Attributes and Barriers Impacting Diffusion of Online Education at the Institutional Level: Considering Faculty Perceptions Free

The traditional model of face-to-face instruction continues to dominate the higher education landscape. However, over the past decade online education has entered the mainstream. Universities across the broad spectrum from state schools, to small private schools, to Ivy League schools are getting into the marketplace of online education offerings. Allen and Seaman (2013) report that over 6.7 million students, or 32% of total higher education enrollment, are taking at least one online course.

Online education is a subset of distance education. Schlosser and Simonson (2010) define distance education as “institutionally-based, formal education where the learning group is separated, and where interactive telecommunications systems are used to connect learners, resources, and instructors” (p. 1). Distance education is not new. It has its roots in the 19th century with correspondence courses. Simonson, Schlosser, and Orellana (2011) describe the evolution of distance education in three phases first, correspondence study, with its use of print-based instructional and communication media; second, the rise of the distance teaching universities and the use of analog mass media; and third, the widespread integration of distance education elements into most forms of education, and characterized by the use of digital instructional and communication technologies. (p. 131) Online education, characterized by delivery of instruction using a learning management system via the Internet, has become the dominant platform for distance education in the third stage.

Unlike most technologies, online educa-tion, and distance education in general, is a disruptive innovation (Simonson, Smaldino, Albright, & Zvacek, 2012). An innovation is “an idea, practice, or object that is perceived as new by an individual or other unit or other unit of adoption” (Rogers, 2003, p. 12). A disruptive innovation may enter an environment and challenge the status quo by addressing a need the current technology is ignoring or not able to meet. Online education provides students access to academic programs they might not otherwise have, or schedule flexibility permitting participation without physical presence in a particular time and place. Innovations, whether disruptive in nature or not, present an individual with the choice to adopt or reject its use. As individuals across an organization or other populations choose to adopt, the use of the innovation spreads. Rogers' (2003) diffusion of innovation theory describes this as the innovation-decision process.

The diffusion of online education in higher education involves many stakeholders, including faculty. Faculty are at the core of the teaching and learning process directly impacting student achievement. Whether faculty choose to adopt or reject online education as a delivery model for instruction depends on many factors. Understanding these factors and the faculty perceptions of the impact these factors have on the diffusion process informs the educational community, including scholars and policy decision makers (Mitchell & Geva-May, 2009).

The rapidly changing higher education marketplace requires institutions to strategically consider how to enter the online market and the implications of such change. Nearly 70% of academic leaders report online learning as critical to the long-term strategy of the institution (Allen & Seaman, 2013). Some administrators are even viewing online education as a necessity for survival in higher education (Lesht & Windes, 2011). This entrée into the online marketplace becomes extremely complex for small private institutions operating on thin profit margins, small endowments, and minimal amounts of reserve funds for the development costs needed to enter the online market.

Concordia University Irvine (CUI) was founded in 1972 as a parochial college committed to preparing professional church workers. A School of Education and School of Arts and Sciences were formed in 1988 and 5 years later the college became a university and joined a national system of nine other sister universities. In 1999 the original college was restructured and a School of Theology emerged. Three years later a School of Business and a School of Adult Studies were established, resulting in the five schools that currently make up the university.

About a decade ago the university invested in an online course management system and schools within the university began to independently explore using the course management system to deliver instruction. The School of Education was the first to offer a complete academic program online, beginning in 2003. The School of Arts and Sciences followed in 2008. The university has recently formally included an initiative to systematically expand online education as part of its strategic plan.

Efforts are escalating to carry out the initiative. An assistant provost position specifically tasked with expanding online education was created and filled. In this position, Doug Grove, with the support of the president and provost, acts as the primary change agent in the diffusion process at CUI. Additional human resources are being added and strategies for short and long-term growth are being investigated and developed.

When attempting to diffuse online education across an institution, it is critically important for leadership to understand faculty perceptions. Faculty participation in online education will not increase substantially unless leadership minimizes barriers that inhibit faculty participation (Betts, 1998). For example, faculty may perceive online education as not aligned to their respective discipline contributing to breakdown of the innovation during implementation (Hannon, 2009). Using inclusive processes to gain buy-in, garnering commitment, developing a vision, and providing appropriate support to faculty during the implementation process promotes adoption of online education (Bremner, 2007). At CUI, Grove has emphasized that developing and communicating with faculty the institutional vision of online education is central to his role and responsibilities.

