As online education continues to expand across the nation and world, studies on online learners need to continually address student needs for and satisfaction with advising. However, to date, academic advising for online education has been explored rarely. Therefore, this quantitative study was conducted on graduate students' perceptions of academic advising experiences in online education programs in terms of communication, academic advisor knowledge of support services, and academic advisor behaviors. The data indicated that students agreed to statements about academic advisors as effective and that they expected proactive, timely, and knowledgeable advising. Implications for advisors of online students and suggested strategies emerged from the data and may enhance current advising practices.

The most recent National Center for Education Statistics (2016), Enrollment in Distance Education Courses reported that, in Fall 2014, of all graduate students in the United States, 32.7% were enrolled exclusively in distance education programs or taking at least one distance education course. Although enrollments continue to increase in online programs and courses, the retention of online students poses a challenge for administrators at public, higher education institutions. Research shows high online student attrition rates compared to those found for on-campus students (Atchley, Wingenbach, & Akers, 2013; Carr, 2000; Willging & Johnson, 2009). In response to this and other concerns, NACADA: The Global Community for Academic Advising (NACADA) published the first distance education advising standards in 2010 and provided a framework for advisors to ensure student access to academic, financial, and technical support information throughout their programs.

The typical model of graduate advising is based on in-person interaction with graduate faculty members (Exter, Korkmaz, & Boling, 2014), but a growing trend of professional staff taking responsibility for advising graduate students should be explored. Furthermore, with nearly one third of graduate students completing programs online, graduate advising models, in particular, must feature strategies adapted to ensure that appropriate advising is offered. Despite the potential difficulties of implementing advising strategies for graduate students, particularly in an online environment, little research has been directed at distance advising for graduate students. With the changing dynamic of advising providers, investigation into student perceptions of faculty and professional advising delivered online proves a timely and important topic to explore.

Therefore, a quantitative study was used to examine graduate students' perceptions of advising delivered online and to analyze any differences between students' satisfaction of faculty advisors and professional staff advisors at the institution studied. Because advising refers to a broad number of responsibilities, three aspects of advising were specifically studied: timely communication between advisor and advisee (Irani, Wilson, Slough, & Rieger, 2014; Ortiz-Rodriguez, Telg, Irani, Roberts, & Rhoades, 2005), advisor knowledge of support services (Aversa & McCall, 2013; Cain, Marrara, Pitre, & Armour, 2003), and academic advisor behaviors (Bloom, Cuevas, Hall, & Evans, 2007; Varney, 2009). While these three key aspects of advising have not been combined in student satisfaction research to date, each has been consistently shown as a factor for student persistence and satisfaction.

Students enrolled in 16 online graduate programs at a 4-year, public comprehensive institution in southeastern Georgia were surveyed about communication, advisor knowledge of support services, and perceived advisor behaviors to address following questions:

RQ1

How do students rate their advisors overall for communication, knowledge of support services, and behaviors?

RQ2

Do students' advising ratings differ by key aspects of advisor responsibility and advisor type?

RQ3

What experiences and expectations do online students describe for their advisor relationships?

Key Advisor Responsibilities

Advisor Communication

Quality communication factors have been recognized as important indicators of a student's sense of satisfaction in an online program (Irani et al., 2014; Ortiz-Rodriguez et al., 2005). Building an online community, increased communications, and positive interactions with administrative staff and offices (registration, financial aid, technical offices, etc.) lead to increased student satisfaction in online programs (Ortiz-Rodriguez et al., 2005). Irani et al. (2014) added that support systems, such as online orientation, centralized information access, and regular communication outside of the academic setting, also help students in the online environment. Therefore, as the most important factor of positive student satisfaction, indicated across the research cited herein, advisor communication and timely feedback were specifically explored in this study.

Advisor Knowledge of Support Services

Cain et al. (2003) found that a majority of graduate students reported unawareness of support services available to them and did not think they needed such services, and these findings highlighted an unrealistic set of expectations placed on graduate course instructors by students who, in addition to the academic and course requirements, believed that instructors know about campus resources such as financial aid, registration, and the academic policies necessary for student success. They also found that students want online instructors to offer advising. This expectation for support services (e.g., financial aid, registration, and academic policies) through online programs formed one basis of exploration for this study: Students expect someone in their academic program, either advisors or instructors, to share information about institutional support.

