The proliferation of technological advancements in professional counseling and counselor education has been identified as a major trend in the field (Layne & Hohenshil, 2005; Sampson, 2000; Sampson, Kolodinsky, & Greeno, 1997). An inclination toward the utilization of technology within the profession is evident as educators endeavor to integrate advancements into therapeutic and preparatory environments. Opportunities to provide alternatives and extensions to traditional modes of training have increased in frequency. These academic alterations parallel the needs of contemporary societal and global trends (Easton, 2004; Hohenshil, 2000; Mallen, Vogel, Rochlen, & Day, 2005).

The trend toward advanced technology presents several implications for the counseling profession. For example, electronic innovations provide opportunities for individuals, who have been otherwise limited, to receive counseling and testing services (Sampson, 2000). In addition, progressive technologies have facilitated data collection and research methods with inaccessible populations (e.g., international participants and rural settings), thereby increasing access to diverse data bases (Granello & Wheaton, 2004; Sampson, Kolodinsky, & Greeno, 1997). Advances have also provided support for counselor preparation as it relates to competency and practice. In particular, expansions have created the opportunities for individuals in the field to receive supervision at off-site locations, create electronic portfolios, and participate in video conferences and distance-learning (Layne & Hohenshil, 2005; Sampson, Kolodinsky, & Greeno, 1997). 

Innovations in communication technologies have made it possible to conduct outreach and advocacy for underserved populations and members of multicultural groups. Underserved populations may potentially benefit from the availability of internet counseling services, self-help forums, and psychoeducational materials (Mallen, Vogel, Rochlen, & Day, 2005). Although there are concerns with the safety of new technologies and the protection of clients involved in internet counseling and other innovative practices, the profession is responsible for preparing the next generation of counselors to expand the array of ethical and effective services. Consequently, the counseling profession has attempted to research and understand the diverse and potential implications of technology within the classroom environment.

Recently, Quinn, Hohenshil, and Fortune (2006) surveyed the use of technology within counselor education programs accredited by the Council for Accreditation of Counseling and Related Educational Programs (CACREP). These researchers reported that of the 44 programs surveyed, an average of 65% of the respondents reported integrating various forms of technology into the classroom. Furthermore, results indicated that CACREP core competency areas were being increasingly offered partially online and or through interactive video. Inferences from these findings reveal that technological integration has become more commonplace within traditional preparatory environments.

In conjunction with national inquiry, the Association for Counselor Education and Supervision (ACES, 1999) has recommended several technological competencies for counselor education faculty and students. These suggested proficiencies include the faculty members’ ability to adequately develop and deliver course material within online formats and the students’ capacity to understand and apply technology as it relates to statistics, data collection, research, and ethical implications. Yet as students and faculty are encouraged to become more accustomed as well as proficient with electronic advances, the profession’s ability to document and research such training extensions have received unequivocal support.

            Allowing for these professional responsibilities, researchers have endeavored to examine student learning styles and instructional preferences. In particular, Berry, Srebalus, Cromer, and Takacs (2003) studied 102 counselors-in-training within six CACREP programs in order to determine if associations existed between self-reported learning styles and preferred modes of instruction. A chi square analysis revealed that no significant associations between learning style and mode of instruction were found. Furthermore, Berry and colleagues (2003) found that counselor trainees’ reported that the preference of online instruction was not endorsed by any of the participants with their study. In light of these findings, it is important to note that the instrument selected for the aforementioned study, the Kolb Learning Styles Inventory, possessed low to moderate reliability coefficients. Accordingly, it appears professionally prudent that further examinations of learning styles and pedagogical preferences may reveal additional insight into the realm of technological-supported instruction.

            With universities increasing the number of distance learning courses students and faculty expect a quality online learning environment, and the assurance that standards of education online are equal to the traditional face-to-face lecture (Sales & Cannon-Bowers, 2001). From the literature review, it is evident there has been a lack of adequate studies examining the relationship of learning styles to distance learning success amongst students (Diaz & Cartnal, 1999). In addition, there is a scarcity of published studies examining the relationship of learning styles to student success in distance learning classes amongst counselors-in-training using the Grasha-Reichmann Student Learning Style Scale (GRSLSS). In order to supplement the area of learner disposition and instructional preferences, the present article examines learning style and individual inclination toward either online or face-to-face courses. The purpose of this study was to compare the learning styles of students selecting an online educational experience to those involved in a traditional face-to-face graduate course.

