress one makes with learning goals for gains in knowledge and skill is more effective in developing a sense of personal efficacy and proficiency than goals that focus solely on level of performance accomplishment. Proximal learning goals, therefore, create the means for these proposed accomplishments.

Bandura (1991) found that those who do not set improvement goals are outperformed by those who set themselves goals for progressive improvement accompanied by feedback. Informative feedback enables one to achieve progress leading to beliefs of personal efficacy not evident by level of performance attainments. Schunk and Swartz (1993) verified the benefits of combining training in strategies with feedback of progress in mastering them particularly where transferred skills are necessary. Locke and Latham (1990) identified that self-set goals increase satisfaction but do not improve performance over assigned goals. Researchers further noted that increased perceived efficacy is accompanied by higher academic attainments (Bandura, 1997).

In the area of social cognitive theory, Bandura (1997) adopted an ecological perspective on the contribution of efficacy beliefs to cognitive and social development. Family, education and peer influences operate as multiple interacting influences in shaping the student’s development. Hinshaw (1992) noted that among the different types of competencies, academic deficiencies are those most likely to predict adoption of antisocial styles of behaviour.

At the university level, students need to choose which education directions to pursue and assume responsibility for their own learning. Students who have a high sense of efficacy are more successful in regulating their learning and achieve better academically than those who are uncertain about their intellectual capabilities (Pintrich & Schrauben, 1992). Multon, Brown and Lent’s (1991) meta-analysis of academic achievement provided conclusive evidence showing that efficacy beliefs contribute significantly to scholastic performance. This was supported by other researchers (Shell, Murphy, & Bruning, 1989) who found that beliefs in personal efficacy have substantially greater impact on academic performance than the personal, social, and occupational outcomes expected for proficient performance. Lent, Lopez and Beischke (1993) suggested that students’ beliefs in their academic efficacy mediate the relationship between ability and educational goals and achievements. For the institutions, teachers, or researchers, these findings suggest that the development of scholarly careers, mastery experiences, modeling of strategies, and supportive feedback should be structured in ways that build a clear and strong sense of efficacy.

Researchers (Suls, 1986; Wei, 1994) suggested that social comparison theory would support self-efficacy. They examined the process of seeking out people who are similar to help evaluate themselves. In this process, according to Suls (1986), individuals make causal attributions regarding beliefs or abilities on a given task.

Coleman's (1988) conception of "social capital" identified the importance of a network of sustained personal connections to convey expectations and conventional norms and which can also be acquired through rich and extensive interactions with adults. Coleman (1990) showed how long-standing features of social organization such as trust, norms and networks--all of which constitute social capital--foster spontaneous cooperation and coordination for the common good. According to the theory, the development of social capital by students is significant because it contributes to their readiness to internalize school norms and expectations. These expectations call for personal effort to develop the knowledge and skills that make up human capital, without which students may drop out of school unprepared for responsible participation in mainstream society.

Coleman (1990) explained how social structure shapes and constrains rational action through an understanding of relationship patterns between people. The researcher addressed the source of trust as a central problem in rational choice theory. In observing that differences in the nature of social networks affected the levels of trust among individuals within those networks, Coleman concluded that socio-structural context must be an important factor in construction rational action. This lead to further observations of the creation of outstanding obligations between two individuals constituting a tie between them as well as a resource from which people can draw in times of need. Along with it being rational and self-serving to create social capital that one can draw from in the future, a basis for generalized trust is created when the pattern is in a social network.

Kerka (1997) found that mentoring supports much of what is currently known about learning, including the socially constructed nature of learning and the importance of experientially-situated learning experiences. Constructivism explains that knowledge is synthesized, modified, and is evolutionary in character (Novack, 1985). Researchers (Driver et al., 1994; Hewson et al., 1992; West & Pines, 1985) noted that the learner is not isolated in this interaction between perceptions and internal rules because the social construction of knowledge is critical. Consequently much of what is perceived as knowledge or understanding results from a process of socialization. The impact of the socialization process on individual perspectives and understandings has been well-documented (Erickson, 1991; Sarason, 1981; Bandura, 1977; Erickson, 1991; Sarason, 1981; Bandura, 1977; Lortie, 1975; Kuhn, 1970). Constructivist theory and socialization theory can be interpreted as being deeply embedded in mentoring and learning. Experts facilitate learning by modeling problem-solving strategies which guides learners while they articulate their thought processes. They coach learners with appropriate scaffolds or aids, gradually decreasing assistance as learners internalize the process and construct their own knowledge and understanding (Kerka, 1997). Mentors, functioning as experts, provide authentic, experiential learning opportunities in their diverse roles (Galbraith & Cohen, 1995; Haney, 1997). Bell (1997) used the analogy of birds guiding their young to leave the nest to explain the mentor’s role in guided learning. Kaye and Jacobson (1996) identified trust (social capital) as the foundation of the relationship where mentors give protégés a safe place to try out ideas, skills, and roles with minimal risk. The knowledge acquired is constantly reinterpreted and developed through practice (Cleminson and Bradford, 1996).

