ERIC EJ1164575: Strengths-Based Advising Approaches: Benefits for First-Year Undergraduates

2017·0.1 MB·English

by  ERIC

Strengths-Based Advising Approaches: Benefits for First-Year
Undergraduates
Krista M. Soria, University of Minnesota
Nicole L. Laumer, University of Minnesota
Dale J. Morrow, University of Minnesota
Garrett Marttinen, University of Minnesota
We explored the benefits of strengths-based than their peers who did not use their strengths in
academic advising approaches for first-year the workplace (Tomkovick & Swanson, 2014).
students (N ¼ 1,228). We used propensity score Hence, the benefits of strengths practices initiated
matching techniques to create matched pairs of inhighereducationpersistintostudents’liveslong
studentswhodidanddidnotengageinstrengths- after they graduate.
based advising conversations with an advisor. Framedwithinprinciplesofpositivepsychology
First-year students who experienced strengths- (Seligman & Csikszentmihalyi, 2000; Snyder,
based conversations had significantly higher Lopez, & Pedrotti, 2010), strengths-based ap-
rates of first-year retention and graduation in 4 proaches are based on the belief that individuals
years, levels of engagement, and academic self- achieve greater outcomes when they discover and
efficacy than students who did not participate in develop their natural talents instead of solely
these conversations. Focus groups of 21 advisors mitigating their areas of weakness. Schreiner and
providedinsightsintostrengths-basedadvisingin Anderson (2005) connected strengths with aca-
3 findings: strengths approaches facilitated demic advising in ground-breaking work that
advising relationships (thereby supporting stu- shifted the focus from problems to possibilities.
dents’ engagement, retention, and graduation), They hypothesized that advisors who utilize
enhanced students’ self-awareness and confi- strengths-based approaches in their advising prac-
dence, and advanced advisors’ own personal tices awaken a renewed sense of motivation and
and professional development (thereby positively engagement in students, resulting in students who
influencing student success). possess and exhibit greater confidence, self-
awareness,andtheabilitytofacenovelexperiences
[doi:10.12930/NACADA-16-010]
in a complex, ever-changing society.
KEY WORDS: academic advising, engagement, Despite these positive acclamations, to date,
first-year students, graduation, retention, little research has emerged to support the claims
strengths, StrengthsFinder about strengths-based advising. Therefore, we
investigated the effectiveness of strengths-based
A decade has passed since Schreiner and academic advising approaches. To meet our first
Anderson’s (2005) paradigm-shifting article about goal, an examination of the effects of strengths-
strengths-based academic advising was published. basedacademicadvisingconversationsasreported
During the time that followed, researchers investi- by students, we used quasi-experimental proce-
gated the utility of strengths-based approaches in dures (propensity score matching techniques) to
higher education as potential catalysts for under- construct control groups (students who did not
graduates’success and found that strengths-based engage in strengths-related conversations with
approachesareassociatedwithincreasesinstudent advisors) and treatment groups (students who
engagementand confidence (Soria & Stubblefield, engaged in strengths-related conversations with
2014), sense of belonging (Soria & Stubblefield, advisors) similar to those created for randomized
2015b),leadershipdevelopment(Soria,Roberts,& experiments. Our second goal, to investigate the
Reinhard, 2015), and retention (Soria & Stubble- effects of strengths-based advising conversations
field, 2015a,b). The extended effects of strengths- from the perspectives of advisors who apply these
basedapproachesapplytostudents’postgraduation approaches, was explored through focus group
experiences as well; for instance, college alumni discussions. In this paper, we address both
who utilized their strengths in the workplace perspectives to answer the following research
reported significantly higher job satisfaction, question: What are the effects of strengths-based
organizational commitment, and quality of life academic advising on first-year undergraduates’
NACADA Journal Volume 37(2) 2017 55
Soria et al.
engagement, academic self-efficacy, retention, and (cid:2) teach students that they can transfer their
4-year graduation rates? strengths to several areas of their lives,
(cid:2) help students identify the types of envi-
Strengths-Based Approaches in Higher ronments that might help them flourish,
Education and
Although many strengths-related assessments (cid:2) develop an action plan with students that
appear in the literature, we framed our research they can take to meet their goals.
using the conceptualization of strengths put forth
Although these frameworks are useful to
byGallup,andinparticular,weadoptedtheClifton
practitioners—and researchers continue to investi-
StrengthsFinder 2.0 assessment (Gallup, 2017b),
gate and unpack the benefits of using them with
which along with a program of self-exploration
collegestudents—TomkovickandSwanson(2014)
known as CliftonStrengths for Students (formerly
pointed to a ‘‘surprising scarcity of empirical
StrengthsQuest),alsofromGallup(2017a),isused
researchtosupportmanyofthepurportedbenefits
extensively in higher education. More than 2
of a better understanding of one’s strengths’’ (p.