Advisor Behaviors

Support of students in online education, through effective communication and personal outreach, has been cited as a critical component of effective advising (Bloom et al., 2007; Varney, 2009). Bloom et al. (2007) discussed several advisor characteristics that students perceive as important, including caring about students and their successes, maintaining accessibility, role modeling, advocating for students, and providing appropriate guidance. Varney (2009) presented a brief guide for academic advisors and highlighted that they must communicate frequently with distance education students as soon as possible after the student is admitted. Connecting with students during admission builds a personal relationship between the student and the advisor (Varney, 2009). Overall, best practices and strategies emphasize the importance of communicating clear and accessible information for online learners, and all advisors must also show genuine concern for their students.

Method

In reviewing online learning research, both qualitative and quantitative designs were related to studies on online student perceptions. Based on a Likert-type scale survey, a quantitative approach was undertaken for this study to address the three research questions (as per Creswell, 2008). The specific cross-sectional survey design was used because the data were collected once from a small population as necessarily selected to measure attitudes, beliefs, and community needs or to evaluate a program (Creswell, 2008).

Participants

For this study, students enrolled in 16 online graduate programs within a college of education, which included master's and specialist degree programs, at one institution were surveyed during the Spring 2015 semester. Approximately 700 students were enrolled in the online programs, and to maximize possible sample size, all currently enrolled students were asked to participate. Table 1 shows the breakdown of students who received the survey.

Table 1

Program representation by responses

Program representation by responses
Program representation by responses

The survey respondents remained anonymous. The Institutional Review Board approved the survey method for this population, and each participant gave voluntary consent to participate.

Instrument Development

A review of literature related to online advising did not reveal an existing instrument that encompassed the three research areas of the proposed study. Therefore, the instrument in this study, Online Advising Perceptions, was created. Three content experts with experience working with online students reviewed it, and the survey was used in a small pilot study before full implementation. Although threats to reliability and validity of the instrument were found during the pilot study of the instrument, each question was grounded in a thorough review of the literature available at the time.

The instrument comprised the following items: demographic information; frequency of communication preferences; Likert-type scale assessments of interactions with current academic advisors; and four open-ended prompts for descriptions of positive and negative experiences, overall expectations of advisors, and suggestions for advising improvement. The instrument was created from questions adapted from an existing satisfaction survey on graduate student advising (Zimmerman & Mokma, 2004); in addition, some items were created on the basis of published online learning research.

Data Collection and Analysis

A pilot study was conducted with Fall 2014 graduate students from a small cross section of online programs to test the instrument. Respondents received study information in their graduate student e-mail address, including a link to the Qualtrics-based survey, which they returned anonymously. Two additional questions were added to the pilot survey instrument: (a) What revisions would pilot participants suggest to improve the instrument? and (b) was the instrument understandable? Four of 13 graduate students e-mailed returned responses within the 2-week deadline. No major suggestions or areas of confusion were identified from the pilot study responses, so only minor revisions, based on additional colleague feedback, were made to the survey.

All currently enrolled Spring 2015 graduate students in the 16 online programs were e-mailed information about the importance of the study and the Qualtrics survey link. The survey was open for 3 weeks in February 2015, and three reminder e-mails were sent during this time period to encourage return of the completed instrument. Of the 694 students sent the survey, 182 opened the survey link and began the survey (26.2% response rate), and 165 students fully completed and submitted it (23.8% response rate). Survey data were collected in Qualtrics, downloaded, and analyzed with Excel.

Between the Fall 2014 and Spring 2015 semesters, one of the programs included in the survey, the MEd in Instructional Technology (MEIT), replaced faculty academic advisors with professional staff academic advisors. According to the Likert-type scale data and open-ended responses, some students in the program completed the survey based on their experiences with their faculty advisor in previous semesters and others referenced their experiences with their current professional advisor. To avoid skewing or misinterpreting data, all responses about advisor type from the MEIT program were eliminated from the analysis on advisor type because the mean Likert scale scores were used to identify differences between faculty and professional advisors and so must not over- or under-represent responses on either type. However, the responses from MEIT students were included in demographic tables, reports of the communication preference questions, and in the summaries of the open-ended questions.