The interpersonal relationship of mentor and mentee is recognized as essential to learning in a social context (Kerka, 1997). Galbraith and Cohen (1995) identified two primary functions related to mentoring - career/instrumental and psychosocial. Instrumentally, the mentees benefit from their mentor’s knowledge, contacts, support, and guidance. Psychosocially there is an internal value developed from the ongoing interpersonal dialogue, collaborative critical thinking, planning, reflection, and feedback. This function of mentoring is a form of relational learning (learning from relationships), the value of which is becoming increasingly evident in a less hierarchical, team environment (Kerka, 1998).

Bierma (1996) studied mentoring relationships for executive women. The researcher found that relationships informed the women about their company’s culture and helped them process both cognitive and experiential learning experiences. According to Kerka (1998), mentoring is a personalized and systematic way to be socialized into an organization’s culture. This cultural competence is important in work and academic environments. Galbraith and Cohen (1995) found that first-generation college students experience culture-clash in academic environments that can be overcome with a mentor’s guidance. Cleminson and Bradford (1996) cautioned against socialization as a constraining means of limiting exposure to defined practices, views and expectations. The personal relationship can be adversely affected by gender, racial and ethnic differences. Ensher and Murphy (1997) found that perceived and actual similarity between partners affected the amount of instrumental and psychosocial support mentors provided as well as mentee satisfaction. In contrast, Russell and Tinsley (1997) showed mixed results for diversified mentoring. Jossi (1997) argued that race and gender do not play a role in mentor selection although mentors need to be sensitive to different cultural perspectives.

Seen throughout the literature on mentoring is an array of roles, functions and responsibilities attributed to those who serve as mentors (Jacobi, 1991). Lacking in the literature is a delineation of mentor functions, roles or responsibilities directly associated with positive mentoring relationships in undergraduate education. Jacobi (1991) noted that few studies have documented or confirmed which mentor functions are correlated with increased student academic success, enhanced student development, and overall positive education experiences.

Kram (1988) conducted systematic and detailed research on developmental mentoring relationships within the business setting. The researcher identified two given functions, career functions and psychosocial functions which were elaborated upon in later studies on mentoring within education (Flaxman & Ascher, 1992, Kerka, 1997). According to Kram, career functions relate to providing sponsorship, visibility, coaching, protection, and challenging assignments. Psychosocial functions are aspects of the relationship that enhance sense of competence, identity, and effectiveness in a professional role. Flaxman (1988) categorized mentor functions based on Kram’s analysis and used the term "instrumental" instead of "career" to describe functions which were considered extrinsic and directed at facilitating the mentee in changing the external environment.

Cohen (1993) conducted research of mentor functions within higher education aimed at adult learners while also incorporating functions which have been traditionally associated with facilitating at-risk student populations. The researcher developed a self-assessment instrument for mentor effectiveness. Cohen described six broad categories of mentor emphasis or focus that are critical to mentors of adult learners in undergraduate education. These functions are described as follows: relationship emphasis, in which the mentor conveys genuine understanding of the student’s feelings; information emphasis, in which the mentor provides detailed information and offers suggestions to guide the current and future development and achievement of students’ personal, academic, and career goals; facilitation focus in which the mentor guides students through a reflective review of their interests, abilities, ideas, and beliefs in an effort to facilitate the decision-making process; confrontive focus, in which the mentor respectfully challenges students’ decisions as they relate to their development as adult learners; mentor model, in which the mentor self-discloses fitting life experiences in an effort to serve as a role model and to personalize the mentoring relationship; and student in which the mentor stimulates students’ critical thinking in relation to developing their personal and professional goals.