million college students have taken the Strengths-
198). The dearth of research on strengths-based
Finder assessment, and several hundred colleges
approaches in the academic advising literature
and universities use strengths programming. Some
stands out starkly because in higher education
programs offered at postsecondary institutions
advisingoffersthemostpotentiallyverdantspaces
include curricula embedded in first-year student
where students can receive the intensive and
orientation programs (Bowers & Lopez, 2010;
individualized support for the identification, de-
Soria & Stubblefield, 2014), first-year experience
velopment, and application of their strengths.
courses (Stebleton, Soria, & Albecker, 2012),
Because of the critical importance of advising for
career development initiatives (Dik et al., 2015;
students’ success and retention (Soria, 2012;
Lopez,2014),specificacademicdisciplines(Janke
Young-Jones, Burt, Dixon, & Hawthorne, 2013),
et al., 2015; Lorimer & Davis, 2015), and
advisors who utilize strengths-based approaches
leadershipdevelopmentprogramsorcourses(Lane
may be advantageously poised to create the most
& Chapman, 2011; Wisner, 2011), among other
positive impact on students’ outcomes.
enterprises.
To ascertain whether strengths-based approach-
The Clifton StrengthsFinder (Gallup, 2017b) es in academic advising conversations are associ-
assessment leads individuals to discover their five ated with student outcomes, we examined
most salient talent out of 34 themes—patterns of strengths-based approaches as enacted at a large,
thoughts, feelings, and behaviors that, when public, research university during the 2012-2013
refinedwithknowledgeandskill,canbedeveloped academic year. The institution site of our study
into strengths (Hodges & Harter, 2005). We offered the StrengthsFinder assessment (Gallup,
reference the top five talent themes as top five 2017b) to all incoming first-year students (N ¼
strengths,becausethatphraseistypicallyattributed 5,514), of whom approximately 96% (n¼5,309)
tothem.SchreinerandAnderson(2005)suggested completed the assessment to learn their top five
that advisors administer tools such as Strengths- strengths. Because of the large and decentralized
Finder to help students identify their areas of nature of the institution, not all first-year students
greatest potential; however, they also recommend- wereexposedtostrengths-basedpractices—includ-
ed additional techniques and tools useful for this ing conversations with advisors—within their first
purpose. year of enrollment.
In their innovative work, Schreiner and Ander-
Conceptual Framework
son (2005) suggested several steps useful in a
framework that integrates strengths into advising: We used Astin’s (1993) input-environment-
output model as the conceptual framework for the
(cid:2) help students to identify their strengths, study. The inputs within this model included
(cid:2) affirm students’ strengths and increase students’ pre-college characteristics, experiences,
their appreciation of their unique and demographics. The environment included
strengths, experiences during higher education, and the
(cid:2) discuss students’ aspirations and deter- outputs included outcomes of interest. Inputs can
mine the talent themes students wish to exert an influence on both environmental experi-
develop further, ences and outcomes, which explains the reason
56 NACADA Journal Volume 37(2) 2017
Strengths-Based Advising
researchers commonly take inputs into consider- Methodology
ation when building their statistical models.
Phase 1: Student Survey Data Analysis
Indeed, to test the true impacts of environmental
Procedures. At the end of the academic year,
experiences,thedirecteffectsof inputvariableson
all first-year students (N¼5,514) were invited to
outcomes must be taken into account even as the
participate in an online survey regarding their
potential effects of those input variables on the
strengths-related interactions. We offered a lottery
environmental variables are examined. In the case
incentiveforparticipantsintheformofachanceto
ofstudents’useofacademicadvisingservices,for
win one of four $25 university-bookstore gift
instance, self-selection bias may contribute to
certificates. In the survey, students were asked to
systematic differences between students who assess their strengths-based interactions, academic
decide to meet with advisors and those who do self-efficacy, engagement, and other personal
not meet with advisors. beliefsandcharacteristics.Wereceivedinstitution-
To attempt to reduce some of those self- alreviewboardapprovaltoconductthisstudyand
selection biases, at least in part, educational administer the survey to first-year students.
researchers frequently use quasi-experimental Participants.Theoriginalstudentresponserate
designsinanalyses.Inmostexperimentalstudies, for the survey was 27.33% (n¼1,507). Of these
theyrandomlyassignparticipantstoacontroland students, 59.3% (n ¼ 893) indicated that they
a treatment group to test the effects of the engagedinatleastonestrengthsconversationwith
treatment. While these randomized controlled an advisor during the academic year. Because of
trials are considered the gold standard approach the propensity score methods utilized in the
for estimating the effects of treatments (Austin, analyses, the final sample of matched treated and
2011), such randomization often cannot be untreated pairs was reduced (n¼1,228). Of those
achieved in educational settings. In cases of students, 65.1% are female (n¼800) and 34.9%
impractical randomization, quasi-experimental are male(n¼428).Inaddition,1.1% identifiedas
techniquesareusedtosimulatethecharacteristics Native American or American Indian (n ¼ 14),
of experimental designs. In the quasi-experimen- 11.5%asAsian(n¼141),2.0%asBlack(n¼24),
tal design, groups of students are matched 0.5% as Hawaiian (n¼6), 2.1% as Hispanic (n¼
accordingtovariablessuchthatonlythetreatment 26), 4.2% as international (n¼52), and 78.5% as
(specified experience) differs between the two White (n¼965). White and female students were
groups (Melguizo, Kienzl, & Alfonso, 2011); in slightlyoverrepresentedcomparedtotheuniversity
this case, the treatment consisted of advisees’ first-yearpopulation,whichwas50.7%femaleand
discussions of their strengths with an advisor. 74.9% White.
