Closing the gap: impact of student proactivity and learning goal orientation on e-learning outcomes.

To increase flexibility in course offerings and to enhance student-learning experiences, universities and management educators have introduced and incorporated a number of new and innovative e-learning technologies. However, little systematic research has been conducted to examine the value of using the technology to facilitate learning and student satisfaction. This study investigates several student characteristics, such as proactive personality and learning goal orientation, and a number of e-learning outcomes including the student's perception of the quality of their learning and overall satisfaction. While previous research indicates that e-learning technology can support higher-order thinking by engaging students in authentic and complex tasks, our e-learning model seeks to understand the individual's background and perceptions that may be essential to student education. Results revealed that a student's proactive personality along with his/her learning goal orientation influenced his/her perception of the quality of learning occurred and overall satisfaction of the e-learning course and environment. Interestingly, although quality of learning and satisfaction were higher when a student possessed a high learning goal and high proactive personality, the "gap" closed considerably when proactivity was included in our analyses. Practical implications based on our findings as well as directions for future research are discussed.

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In recent years, universities have introduced a number of e-learning technologies to increase flexibility in course offerings and to enhance student-learning experiences. Educators involved in the many forms of distance education are exploring the potential of e-learning instruction as an extension or even a replacement to their current educational delivery systems. Given the changing workplace environment and the requirement for continual employee learning, many working adults are searching for universities that offer their courses using e-learning technology and programs (Cooper, 1999). However, the rapid growth in e-learning is occurring without research into the value of e-learning tools to students. The purpose of our study is to understand the underlying student factors and motivations that determine their assessment of learning and fulfillment within the e-learning environment. We examine students' proactive personality as well as their learning goal orientation in influencing their perception of quality of learning and overall course satisfaction.

ACHIEVING MULTIPLE OUTCOMES: THE VALUE OF E-LEARNING

The term "e-learning" involves using the Internet as a communications medium where the instructor and students are separated by physical distance (Cooper, 1999). E-learning expands the learning opportunities of students who are time-limited, live in remote communities, and/or have other barriers and commitments that prevent them from attending a traditional classroom learning environment. Common e-learning tools include discussion boards, e-mail, chat rooms, video streaming, document transfer, and other technologies to facilitate the educational process. According to Eduventures, a Boston-based educational research firm, online education has seen phenomenal growth in the last couple of years with the overall market expected to top US $4 billion by 2005. Over 90% of US public colleges offer at least one online course and enrollment in these courses has increased by almost 20% this year (Eduventures, 2003).

CONSIDERING THE INDIVIDUAL STUDENT IN THE E-LEARNING PROCESS

A Student's Learning Goal Orientation

Numerous studies have examined the relationship between student goal orientation in the acquisition of knowledge both in the classroom and in training programs (Burley, Turner, & Vitulli; 1999; Johnson, Beauregard, Hoover, & Schmidt, 2000; Kozlowski et al., 2001; VandeWalle, Cron, & Slocum, 2001). According to Dweck (1986), goal orientation was composed of two primary types; performance goal orientation and learning goal orientation. In performance goal orientation, a person attempts to prove his or her competence by seeking positive feedback and the avoidance of criticism. According to Kozlowski et al. (2001), people with performance goal orientation seek easy situations that reflect their perceived capabilities, thus avoiding any new or challenging learning circumstances where they may receive negative feedback from mistakes committed.

Conversely, an individual with a learning goal orientation attempts to prove one's competency through the acquisition of new skills and knowledge for the sake of learning and to demonstrate mastery of a situation. According to Koestner and Zuckerman (1994), learning goal orientation will normally result in the employment of a wider variety of learning strategies, knowledge exploration, and increased application of their metacognitive knowledge. They are more flexible with change, persistent when confronted with difficult or new tasks, and are affected less by failure (Kozlowski et al., 2001).

The emergence of online learning in the last five years has created a new, more adult or learner-centered learning approach that may be affected by a person's goal orientation characteristics. Not only are online students faced with the difficult task of completing their college education, but they have also selected an information delivery medium that is in its infancy and prone to operational difficulties. Online students must learn to use this new technology and must be persistent in the face of obstacles such as slow network speeds, congestion, hardware and software failure, and the potential for Internet outages. Given these characteristics, a classroom setting with its challenging learning, increased personal effort, and potential for errors or failure creates an environment that may be suited for people with a high learning goal orientation. Additionally, students with high learning goal orientation are more likely to engage in strategies that result in improved learning performance within an online environment. Thus,

Hypothesis 1: Students with a high learning goal orientation will have higher perceptions of the quality of their learning and overall e-learning satisfaction.