Awbrey (1993) conducted a study indicating that students have a tendency to select education-related individuals for career mentor functions while relying on friends for psychosocial mentoring functions. Jacobi (1991) concluded that more research was needed to determine which mentoring functions are most closely associated with undergraduate academic success and retention.

In a qualitative study of five exemplary intergenerational mentoring programs, Freedman (1988) determined that two types of relationships were formed in the mentoring programs: primary relationships and secondary relationships. Primary relationships were identified by the mentor’s unconditional commitment, great intimacy, and engagement of both the "good" qualities and "bad" qualities of the mentee. Secondary relationships depicted more limited but supportive involvement, with the mentor focusing on functions and tasks and retaining more emotional distance. When the purpose of a mentoring program was to improve students’ academic performance and retention, primary relationships may be too close for both mentor and mentee to feel comfortable, especially between cross-gender pairs (Sullivan, 1992).

In attempting to discern the correlation of function to outcome in mentor relationships, the level of intimacy or intensity characterizing the mentoring relationship makes it unclear. Some have described mentoring as the highest end on a continuum of helping relationships (Hunt & Michael, 1983; Kram, 1985). Others (Shapiro, Haseltine, & Rowe, 1978) use a continuum with points in a lickert scale with peer pals at the lowest rank, followed by guides, sponsors, and mentors who represent the most intense and paternalistic type of relationship. Clawson (1980) assessed the relationship by the degree of mutuality in the relationship and the comprehensiveness of the mentor’s influence on the mentee. Alternately, Kram and Isabella (1985) suggested that further studies be conducted to determine how individual differences in developmental task, self-concepts, and attitudes toward intimacy and authority, as well as other individual attributes, shaped the nature of the mentoring relationships.

Gallimore (1992) contrasted planned mentoring and natural mentoring. Planned or formal mentoring is the structured matching of mentor and mentee while natural mentoring relationships usually arise from context and sometimes accidentally. Flaxman (1988) identified natural mentoring relationships as taking the form of friendships, collegiality, advocacy, coaching, and pseudo-parenting usually resulting in a long-term relationship. These are typically voluntary relationships with the mentee seeking the mentor through some link.

Literature depicts famous mentor pairs including Merlin with the young King Arthur, Copland with Leonard Bernstein, and Fleiss with Freud (Flaxman, 1988). According to Flaxman, academic research, popular literature, and personal anecdotal accounts emphasize the value of natural mentoring in every conceivable vocation.

In comparison to natural mentoring, planned mentoring was more purposeful and less intimate. The duration was shorter, the mentor and mentee were matched, and the encounters were less frequent and less sustained over time (Flaxman, 1988). Faddis (1988) pointed out that planned mentoring gained mutual commitment to the relationship from the beginning because of the clearly defined objectives based on the needs of the mentee, as well as, the ability of the mentor to meet the needs and have a plan by which the objectives could be achieved.

Redmond (1990) determined that planned mentoring was a way to address society’s injustices by providing increased opportunities for advancement for racial and ethnic groups targeting those who had experienced societal racism, lack of access to social resources and inadequate educational preparation. The researcher’s concepts are used in many of the current specialized mentoring programs for minorities and at-risk students.

Modern planned mentoring programs started in the corporate world in the late 1970s (Brown, 1995). Collins and Scott (1978) described and glorified mentorship in an article profiling three male executives in The Harvard Business Review. The use of planned mentoring came at a time when women and racial minority groups were entering managerial positions without the natural male mentoring connections (Brown, 1995). Mentoring programs have since become widespread in business, nursing and education (Cheng & Brown, 1992; Slicker & Palmer, 1993).

Planned mentoring programs for at-risk students became prevalent in the 1980s (Brown, 1995). Planned mentoring is a research concept at colleges and universities seeking to improve retention and graduation rates (Ross-Thomas & Bryant, 1994). Redmond (1990) found that psychosocial comfort of mentoring empowers students to successfully remain at the institution. Although there is a wide variety of research available discussing planned mentoring in higher education, few studies are related to undergraduate academic outcomes (Grissom, 1998). Johnson and Sullivan (1995) identified the rampant decentralized growth in the current mentoring movement in higher education with little available research to help direct practice.

