Online learning experience: a case study.

Abstract

This paper reports the results of a case study on college students' perception of their online learning experience. Statistical analysis reveals different perceptions between native English speakers and Asian students, whereas gender and prior online experience do not affect student perception. The results of this study reveal different rating patterns that could bias the assessment of learning effectiveness when educators continue to resort to aggregate measures. We suggest further studies to measure the cultural influence on student ratings and to devise a method to adjust for this difference.

Introduction

Online learning using the Internet for instruction delivery, communication and class management represents the most advanced stage of integrating information technology into the business curriculum (Benbunan-Fich et.al., 2001; Eastman and Swift 2001; Smith 2001). Surveys show the increasing acceptance of online learning. For example, the International Data Corp forecast that online learning in the worldwide corporate market would increase from $2 billion from 1999 to $23 billion by 2004. In the US, it was estimated that 84% of four-year colleges would offer online courses, with over 2.2 million students taking courses online by 2002. Most encouragingly to these online educators and students, the majority of American employers have a favorable impression of online degrees and consider them as credible as their traditional counterparts (Tang 2001).

However, comparative studies of face-to-face versus online learning reveal limitations of the current online experience that might require some pedagogical adjustments. O'Malley and McCraw (1999) found that business students do not perceive online learning to be as effective as the traditional classroom. Even MBA students who prefer the convenience and accessibility of distance learning supported by real-time audio and video interaction do not perceive the same level of learning effectiveness and satisfaction as in the traditional classroom environment (Ponzurick, France, and Logar 2000). At the undergraduate level, Sweeney and Ingram (2001) also found that marketing students preferred a traditional face-to-face learning environment to a synchronous or asynchronous web-based learning environment. Students considered the face-to-face environment to be more effective for learning; consequently, they gained more satisfaction and achievement. Interestingly, the study found that Asian students differed from their Australian classmates in their assessment of the various learning environments. Specifically, Asian students favored bulletin boards and chat rooms more than the Australian students. Sweeney and Ingram concluded that Asian students had a more favorable attitude toward a web-based learning environment than Australian students.

Research reveals differences in learning styles among student groups of different ethnic backgrounds; yet little is known about their difference in attitude towards learning online. For instance, significant differences were found in learning style preferences between Southeast Asian and white students (Park 2000). A recent large-scale study shows that college students of Asian ethnic background tend to prefer formal study arrangements and hands-on activities. They are also less willing to verbalize or state opinions than their peers from other ethnicities (Hardigan and Sisco 2001). Gifted American-born Chinese students preferred studying in the afternoon and bright light and did not prefer noise, structure, and the presence of authority figures (Ewing and Yong 1993).

Cote and Tansuhaj (1989) studied the behavioral intention of American and foreign students for the prediction of academic behavior. In their analysis, 27 percent of the discrepancy in behavioral intention toward academic behavior was attributable to differences in culture variables. In a study comparing the American and Hong Kong students, Malhotra and McCort (2001) found that students of the two cultures differed in their thought processes that led to different intention formation. Liu and Ginther (1999) proposed adapting the design of distance education to students' cognitive styles. Their underlying principle is that learner characteristics create differential responses to the learning environment as well as instructional contents, methods and styles. Relevant to this paper is their contention that even evaluation methods and assessment techniques should adapt to learner characteristics.

This paper reports the results of a study on student evaluations of their online learning experience. We investigated the influence of learner characteristics such as gender, cultural background, and prior online learning experience on course evaluation.

Evaluation of the Online Learning Experience

The evaluation scheme for traditional learning modes needs to be adjusted for adaptation to an online environment (Clow 1999). Our framework for evaluation of the online learning experience stems from the key ingredients of educationally powerful environments suggested by Chickering and Jackson (1999). These include clear purposes, maximization of human interaction, pedagogies for active learning, recognition of individual differences, integration of academic and experiential learning, and high expectations. Based on research of college teaching and learning, Chickering and Gamson (1987) identified seven principles that can help to improve learning:

1. respect diverse talents and ways of learning;

2. communicate high expectations;

3. emphasize time on task;

4. give prompt feedback;

5. use active learning techniques;

6. develop reciprocity and cooperation among students; and

7. encourage contacts between students and faculty.

