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Students' attitudes toward online interaction.

Abstract

This study sought to explore students' attitudes toward four types of interaction in the online learning environment: instructional, affective, collaborative, and vicarious interactions. The results indicated that students had significant differences in their attitudes toward the four types of interaction. Learners' attitudes were related to their course satisfaction, and their attitudes significantly predicted course satisfaction. The findings of this study offered some explanation of college students' attitudes toward online interaction, and should help educators better understand how to make online learning more satisfying to the students.

Introduction

While efforts have been made in the field of online learning to facilitate activities that can support higher levels of learning, the main concerns about online learning research have centered on aspects of designing effective online learning environments. Studies have shown that interaction in the online learning environment may lead to positive educational outcomes, greater retention rates (Bocchi, Eastman & Swift, 2004; Lenning & Ebbers, 1999), and increased effectiveness of distance education (Flottemesch, 2000; Kearsley, 2000; McLoughlin & Luca, 2003). Interaction is an essential element in the learning environment (Northrup, 2002) and a quality indicator in any online course (Cohen & Ellis, 2003). If the learning environment is focused on interaction, it follows that it would most likely be a learner-centered approach (Bruner, 1966) that encourages interaction between learners (Bragg, 1999).

Theoretical Framework of the Study

In spite of the widely held belief that interaction can influence the quality of online learning (Roblyer & Ekhaml, 2000), there has been relatively little empirical research investigating how online learners would view the different types of interaction. Jung, Choi, Lim, and Leem (2002) researched the students' preferences with respect to interaction, and they found that different types of interaction varied in terms of the effects on learner achievement, satisfaction, and participation in interaction. Their results demonstrated that the social interaction group outperformed the other groups (including collaborative and academic groups), and the collaborative interaction group expressed the highest level of satisfaction with their learning process. The collaborative and social interaction groups were more active in posting their opinions to the discussion board than was the academic interaction group. Given the importance of interaction in instruction, we proceeded to investigate the basic elements of interaction with regard to its function in the learning process. Four types of interaction were examined in this study: instructional, affective, collaborative, and vicarious interactions.

Instructional interaction is content-centered and tends to overlap with learner-content interaction. It is a basic type of interaction; it always occurs when the learner reads online materials, gets task-oriented feedback from the instructor or from more competent peers, or participates in task-oriented learning activities (Jung, et al., 2002). Social and interpersonal interactions have some functions overlapping with each other. In this study we focused on the common element of "affect" and explored affective interaction. The existence of a learning community and collaboration are both key factors in facilitating online learning and generating course satisfaction (Palloff & Pratt, 1999). Therefore, collaborative interaction was also included in the study. Not all learners choose to participate in or benefit from observing other participants' interaction (vicarious interaction) (Sutton, 2001). To demystify this phenomenon, we explored vicarious interaction. Negative attitudes toward computers have been considered one of the most important factors in inhibiting effective use of computers in education (Bozionelos, 1997). To explore issues related to the effectiveness of online learning, we decided to investigate students' attitudes toward interaction by focusing on the four types of interaction. Research studies have found that engaging in different types of interaction can enhance online learners' learning experience and motivate them in the course (Northrup, 2002; Sherry, 2000). The different types of interaction may influence learning outcomes, contribute to students' learning (Harasim, 1990; Miltiadou, 2001), and influence learners' satisfaction (Zirkin & Sumler, 1995). To confirm their conclusion, the study examined the relationship between students' attitude and course satisfaction. The central questions guiding this research are:

1. What are students' attitudes toward the four types of interaction?

2. Are there significant differences among students' attitudes toward the four types of interaction?

3. Is there any relationship between students' attitudes toward the four types of interaction and course satisfaction? If so, can course satisfaction be predicted by students' attitudes towards the four types of interaction?

Methodology

Participants and Setting

The participants came from a heterogeneous composition of about 2000 students, registered in Spring 2004 online courses in a community college in a southwestern American state. There were 64 courses provided in the liberal arts, 17 in the natural sciences, 6 in business, and 2 in English as a Second Language (ESL). The participants' courses incorporated a variety of collaborative activities (i.e., exchanging documents, writing group papers, and conducting group projects). Hybrid courses were excluded from the study.

