This study investigated the attitudes of peer tutors who received web conferencing training in preparation for synchronous online tutoring. A quasi-experimental design was employed to evaluate changes in peer tutors' attitudes toward distance learning following participation in an online tutor training program. Peer tutors were found to have: (a) an increased sense of the importance of distance learning offerings to adult learners' success, (b) an increased sense of the effectiveness of distance education programs compared to face-to-face, (c) an increased sense of experience level using distance learning tools, and (d) an increased sense of comfort using distance learning tools. Participants also demonstrated an increased overall positive attitude toward distance education. No significant difference in training effects between gender and age groups was found. Implications and suggestions for future research are discussed.
Online tutoring is rapidly expanding among college tutoring centers across the United States (Dvorak & Roessger, 2012). As campuses increase their online course offerings (Allen & Seaman, 2010), students may become exceedingly comfortable collaborating online and, therefore, participate more frequently in online support services. Peer tutors play an important role in helping make these services available. Their buy-in impacts the number of online tutoring sessions they hold each semester. To ensure peer tutors possess requisite skills and knowledge to succeed in the online environment, a formal online tutor training program is essential (Dvorak & Roessger, 2012).
The impact of training on peer tutors' attitudes toward distance education, however, has not been explored. Given the correlation between strong attitudes and subsequent behavior (Holland, Verplanken, & Knippenberg, 2002; Peng, Tsai, & Wu, 2006; Perez-Cereijo, 2006; Tabata & Johnsrud, 2008; Tello, 2004), training may play a decisive role in the success of an online tutoring initiative, particularly in ensuring that peer tutors embrace the platform and view it as an effective alternative to face-to-face services. In this study, the authors worked from the assumption that positive changes in peer tutors' attitudes correlate with positive behavioral change. The purpose of this study, then, was to investigate technology training's impact on the attitudes of peer tutors who participated in a formal training program in preparation for synchronous online tutoring.
Methodology
A quasi-experimental design was utilized in which a sample group was given a pretest survey prior to training participation and a posttest survey upon training completion. Pre- and post-training surveys were then analyzed for changes in peer tutors' responses. The training program focused on developing tutor competency using a web conferencing platform. Training sessions were divided into four weekly 1-hour modules: (a) introducing the web conferencing program, (b) utilizing web conferencing tools, (c) integrating interactive whiteboard technology with the web conferencing program, and (d) fostering student interactivity in a synchronous online tutoring session. In each session, skills were first introduced and modeled on an overhead screen. Participants were then given practice time to apply skills and knowledge to their subject areas. Sessions incorporated approximately 25% trainer modeling and 75% guided practice. During the latter phase, questions were posed to the group to promote dialogue and build connections between new information and tutors' subject area knowledge.
Participants
The survey was administered to 28 undergraduate and graduate peer tutors (N = 28) at a large Midwestern public university. Nineteen subjects were male; nine were female. Their ages ranged from 18 to 44. The sample included veteran and newly hired peer tutors, each of whom maintained a 3.0 grade point average or higher, and had earned between an A and B+ in their subject area.
Instrument
The survey instrument was developed by the authors to assess participants' attitudes toward distance learning. The instrument utilized a mixed format approach, consisting of five 10-point Likert-type scale questions, and four hierarchical response multiple-choice questions (see Table 1). Survey items were grouped into three three-item interpretable categories: (a) distance and face-to-face learning comparisons, (b) distance learning tools in personal practice, and (c) distance learning and the adult learner. Responses were structured so that higher numerical scores represented more favorable attitudes toward distance learning. Two anonymous participant characteristic items were included at the beginning of the survey to assess participants' gender and age.