A Student's Proactive Personality

The proactive personality is defined by Bateman and Crant (1993) as one that takes action to influence environmental change. Proactive personalities "scan for opportunities, show initiative, take action, and persevere until they reach closure by bringing about change" (Bateman & Crant). According to Crant and Batemen (2000), people with proactive personalities effect their environment by employing personal initiative, active problem solving actions and will persevere until achieving their goal. Conversely people with a low proactive personality will tend to demonstrate a more passive approach to situation and changes. People with proactive personality may influence their vocational choice and may be drawn toward entrepreneurship in particular (Crant, 1996). One can argue that students who possess a proactive personality will be inclined to perform well in an online course where the learning paradigm has shifted from teacher to learner-centered environment. In this new learning environment, students must assume the initiative for their learning and the teacher becomes a coach or a guide in the educational process. Given an educational setting where the student is expected to assume the responsibility for learning, a person who demonstrates a low proactive personality will be less likely to succeed since their tendency is to passively adapt to the online circumstances. This passive adaptive response is not well suited for a learner-centered environment found within an online course. Therefore,

Hypothesis 2: Students with a high proactive personality will have higher perceptions of the quality of their learning and overall e-learning satisfaction.

COMBINING THEIR INFLUENCE: LINKING BOTH LEARNING GOAL ORIENTATION AND PROACTIVE PERSONALITY

While both e-learning goal orientation and proactive personality may independently be important in determining a student's perception of the quality of their learning and satisfaction, the combined influence of both of these personal factors may strengthen their e-learning beliefs and outcomes. Effective online classes shift the focus from instructor-centered education to one where the student assumes the responsibility for his or her education. In a student-centered learning environment, such as an online class, the student must become increasingly self-sufficient with the responsibility of "going to class," meeting assignment deadlines, and having to solve issues from both a course content and technology context.

Students in an e-learning environment should also have the ability to work with minimal direction and rely heavily on their past experiences when confronted with new learning situations. E-learners with a strong learning goal orientation may prefer and appreciate the experiential learning situations often found within an e-learning course, but they must also be proactive in how they relate and transform theory into practical applications outside of the classroom Thus, their learning goal orientation combined with their proactive personality may further enhance their perceptions of the quality of learning received and overall fulfillment of participating in an e-learning course. Thus,

Hypothesis 3: The interaction of learning goal orientation and proactive personality will influence perceptions of the quality of learning and satisfaction. That is, students with a high learning goal orientation and high proactive personality will have higher perceptions of the quality of their learning and overall e-learning satisfaction.

METHOD

Participants

There was a total of 241 participants in the study including both graduate and undergraduate students taking courses in Health Arts, Nursing, Professional Arts, the MBA program, and the Health Services Administration field at a private, Midwestern university. All students were enrolled in the university's online program and received all of their classroom instruction through the school's Internet-based course system. The students were geographically dispersed across the United States. The data for the study was gathered using an Internet, web-based questionnaire and was an optional component of the students' courses during the spring of 2001. Of the 241 participants, 24% were graduate students enrolled in a management-related program, 72% were undergraduate students, and 4% did not indicate their major. Of the undergraduate students, 85% were enrolled in a Health Arts degree completion program designed for full-time, working adults, 7% were Nursing students, and 8% were undergraduate business students. Over 90% of the participants in this study were either employed full-time in the business and health care field, or were enrolled in a business-related program.

Questionnaire and Measures

The instrument used in this study was based on various questions asking the students to evaluate the effectiveness of online classes, goal orientation, self-efficacy, and several other constructs. During the last three weeks of a course, students completed the research questionnaire as a component of the university's course/instructor assessment. The learning goal orientation component of the questionnaire consisted of 10 questions using the same 7-point Likert scale to rate each response (Button, Mathieu, & Zajac, 1996). For the purpose of analysis, median-splits were conducted on proactive personality and learning goal orientation to classify individuals with either high or low proactive personality and high or low learning goal orientation. Internal Consistency (Cronbach's Alpha) for this scale was .86

To assess proactive personality, we used five items from Bateman and Crant's (1993) scale. Items included in this measure: "I enjoy facing and overcoming obstacles to my ideas," "Nothing is more exciting than seeing my ideas turn into reality," "I excel at identifying opportunities," "I love to challenge the status quo," and "I can spot a good opportunity long before others can." Participants rated these items on a seven-point Likert scale (1 = "strongly disagree;" 7 = "strongly agree"). Cronbach's alpha of this scale was .88.