This is a combined quantitative and qualitative research project designed to study the effects of mentorship in supporting first-year students through the transition from high school to university. The effects will be measured quantitatively by comparing academic averages before study with the academic averages following one semester of mentorship for the research subjects and the control group. The Manitoba Satisfaction Survey for first year students will be conducted for both groups to determine effect of mentorship on student satisfaction. There are 80 research subjects in total. The subjects will be randomly selected from the volunteer pool to participate in either the research group or the control group. The qualitative potion of the research will be in the form of audio- or video-taped interviews of the randomly selected mentors and mentees to evaluate the qualities of the program to the mentors and mentees respectively.

Instruments for analysis:

meet with their mentor on a regular basis – once per week for a minimum of 30 minutes to a maximum of 2 hours (September to May),

develop an education plan with their mentor,

assess the program in meeting their needs as a student, and

maintain confidentiality in participation in the study.

The mentor will:

2. meet with the subject at a convenient time in the Faculty of Education building,

3. contact the subject by email or by phone,

4. establish a safe, nurturing environment,

5. promote confidentiality within ethical guidelines,

6. apply practical strategies to enhance the subject’s learning,

7. motivate the subject to set realistic education goals,

8. create timelines with the subject,

9. assist the subject to identify and use appropriate resources offered by the university,

 

	1. be a Faculty of Education student who will be marked on their involvement in this project.,
	10. make the subject aware of the various workshops and activities that would enhance the subject’s academic performance and achievement,

will be assessed and graded by the instructor as a course requirement,

maintain professionalism throughout the study, and

guide the subject toward resources available on campus.

The Mentor Will Not:

provide personal, psychological, or academic counseling, nor

be a tutor.

Those Assigned to the Control Group Will:

give permission to the researcher to obtain their OAC averages and then their final averages at the end of the first semester

2. complete the Manitoba Satisfaction Survey conducted by the researcher

This program will be assessed by the researchers through logs by mentors and self and program assessment by student subjects, mentors and academic advisors. The assessment instruments (to be developed) will provide information on the purpose of each meeting, length of meeting, steps initiated and completed, assessment of the meeting, and follow up expectations. The student subjects will develop an Individual Education Plan (similar to, but not exclusive of, that established in high school) to assess progress in meeting their goals.

The researcher along with the academic advisors of the Faculty of Science and the Faculty of Arts and Social Sciences and Teacher Advisor Coordinator from the local School will train the mentors and assess their progress as a component of their work in 80-303, an integrated course. A research project is the culminating assessment task for the mentors that are presented to their peers and the Faculty Advisors.

The names of the subjects will remain confidential, as they will be given numbers for identification purposes. The subject data will remain confidential in the student logs since the participant will be referred to by number rather than by name. The researcher will collect both quantitative and qualitative data from the program. The information collected will remain with the researchers to be analyzed and used in examining the effects of the program on retention.

Potential Risks and Discomforts: The only possible risk is a poor mentor-mentee match. If the differences are irreconcilable than, either party may drop out of the program and/or seek a different partner.

Potential Benefits: If the program proves to be successful, then mentorship can be made available for all students requesting it. It will provide a service to meet the needs of first-year students in making the transition to university a successful and productive journey. It will provide students with the skills needed to continue successfully throughout their post secondary career.

Confidentiality: Any information that is obtained in connection with this study and that can be identified with the subjects will remain confidential and will be disclosed only with the subjects’ permission. Numbers will identify participants; no names will appear in the logs. The student mentors will be in charge of the logs until the end of the program and are bound by confidentiality not to reveal the contents outside of the project. All logs and data collected will remain in a safe in the office of the Faculty of Education and will be destroyed, by shredding, following publication of the research for educational purposes. Discussions by mentors in their Advisory class will not disclose any names. Only number will identify students.

Bibliography

American College Testing Program (1998). National College Dropout and Graduation Rates, 1997. Retrieved from the world wide web at: http://www.act.org.news/04-0d1b98.html , March 23, 2002.

Astin, A. W. (1972). College dropouts. A national Profile. ACE Research Reports, 7(1).

Astin, A. W. (1974). Preventing students from dropping out. San Francisco, CA: Jossey- Bass.

Astin, A. W. (1977). Four critical years. San Francisco, CA: Joseey-Bass.

Astin, A.W. (1984). Student Involvement: A developmental theory for higher education. Journal of College Student Personnel (25),p. 297- 308.

Astin. A. W. (1993). What matters in college: Four critical years revisited. San Francisco, CA: Joseey-Bass.