Using quasi-experimental design methods, re- Measures. We took three types of measure-
searchers match students on the basis of pretreat- mentsinthisstudy.Thesemeasureswerebasedon
ment characteristics that approximate randomiza- studentresponsestoitemsrelatedtodemographics,
tion by balancing the observable characteristics the dependent variables, and specific strengths-
betweenthetreatmentandcontrolgroups(Becker based interactions with advisors.
& Ichino, 2002). The results can help researchers Covariate measures. The covariate measures
better estimate the effects of treatments on utilized for propensity score matching analyses
outcomes with a greater degree of accuracy. were intentionally selected because of their poten-
Therefore, in the study, we utilized propensity tial relationships to students’ use of academic
score matching techniques to estimate the effects advising and the dependent measures (Table 1).
offirst-yearstudents’strengths-relateddiscussions Thesemeasuresincludeddataonstudents’raceand
with advisors. ethnicity,sex,collegeofenrollment,socioeconom-
In addition, to expand our understandingof the ic status as measured by Pell-grant status, and
strengths-based approaches used in academic incoming ACT or SAT scores (Bozick, 2007;
advising conversations, we conducted six focus Jones-White, Radcliffe, Huesman, & Kellogg,
groups to hear advisor perspectives on benefits 2010; Miller & Herreid, 2008; Soria & Stubble-
theyperceivedaboutstrengths-basedconversations field, 2014). We included measures related to
with their advisees. We present our methods and students’ participation in Access to Success, a
resultsaccordingtoPhase1(students’survey)and small advising community created to increase the
Phase 2 (advisors’ focus groups) of the study. retention of students from underrepresented
NACADA Journal Volume 37(2) 2017 57
Soria et al.
Table 1. Descriptive statistics of covariate We used an 8-item measure of academic self-
measures efficacy developed by Chemers, Hu, and Garcia
(2001).Studentswereaskedtoratetheiragreement
Measure n %
with statements reflecting confidence in their
Pell Grant Recipient 258 21.0
ability to perform optimally on academic tasks
Pell Grant Nonrecipient 970 79.0
(1 ¼ very untrue to 7 ¼ very true). Soria and
College of Biology 98 8.0
Stubblefield (2015a) reported the measure as
College of Design 49 4.0
internally consistent (a ¼ .85) and, in this study,
College of Agricultural Sciences 56 4.6
themeasurealsoshowedhighreliability (a¼.85).
College of Liberal Arts 513 41.8
We obtained data from the Office of Institu-
College of Engineering 240 19.5
tional Research regarding students’retention from
College of Business 154 12.5
their first to their second year of enrollment and
College of Education 118 9.6
their graduation in 4 years. The average rate of
Access to Success Participant 78 6.4
studentretentionatthisinstitutionwas90.4%,and
Not an Access to Success 1,150 93.6
withinthesamplereducedbygraduationrates, the
Participant
averageretentionratewasslightlyhigherat94.6%.
M SD The 4-year graduation rate was 65.3% for the
ACT Scores 27.99 3.40 institutional population and81.92% for the survey
Value of Strengths 3.48 1.24 sample.
Proportion of Strengths 2.65 1.17 Strengths discussions with an advisor. In the
Discussions Initiated survey, we asked students whether they had a
strengths-related conversation with an advisor
Note. SAT scores were converted to ACT scores.
during the academic year. As noted, over one half
(59.3%, n ¼ 893) of students indicated that they
backgrounds (Soria, Lingren Clark, & Coffin had engaged in at least one strengths-based
Koch, 2013). conversation with an advisor during the academic
Finally, we sought to control for students’ year. Using this result and propensity score
enthusiasm for the strengths program because this techniques, we created the treatment and control
factor mayleadstudentstoinitiatestrengths-based variables, discussed strengths with an advisor and
discussions in academicadvising conversations on did not discuss strengths with an advisor, respec-
their own. To this end, we asked students to rate tively. We found one notable difference between
(1¼strongly disagree to 5¼strongly agree) their students who discussed strengths with an advisor
and those who did not engage in strengths-based
agreement that strengths had value for them and
discussions: A higher percentage of education and
the proportion of strengths discussions that they
business students reported experiencing strengths-
had initiated without prompting from the advisor
based discussions. Both the College of Education
(1¼none to 5¼all).
and the Business College had adopted strengths
Dependent measures. We used four dependent
initiatives early and remain strong supporters of
variables:first-yearstudents’engagement,academ-
strengths-based approaches. We observed no other
icself-efficacy,first-to-secondyear retentionrates,
demographic differences between students who
and rate of graduation in 4 years. To measure
reported a strengths conversation with an advisor
students’ engagement, we used a 12-item assess-
andthosewhodidnotreportexperiencewiththese
ment known as the College Student Engagement
conversations.