            The researchers in the study were interested in the comparison of counselors-in-training learning styles as well as preferences of instruction with respect to a CACREP Introduction Marriage and Family Counseling Course. The study was guided by the following research questions:

1.                            Are there significant differences in learning styles between students who enrolled in an online counselor education class verses a traditional face-to-face class, as measured by the GRSLSS?

2.                            What are the preferred modes of instruction for counseling graduate students enrolled in an Introduction to Marriage and Family Counseling class?

                                                                        Method

Participants

            The target for this study were students enrolled in a CACREP counseling program. Data were collected from 44 master’s level graduate students enrolled in an Introduction to Marriage and Family Counseling course at a South Texas university. Two groups of participants were compared for the main analyses: students enrolled in the traditional face-to-face method of instruction, (n=27, 61.4%), and students enrolled in an equivalent online experience, (n=17, 38.6%). One-hundred percent (n=44) of the students completed the research measures and were included in the final analysis.

The majority of the participants were women (n=38, 86.4%). Participants ranged in age from 20 to 50 years or above, with most of the students indicating they were between the ages of 25 and 29. Of the students in the sample, a vast majority (n=33) indicated their racial preference as White (75%). The racial preference of the remaining participants were as follows: 4.5 % American Indian/Alaskan Native, 2.3% American Indian/Alaskan Native/White, 18.2% other race. Zero percent identified themselves as Asian alone, Black/African American alone, Native Hawaiian, Asian/White, Black/White, or American Indian/Alaskan Native/Black. The ethnic background was collapsed into two categories: 1) non-Hispanic/non-Latino/a and 2) Hispanic or Latino/a. Twenty eight students (63.6%) identified their ethnicity as non-Hispanic/non-Latino/a; while sixteen students (36.4%) of students identified themselves as Hispanic or Latino/a.

Forty-three students (97.7%) indicated that it was not their first semester enrolled in the counseling program. The majority of the students were currently taking 4-6 credit hours (38.6%) or 7-9 credit hours (38.6%). In addition, twenty-five students (56.8%) reported being employed full time, twelve (27.3%) part-time, six (13.6%) not employed, and one person (2.3%) self-employed. The majority of students (63.6%, n=28) indicated that they live less than 10 miles from campus. Twelve students (27.3%) reported living 10-40 miles from campus and four students (9.1%) reported living 50 miles or more from campus. Only two students indicated that they were currently taking an additional online course.

Students were asked to give their consent to participate in the study. Once consent was obtained participants completed a demographics questionnaire. Upon completion of the demographics questionnaire the researcher administered the GRSLSS.

 

Instrumentation

            The instruments used in this study included a demographic data questionnaire, and the Grasha-Reichmann Student Learning Style Scales (GRSLSS). Besides asking the basic information in the demographics questionnaire as age, gender, race, or ethnicity, the researcher queried items regarding employment status, credit hours currently enrolled, and their experiences in other online courses. Students who chose the online course as their preferred method of instruction were also asked to indicate three reasons for enrolling in the online section. 

 The rationale for including the GRSLSS for this study includes: a) appropriateness for college students, b) its focus on students’ interactions with each other, the instructor, and the learning environment, c) its ability to assist faculty in the development of courses that meet student learner needs, and d) its ability to avoid stereotyping by indicating all students possess to some degree each of the learning styles (Diaz & Cartnall, 1999; Hruska-Riechmann & Grasha, 1982; Grasha, 1996).

Although the GRSLSS provides many advantages listed above, a major disadvantage is the scarcity of evidence on its validity and reliability. However this seems to be a concern with most learning style inventories.

            The GRSLSS measures six major learning styles: independent, dependent, competitive, collaborative, avoidant, and participant learners. Students may possess all six learning styles, but usually gravitate towards one or two of the learning preferences. Grasha (1996) describes the individual learning styles in the following manner. The “independent learner” is characterized as a student who prefers to work independently, likes to think for oneself, and has confidence in one’s learning ability. The “dependent learner” is described as a student who looks toward an authority figure and peers for guidance and structure, lacks intellectual curiosity, and typically performs only the duties that are assigned. The “competitive learner” is one who enjoys receiving recognition for their achievements in class and competes to perform better than one’s peers. Grasha, (1996), describes the “collaborative learner” as one who works well with both the instructor and student, enjoys sharing ideas and knowledge, and prefers lectures that involve group discussion and group projects. The “avoidant learner” is classified as by Grasha, (1996), as a student who is does not participate in class, is often uninterested and overwhelmed by class activities. The “participant learner” is eager to take part and will do as much class work as possible, desires to meet the instructor’s expectations, and expresses an interest in both class discussions and activities.