Astin, A. W., Tsui, L., & Avalos, J. (1996). Degree attainment rates at American colleges and universities: Effects of race, gender, and institutional types. ERIC Document Reproduction Service No. ED 400749.

Awbrey, S. (1993). Sources of mentors selected by undergraduate students at Michigan State University. (Eric Document Reprduction Service No. ED 363 626).

Bandura, A. (1986).Social foundations of though and action: A social cognitive theory. Englewood Cliffs, NJ: Prentice-Hall.

Bandura, A. (1989). Regulation of cognitive processes through perceived self-efficacy. Developmental Psychology, 25, 729-735.

Bandura, A. (1997). Self-efficacy: The exercise of control. USA: W.H. Freeman and Company.

Bandura, A. & Schunk, D. H. (1981). Cultivating competence, self-efficacy and intrinsic interest through proximal self-motivation. Journal of Personality and Social Psychology, 41, 586-598.

Bandura, A & Walters, R. H. (1963). Social learning and personality development. NY: Holt, Rinehart and Winston, Inc.

Beal, P. E. & Noel, L. (1980). What works in student retention? Iowa City, IA: American College Testing Program.

Bean, J. (1980). Dropouts and turnover: The synthesis and test of a causal model of student attrition. Research in Higher Education, 12, 155-187.

Bean, J. (1983). The application of a model of turnover in work organizations to the student attrition process. The Review of Higher Education, 6, 129-148.

Bean, J. P. & Metzner, B. S. (1985) A conceptual model of nontraditional undergraduate student attrition. Review of Education Research, 55, 485-540.

Bell, C.R. (1997). The Bluebird's Secret: Mentoring with Bravery and Balance.Training and Development 51(2), 30-33.

Bierema, L.L. (1996). How Executive Women Learn Corporate Culture. Human Resource Development Quarterly 7(2), 145-164.

Blackwell, J.E. (1989). Mentoring: An action strategy for increasing minority faculty. Academe, 75, 8-14.

Blimling, G. S. (1989). A meta-analysis of the influence of college residence halls on academic performance. Journal of College Student Development, 38, p. 3-12.

Bouffard-Bouchard, T. (1990). Influence of self-efficacy on performance in a cognitive task. Journal of Social Psychology, 130, 255-263.

Bouffard-Bouchard, T., Paretn, s., & Larivee, S. (1991). Influence of self-efficacy on self-regulation and performance among junior and senior high-school age students. International Journal of Behavioural Development, 14, 153-164.

Braunstein, A, & McGrath, M. (1997). The retention of freshmen students: An examination of the assumptions beliefs, and perceptions held by college administrators and faculty. College Student Journal, 31 (2), 188-200.

Brown, A. (1995). New advisement system at Baker University. The freshman Year Experience Newsletter, 7 (3). 6.

Brown, I, Jr., & Inouye, D. K. (1978). Learned helplessness through modeling: The role of perceived similarity in competence. Journal of Personality and Social Psychology, 36, 900-908.

Carr, R. (2001). The changing nature of mentorship in Canada. Peer Resources. Retrieved from the world-wide web at: http://www.peer.ca/Projects.html on March 23, 2002.

Capolupo, R. F., Fuller, R., & Wilson, L. (1995). Retention at Drexel University: A look at a successful model. The Act 101 Journal 2(2). 8-9.

Cheng, M. & Brown, R. S. (1992). A two-year evaluation of the peer pilot project for new teachers. Toronto Board of Education. (ERIC Document Reproduction Service No. ED 346 082).

Choices into Action, (1999). Ontario Ministry of Education Document Services. Retrieved from the world wide web at: www.edu.gov.on.ca , March 23, 2002.

Clawson, J. G. (1980). Mentoring in managerial careers: Work, family and the career: New frontiers in theory and research. NY: Praeger.

Cleminson, A., and Bradford, S. (1996).Professional Education. Journal of Vocational Education and Training,,48(3), 249-259.

 

Cohen, J. (1986). Theoretical considerations of peer tutoring. Psychology in the Schools, 23, 175-187.

Collins, J. L. (1982). Self-efficacy and ability in achievement behaviour. Paper presented at the annual meeting o f the American Education Research Association, New York.

Collins. E. G. C., & Scott, P. (1978) Everyone who makes it has a mentor. Harvard Business Review, 56, 217.

Coleman, J. S. (1987). Families and schools. Education Researcher, 16(6), 32-38.