Scale, an instrument based on Gallup Q12, which
Analysis. We utilized propensity score match-
was designed to measure attitudinal outcomes and
ing techniques in SPSS 23.0 according to proce-
engagement levels (Harter, Schmidt, Killham, &
dures outlined by Thoemmes (2012). We initiated
Agrawal, 2009). The scale asks students to rate the study by using binary logistic regression to
their agreement (1 ¼ strongly disagree to 5 ¼ compute propensity scores for individual students.
stronglyagree)onavarietyof items(e.g.,‘‘Atthis Next, we used 1:1 nearest neighbor matching
school,IhavetheopportunitytodowhatIdobest without replacement, meaning that data from each
every day’’). The instrument has been shown to studentinthetreatmentconditionwerematchedto
demonstrate strong reliability (a ¼ .90) (Soria & data from a student in the control population with
Stubblefield,2014),afindingalsoreplicatedinthis the most similar estimated propensity score. We
study (a¼.91). discardedalldataunitsthatfelloutsideofthearea
58 NACADA Journal Volume 37(2) 2017
Strengths-Based Advising
of common support to avoid extrapolation to the2012-2013academicyearbysendingane-mail
students who were so dissimilar that no compar- to all on-campus advisors through a central
isons could be made between them (Thoemmes, academic advising e-mail list. We provided advi-
2012). sors a meal as an incentive for their attendance.
We checked whether the matching procedures The advisors recruited for the focus groups
balanced the distribution of variables in both the included 5 men and 16 women, who had held
treatment and control groups. Specifically, we primary positions as academic advisors for under-
looked at standardized mean differences (the graduates. The advisors were well represented
meandifferencesbetweenthetwogroupsdivided among the seven largest first-year student-admit-
bythestandarddeviationofthecontrolgroup)in ting colleges at the university. Each focus group
the treatment and control groups before and after lasted approximately 1 hour and the participants
matching. We detected no large imbalances wereaskedthesameseriesofquestions,including,
(greaterthan.25)aftermatchingineachanalyses, for example, the following:
and these findings meet the threshold suggested
by Rosenbaum and Rubin (1985). These results (cid:2) Doyou discuss strengths with students?
imply that, before matching procedures were (cid:2) What are students’ reactions to the
implemented, the covariates within the treatment strengths conversations you have? and
and control groups differed significantly. These (cid:2) To what extent, if any, do you see an
results also reveal that the propensity score impactofthesestrengthsconversationson
matching decreased bias by making the observed your advisees?
and treatmentgroups more similarwithregard to
A graduate student assistant transcribed audio
covariates.
recordings from the six focus groups, which
To test whether strengths-related discussions
yielded 101 single-spaced pages of text.
are associated with students’ engagement and
Analyses.Weindividuallyreviewedeachfocus-
academic self-efficacy (continuous variables), we
group transcript and identified key codes, themes,
used linear regression analyses. We included the
or potential areas of interest. We convened to
propensity scores as controls to remove the
discuss our coding schemes, and in the process of
correlation component from the assignment
process (Melguizo et al., 2011). In the end, we integrating the data and refining the categories,
utilized binary logistic regression to examine the central themes emerged that explained relation-
relationships between first-year students’ shipsamongthedata.Webuiltthesecentralthemes
strengths discussions with advisors and their by gleaning ‘‘bits and pieces of information’’ that
second-yearretentionand4-yeargraduationrates. were‘‘combinedandorderedintolarger themesas
As in the other models we created, we included the researcher works from the particular to the
students’propensityscoresascontrolvariablesin general’’ (Merriam, 2009, p. 15). Within group
the analyses. Whereas beta coefficients, standard meetings, we sorted and reviewed themes for
errors,andsignificancelevelsarecommonlyused similarities and differences until the point of
to describe the results of ordinary least squares saturation, defined as the time during the process
regression, odds ratios—which are calculated by when additional analysis does not offer any
exponentiatingthebetacoefficient(eb)—areused additionalinsight(Creswell,2007).Weuseddirect
inlogistic regression toexplainthewayachange quotes to authenticate the findings (Merriam,
in an independent variable influences the depen- 2009). Each of member of our research team
dent variable when other variables are held verified the codes and themes in a step that
constant (Cragg, 2009; Hosmer & Lemeshow, enhanced the validity of the analyses (Creswell,
2000). In the context of the present study, the 2007). We also represented participants’ experi-
odds ratio value indicates the odds of reenroll- ences using rich description involving numerous
ment in the second year of higher education (the direct quotes from students’ responses (Creswell,
oddsofgraduatingin4yearsovernotgraduating) 2007).
for every one-unit increase in an independent
variable when other variables are held constant. Results
Phase 1: Student Survey Data Analysis
Phase 2: Advisors’ Perspectives The results of the first linear regression
Procedures and participants. We recruited 21 predicting students’ engagement suggested that
academicadvisorsforsixfocusgroupsheldduring students who discussed their strengths with an
NACADA Journal Volume 37(2) 2017 59
Soria et al.