The perception of the quality of learning and overall satisfaction were assessed by ratings of traditional and online courses using the Relative Percentile Method (Goffin, Gellatly, Paunonen, Jackson, & Meyer, 1996). In this method, participants rate the online courses on various dimensions by comparing them to the traditional classroom course they may have taken in the past. Participants were informed that this method of rating is based on percentages ranging from 0 to 100. A student believing there was no difference between a typical traditional classroom and an online class should be situated in the middle of the scale and would receive a "percentile rank" of 50. For the quality of learning question, participants were asked to: "rate the overall quality of learning in an online class as compared with the quality you have experienced in the traditional classroom." For overall satisfaction, participants were asked to: "rate your overall satisfaction with your online course compared with traditional classes you have taken." The final version of the questionnaire was converted into a web-based form for use by the students from their home computer.

Although Internet-based surveying may require sophisticated programming expertise (over the traditional paper and pencil format), the software used to develop the questionnaire can be programmed automatically to collect summaries of the data that can be readily tabulated and analyzed. Researchers who have compared online and traditional mail respondents have concluded that there are no significant response biases between these two methods in regards to demographic and/or attitudinal data (Bachmann, Elfrink, & Vazzana, 1996; Mehta & Sivadas, 1995; Tse, 1998).

Statistical Analysis

Analysis of variance (ANOVA) was used to analyze our data. Both "proactive personality" and "learning goal orientation" consisted of our independent variables and "perceived quality of learning" and "satisfaction" served as our dependent variables.

RESULTS

An ANOVA of the means revealed significant differences between proactive personality groups (high vs. low) regarding quality of learning (main effect, F=11.56, p<.05) and overall satisfaction (main effect, F=5.37, p<.05). Additionally, we also found differences between learning goal orientation groups regarding quality of learning (main effect, F=3.56, p=.06) and overall satisfaction (main effect, F=7.14, p<.05). More importantly we found interactions between proactive personality and learning goal orientation on both e-learning outcomes (F=2.85, p=.09 for quality of learning; F=5.27, p<.05 for overall satisfaction). Tables 1 through 3 display the means, standard errors, and confidence levels for each independent variable and interaction related to perceived quality of learning and satisfaction.

To further depict our results, we also conducted follow-up profile plots of the interaction and role of proactive personality on perceived quality of learning and satisfaction (see Figure 1).

[FIGURE 1 OMITTED]

DISCUSSION

As we begin to increase our understanding of the value of incorporating e-learning technology in our courses, it may be important to understand a student's personality and learning goals. Our study examined students' proactive personality and learning goal orientation and its influence on the perception of the quality of learning and satisfaction. Our results demonstrate that proactive personality can be a motivating factor along with a student's learning goals on his/her assessment of learning and fulfillment within the e-learning environment.

Given our findings on both the learning goal orientation and proactive personality, students that have these traits have higher levels of perceived learning and satisfaction with their online class. Most online courses shift the focus from instructor-centered education to one of which the student assumes the responsibility for his/her learning. Students within an online environment must be able to navigate through several learning areas and modules (e.g., discussion module, an assignment area, chat rooms, and online examinations or assessments). In a student-centered learning environment, which characterizes most online courses, the student must become increasing self-sufficient, goal-directed, and proactive in how he/she fulfills their responsibilities of meeting assignment deadlines, and having to solve issues from both a course content and technology context.

While learning goal orientation was a key factor in influencing learning and satisfaction, proactive personality played a pivotal role in enhancing students learning. Although quality of learning and satisfaction was higher when a student possessed a high learning goal orientation and high proactive personality, the "gap" closed considerably when proactivity was included in our analyses (as shown on the follow-up profile plots). Since students function within an online environment that is less structured and learning centered, having a learning goal orientation may be only one key prerequisite to their learning and fulfillment. A student's proactivity may further propel them to engage in complex assignments and problems, and persevere until they have achieved their desired learning goals.