No more than 20 students can sign up for a single online class. The average retention rate for the online classes was 75%. During the semester, most students did not have face-to-face meetings except for the orientation, the mid-term, and the final exam. Test locations were on campus. Exceptions were made for truly distant students, who took the test in a proctored environment near them (often a local college). Two questionnaires were developed and placed on the researchers' Website with database-driven functions, and they were distributed online to all online students between late March and early May of 2004. After this research project was approved by the college administrators, the students received an e-mail invitation outlining the research objectives and the Website address. All students participated in the study voluntarily.

Instrumentation

The Scale consists of three sections: demographic information, course information, and the 20 5-point Likert scale items, which measure students' attitudes toward the interactions. A pilot study using a 48-student sample of the population base was conducted in Fall of 2003 to determine the validity and reliability of the scale and also to test the distribution process. To test the content validity, two online instructors and two graduate students reviewed the question items and confirmed that they could accurately measure the interactions before the questionnaire was distributed to the participants.

The Survey was developed to evaluate the general level of course satisfaction. The questionnaire employs 12 items with a 5-point Likert scale for each. The differences between the mean score of each item and the overall mean score for all 12 items were examined. The results indicated there was no significant difference between the mean score for each item and the total mean score. Therefore, the 12 items were collapsed together and the mean score for all 12 items for each student was calculated in order to evaluate the degree of course satisfaction

Results

Students' attitudes toward the four types of interaction

One hundred and eighty-two (9%) of the 2000 online participants completed both questionnaires. Calculations based on descriptive statistics were used to summarize the data gathered from the Attitude Toward Interaction Scale. The results showed that students had the highest mean scores for instructional interaction (M=4.09, SD=0.53), the second highest for affective interaction (M=3.66, SD=-0.67), the next highest for collaborative interaction (M=3.25, SD=-0.78), and the lowest mean score for vicarious interaction (M=2.74, SD=0.84). All of their attitudes toward interaction except for the attitude toward vicarious interaction were above the neutral level (3), and thus were interpreted as positive attitudes.

For the second research question, the results showed a significant difference in the attitudes for the four types of interaction, F(3, 173)=189.83, p<.001. This indicated that the students' attitudes toward the four types of interaction were significantly different. Given the result, six pair-wise comparisons among four types of interaction were conducted, and the results showed that all differences between the means for any two types of interaction were significant. That is, students had the most positive attitudes toward instructional interaction, affective, collaborative, and vicarious interactions in that order; that is, they had the least positive (slightly negative) attitudes toward vicarious interaction.

Relationships between course satisfaction and students' attitudes toward the four types of interaction

Statistical analysis revealed significant correlations at or beyond the .05 level. A multiple regression analysis was then conducted to see whether course satisfaction can be predicted by students' attitudes toward interaction, with instructional, affective, collaborative, and vicarious interactions as predictor variables and course satisfaction as the criterion variable. The result indicated that 18% of the students' course satisfaction was explained by the independent variables of students' attitudes toward the four types of interaction. The data showed a significant value at p <.001 (F=9.261). That is, students' attitudes toward the four types of interaction can predict their course satisfaction.

To further investigate the factors which were found to be significant, the standardized Beta coefficients provide a measure of the contribution of each variable to the model. The t and p values give an indication of the impact of each interaction attitude on course satisfaction. The highest Beta weight was .41 (instructional), and was significant at the p<.001 level. The second highest Beta weight was -. 14 (vicarious), which was significant at the p<.05 level. Therefore, the students' attitudes toward instructional and vicarious interactions were regarded as contributing significantly to their course satisfaction. The other two variables did not have significant Beta weights, and therefore did not contribute to course satisfaction significantly.