Table 2. Results of regression models predicting student outcomes
Engagement Academic Self-efficacy Retention Graduation
Predictor b b eb eb
Strengths Discussion with Advisor .088*** .126*** 1.530*** 1.903***
Propensity Score .227*** .007 1.02 1.31*
Note. *p , .05. ***p , .001.
advisor at least once in the academic year had entered into the analyses reflected factors that
experienced significantly higher engagement, on exerted little influence on students’ graduation
average,thantheir peerswhodidnotengage ina (pseudo-R2 values of .050) as per Nagelkerke
strengths-based discussion with an advisor (b ¼ (1991).
.088, p , .001) (Table 2). The variables entered
into the analyses (discussing strengths with an Phase 2: Advisors’ Perspectives
advisor and the propensity scores) explained The results of the qualitative data analyses
8.2% of the variance in students’ engagement revealed several primary themes that may help
measures. advance the understanding of the effects of
The results of the second linear regression
strengths-based advising conversations on stu-
predicting students’ academic self-efficacy sug-
dents’ retention, graduation, engagement, and
gestedthatstudentswhodiscussedtheirstrengths
academicself-efficacy.Severaladvisorsdiscussed
withanadvisoratleastonceintheacademicyear
the ease with which they were able to build
reported significantly higher levels of academic
relationships with students, thus supporting
self-efficacy, on average, than study participants
advisee engagement, retention, and graduation.
who had not engaged in a strengths-based
Advisors believed that strengths-based conversa-
discussion with an advisor (b ¼ .126, p ,
tions helped students with their development of
.001). The variables entered into the analyses
confidence and in taking ownership over their
(discussing strengths with an advisor and the
academicsuccess.Also,advisorsdiscussedusing
propensityscores)explained1.7%ofthevariance
strengths approaches within their own advising
in students’ academic self-efficacy.
circles for professional development; thus,
The results of the first logistic regression
through modeling strengths-based practices in
analysis show that students who discussed their
their own professional work, advisors who
strengthswith anadvisorweresignificantlymore
embraced strength-based approaches benefited
likelytoenrollforasecondyearattheuniversity.
their advisees.
Specifically,theresultssuggestthatstudentswho
Establishing advising relationships and en-
discussed strengths with an advisor were 1.530
hancing engagement. One advisor suggested that
times more likely to return for their second year
of enrollment (eb ¼ 1.530, p , .001). The academicadvisingcontextsofferthebestplaceson
campus to engage in strengths-based conversa-
variables entered into the analyses revealed that
the factors they represented exerted little influ- tions,notingthat‘‘advisingconversationsareoften
ence on students’retention (pseudo-R2 values of the most intimate and personal conversations
.040) as per Nagelkerke (1991). students have with any staff on campus, even
The results of the final logistic regression compared with faculty, although they may see
analysis we conducted suggest that students who faculty more often.’’ Another advisor explained
discussed their strengths with an advisor were that strengths approaches ‘‘lay a foundation for
significantly more likely to graduate in 4 years students’’ to enter into positive advising relation-
than their peers who did not engage in a ships:‘‘Weareinthistogether.Iamheretosupport
strengths-based conversation with an advisor in yourgoals.Iamheretohelpyoulearnmoreabout
their first yearof enrollment. The results indicate yourself, but also affirm that you are unique.’’
that students who discussed strengths with an Addressing the ways in which strengths awakened
advisor were 1.903 times more likely tograduate students to new, positive aspects of themselves,
in 4years(eb¼1.903, p , .001) than thosewho anotheradvisorarguedthatstrengthshelpstudents
had not engaged in strengths-based discussions. who were ‘‘struggling with, you know, seeing
As in the first model we analyzed, the variables where they fit on campus, and so I think that is a
60 NACADA Journal Volume 37(2) 2017
Strengths-Based Advising
helpful tool to affirm who they are and the vocabulary, the more positive way of speaking
possibilities for where they are going.’’ about themselves.’’ Another advisor remarked that
One advisor explained that acknowledgment leveraging strengths ‘‘gives student their own
of strengths ‘‘enriches advising because it helps voice’’ and helps them to see ‘‘what they are good
with relationship building, and then hopefully at and how they can apply those qualities in
students know that there is someone on campus different ways, which empowers them once they
that cares about them and wants to learn about know more about their own strengths and what
and help them grow and develop.’’ Another they bring to make decisions.’’