More relevant to this study, Levin et. al. (2001) identified five dimensions that contribute to effective online learning:

1. relevant and challenging assignments;

2. coordinated learning environments;

3. adequate and timely feedback from instructors;

4. rich environments for student-to-student interaction, and

5. flexibility in teaching and learning.

The Study

Students who completed an online course in Business Communication at a west-coast state university in 2001-2002 were invited to participate in an online survey. The class is conducted entirely on the Internet using an asynchronous mode of delivery and outcome assessment, supplemented by chat room interactions and voice mail messages. CourseInfo/Blackboard was adopted to support class management. The null hypothesis of the study is that student characteristics such as gender, cultural background, and prior online experience will not affect student perception of learning experiences.

Results and Analysis

The analysis is based on information provided by 106 respondents, 46% male and 54% female, who completed the survey. The response rate was over 95%. Only 50% of the students were native English speakers. The rest of them regarded English as their second language: 46% of the respondents came from Asia, others came from South America and Mexico. About 66% of them had no prior distance learning experience. They had background in various disciplines of business such as management science (22%), accounting (16%) and general management (15%).

Students responded to ten statements that measure the quality of their online learning experience according to the principles of good practice in education (Chickering and Gamson 1987) and online learning (Levin et.al. 2001), as follows:

1. My personal circumstances (work full time, children at home, disabled, etc.) would have prevented me from taking this class in person this semester.

2. This online class was more convenient for me.

3. This online class provided as much opportunity to learn as an on-campus class would have.

4. This class is intellectually challenging.

5. The number of assignments and exams was about right for an online class.

6. I had enough time to complete all the assignments.

7. The instructor responded to my questions and other inquiries promptly.

8. I was independent in studying for this class; that is, I tried to figure out what to do from the directions, handouts, and text.

9. After I read the directions and handouts for this class, I knew what to do.

10. Sometimes I emailed or chatted with other students in this online class when I had a question.

Statements 1 to 3 focus on the key benefits of online classes to students, and measure the extent that the online class accommodates diverse backgrounds and ways of learning, or flexibility in teaching and learning. Over 65% of the respondents would not be able to access the education opportunity if online classes were not offered. Ninety-six percent of online students believed that online learning was more convenient for them. Statement 3 measured the efficacy of online learning for students of diverse backgrounds. About 86% of respondents considered their online learning as effective as an in-classroom experience.

Ninety-nine percent of the respondents regarded the learning experience as intellectually challenging (Statement 4). Over 96% of them considered that the amount of work and tests were right (Statement 5) and that they had sufficient time to complete their work (95% in Statement 6). About 99% of respondents were satisfied with the timely responses of the professor (Statement 7). Over 98% took the initiative to learn from written directions (Statement 8), and only 15% needed help in following written directions (Statement 9). In terms of student interactions, over 77% had sought online help or chat with fellow students for the purpose of learning (Statement 10). The results show an overwhelmingly positive attitude towards the e-learning experience.

Furthermore, over 93% of respondents intended to take more online classes. Of those who had previous experience of online classes (34% of respondents), about 85% consider the above-evaluated class as good or better than other online classes. Only 9% of the experienced respondents had had better online learning experience than the above class. These statistics put the results of this case study in a larger perspective: the favorable evaluation of this class was not uncommon for online learning!

For further analysis on the differences in responses of different groups, the researchers assigned a four-point scale to the categories of Strongly Agree (4) to Strongly Disagree (1). Independent sample t-tests were conducted with the following results: There is no significant difference in mean responses of the male and female students to Statements 1 to 10 (df 93, [alpha] = 0.05). Similar tests show no significant difference in mean responses between the first-timers and those who had prior experience with online classes. The exception occurred in response to Statement 8: the experienced online students tend to agree more strongly that they were independent and tried to figure out what to do from the directions, handouts, and text (t = 2.0, df = 77 for unequal variances, [alpha] = 0.05). The most interesting results came from the comparison between the group of American students (50%) and Asian students (46%), which consisted of a diversified group of respondents from Indonesia (7% of total respondents), Taiwan (7%), Korea (5%), Vietnam (9%), China (4%), Japan (5%), Laos, and Thailand.