Colton, G. M., Connor, U. J., Shultz, E, & Easter, L. M. (1999). Fighting attrition: One freshman year program that targets academic progress and retention for at-risk students. Journal of College Student Retention, 1(12). 147-162.

CSRDE report, (2001). Highlights from the CSRDE report. Retrieved from the world wide web at: www.montclair.edu/pages/vpbpit/CSRDE_AY2001.pdf. On March 23, 2002.

Dale, P. (1992). A successful college retention program. Indiana. (ERIC Document Reproduction Service No. ED 380 017).

Daloz, L. A. (1987). Effective teaching and mentoring: Realizing the transformational power of adult learning experiences. SF: Jossey -Bass.

Day, B. E., & Breegle, G. (1989). Retention in higher education: A statewide perspective. Paper read at Association for Institutional Research, Baltimore. (From Higher Education Abstracts, 25 (1) no. 0231-25.

Driver, R., Ssoko, J., Leach,J., Mortimer, E., & Scott, P. (1994). Constructing scientific knowledge in the classroom. Educational Researcher, 23(7). 5-12.

Ensher, E. A., & Murphy, S. E. (1997). Effects of race, gender, perceived similarity, and contact on mentor relationships. Journal of Vocational Behaviour 50(3), 460-481.

Erickson, F. (1991). Conceptions of school culture: an overview. In N. Wyner (Ed.,), Current Perspectives on the Culture of Schools (pp. 1-2): Brookline Books.

Erkut, S. & Moros, J. R. (1984). Professors as models and mentors for college students. American Education Research Journal, 21, 399-417.

Faddis, B. (1988). The role of mentoring in higher education. Community Review, 8(2), 22-27.

Fidler, P. P. (1991). Relationship of freshman orientation seminars to sophomore return rates. Journal of the Freshman Year Experience, 3 (1), 7-38.

Flaxman, E. (1988). Youth mentoring: Programs and practice. Urban Diversity Serieis, 97, 257-268.

Flaxman, E. & Ascher, A. (1992). Mentoring in action: The effects of programism. NY: Columbia University.

Freedman, M. (1988). Partners in growth: Elder mentors and at-risk youth. ERIC document Reproduction Service no. ED 303 561.

Gallimore, R. (1992). The development and sociocultural foundations of mentoring. NY: Longman.

Galbraith, M.W., & Cohen, N.H. (1995) Mentoring: New strategies and challenges: New directions for adult and continuing education. CA: Jossey-Bass.

 

Gardner, J. N. (1996). Helping America's first-generation college students: A bottom-line list of institutions of higher learning must do. About Campus, Nov-Dec, 31-32.

Gordon, V., & Grites, T. J. (1984). The freshman seminar course, helping students to succeed. Journal of College Student Personnel, 25(4), 315-320.

Grissom, C. B. (1998). Perceived effects of a formal mentor program on undergraduate students at a small liberal arts college. (Doctoral dissertation, Indianan University, 1998). Dissertation Abstracts International, 981806.

Haensly, P. A. & Parson, J. L. (1993). Creative, intellectual and psychological development through mentorship. Youth and Society, 25(2), 202-220.

Haney, A. (1997). The role of mentorship in the workplace. In MC. Taylor (Ed), In Workplace education. ON: Culture Concepts (pp.

Hinshaw, S. P. (1992). Externalizing behaviour problems and academic underachievement in childhood and adolescence: Causal relationships and underlying mechanisms. Psychological Bulletin, 111, 127-155.

Hewson, P. W., Zeichner, K. M., Tabachnick, B.R., Blomker, K. B., & Toolin, R. (1992). A conceptual change approach to science teacher education at the University of Wisconsin-Madison. Paper presented at the Annual Meeting of the American Education Research Association, San Francisco, CA.

Hunt, D. M. & Michael, C. (1983). Mentorship: A career training and development tool. Academy of Management Review, 8, 475-485.

Jacobi, M. (1991). Mentoring and undergraduate academic success: A literature review. Review of Education Research, 61(4), 505-532.

Jones, J. W. (1989). Personality and epistemology: Cognitive social learning theory as a philosophy of science. Zygon, 24(1), 23-38.

Johnson, C. S. (1989). Mentoring programs. The freshman year experience: Helping students succeed and survive in college. SF: Jossey-Bass.

Jossi, F. (1997). Mentoring in changing times. Training & Development, 51(8), 50-54.