related that strengths discussions help students More than one half the advisors in the focus
to‘‘feellikeyouaretheiradvocate—theyseeyou groups noted the potential for strengths-based
connect with them as their advocate in a advising to help students with major and career
welcoming space.’’ To build these relationships, selection processes; for instance, one advisor
advisors often shared their own personal stories suggested, ‘‘When students know their strengths,
of using or developing their own strengths. Four they can use their strengths in the decision-
advisors also saw the potential for strengths making process rather than simply choosing a
approaches to help students connect not only major to fit their strengths, as all strengths are
with advisors but also with other students at the great in all fields.’’ Nine other advisors framed
university; for instance, one advisor suggested, strengths approaches in terms of the potential to
empower students to take responsibility for their
Ithink[astrengthsapproach]doeshelpthem education and future. As one advisor explained
build relationshipswith their classmates and the advantages of strengths-based approaches:
others who are pursuing the same major. So
every time they get to know each other. . . I think it helps to empower the students and
it’s like an affirmation of ‘‘I see this about take over or shift over and experience that
you, I am going to remember this about they are up to take on and whether it is
you.’’ choosing a major or taking classes or
developing a plan for four years down the
Another advisor pointed out: ‘‘If someone knows road. It helps them have some level of
somethingaboutyou,itenhancestherelationship ownership.
and it makes you feel like you belong in the
community.Itleadstoretention,andithasripple Another advisor suggested that knowledge of
effects beyond the first year.’’ strengths helps students to ‘‘form and own their
We hypothesized that when they can more ownbrandthatcanbeappliedtotheirchoiceofa
quickly develop personal relationships with major, in the classroom, or beyond graduation
academic advisors and their classmates by and working in their job.’’ This ownership, we
viewingsituationsthroughastrengths-basedlens, hypothesized, leads to enhanced confidence and
studentsmayfeelmoreengagedbecausetheyfeel academic self-efficacy; that is, students feel
validated and supported by critical institutional preparedandcapableofachievingacademictasks
representatives. When they know their students’ and fulfilling their academic potential. In return,
strengths, advisors can encourage students to this confidence can lead to greater retention and
connectwithopportunitiestoperformattheirbest graduation rates (Chemers et al., 2001).
every day in curricular and cocurricular experi- Trickle down effects: Strengths as profes-
ences;thisinvolvementleadstomoreandgreater sional development for advisors. While all 21
ways to maintain retention and graduation advisors were asked to discuss the potential
because students feel more connected to their benefits of strengths for undergraduates, 5 also
institutions through the social support they openly discussed the benefits of a strengths
receive from advising (Jones, 2010). approach for them personally. These 5 advisors
Enhanced self-awarenessand confidence.All recounted that they more enthusiastically utilized
of the advisors in the focus groups discussed the strengths approaches in their advising after learn-
benefits of strengths in relation to students’self- ing, understanding, and applying strengths con-
awareness and enhanced self-confidence. One cepts in their daily lives.For instance, one advisor
advisor stated, ‘‘Strengths get students on the path related, ‘‘It is like peeling back another layer of
ofidentityandreflectioninamoremeaningfulway understanding of myself,’’ and echoing those
thatwouldn’texistiftheydidn’tgetexposedtothe sentiments, another advisor said,
NACADA Journal Volume 37(2) 2017 61
Soria et al.
Iknowthathelpedmeinmypersonallifein rates of retention and graduation than their peers
that way and also communicating to poten- who did not engage in strengths-related conversa-
tialemployers:Itgavemevocabularytotalk tions. The results lend weight to Schreiner and
aboutwhatIthink Iamgoodatso Iuse my Anderson’s(2005)propositionthatstrengths,when
personal experience in that way too, to talk identified and utilized in academic advising
to students about it. settings, can yield great benefits for students. The
results also align with prior research that explored
Advisors benefited personally from using a the benefits of strengths-based approaches on
strengths approach, noting that their interactions student outcomes such as engagement, self-effica-
withcolleaguesandthatteamdynamicsimproved cy,retention,andgraduation;thisstudyparticularly
after incorporating strengths approaches within supports assertions about the powerful impact of
their units, departments, or colleges. One advisor strengths-based academic advising conversations
articulated the benefits of strengths-based ap- (Soria & Stubblefield, 2014, 2015a, b).
proaches for advisors: In addition, the results of the second phase of
the study—the qualitative analyses of the focus
group data—suggest that advisors who leveraged
I think [a strengths approach] gives us
strengths in their own work believe that strengths-
common language, and I think that is huge.
based approaches serve as a bridge to establish
Without it, there wouldn’t be those conver-
more immediate advising relationships with stu-
sations. I think it is good for staff develop-
dents. The results also extend the literature in the
ment. I work with a team of advisors, and I
field by pointing toward the potential benefits of
ask new advisors each year to take their
strengths-based advising approaches to advisors’
strengths assessment. So, then, even in the
own personal and professional development. Fur-
wayweorganize ourworkwehavea shared
thermore, advisors who apply their own strengths
language, and it helps us focus on what we
in practice reported their belief that students can
like doing best, and then it helps us connect
use their own strengths to develop confidence, a
withourstudentsandwithotherpeoplewho
sense of empowerment, and connections to oth-
aren’t even in our units.
ers—findings that we hypothesized would lead to
enhanced engagement, improved academic self-
Another related,
efficacy,andhigher retentionandgraduationrates.