Discussion

Students' attitudes toward the four types of interaction

In line with the results of Sabry and Baldwin's (2003) study, our findings suggested that students have the most positive attitude toward interactions which can provide them with specific feedback or information on tasks. The students ranked affective interaction as the second most preferred type of interaction. This indicates that when they learn online, in addition to content- oriented feedback, students like to have motivational and emotional support. Collaborative interaction was ranked as the third most preferred type of interaction. Some participants indicated that their courses were not integrated with enough collaborative activities, and the instructors were not responsive and involved in class all the time. This implies that some students may have formed their attitudes toward collaborative interaction based on their limited experience of collaboration in class. Therefore, the less positive attitude toward collaborative interaction may be due to students' limited exposure to collaborative activities, and the ineffective design of those activities they experienced. There was less agreement among students as to whether they liked vicarious interaction when they learned online. This may imply that they did not like merely observing a class that they had expected to participate more in their online activities and discussions. It may also simply mean that observation would be their last choice among the choices they were presented with. As Sutton (2001) suggested, not all learners like to participate in or can benefit from vicarious interaction, and in any case vicarious interaction cannot achieve the same effects as direct interaction.

Course satisfaction and students' attitudes toward the four types of interaction

The finding indicates that the more a student liked instructional, affective and collaborative interactions, the greater was the student's satisfaction with the course. It also indicates that the more a student chose to participate indirectly through passive observation, the less satisfied he or she was. This last result was consistent with the literature indicating that active interaction is directly related to students' course satisfaction (Strachota, 2003; Zirkin & Sumler, 1995). The correlations between course satisfaction and students' attitudes toward collaborative and vicarious interaction, while significant, were relatively weak. This may be due to the various levels of interaction or lack of interaction occurring in different classes.

Students' attitudes toward the four types of interaction significantly predicted course satisfaction. Of the four types, students' attitudes toward instructional interaction (positively) and vicarious interaction (negatively) significantly predicted course satisfaction. This finding corresponds with that of a recent study by Strachota (2003), which compared the impacts of learner-content, learner-learner, learner- instructor, and learner-technology interactions on online course satisfaction. Such findings suggest that instruction is indeed the most important factor when it comes to student satisfaction with online courses (Bolliger & Martindale, 2004).

Our study found that when a student observes rather than participates, he or she is less satisfied with the course. This finding suggests that when students participate more directly, they are more satisfied with their courses. This result is in line with Kawachi's study (2003), which indicated that active participation is the essential factor in learning, although no evidence was given to show that vicarious interaction would lead to improved quality of learning. This study had several limitations. The students' experiences varied widely, with regard to both the type and intensity of interaction they underwent in their online courses, thus generating "noisy" data. Furthermore, the degree of instructors' involvement in these online courses varied. Students' attitudes toward the four types of interaction depended on how frequently each type of interaction appeared in each course. The lack of significant coefficients of affective and collaborative interactions for predicting course satisfaction may be due to the fact that the motivational support students received and the collaborative activities they were exposed to during the time were too limited to have any significant effects. Future studies should replicate the findings by using a different population and by controlling more variables.

Conclusion

Interaction is a complex variable with many different facets (Kearsley, 1995). It is a multi-dimensional concept where each dimension is embedded within the other dimensions. Instructional designers and instructors should keep in mind that facilitating interaction is necessary for online learning, and integrating different types of interactions into online courses is essential. To improve course satisfaction, one cannot afford to neglect any type of interaction.

References

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Roblyer, M. D., & Ekhaml, L. (2000). How interactive are your distance courses? A rubric for assessing interaction in distance learning. Paper presented in the Distance Learning Administration 2000 Conference, Callaway, GA.

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Endnotes

Our gratitude goes to the Academic Paper Editing Clinic, NTNU.

Yungwei Hao, Ph.D., is Assistant Professor of Department of Education, in National Taiwan Normal University, Taiwan, and Min Liu, Ed.D., is Professor and Program Coordinator of Department of Curriculum and Instruction, in the University of Texas at Austin.
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Author:Liu, Min
Publication:Academic Exchange Quarterly
Date:Dec 22, 2006
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