The Grasha-Reichmann Student Learning Style Scales has sixty items in which 10 items are assigned to each learning construct by using a Likert scale of 1 to 5. As an example, item 15 states, “I enjoy hearing what other students think about issues raised in class.” The participant is then asked to rate each sentence between 1 and 5, with 1 being you strongly disagree with the statement, 2 if you moderately disagree with the statement, 3 if you are undecided, 4 if you moderately agree with the statement, and 5 if you strongly agree with the statement.

Procedure

            Approval from the university’s institutional review board was obtained. The population of the study included 44 students enrolled in the Introduction to Marriage and Family Counseling course. During the first class session, students were informed they had an option of taking this course either face-to-face or online. After students chose their preferred method of instruction the primary author distributed a cover letter, informed consent information, and a coded questionnaire. Students were informed that participation was voluntary. The GRSLSS and a demographic questionnaire were distributed. Participants were permitted as much time as needed to complete all instruments. Students were informed they could withdraw from the study at any time without negative consequences. Students self-scored the GRSLSS inventory with scoring accuracy reviewed by the primary author who calculated and obtained the raw score for each of the learning style measures.        

The face-to-face lecture was taught by the primary and secondary author, while the online course was taught by the secondary author and a doctoral teaching assistant. Online and face-to-face course members utilized the same syllabi, Power Point presentations, and textbook. Both sections covered the same lecture material and took the same examinations throughout the semester.

Each section received the same material. However, the modes of instruction, interaction between students, and assignment of homework were different in delivery between the two groups. While students enrolled in the face-to-face section heard Power Point presentations, videos, and other lecture material in class, the online section reviewed the Power Points, videos, and other lecture material online through WebCT. Students that enrolled online participated in class discussion with their peers and the teachers by posting discussion questions and comments through WebCT, while students in the traditional classroom participated in face-to-face discussions. The online class received and submitted their timed exam through WebCT, while the face-to-face section completed their exams in class.  

 

 

Results

To explore learning style differences as related to preferred learning format (face-to-face vs. online) the Grasha-Reichmann Student Learning Style Scales (GRSLSS) was administered. Standard scoring on the GRSLSI provided six independent of learning styles. Each question was answered on a scale of 1 to 5 with 5 being strongly agreed. The six dimensions are seen as independent of each other. Further scoring was used to indicate describe the level of strength of each dimension (low, moderate, and high).

The initial results revealed that 17 of the 44 participants, (38.6%), selected to the online class format. There were no significant differences in class format choice by gender with about an equal percentage of males and females selecting face-to-face (66% and 61% for males and females respectively). Seventy-five percent of Hispanic students verses 53.6% of non-Hispanic students chose face-to-face over online.

Table 1: Learning Style Mean Scores

Learning Style Dimension	Average Scores		Significance
	Face-to-face	ONLINE
Independent	3.3(.55)	3.9(.15)	*F(1,42)=10.62,  p<.005
Avoidant	1.9(.53)	2.4(.69)	*F(1,42)=7.9,  p< .007
Collaborative	4.0(.66)	3.9(.54)	Ns
Dependent	3.5(.50)	3.5(.45)	Ns
Competitive	2.0(.47)	2.3(.88)	Ns
Participant	4.2(.52)	4.0(.48)	Ns

*p <.05

The average scores on the 6 learning style dimensions are presented in Table 1. The six learning styles average scores and standard deviations are indicated for online and face-to-face groups. All scores were subjected to 2 (Choice ) X 6 (Learning style) MANOVA. Significant Wilk’s lambda= .622, p< .05; suggested a significant difference in learning style scores between face-to-face and online learners. A follow up analysis revealed a mean difference in scores on avoidant and independent styles between the two groups. Results indicated that average scores on the independence and avoidant dimensions were significantly different as a function of choice. Specifically, online learners had higher scores on both the independent dimension and the avoidant dimension when compared to the face-to-face learners. There were no significant differences in learning style scores on the four other dimensions.