To the survey given to advisees, 88% of
I would agree on that staff development
students responded with somewhat to strong
piece. . . . The more we can develop agreement that knowing their strengths has posi-
ourselves, the more we develop ourselves tivelyaffectedtheirselectionofanacademicmajor,
for students, and not only the direct and 82.6% somewhat or strongly agreed that
interactions in advising appointments, but knowing their strengths helped them in thinking
also in terms of coworker and team dynam- aboutpotentialcareer paths.Wealsohypothesized
ics. that these factors help to promote students’
retention and eventual graduation from the univer-
We hypothesize that these enhanced professional sity; however, future research is needed to
development opportunities trickle down to stu- investigate the potential relationships between
dents, who benefit by observing positive self- strengths-basedpracticesandthestudentoutcomes
development,reflection, andself-awarenessmod- hypothesized in the study.
eled by academic advisors (Guthrie, Woods, Although the results of the quantitative and
Cusker, & Gregory, 2005). qualitative analyses are encouraging, several
limitationstothepresentstudyneedacknowledg-
Discussion and Limitations
ment. For instance, the study was conducted at a
The results of the first phase of our study—the large,urban,public,research-extensiveuniversity,
quantitative analyses—suggest that first-year un- which may limit the generalizability of the
dergraduates who engage in strengths-related findings to this institutional context. Because all
discussions with their advisors had significantly first-year students were invited to complete the
(p , .05) higher levels of engagement, demon- StrengthsFinder assessment (Gallup, 2017b), and
strated significantly (p , .05) greater academic several departments on campus offered strengths-
self-efficacy,andhadsignificantly(p,.05)higher related programming (e.g., in housing and
62 NACADA Journal Volume 37(2) 2017
Strengths-Based Advising
residence life), the potential effectiveness of strengths so that advisors can look up
strengths in the academic advising contexts students’strengthsandrevisitthemduring
cannot be isolated. Furthermore, the variables advising appointments;
usedintheregressionmodelspredictedonlyvery (cid:2) use interactive conversations as means to
small amounts of variance in the dependent elicitstudents’criticalthinkingabouttheir
variables, suggesting several variables may more strengths;
strongly predict students’ engagement, self-con- (cid:2) allow students flexibility to claim their
fidence, and retention. The coefficients in the own strengths; and
models also suggest weak relationships between (cid:2) help students envision, using their
strengths-based discussions and student out- strengths, to make decisions or tackle
comes. Researchers should include additional obstacles in academic-, personal-, or
measures in their models to more fully capture career-related contexts.
students’ experiences—a step that may help to
Asking students to identify how they can use
isolate better the effects of specific strengths-
their own strengths to meet their goals and
based approaches on student outcomes.
affirming students’ unique strengths as they are
In addition, advisors self-selected to join the
usedinactioncanfurtherencourageandempower
focus groups and understood in advance that they
students to overcome challenges. These strategies
would be discussing strengths-based approaches
also make students feel welcome in their campus
and potential benefits for students. Therefore, the
communities as they connect to other students.
advisors who chose to participate may favor
Finally, additional research on the effectiveness
strengths-based approaches; however, several ad-
of strengths-based approaches should take priority
visors stated that they chose to attend the focus
on college campuses within different institutional
groups because they did not use strengths-based
contexts and among underrepresented groups of
approaches and wished to use the opportunity to
students. Although we examined a few important
learn from other advisors the ways to incorporate
outcomes in this paper, additional areas critical to
strengthsintotheirpractice.Theresultsofboththe
studentsuccessshouldbeexplored—includingthe
quantitative and qualitative analyses should be
potential longitudinal impacts of strengths-based
interpreted in light of these limitations.
approaches on students’ career development and
Recommendations satisfaction beyond higher education.
We recommend that colleges and universities
Conclusion
invest in their students—and advisors—by provid-
Inconclusion,theresultsofthisstudyhighlight
ingthemwithtoolstohelpthemgainawarenessof
their strengths. Along with investment in tools or the potential benefits of strengths-based approach-
assessments, we recommend that administrators es in academic advising relationships. We em-
seektoinstitutionalizestrengths-basedpracticesby ployed rigorous methodology in our analyses to
offering educational training opportunities to staff test the effects of strengths-based academic
and faculty members seeking to implement advising conversations and collected data from
strengths in their daily practices with students advisorsrelatedtotheir perceptionsofthebenefits
(Soria & Stubblefield, 2015a). Like Schreiner and of strengths for students. Although more work
Anderson(2005),wealsobelievethattheadvising needs to be undertaken to continue to shift
relationship offers one of the best tools to help prevailing paradigms of deficits and problems to
undergraduates identify, affirm, and develop their those of strengths and possibilities, we argue that
own strengths, so we recommend that institutions strengths-based approaches present actionable
place a special emphasis on integrating strengths- opportunities to help students develop confidence,
based educational opportunities in academic ad- engage in their educational experience, and
vising contexts. ultimately to achieve their educational goals.