Kaye, B., & Jacobson, B. (1996). Reframing mentoring. Training & Development 50(8), 44-47.

Kerka, S.(1997). Constructivism, workplace learning, and vocational education. ERIC digest no. 181. (ED 407 573).

Kerka, S. (1998). New Perspectives on mentoring. ERIC documents, digest no. 194.

Kram, K. E. (1984). Phases of mentoring relationships. Academic Mentoring Journal, 26(4), 608-625.

Kram, K. E. & Isabella, L.A. (1985). Mentoring alternatives: The role of peer relationships in career development. Academic Management Journal, 28 (1), 110-132.

Kuhn, T. (1970). The structure of scientific revolutions. Chicago: Chicago University Press.

Lang, M. & Ford, C. (1992). Strategies for retaining minority students in higher education. IL: Charles C. Thomas.

Lent, R.W., Lopez, F.G., & Bierschke, K. J. (1993). Predicting mathematics-related choice and success behaviours: Test of an expanded social cognitive model. Journal of Vocational Behaviour, 42, 223-236.

Levine, A. (1991). Perspectives on the freshman year. Columbia, SC: National Resource Center for the Freshman Year Experience.

Levinson, D. (1978). The seasons of a man’s life. NY: Knopf Publishers.

Locke, E.A., & Latham, G. P. (1990). A theory of goal setting and task performance. NJ: Prentic-Hall.

Lortie, D. C. (1975). School teacher – a sociological study. Chicago: Chicago University Press.

Lyman, R. D., Prentice-Dunn, S., Wilson, D. R. & Bonfilio, S. A. (1984). The effect of success or failure on self-efficacy and task persistence of conduct-disordered children. Psychology in the Schools, 21, 516-519.

McCormack-Brown, K. (1998). Social Cognitive theory. Retrieved from the world wide web at: http://hsc.usf.edu/~kmbrown/Social_Cognitive_Theory_Overview.htm., on March 23, 2002.

Milem, J. F., & Berger, J. B. (1997) A modified model of college student persistence: Exploring the relationship bet1ween Astin’s theory of involvement and Tinto’s theory of student departure. Journal of College Student Development, 38(4), 387-399.

Meriam, S. (1983). Mentors and protégés: A critical review of the literature. Adult Education Quarterly, 33, 161-173.

Moses, Y. T. (1989). Black women in academe: Issues and strategies. ERIC Document Reproduction Service No. ED 311817.

Multon, K. D., Brown, S. D., & Lent, R. W. (1991). Relation of self-efficacy beliefs to academic outcomes: A meta-analytic investigation. Journal of Counseling Psychology, 38, 30-38.

Nagda, B. A., Gregerman, S. R., Jonides, J., Von Hippel, W., & Lerner, J. S. (1998). Undergraduate student –faculty research partnerships affect students retention. The Review of Higher Education, 22 (1), 55-72.

Novack, J. D. (1985). Metalearning and metaknowledge strategies to help students learn how to learn. In L. West & A. L. Pines (Eds). Cognitive structure and conceptual change (pp. 189-209). FL: Academic Press.

Pajares, F. & Kranzler, J. (1995). Self-efficacy beliefs and general mental ability in mathematical problem-solving. Contemporary Educational Psychology, 20, 426-443.

Parajes, F & Miller, M. D. (1994). Role of self-efficacy and self-concept beliefs in mathematical problem-solving: A path analysis. Journal of Educational Psychology, 193-203.

Parajes, F., Urdan, T. C., & Dixon, D. (1995). Mathematics, self-efficacy and performance attainments of mainstreamed regular, special education and gifted students. Submitted for publication.

Pascarella, E. T., & Smart, J. C. (1991). Impact of intercollegiate athletic participation for African American and Caucasion men: some further evidence. Journal of College Student Development, 32, 123-130.

Pascarella, E. T. & Terenzini. P. (1977). Pattern of student-faculty informal interaction beyond the classroom and voluntary freshman attrition. Journal of Higher Education, 48(5), 540-552.

Paul, R. (2001). State of the University Address. University of Windsor. Retrieved from the world wide web at www.uwindsor.ca , March 23, 2002.

Peltier, G., Laden, R., & Matranga, M. (1999). Student persistence in college: A review of research. Journal of College Student Retention, 1(4), 357-375.

