Editor’s Note: This is a straightforward study using a previously designed and tested instrument with six scales of preference. A generous number of respondents and high statistical reliability provides excellent guidelines for design and implementation of online constructivist learning.

College of Education Faculty Members’ Preferences Towards Internet-based Learning Environments

Ismail Sahin

Turkey

Abstract

In an effort to explore College of Education (COE) faculty members’ preferences toward constructive Internet-based learning environments, the present study was conducted. The data collection instrument for this study was a survey that was originally developed by Lee and Tsai (2005) to assess high school students’ and teachers’ preferences toward constructive Internet-based learning environments. The instrument included the following six scales: (1) ease of use, (2) multiple sources, (3) student negation, (4) reflective thinking, (5) critical judgment, and (6) epistemological awareness. Also, faculty preferences of teaching environments were asked. The respondents of the present study consisted of 109 COE faculty members from three recognized universities in Turkey. The results suggested that COE faculty members are either aware or favor distance education teaching environments. The Cronbach standardized item alpha for each scale was high, confirming the reliability of the survey used in the present study. A majority of faculty members reported that each characteristic of the Internet-based learning environments was crucial. All correlations among the variables were statistically significant. Future research may utilize qualitative research methods to provide in-depth insights into faculty members’ preferences towards characteristics of constructivist Internet-based learning environments.

Keywords: College of education, Faculty, Distance education, Internet-based learning environments

Introduction

Rapid advances in computer and Internet technologies provide new opportunities to support teaching and learning (Lee & Tsai, 2005; Savery, 2002). An Internet-based-education environment “facilitates student learning without the constraints of time and distance, giving students more opportunities to control their own learning” (Wang, 2007, p.171). Internet-based teaching, “described using terms such as online teaching, networked teaching, e-moderating, e-tutoring and web-based teaching” (Twomey, 2004, p. 452) has become a popular form of education. This type of education is usually learner-centered (Milheim, 2001) and supports knowledge construction and meaningful learning (Wu & Tsai, 2006). However, the role of instructor is still critical in this form of education. In fact, for a distance education program to thrive, it should consider the motivating or inhibiting factors for faculty participation in an online learning environment (Schifter, 2004) and convince them to adopt it (Lindner, Murphy, & Dooley, 2002).

Anderson et al. (2001) list three categories of teaching presence in a distance education learning environment:

§  Instructional design and organization

§  Facilitating discourse

§  Direct instruction

In fact, “design, facilitation, and direction of cognitive and social processes for the purpose of realizing personally meaningful and educationally worthwhile learning outcomes” (Anderson et al., 2001, p. 5) are vital in an online learning environment. Furthermore, the literature suggests organization and reflection are essential for effective online instruction also support traditional teaching (Downing & Chim, 2004).

Although Internet users still encounter some barriers such as a lack of skills, a lack of training, and higher costs for accessing the Internet (Eastin & Larose, 2000; Jones et al., 2002; Olcott & Wright, 1995; Tsai & Tsai, 2003), the uses of the Internet and distance education have become common worldwide (Tsai, 2005). As an alternative learning environment (Milheim, 2001), distance education needs to be integrated partly or completely into education. Especially, college of education (COE) faculty members should have knowledge of the online learning tools and model the effective uses of these technologies in their classrooms.

The characteristics of Internet-based learning environments can be categorized into certain groups. In their study, Lee and Tsai (2005) propose three components of Internet-based learning environments: learner (person), content (system or machine), and activity. In Figure 1, the relationships between these variables are displayed.

Figure 1. Three dimensions of Internet-based learning environments
suggested by Lee and Tsai (2005)

As stated by Lee and Tsai (2005), the interior dimension of Internet-based learning environments explains the engagement of an individual in the activity, while the learner-content relationship, the exterior dimension of these learning environments, focuses on the interaction between the learner and system or machine. Based on these two dimensions, Lee and Tsai describe five aspects of Internet-based learning environments: technical, content, cognitive, meta-cognitive, and epistemological. Using these dimensions and aspects as their framework, Lee and Tsai construct the Constructivist Internet-based Learning Environment Survey-Improvement (CILESI)Each CILESI scale is classified, based on these constructs and presented in Table 1.

Before designing online and constructivist learning environments, it is crucial to learn about the preferences of learners (Tsai, 2007 in press) and instructors toward these environments. In fact, “teacher perceptions of learning technologies are likely to be key factors in the successful integration of learning technologies” (Cope & Ward, 2002, p. 72). The literature suggests that attitudes and preferences of learners affect their motivation, interests, and performance in online learning environments (Peng, Tsai, & Wu, 2006).