Survey Content Used to Assess Participants' Attitudes Toward Distance Learning
| Category | Item | Question | Scale |
|---|---|---|---|
| Distance and face-to-face | 8 | When comparing how much time an educator must devote to |
|
| 2 | How effective do you feel distance learning programs are compared to face-to-face ones? | 1 (much less effective) ... 10 (much more effective) | |
| 3 | What is your preference about interacting in an online environment as opposed to a face-to-face one? |
| |
| Distance learning tools in personal practice | 4 | How likely would you be to use distance learning tools to supplement your current practice if not mandated to do so? | 1 (not likely) ... 10 (very likely) |
| 5 | How would you rate your experience level using distance learning tools? | 1 (no experience) ... 10 (very experienced) | |
| 6 | How would you rate your level of comfort with distance learning tools? | 1 (not comfortable) ... 10 (very comfortable) | |
| Distance learning and the adult learner | 7 | How do you feel distance education has affected the quality of adult education? |
|
| 1 | How important do you feel that providing distance learning opportunities is to the success of adult learners? | 1 (not important) ... 10 (very important) | |
| 9 | Which statement would you most closely agree with? |
|
| Category | Item | Question | Scale |
|---|---|---|---|
| Distance and face-to-face | 8 | When comparing how much time an educator must devote to | 1- Distance education programs require significantly more of a time investment. 2- Distance education programs require somewhat more of a time investment 3- Both approaches require the same time investment. 4- Face-to-face programs require somewhat more of a time investment 5- Face-to-face programs require significantly more of a time investment |
| 2 | How effective do you feel distance learning programs are compared to face-to-face ones? | 1 (much less effective) ... 10 (much more effective) | |
| 3 | What is your preference about interacting in an online environment as opposed to a face-to-face one? | 1- Strongly prefer face-to-face 2- Somewhat prefer face-to-face 3- Somewhat prefer fully online 4- Strongly prefer fully online | |
| Distance learning tools in personal practice | 4 | How likely would you be to use distance learning tools to supplement your current practice if not mandated to do so? | 1 (not likely) ... 10 (very likely) |
| 5 | How would you rate your experience level using distance learning tools? | 1 (no experience) ... 10 (very experienced) | |
| 6 | How would you rate your level of comfort with distance learning tools? | 1 (not comfortable) ... 10 (very comfortable) | |
| Distance learning and the adult learner | 7 | How do you feel distance education has affected the quality of adult education? | 1- It has significantly decreased the quality of adult education 2- It has somewhat decreased the quality of adult education 3- It has had no effect on the quality of adult education 4- It has somewhat improved the quality of adult education 5- It has significantly improved the quality of adult education |
| 1 | How important do you feel that providing distance learning opportunities is to the success of adult learners? | 1 (not important) ... 10 (very important) | |
| 9 | Which statement would you most closely agree with? | 1- Distance education is not applicable to any subject area 2- Distance education is applicable to a few subject areas 3- Distance education is applicable to some subject areas 4- Distance education is applicable to all subject areas |
“…” indicates omitted whole number intervals of Likert-type scale.
The instrument's reliability was determined using a Cronbach's alpha reliability test on both pre- and post-test scores. The pretest consisted of nine items (α = .73), as did the posttest (α = .79). Reliability coefficients exceeded the 0.7 acceptability cutoff as indicated by Nunnaly and Bernstein (1994) and George and Mallery (2003).
The instrument's validity was assessed using three criteria: face validity, content validity, and predictive criterion validity. Face validity (Nunnally & Bernstein, 1994) was determined by presenting initial drafts of the instrument to members of the subject group (i.e., peer tutors) and soliciting their reactions. Content validity (Messick, 1993) was determined by presenting the instrument draft to four content experts in the area of online peer tutoring (i.e., student services administrators), then making subsequent changes according to their recommendations. Predictive criterion validity (Cronbach, 1984) was established by collecting criterion data following the study's completion. Peer tutor participation in online synchronous tutoring sessions increased 940% following participation in the aforementioned formal training program as compared to the preceding semester. Given the survey results discussed later in this research brief, this correlation was consistent with the authors' assumption that positive changes in peer tutors' attitudes correlate with positive behavioral change, thus demonstrating the survey's predictive criterion validity.
following participation in the aforementioned formal training program as compared to the preceding semester. Given the survey results discussed later in this research brief, this correlation was consistent with the authors' assumption that positive changes in peer tutors' attitudes correlate with positive behavioral change, thus demonstrating the survey's predictive criterion validity.
Results
Data were first analyzed using paired samples t tests. Table 2 provides pre- and post-training means for each survey item along with its corresponding standard deviation. Results demonstrated significant changes in four pre- and post-test survey items. Each three-item interpretable category was impacted. First, peer tutors' item one responses indicated an increased sense of the importance of providing distance learning opportunities to adult learners' success (t = −2.448, p = .021). Second, tutors' item two responses indicated an increased sense of the effectiveness of distance learning programs compared to face-to-face programs (t = −3.124, p = .004). Third, tutors' item four responses indicated an increase in experience level using distance learning tools (t = −3.187, p = .004). Finally, tutors' item five responses indicated an increased level of comfort using distance learning tools (t = −2.204, p = .037). In addition, a cumulative mean response score was calculated for each completed survey, indicating a participant's overall attitude toward distance education. Cumulative mean response scores significantly increased on posttraining surveys (t = −3.283, p = .003).