Results

At least one student from each of the 16 programs surveyed submitted a response. The sample was representative of the original program population. One of the demographic questions asked respondents to identify their advisor by type: faculty, professional staff, or unsure/do not know. Fifteen percent of students selected unsure/do not know, 14% indicated that they worked with a professional staff advisor, and 58% indicated they were advised by a faculty member. The actual percentage of staff and faculty advisor was 41 and 59%, respectively, as determined by university records, demonstrating that many students did not know the type of advisor to which they were assigned.

Table 2 shows that the sample was representative of the sex and age characteristics of the overall online graduate student population within the education college at the institution. Responses on sex and age were optional responses, and not all respondents identified their sex.

Table 2

Demographic characteristics of respondents

Demographic characteristics of respondents
Demographic characteristics of respondents

Table 3a shows that 76% of students typically interact formally or informally with their academic advisors once per month or never, but of that group, 25% indicated they had expected more formal or informal contact with their advisor. Table 3b shows that 38% of students rarely or never consulted with their academic advisor prior to registration, which could indicate future problems because self-advising might lead to failure to meet requirements or to take classes in the proper sequence.

Table 3a

Current advising communication experiences from respondents (%)

Current advising communication experiences from respondents (%)
Current advising communication experiences from respondents (%)
Table 3b

Current advising communication experiences from respondents (%)

Current advising communication experiences from respondents (%)
Current advising communication experiences from respondents (%)

Research Questions 1 and 2

RQ1 addressed students' ratings of advisors' performance according to level of communication, knowledge of support services, and behaviors. Items 10–23 featured Likert-type scales from 1 = strongly disagree to 5 = strongly agree. The second research question addressed a possible statistical difference between advisor type (faculty or professional) and students' ratings.

Table 4 presents the t test for statistical significance level of agreement with a statement and advisor type (faculty or professional staff) as determined by the mean value of respondent scores for each item. As seen in Table 4, all items except No. 19 showed statistically significant differences between mean responses according to advisor type. A considerable variance was found in the standard deviation for the mean scores given for statements about faculty advisors, but less variance was found for means of scores given for professional staff advisors. In the areas of communication, support services, and advisor behaviors, higher (positive) ratings were given for professional staff advisors than for faculty advisors. Overall, respondents agreed to positive statements about their experiences regardless of advisor type.

Table 4

Results of t tests used to compared mean ratings of faculty and staff advisors by students

Results of t tests used to compared mean ratings of faculty and staff advisors by students
Results of t tests used to compared mean ratings of faculty and staff advisors by students

Research Question 3

The third research question addressed students' experiences and expectations of their academic advisors and was answered through responses to Questions 24–27 through which respondents could describe positive and negative advising experiences, expectations for advising, and suggestions to improve current programs. Approximately 50% of survey respondents provided narrative feedback in these open-ended questions. The responses were reviewed and categorized according to the advisors' communication, knowledge of support services, and behaviors. The responses were categorized after they were simplified into smaller phrases or words and aligned with others featuring similar terms related to the three main aspects of advisor responsibility identified for this study. Tables 5 and 6 present the total responses as categorized by key advising responsibilities.

Table 5

Respondents' positive advising experiences (n = 80) by category and advisor type

Respondents' positive advising experiences (n = 80) by category and advisor type
Respondents' positive advising experiences (n = 80) by category and advisor type
Table 6

Respondents' negative advising experiences (n = 82) by category, advisor type, and program

Respondents' negative advising experiences (n = 82) by category, advisor type, and program
Respondents' negative advising experiences (n = 82) by category, advisor type, and program

The data shown in Table 5 indicate that most of the positive advising experiences were associated with advisors' timely responses, knowledge of programs and policies, and helpfulness. Minor differences were found among students' responses according to advisor types, but no significant variance was revealed.