Many of the students surveyed who had a high proactive personality also made some interesting comments that are related to e-learning processes, the perception of quality of online learning they received, and the learning outcomes of their online classes. From the students' perspectives, here are just a few of the comments that were gathered in the online program:

  I particularly like the discussion portion of the classroom or online
  setting, as it is a very meaningful part of how I learn. The online
  forum actually has allowed me to participate in discussions all week
  versus one night a week.

  I feel like I can express myself more on the Internet than in a
  regular classroom. Maybe talking in front of everyone is more
  intimidating than talking on the Internet. You can get a lot of good
  feedback from your fellow students as well as your instructor. All of
  the information is very educational and helps you to expand your
  knowledge on the subject.

  The rapid feedback from the professor and the interaction with peers'
  homework assignment sparked class discussion.

  The online class allowed me to take as much time as I want to read and
  think about subject material including classmate discussion remarks.
  Being able to e-mail my professor or anyone in my class any time I
  like was a great advantage.

  I wish people would stop trying to compare this forum of learning with
  that of an onsite classroom. I have by far had more interaction and
  more discussion online than I ever had in a conventional classroom.

NEW IDEAS AND DIRECTIONS FOR FUTURE RESEARCH

Although this research examined the role of the individual learner in the preference of e-learning tools and programs, future work should also investigate the context of learning, information technology issues, and the instructor/learning design (Alexander, 2001; Alexander & Blight, 1996) from both a quantitative and qualitative student perspective. For context of learning, the level of learner support made available to the student at the course, departmental, and university level should be examined. Moreover, the technology support and design needs to be evaluated. That is, does the current technology support and enhance the learning environment for all types of management courses and audiences? What are the various methods of interaction made possible with the online technology? Finally, what kinds of learning strategies as well as designs are appropriate for the nature of the management course and context? What are the various assessment opportunities for students to engage in throughout the course? How do these methods and assessments influence the different types of audiences that may be interested in an e-learning course (i.e., variability between adult returning graduate students or traditional undergraduate students)?

For universities and management programs that are considering the adoption and utilization of e-learning tools and programs, Morgan (2001) discussed the different stages of e-learning applications (first generation, second generation, and third generation). In the first generation, the Internet technology is controlled by the instructor and is seen as a delivery mechanism (a method to distribute materials, outlines to students). In the second generation, the learning needs of the students drive the design of the educational environment. "The educational system adapts to the learner, not the other way around--as in the 'text or course online' models" (p. 209). Students can receive information on management ideas and issues in a "just-in-time, just enough" basis. In the final and third generation. learning systems are built and enhanced around the philosophy of the second generation. Central to this third generation learning system will be high bandwidth learning technology that is able to support virtual classrooms and collaboration as well as complex simulations that have the potential to improve the e-learning environment.

If past educational technology trends continue, high bandwidth technology will be introduced before critical learning support mechanisms are provided to students, faculty, and administrators. As multimedia content containing video and audio transmissions are integrated into online courses, the need for technological support for distance students and faculty will also increase. Kickul and Kickul (2001) found a significant relationship between academic support functions and students' utilization of e-learning tools and programs. These support functions also apply to preparing and assisting faculty in the teaching of online courses and will increase as we move to a high bandwidth-learning environment. From an administrative perspective, there will be a struggle with providing new technology requiring high bandwidth into geographical areas that lack sufficient communication infrastructure. These major issues and concerns will need to be adequately addressed before the Morgan's third generation learning system becomes a reality.

CONCLUSION

With the restrictions of time and location, e-learning may prove to be an attractive option for many students who have increasing commitments to family and work. Restrictions and commitments aside, it may be important to understand how their background, underlying personality, and motivations affect how they assess the quality of their own learning and gained satisfaction from taking an e-learning course. Although more work remains to be done, it is our hope that future researchers will continue to examine practical ways universities and management educators can develop new e-learning courses that address the challenges of meeting many of the needs of students with differing preferences, needs, and motivations.

References

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Alexander, S., & Blight, D. (1996). Information technology in international education, Canberra, Australia: IDP.

Bachmann, D., Elfrink, J., & Vazzana, G. (1996). Tracking the progress of e-mail vs. snail-mail. Marketing Research, 8, 30-36.

Bateman, T. S., & Crant, J. M. (1993). The proactive component of organizational behavior: A measure and correlates. Journal of Organizational Behavior, 14, 103-118.

Burley, R. C., Turner, L. A., & Vitulli, W. F. (1999). The relationship between goal orientation and age among adolescents and adults. The Journal of Genetic Psychology, 160(1), 84-88.