Pintrich, P. R. & Schrauben, B. (1992). Students’ motivational beliefs and their cognitive engagement in classroom academic tasks. In D. Schunk & J. Meece(Eds), Student perception in the classroom: Causes and consequences. (pp. 149-184). NJ: Erlbaum.

Redmond, S. (1990). Mentoring and cultural diversity in academic settings. American Behavioural Scientist, 34(2), 188-200.

Ross-Thomas, E. & Bryant, C. E. (1994). Mentoring in higher education: A descriptive case study. Education, 115(1), 70-78.

Russell, J.E.A., & Tinsley, H.E.A., (1997). Special issue on mentoring in organizations. Journal of Vocational Behaviour, 51(1),489-498.

Sarkar, G. (1993). SIAST Retention study: Factors affecting retention of first-year students in a Canadian Technical Institute of Applied Science and Technology. A Paper prepared for the: Canadian Institutional Researchers and Planners Conference.

Sarason, S. B. (1981). The culture of the school and the problem of change. Boston: Allyn and Bacon, Inc.

Schlossberg, N. K. (1984). Counseling adults in transition: Linking practice with theory. NY: springer.

Schunk, D. H. (1996). Goal and self-evaluative influences during children’s cognitive skill learning. American Educational Research Journal 33, 359-382.

Schunk, D. H. & Rice, J. M. (1993). Strategy fading and progress feedback: Effects on self-efficacy and comprehension among students receiving remedial reading services. Journal of Special Education, 27, 257-276.

Schunk, D. H. & Swartz, C. W. (1993). Writing strategy instruction with gifted students. Effects of goals and feedback on self-efficacy and skills. Roeper Review, 15, 225-230.

Shapiro, E., C., Haseltine, F. P., & Rowe, M.P. (1978). Moving up: Role models, mentors and the "patron system." Sloan Management Review, 19, 51-58.

Shell, D. F., Murphy, C. C., & Bruning, R. H. (1989). Self-efficacy and outcome expectancy mechanisms in reading and writing achievement. Journal of Educational Psychology, 81, 91-100.

Stegman, W., N. (1969). A study to develop living area activities designed to improve the retention ratio of potential student dropouts. Final Report. (ERIC Document Reproduction Service No. ED 035 379).

Strom, S. (1995). Enjoying the benefits of minority mentoring. The Freshman Year Experience Newsletter, 7 (3), 9.

Strommer, D. (1993). Portals of entry: University colleges and undergraduate divisions. Columbia, SC: National Resource Center for the Freshman Year Experience.

Suls, J. (1986). Notes on the occasion of social comparison’s thirtieth birthday. Personality and social Psychology Bulletin, 12(3), 289-296.

Terenzini, P., T. (1995). First-generation college students: Characteristics, experiences, and cognitive development. Pennsylvania. (ERIC Document Reproduction Service No. ED 387 004).

Tinto, V. (1987). Leaving college: Rethinking the causes and cures of student retention. Chicago, II: The University of Chicago Press.

Tinto, V. (1993). Leaving college: Rethinking the causes and cures of student retention. Chicago, II: The University of Chicago Press.

Tinto, V. (1996). Restructuring the first year of college. Planning for higher Education, 25, 1-6.

Tinto, v. (1998). Colleges as communities: Taking research on student persistence seriously. The Review of higher Education, 21(2), 167-177.

Thompson, J., Samiratedu, V., & Rafter, J. (1993). The effects of on-campus residence on first-time college students. NASPA Journal, 31, p. 41-47.

Tucker, J. E., (1999). Tinto’s model and successful college transitions. Journal of College Student Retention, Vol. 1(2) 163-175.

Watford, J. (1995). Revisiting the role of HBCU’s in the academic development and retention of student-at-risk. The Act 101 Journal, 2 (2), 4-7.

Wei, J. (1994). A study of the effects of a community college mentoring program on student academic performance and retention. Unpublished doctoral dissertation, University of Central Florida.

West, H. T., & Pines, A.L. (Eds). (1985). Cognitive structure and conceptual change. FL: Academic Press.

Wrightsman, L. S. (1981). Research menthodologies for assessing mentoring. Paper presented at the Annual conference of the American Psychological Association, Los Angeles, CA.

Wunsh, M. A. (1994). Mentoring revisited: Making an impact on individuals and institutions. New Directions for Teaching and Learning. SF: Jossey-Bass.