The Impact of Training on Participants' Survey Item Responses
| Item # | Pretraining Mean (SD) | Posttraining Mean (SD) | t Value | 2-tail Prob. |
|---|---|---|---|---|
| 1 | 6.75 (1.86) | 7.86 (1.41) | −2.448 | 0.021* |
| 2 | 3.86 (1.80) | 5.57 (2.46) | −3.124 | 0.004** |
| 3 | 1.35 (0.56) | 1.50 (0.56) | −1.000 | 0.327** |
| 4 | 4.39 (2.38) | 5.32 (2.88) | −1.714 | 0.098** |
| 5 | 3.79 (2.13) | 5.68 (2.63) | −3.187 | 0.004** |
| 6 | 5.20 (2.31) | 6.64 (1.93) | −2.204 | 0.037* |
| 7 | 3.60 (0.96) | 3.92 (1.04) | −1.317 | 0.200** |
| 8 | 3.20 (1.04) | 2.76 (1.13) | −1.325 | 0.198** |
| 9 | 3.04 (0.46) | 3.16 (0.75) | −0.768 | 0.450** |
| 1-9 | 3.92 (0.94) | 4.76 (1.13) | −3.283 | 0.003** |
| Item # | Pretraining Mean (SD) | Posttraining Mean (SD) | t Value | 2-tail Prob. |
|---|---|---|---|---|
| 1 | 6.75 (1.86) | 7.86 (1.41) | −2.448 | 0.021 |
| 2 | 3.86 (1.80) | 5.57 (2.46) | −3.124 | 0.004 |
| 3 | 1.35 (0.56) | 1.50 (0.56) | −1.000 | 0.327 |
| 4 | 4.39 (2.38) | 5.32 (2.88) | −1.714 | 0.098 |
| 5 | 3.79 (2.13) | 5.68 (2.63) | −3.187 | 0.004 |
| 6 | 5.20 (2.31) | 6.64 (1.93) | −2.204 | 0.037 |
| 7 | 3.60 (0.96) | 3.92 (1.04) | −1.317 | 0.200 |
| 8 | 3.20 (1.04) | 2.76 (1.13) | −1.325 | 0.198 |
| 9 | 3.04 (0.46) | 3.16 (0.75) | −0.768 | 0.450 |
| 1-9 | 3.92 (0.94) | 4.76 (1.13) | −3.283 | 0.003 |
Significant at the 0.05 level.
Significant at the 0.01 level.
The Impact of Training on Participants' Survey Item Responses
| Sum of Squares | df | Mean Square | F | Sig. | |
|---|---|---|---|---|---|
| Pretest between groups | 0.286 | 1 | 0.286 | .314 | .580 |
| Pretest within groups | 23.664 | 26 | 0.910 | ||
| Total | 23.950 | 27 | |||
| Posttest between groups | 0.039 | 1 | 0.039 | 0.029 | .866 |
| Posttest within groups | 34.671 | 26 | 1.334 | ||
| Total | 34.710 | 27 |
| Sum of Squares | df | Mean Square | F | Sig. | |
|---|---|---|---|---|---|
| Pretest between groups | 0.286 | 1 | 0.286 | .314 | .580 |
| Pretest within groups | 23.664 | 26 | 0.910 | ||
| Total | 23.950 | 27 | |||
| Posttest between groups | 0.039 | 1 | 0.039 | 0.029 | .866 |
| Posttest within groups | 34.671 | 26 | 1.334 | ||
| Total | 34.710 | 27 |
One Way ANOVA – Training Effect Differences by Age
| Sum of Squares | df | Mean Square | F | Sig. | |
|---|---|---|---|---|---|
| Pretest between groups | .042 | 1 | .042 | .046 | .832 |
| Pretest within groups | 23.907 | 26 | .920 | ||
| Total | 23.950 | 27 | |||
| Posttest between groups | 3.638 | 1 | 3.638 | 3.044 | .093 |
| Posttest within groups | 31.073 | 26 | 1.195 | ||
| Total | 34.710 | 27 |
| Sum of Squares | df | Mean Square | F | Sig. | |
|---|---|---|---|---|---|
| Pretest between groups | .042 | 1 | .042 | .046 | .832 |
| Pretest within groups | 23.907 | 26 | .920 | ||
| Total | 23.950 | 27 | |||
| Posttest between groups | 3.638 | 1 | 3.638 | 3.044 | .093 |
| Posttest within groups | 31.073 | 26 | 1.195 | ||
| Total | 34.710 | 27 |
Data were then analyzed for potential training effect differences by gender and age (see Tables 3A and 3B). A one-way ANOVA indicated no significant difference by gender in pretest responses (F = .314, p = .580) or posttest responses (F = .029, p = .866), and no significant difference by age group in pretest responses (F = .046, p = .832) or posttest responses (F = 3.04, p = .093).