Table 2: Distribution of Learning Styles

	LOW	Moderate	HIGH
Independent	5	23	16
Avoidant	18	22	4
Collaborative	3	4	37
Dependent	4	36	4
Competitive	13	25	6
Participant	1	21	22

 

Table 2 shows the distribution of learning styles. Each participant’s level of endorsement of a particular learning style was scored according to the GRSLSS scoring guidelines as low, moderate, or high. All six learning styles were endorsed at least once within each level. The modal level of endorsement for a learning style was moderate for all styles with the exception of the collaborative and participant styles. This pattern is consistent with previous findings and suggests that all styles are represented as a preference for most individuals.

Table 3: Percentage and Distribution of Learning Style Choice                         

Learning Style/Level	Low                              Moderate                             HIGH
	Face-to- Face	online	Face-to- Face	Online	Face-to- Face	online
*Independent	80 (4)	20(1)	78(18)	22(5)	31(5)	69(11)
Avoidant	78(14)	22(4)	55(12)	45(10)	25(1)	75(3)
Collaborative	67(2)	33(1)	50(2)	(50(2)	62(23)	38(14)
Dependent	75(3)	25(1)	56(20)	44(16)	100(4)	0(0)
Competitive	69(9)	31(4)	64(16)	36(9)	33(2)	67(4)
Participant	100(1)	0(0)	48(10)	52(11)	73(16)	27(6)

 

^*Chi-sq. (2)= 9.6 p< .008

 

Table 3 shows the distribution of choice (face-to-face vs. online) across different levels of independent learning style dimensions. The proportions represented in Table 3 were subjected to a series of 2X2 Chi-Square tests for independence. Significant Chi-Square values indicated a statistically significant relationship between the specific learning style dimension and preferred mode of instruction (face-to-face vs. online). Results revealed that only for the independent dimension of learning style did level of endorsement relate significantly to choice. In specific, face-to-face was preferred about 4:1 at low and moderate levels of independent learning style while online was preferred about 2:1 at the high level.

Students who selected the online method of instruction were asked to indicate their top three reasons for enrolling in the online section. Seventy-one percent of the students indicated that convenience was their top reason for selecting the online section. Thirty-five percent stated they selected the online section because it was their preferred mode of instruction. A third reason for enrolling in the online section was because it would give them greater flexibility with their work schedule.

Discussion

Layne and Hohenshil (2005) predicted marked expansion, in both scope and content, of online counselor education courses, particularly those without a clinical aspect. They further asserted that, with new advances in technology, even courses with a strong clinical base will likely be part of future computer-based learning.

The refinement of technology competencies enumerated by entities such as CACREP and ACES reflected the importance of increasing the computer literacy of practitioners, students, and counselor educators, alike. Accordingly, authors such as Berry, et al. (2003) have underscored the need for the quality of online instruction in counselor education programs to equal that of face-to-face learning in a traditional setting.

One productive venue to maximize the effectiveness of online counselor education courses would be a detailed investigation of the interaction of instructor, student, and styles of learning—which was seen in the findings from this study.

 

 

Summary

            Although the majority of students preferred the traditional method of instruction, a notable proportion (38.6%) did select the online format with most, at 70.6%, citing convenience as the main reason for their choice. Other reasons for choosing online instruction included its format being a preferred method of study, and offering flexibility in one’s work schedule. There was no significant difference in gender as related to choice of instruction, however a pattern emerged regarding cultural background with face-to-face instruction preferred by 75% of Hispanic students, compared to 53.6% of non-Hispanic participants.          

A significant finding revealed that students selecting the online experience had significantly different scores in independent and avoidant learning styles when compared to participants choosing the face-to-face instruction. High level independent type learning style students preferred the online experience at a ratio of 2:1. These finding seem to fit with what might be expected of students preferring a more flexible learning environment allowing them to study away from campus on their own time frame. The avoidant learner style student has been described as one who does not participate in class and is often uninterested (Grasha, 1996). Perhaps this is a valid description of how a number of students respond to several classes taught under the traditional format and therefore choose on-line courses when offered.

Limitations

Although these findings indicated some significance the small sample size and purposeful nature of the sampling itself provides a word of caution when attempting to generalize to other populations. In addition, factors other than those investigated may have affected the students’ decision to choose either the face-to-face or the on-line course format. These factors include instructor personality, the close proximity of the university to the students’ place of residence, and the ease of parking on the campus.

Implications

The number of participants in this study who selected computer-based instruction perhaps reiterates the continued interest in online course offerings in counselor education. Consistent with earlier findings by Margaret Cannon et al. (2001), online learners in this project were attracted to this option because of convenience, scheduling flexibility, and simply having a basic preference for computer-based learning. 