Table 6 highlights several issues related to students' reported negative experiences: advisors who did not address concerns proactively or in a timely manner, need to self-advise because of lack of advisor contact, and personality and behavioral barriers. These data show that the majority of negative experiences aligned with faculty advisors and those students in the MEIT program.

Tables 7 and 8 show the data on the narrative feedback of students' expectations of their advisors. Categorization and counts by the key aspects of advisor responsibility used in this study indicated that students expected advisors to communicate and effectively guide program of study progression.

Table 7

Respondents' expectations of their academic advisors (n = 77)

Respondents' expectations of their academic advisors (n = 77)
Respondents' expectations of their academic advisors (n = 77)
Table 8

Additional suggestions for academic advising practice improvements (n = 57)

Additional suggestions for academic advising practice improvements (n = 57)
Additional suggestions for academic advising practice improvements (n = 57)

Limitations

The primary limitation for this study was the use of an instrument not yet validated. Also findings cannot be generalized because of the small sample size and single education department from which students were surveyed. Likewise, data from education majors may not align with responses to other online student populations.

Despite the adequacy of the response rate for data analysis, more responses would have strengthened the confidence in the conclusions. Because data on advisors from the MEIT needed to be removed, fewer responses contributed to the specific analysis of advisor types. Although these limitations should be considered, the data reported and analyzed offer useful insights to consider for practice and as a basis for further studies.

Discussion and Implications for Academic Advising

Through this research, I sought to answer questions on student perceptions of their advisors based on experiences and expectations. The sample response rate proved adequate but could have been improved. As seen in the Likert-type scale responses, students reported overall satisfaction with their current advisors and advising practices. The open-ended feedback reinforced the data from student responses to the Likert-type scale items, including respondents' expectations for advisor-initiated contact. Overall, students expect and appreciate academic advisors who offer prompt responses, know about programs and policies, assist in student progress in programs of study, and demonstrate positive behaviors. The open-ended feedback specifically showed students most frequently referred to advisor timely and proactive communication; this finding comports with prior research regarding quality and punctual communication as a primary indicator of students' satisfaction in online programs (Irani et al., 2014; Ortiz-Rodriguez et al., 2005).

Many students expressed a desire for advisors to initiate contact proactively, indicating that they want to feel connected to their advisor or program and expect the advisor to make the first steps in advising them. This is consistent with research highlighting learners' desire for advisors to reach out to them to help make the transition to a new learning environment, in this case online, easier (Varney, 2009). The responses on positive advisor behaviors (e.g., helpful, caring, supportive) align with findings on students' attribution of importance to advisor caring about their successes, role modeling, advocating for them, and providing appropriate guidance (e.g., Bloom et al., 2007).

The means of Likert-scale responses regarding faculty and staff advisors showed statistical differences. Professional staff advisors were rated highly across all the key advising responsibility categories of this study, and students indicated that their advisors practiced timely communication, approachability, and availability. The research question on advisor expectations and experiences (RQ3) had not been explored simultaneously in previous research, and therefore, adds to the research on graduate advising. Although the findings from this study cannot be used to determine a generalizable difference in advising satisfaction by advisor type, they indicate a difference that should be examined further.

The findings for this study suggest that all academic advisors, whether faculty or professional, should understand students' perceptions and consider them to enhance the academic advising experiences of advisees. Online students expect and rate highly advisors who show accessibility and knowledge.

These data also validate the move of advising from faculty to professional advisors at this particular institution because the graduate students rated support services, communication, and knowledge of programs from the professional advisors positively. This finding supports the growing trend of using professional advisors instead faculty advisors for graduate students.

Further research on online advising, particularly at the graduate level, is needed. Although either a quantitative or qualitative study would likely yield interesting findings and could support or refute these findings, a case study or program evaluation would be particularly useful at the institution studied.

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Author notes

Author's Note

Lydia Karakolidis Cross, EdD, currently serves as the Assessment Coordinator in the College of Education at Georgia Southern University. She formerly served as the Director of the Graduate Academic Services Center at Georgia Southern University and has 9 years of graduate academic advising experience. Her research interests involve advising and support services access for online graduate students. She can be reached at lcross@georgiasouthern.edu.