Additional recommendations we drew from
References
some of the strengths-development strategies that
Astin, A. W. (1993). What matters in college:
advisors on this campus employed include the
Four critical years revisited. San Francisco,
following directives for administrators and advi-
CA: Jossey-Bass.
sors:
Austin, P. C. (2011). An introduction to propen-
(cid:2) keep an institutional repository of sity score methods for reducing the effects of
NACADA Journal Volume 37(2) 2017 63
Soria et al.
confounding in observational studies. Multi- Yee, G. C. (2015). StrengthsFinder signature
variate Behavioral Research, 46(2), 399–424. themes of talent in Doctor of Pharmacy
Becker,S.O.,&Ichino,A.(2002).Estimationof studentsinfiveMidwesternpharmacyschools.
average treatment effects based on propensity American Journal of Pharmaceutical Educa-
scores. Stata Journal, 2(4), 358–377. tion, 79(4), 1–9.
Bowers, K. M., & Lopez, S. J. (2010). Capital- Jones, W. A. (2010). The impact of social
izingonpersonalstrengthsincollege.Journal integration on subsequent institutional com-
of College and Character, 11(1), 1–11. mitment conditional on gender. Research in
Bozick, R. (2007). Making it through the first Higher Education, 51(7), 687–700.
yearofcollege:Theroleofstudents’economic Jones-White,D.R.,Radcliffe,P.M.,Huesman,R.
resources, employment, and living arrange- L.,&Kellogg,J.P.(2010).Redefiningstudent
ments. Sociology of Education, 80(3), 261– success: Applying different multinomial re-
284. gression techniques for the study of student
Chemers, M. M., Hu, L., & Garcia, B. F. (2001). graduationacross institutionsof highereduca-
Academic self-efficacy and first-year college tion. Research in Higher Education, 51(2),
student performance and adjustment. Journal
154–174.
of Educational Psychology, 93(1), 55–64.
Lane, F. C., & Chapman, N. H. (2011). The
Cragg, K. M. (2009). Influencing the probability
relationship of hope and strength’s self-effica-
for graduation at four-year institutions: A
cy to the social change model of leadership.
multi-modal analysis. Research in Higher
Journal of Leadership Education, 10(2), 116–
Education, 50, 394–413.
137.
Creswell, J. W. (2007). Qualitative inquiry and
Lopez,S.J.(2014).Agoodjobishardtofind...
research design: Choosing among five ap-
until students know what they do best. About
proaches (2nd ed.). Thousand Oaks, CA:
Campus, 19(1), 2–6.
Sage.
Lorimer, S., & Davis, J. A. (2015, June). Using
Dik, B. J., Duffy,R.D.,Allan, B.A., O’Donnell,
strengths of first-year engineering students to
M. B., Shim, Y., & Steger, M. F. (2015).
enhance teaching. Paper presented at the
Purpose and meaning in career development
American Society for Engineering Education,
applications. The Counseling Psychologist,
Seattle, WA.
43(4), 558–585.
Melguizo, T., Kienzl, G. S., & Alfonso, M.
Gallup. (2017a). CliftonStrengths for Students.
(2011). Comparing the educational attainment
Retrieved from https://www.strengthsquest.
of community college transfer students and
com/205382/cliftonstrengths-students.aspx
four-year college rising juniors using propen-
Gallup.(2017b).StrengthsFinderAssessment2.0.
sity score matching methods. The Journal of
Retrieved from http://www.gallup.com/
Higher Education, 82(3), 265–291.
products/170957/clifton-strengthsfinder.aspx
Merriam, S. B. (2009). Qualitative research:
Guthrie,V.L.,Woods,E.,Cusker,C.,&Gregory,
Guide to design and implementation. San
M.(2005).Aportraitofbalance:Personaland
Francisco, CA: Jossey-Bass.
professional balance among student affairs
professionals.CollegeStudentAffairsJournal, Miller,T.E.,&Herreid,C.H.(2008).Analysisof
24(2), 110–127. variablestopredictfirst-yearpersistenceusing
Harter, J. K., Schmidt, F. L., Killham, E. A., & logisticregressionanalysisattheUniversityof
Agrawal, S. (2009). Q12 meta-analysis: The SouthFlorida.College&University,83(3),2–
relationship between engagement at work and 11.
organizationaloutcomes.Omaha,NE:Gallup. Nagelkerke, N. J. D. (1991). A note on a general
Hodges,T.D.,&Harter,J.K.(2005).Areviewof definition of the coefficient of determination.
the theory and research underlying the Biometrika, 78, 691–692.
StrengthsQuest program for students. Educa- Rosenbaum, P. R., & Rubin, D. B. (1985).
tional Horizons, 83(3), 190–201. Constructing a control group using multivar-
Hosmer, D. W., & Lemeshow, S. (2000). Applied iate matched sampling methods that incorpo-
logistic regression (2nd ed.). New York, NY: rate the propensity score. American Statisti-
Wiley-Inter-Science. cian, 39(1), 33–38.
Janke, K. K., Farris, K. B., Kelley, K. A., Schreiner, L. A., & Anderson, E. (2005).
Marshall, V. D., Plake, K. S., Scott, S. A., ... Strengths-based advising: A new lens for
64 NACADA Journal Volume 37(2) 2017