Previous studies by authors, such as Berry et al. (2003), have indicated a general preference by counseling students for face-to-face instruction. In this study a significant proportion of Hispanic counselors-in-training also preferred face-to-face instruction perhaps reflecting the general population.

Findings from the GRSLSS have indicated that students demonstrate a mix of the different learning styles, with one or more learning style being “stronger,” or having a higher level of endorsement. Findings from the current study imply that students exhibiting an independent learning style are serious candidates for participating in online courses. When reviewing the learning style profile for participants in this study, collaborative and participant dimensions produced the highest levels. These findings reflect positively on counselors in training, characterized as learners representing styles of being enthusiastic and interested, wanting to meet high expectations, and enjoying classroom activities.

Accordingly, an instructor with a clear understanding of the above group profile would be motivated to include learning experiences that engage students. In addition, since participants in this study reflected all six learning styles to one degree or another, as recommended by Diaz and Cartnal (1999), perhaps instructors could also, incorporate growth experiences in which students participate in activities that engage less dominant learning styles in a nonthreatening environment in order to expand overall learning abilities. Having knowledge of the student learner profile perhaps could make both online and traditional course development more effective.

Recommendations

Further research, with replication and expansion, could provide additional information with the possibility of broader applications. Recommendations include utilizing more counselor education classes and studying student characteristics, preferences, and personal feedback. Mixed method paradigms are recommended including measuring and controlling additional variables, and conducting follow-up interviews with students and faculty participating in online education.  Additional instruments are recommended as the Dundee Ready Education Environment Measure (DREEM). This inventory purports to measure the educational environment, including evaluating the learning atmosphere, teacher, student, social interaction, and academic self-perception (Varma et al., 2005).

 

 

 

Questions useful to future researchers could include:

Are there differences in the cultural backgrounds of students as related to their selection or preferences for online instruction?

What is the relationship between online learning experiences and student learning styles?

What is needed to assure that online learning courses meet the standards of effectiveness and attractiveness that are present in most traditional face-to-face environments?

Given that a number of participants in this project chose online instruction, as contrasted to a lesser interest expressed in earlier studies, perhaps counselor educators should continue to investigate ways to help students increase their level of confidence in computer skills. Edwards, Portman, and Bethea (2004) proposed the inclusion of a computer technology course during the first year of study, as a pass/fail offering, which could benefit students by alleviating common stress associated with completing computer-based assignments.

Layne and Hohenshil (2005) highlighted the breadth of evidence concerning the success of practitioners and counselor educators working to meet the challenges of effectively using technology. This is a trend that appears to be well on its way to becoming part of the norm. The authors contend that by adding interactive television and videoconferencing this technology could quickly become more commonplace in meeting the needs of underserved students,  and those living in remote areas, or studying on satellite campuses.

During this period of change and innovation it is recommended that counselor educators explore ways to maximize the effectiveness and student friendliness of online instruction, along with traditional methods of teaching. Whether instruction is face-to-face, online, or hybrid, perhaps a profile of student learning styles can be helpful, allowing faculty to match curriculum, course design, and teaching methods to coincide with the specific needs and characteristics of students enrolled in counselor preparation programs.

 

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Authors’ Information

            Brandé Flamez, M.A., is a doctoral student in Counselor Education at Texas A&M University-Corpus Christi. She presently serves as the graduate student member on the International Association of Marriage and Family Counseling (IAMFC) Board of Directors, as well as, on the ACA’s Graduate Student standing committee.  She has presented at both national and international levels.

Robert L. Smith, Ph.D., is Professor and Chair of the Counseling and Educational Psychology Department at Texas A&M University-Corpus Christi. Dr. Smith is also the Director of the Counselor Education Doctoral Program, and is the Executive Director of IAMFC.

James M. Devlin, Ph.D., is an Assistant Professor at Seattle Pacific University in School Counseling and Psychology. He currently serves on the Executive Committee of the IAMFC and is the Chair of the ACA’s Graduate Student standing committee. Dr. Devlin is also the founder and lead consultant for the Counselor Education Research Consortium.

            Richard Ricard, Ph.D., is a Professor at Texas A&M University-Corpus Christi in the Counseling and Educational Psychology Department.

Margaret Sherrill Luther, Ph.D., is a Visiting Professor at Texas A&M University-Corpus Christi in the Counseling and Educational Psychology Department.