The results of independent t-tests reveal consistent differences between the perceptions of the two groups, except for Statements 1, 7, and 10. That is, both groups share similar personal circumstances leading to taking the online class (Statement 1), and similar interaction experience with the professor (Statement 7) and other students (Statement 10). Yet, the American students have a more favorable opinion of their online experience than the Asian students. Their ratings of the rest of the Statements are more positive than the Asian students'. Put another way, the perceptions of Asian students were more conservative regarding the learning environment (Statement 2 [t=3.21, df=74.7] and Statement 3 [t=2.26, df=87]), the relevancy and challenge of assignments (Statement 4 [t=2.06, df=77.6]); Statement 5 [t=4.00, df=67.6]; and Statement 6 [t=2.69, df=89]), and the delivery of instructions (Statement 9 [2.80, df=86.6] and Statement 10 [t=-1.54, df=84.9]).

There are three possible explanations for this result: The Asian students had a higher expectation of the online learning experience than the native English speakers. The Asian students were more reserved and tended to be moderate in responses and perceptions. The language medium creates a moderating effect on the learning experience of the non-native English speakers.

Discussion

An objective of offering online classes is to increase student enrollment and better meet the needs of students whose personal circumstances might have prevented them from taking traditional classroom courses. In a way, online learning is an alternative to enhance learning experience and improve satisfaction in education for certain student segments. Therefore, it is important to understand the perception and evaluation of different student groups. Using a different evaluation scheme than Sweeney and Ingram (2001), this study also found that language or cultural background influence the perception of online learning experiences. The American students in this study showed a more favorable perception of an online course than the Asian students, and the Asian students in Sweeney and Ingram's study (2001) showed a more favorable perception of web-based tutorials than the Australian students. The results nevertheless reveal different rating patterns that might bias the assessment of learning effectiveness when educators continue to resort to aggregate measures.

Are the results influenced by language differences, or by cultural differences? This study uses the measure 'English as a second language' and 'country of origin' as a surrogate measure of cultural background instead of identifying the cultural elements that affect student perceptions. Therefore, language barrier could be the primary variable affecting student perceptions of online experience in this study. But then, language barrier could not explain the findings of Sweeney and Ingram (2001). We suggest further studies examining the possible relationship between cultural influence and behavioral intention (Cote and Tansuhaj 1989; Malhotra and McCort 2001), learning style (Hardigan and Sisco 2001; Park 2000;) and cognitive style (Liu and Ginther 1999). Understanding how these factors might affect perception in student ratings would enable educators to devise methods to adjust for this difference.

Meanwhile, it is practical for online educators to recognize that students of different cultural backgrounds might have different preferences, and hence apply different measures of learning satisfaction. With this recognition, the educators can address the issue of enhancing student learning experience more effectively by customization. For example, the instructor might observe and consult with the students regarding their learning expectations and preferences, and negotiate a learning experience that is most satisfactory to the learners as well as the instructor. Customization also permits the educators to relate to learners differently. This approach might create the challenge of a delicate balance between flexibility and fairness in instruction delivery, communication and class management. Yet, a greater challenge is for an instructor to be conscious of his/her own learning preferences and to assess how closely these match the preferences of students in designing the course activities.

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Catherine T. Atwong, California State University, Fullerton Gayle Vogt, California State University, Fullerton Irene Lange, California State University, Fullerton

Atwong is an associate professor of marketing. She published in the Journal of Marketing Education, the Journal of Marketing Theory and Practice, and the Journal of Product and Brand Management among others. Vogt specializes in distance learning and teaching foreign-born students. She has published in the Journal of Language for International Business and the Association for Business Communication Quarterly among others. Lange is the chair and professor of marketing and a past editor of the Journal of the Academy of Marketing Science.