Button, S. B., Mathieu, J. E., Zajac, D. M. (1996) Goal orientation in organizational research: A conceptual and empirical foundation. Organizational Behavior and Human Decision Processes, 67. 26-48.

Cooper, L. (1999). Anatomy of an online course. T.H.E. Journal, 26(7), 49-51.

Crant, J. M. (1996). The proactive personality scale as a predictor of entrepreneurial intentions. Journal of Small Business Management, 34(3), 42-50.

Crant, J. M., & Bateman, T. S. (2000). Charismatic leadership viewed from above: The impact of proactive personality. Journal of Organizational Behavior, 21(1), 63.

Dweck, C. S. (1986) Motivational processes affecting learning. American Psychologist, 41, 1040-1048.

Eduventures (2003, August). Learning markets & opportunities 2003: New models for delivering education and services drive pre-K-12 and postsecondary sector growth, (Eduventures Report).

Goffin, R.D., Gellatly, I.R., Paunonen, S.V., Jackson, D.N., & Meyer, J.D. (1996). Criterion validation of two approaches to performance appraisal: The behavioral observation scale and the relative percentile method. Journal of Business and Psychology, 11(1).

Johnson, D. S., Beauregard, R. S., Hoover, P. B., & Schmidt, A. M. (2000). Goal orientation and task demand effects on motivation, affect, and performance. Journal of Applied Psychology, 83(5), 724-738.

Kickul, J, & Kickul, G. (2001) Implementing e-Learning innovations and technologies: Test of an integrated model within a university setting. The Business, Education and Technology Journal, 3(1).

Koestner, R., & Zuckerman, M. (1994) Causality orientation, failure, and achievement. Journal of Personality, 62, 321-345

Kozlowski, S. W., Gully, S. M., Brwon, K. G., Salas, E., Smith, E. M. & Nason, E. R. (May, 2001). Effects of training goals and goal orientation traits on multidimensional training outcomes and performance adaptability. Organizational Behavior and Human Decision Processes, 85(1), 1-31.

Mehta, R., & Sivadas, E. (1995). Comparing response rates and response content in mail versus electronic mail surveys. Journal of the Market Research Society, 37(4), 429-439.

Morgan, G. (2001). Thirteen "must ask" questions about e-learning products and services. The Learning Organization, 8(5), 203-210.

Tse, A.C.B. (1998). Comparing the response rate, response speed, and response quality of two methods of sending questionnaires: E-mail vs. mail. Journal of the Market Research Society, 40(4), 353-361.

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GERARD KICKUL

University of St. Francis, USA

[e-mail]

JILL KICKUL

Simmons School of Management, USA

[e-mail]

Table 1 Proactive Personality (1=high, 2=low)

                                   Std.   95% Confidence
Dependent                  Mean    Error  Interval
Variable        Proactive                 Lower Bound     Upper Bound

Perceived       1.00       73.425  1.906  69.664          77.185
  Quality
                2.00       82.427  1.833  78.811          86.044
Perceived       1.00       79.363  2.228  74.968          83.757
  Satisfaction
                2.00       86.531  2.142  82.305          90.756

Table 2 Learning Goal Orientation (1=high, 2=low)

                                  Std.   95% Confidence
Dependent                 Mean    Error  Interval
Variable        Learning                 Lower Bound     Upper Bound

Perceived       1.00      75.432  1.705  72.068          78.795
  Quality
                2.00      80.420  2.022  76.432          84.409
Perceived       1.00      78.817  1.992  74.887          82.747
  Satisfaction
                2.00      87.076  2.363  82.416          91.737

Table 3 Proactive Personality by Learning Goal Orientation

                                    Std.   95% Confidence
Dependent                   Mean    Error  Interval
Variable                                   Lower Bound     Uper Bound

Perceived       1.00  1.00  68.701  1.943  64.869          72.534
  Quality
                      2.00  78.148  3.281  71.676          84.620
                2.00  1.00  82.162  2.803  76.634          87.691
                      2.00  82.692  2.364  78.029          87.356
Perceived       1.00  1.00  71.688  2.270  67.210          76.166
  Satisfaction
                      2.00  87.037  3.834  79.475          94.600
                2.00  1.00  85.946  3.275  79.486          92.406
                      2.00  87.115  2.763  81.666          92.565