Discussion
The results of this study reveal online tutor training's immediate impact on peer tutors' attitudes toward distance education. One important implication is that a structured tutor training program may increase peer tutor participation and commitment to online synchronous tutoring. Several findings are particularly notable. First, participants demonstrated an increased sense of the importance of distance learning offerings to adult learners' success. As the number of older, nontraditional age students entering higher education increases (Choy, 2002), it is important that peer tutors perceive online tutoring programs as useful and effective at meeting this group's needs. The significant changes in peer tutors' attitudes in this area may be due in part to the increased flexibility online tutoring offers learners. Peer tutors may view online tutoring as a useful tool for off-campus learners unable to attend regularly scheduled face-to-face sessions. They may also see online tutoring as a way to hold additional tutoring sessions on weekends or evening hours when nontraditional adult students are typically more available.
Another significant finding was peer tutors' increased sense of the effectiveness of distance education programs compared to face-to-face programs. Interestingly, this finding may be particularly useful in determining training's impact on performance or program implementation. In a study examining the impact of introducing new technologies in a healthcare setting, Ben-Zvi and Rohmeyer (2011) found that perceived effectiveness correlates significantly with improved company performance. As participants' perceived effectiveness of new technologies increased, so did their subsequent performance in relation to the new technologies.
A further significant finding was peer tutors' increased sense of experience level and comfort using distance learning tools (i.e., survey items five and six). Each of these items is grouped in the second interpretable category, distance learning tools in personal practice. This category differs from categories one and three in that it focuses on how peer tutors perceive their own abilities using distance learning technologies (e.g., web conferencing platforms). It can be argued that this category measures a limited degree of a participant's self-efficacy construct. Bandura (1998) defines self-efficacy as, “people's beliefs about their capabilities to produce designated levels of performance that exercise influence over events that affect their lives” (p. 421). High or increased technology self-efficacy scores have been repeatedly linked to improved technology performance (Peng et al., 2006; Tsai & Tsai, 2003). In addition, computer training has been shown to have a positive impact on participants' perceived computer self-efficacy (Compeau & Higgins, 1995; Torkzadeh & Van Dyke, 2002). The present study's findings, then, suggest that specific investigations into the relationship between peer tutors' perceived self-efficacy and formal training programs are indeed warranted and necessary.
Although the current study found no training effect differences by gender or age, previous research has repeatedly demonstrated gender differences. Peng et al. (2006), for example, found that male undergraduates exhibited more positive Internet attitudes than females. Torkzadeh and Van Dyke (2002) found that on pre- and post-training tests males consistently scored higher in Internet self-efficacy and computer user attitudes.
There are several potential reasons for discrepancies between these and the current study's findings. One is that this study's relatively small sample sizes (nmales = 19, nfemales = 9) may have muted possible differences between groups. Female responses to survey item four, for example, yielded a high t score (t = −2.294, p = 0.51), yet failed to meet the significance criterion by one one-hundredth of a percent. A second possible explanation for this discrepancy is that female attitudes toward distance education have begun to align with males' in the time since Peng et al. (2006) and Torkzadeh and Van Dyke's (2002) findings. In a contemporary analysis of college students' Internet-related attitudes, Chou, Wu, and Chen (2011) found that both genders equally perceived the importance of four of six measureable Internet dimensions. Their findings indicate that the attitudinal gap may be closing.
Conclusion
This research suggests that a formal online tutor training program has a significant effect on peer tutors' attitudes toward distance education. The findings presented here are consistent with research examining the impact of technology training on other demographics' behaviors and constructs, such as instructors' participation in distance learning (Dobbs, 2004; Lee & Busch, 2005; Galusha, 1998), students' attitudes toward computers (Torkzadeh & Koufteros, 1993), professors' and administrators' attitudes toward distance education (Savage, 1999), and academic professionals' perceived confidence and capability (Ng, 2007). The current study adds to this body of research by examining technology training's impact on peer tutors' attitudes toward distance education. In conclusion, a structured tutor training program may be a useful tool for increasing peer tutor participation and commitment to an online synchronous tutoring program. The findings presented here can serve to generate further research into the impact of online tutor training on peer tutors and student success.