Numerous researchers have studied university students’ preferences toward constructive Internet-based learning environments (Deture, 2004; Sahin, 2007; Tsai, 2007 in press; Tsai & Lin, 2004; Wu & Tsai, 2006). Although the literature stresses the important role of faculty in distance education (Lindner et al., 2002), there is limited research that considers faculty members’ preferences toward these environments (Jones et al., 2002). In fact, what the faculty members, as the actual implementers and facilitators of those environments, think is critical for making the environments more successful and effective. In an effort to explore COE faculty members’ preferences toward constructive Internet-based learning environments, the present study is conducted.

Table 1

Classification of each CILESI Scale
suggested by Lee and Tsai (2005)

Methods

The data collection instrument of this study was a survey originally developed by Lee and Tsai (2005) to assess high school students’ and teachers’ preferences toward constructive Internet-based learning environments (see Appendix A for the survey items). The instrument, CILESI, included the following six scales: (1) ease of use, (2) multiple sources, (3) student negation, (4) reflective thinking, (5) critical judgment, and (6) epistemological awareness. A five-point Likert-type set of alternatives, ranging from “1=not important at all” to “5=totally important,” was used to explore the opinions of COE faculty members on these environments. Higher scores in a certain scale reflected stronger preferences toward constructive Internet-based learning environments. Also, faculty preferences of teaching environments were asked. The respondents of the present study consisted of 109 COE faculty members from three recognized universities in Turkey.

In the current study, factor analysis was used to check if the survey items for each subscale successfully measured each variable. The Cronbach alpha value was used to measure the reliability of each survey scale. Next, correlation coefficients between the survey scales were calculated and interpreted. Statistical analyses were conducted using SPSS (Statistical Package for Social Sciences) 13.0 software.
 

Findings

Data collected from COE faculty members in Turkey suggest that the CILESI showed a high level of reliability in assessing faculty responses (see Appendix A for the results of mean scores, factor analyses, and reliability tests). As presented in Figure 2, faculty preferences of the teaching environments varied.

Figure 2. Faculty Preferences of Teaching Environments

The most frequent teaching preference was face-to-face education, but supported by distance education (62%), followed by totally face-to-face education (15%), mostly distance education but supported by face-to-face education (12%), equal use of distance education and face-to-face education (10%), and totally distance education (1%). These results suggest that COE faculty members are either aware or favor distance education teaching environments.

In addition, factor analysis was conducted to reduce the number of variables. As shown in Appendix A, items were loaded on only one factor for each scale. In the factor analysis, the correlation matrix and the component matrix showed positive, high correlations among the items for each scale. Also, the value of the Cronbach standardized item alpha for each scale was high. Overall, the loadings of the six factors were generated from 29 survey items with high reliability (standardized item alpha = 0.93). These results confirmed the reliability of the survey used in the present study. In fact, similar reliability scores were found in the literature (Tsai, 2007 in press).

As seen in Table 2, the scale percents were categorized based on the survey’s options. A majority of the faculty members reported that each characteristic of Internet-based learning environments was crucial. For instance, only about 2% of the participants thought that reflective thinking was not an important feature for these environments.

Table 2

Percentage Distribution of Variables Based on Survey Options

In Table 3, the correlations among the survey scales were presented. All correlations among the variables were statistically significant, ranging from 0.35 to 0.68. For example, COE faculty members, who preferred that navigating Internet-based learning environments should be easy to use, also reported these environments should include multiple sources (r = 0.50)

Table 3

Correlations between Variables Used in the Study

Conclusions

Using instructional technologies and distance education tools, specifically the Internet, in education in part or whole has become inevitable. The integration process of these technologies into education should first involve faculty choices regarding these tools. The literature highlights the crucial effect of learners’ perceptions of the Internet on their attitudes toward Internet-based learning environments and, eventually, their performances in these learning environments (Peng et al., 2006). Hence, involving faculty members’ preferences toward the characteristics of online learning environments in designing these environments may increase their positive attitudes toward and use of the environments.

In order to meet the emerging demand for distance education courses and to build more favorable settings for these courses, higher education institutions should consider faculty preferences toward online learning environments. In fact, faculty, who are well-supported by their institutions, have higher commitment and motivation toward distance education (Lee, 2001). As suggested by Wu and Tsai (2006), higher education institutes may increase low levels of their faculty preferences toward online learning environments by organizing faculty training programs.

In the current study, COE faculty members’ preferences toward the constructivist Internet-based learning environments were assessed. The present study confirmed the reliability of the CILESI in assessing faculty responses regarding the characteristics of constructivist Internet-based learning environments. Also, a majority of COE faculty reported their teaching preference was mostly face-to face education, but supported by distance education.

In conclusion, COE faculty members expressed strong preferences towards the following features of constructivist Internet-based learning environments: ease of use, multiple sources, student negotiation, reflective thinking, critical judgment, and epistemological awareness. Designers and researchers of distance learning environments should pay more attention to these characteristics when developing and improving Internet-based learning environments. Future research may utilize qualitative research methods to provide in-depth insights into faculty members’ preferences towards characteristics of constructivist Internet-based learning environments.
 

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Appendix A

Results of mean scores, factor analyses and reliability tests