Since faculty are the direct connection to students, it is crucial to understand the perceptions of faculty when considering any major change to the teaching and learning process. Moore and Kearsley (1996) emphasize that faculty must remain a central figure in the transition from traditional teaching to distance education. Success of online education rests on the commitment of the faculty to develop and deliver online courses (Betts, 1998). When administrators are aware of particular faculty barriers to online education, targeted strategies, including effective policy development, can be implemented to increase motivation and mitigate barriers at their own institution (Howell, Saba, Lindsay, & Williams, 2004; Mitchell & Geva-May, 2009).

The expanded use of online education at CUI involves substantial change for all stakeholders, faculty and students being most affected. The change process is complex and teacher advocacy is a key factor to the initiation stage of successful change (Fullan, 1982, 1993; Fullan & Stiegelbauer, 1991). Actively engaging faculty in the change process involves understanding and responding to faculty perceptions about the adoption of online education. Rogers' (2003) diffusion theory emphasizes the importance of understanding the perceptions of potential adopters of an innovation, online education in this case, in the process of adopting an innovation.

Allen and Seaman (2013) report higher education faculty acceptance of online learning as valuable and legitimate at about 30%, a level that has remained relatively unchanged over the past decade. There is a widening gap between the view of academic leaders about online education as critical to the long-term strategy (almost 70%) and the faculty acceptance of online learning as valuable and legitimate (Allen & Seaman, 2013).

Rogers (2003) defines diffusion as “the process in which an innovation is communicated through certain channels over time among the members of a social system” (p. 5) Revealed in the definition are the four main elements of diffusion: an innovation, communication channels, time, and a social system. Diffusion theory has often been applied to the study of technology innovations (Sahin, 2006) and specifically used as the theoretical framework for studying diffusion of online education in higher education (Alhawiti, 2011; Bassett, 2012; Li, 2004). Eineke's (2004) study of online professional education demonstrated how the diffusion of innovations theory could be used as a successful structure to improve understanding of the adoption process and implementation of online education.

Diffusion of innovations theory is useful in many fields of study. Ellsworth (2001) summarized educational change theories through the lens of a change communication model. In doing so, he identified applications of change theory for educational practitioners. More specifically, Ellsworth constructed typical questions a practitioner might answer with an application of a theoretical framework. He proposed that diffusion theory could help address questions such as “What attributes can I build into the innovation or its implementation strategy to facilitate its acceptance by the intended adopter?” and “How can the presence or absence of these attributes affect the rate of acceptance by the intended adopter (or prevent acceptance altogether)?” (Ellsworth, 2001, p. 37).

All innovations are not equal when it comes to the rate at which members of the social system adopt their use. Some inno-vations may be adopted over a period of years while others may take decades. Rogers (2003) describes five attributes (relative advantage, compatibility, complexity, trialability, observability) of an innovation that contribute to the variance in rate of adoption. It is important to understand that these attributes are measured as perceptions of the potential individual adopter.

Relative advantage is defined as “the degree to which an innovation is perceived as better than the idea it supersedes” (Rogers, 2003, p. 15). An individual is more likely to adopt an innovation if she perceives it provides an advantage over current practice. What constitutes an advantage can vary with the potential adopter or the innovation. For instance, Alwahiti (2011) found that a majority of Saudi faculty viewed online education as a means to reach more students, indicating an advantage over traditional face-to-face instruction. The possible reasons for being able to reach more students could be due to geographic location, family time com-mitments, or flexibility in scheduling. The important factor in relative advantage con-tributing to the overall rate of adoption is that the potential adopter perceives some advantage. The reason for the advantage is not necessarily the focus. There is a direct, positive relationship between relative advantage and rate of adoption. The more an innovation is perceived as advantageous, the faster the rate of adoption (Rogers, 2003).

Compatibility is define as “the degree to which an innovation is perceived as being consistent with the existing values, past experiences, and needs of potential adopt-ers” (Rogers, 2003, p. 15). There can be different reasons why a potential adopter may not find online education compatible with values, experiences, and needs. Some studies have found that faculty perceive online education as compatible with their values and current teaching practice (Alwahiti, 2011; Li, 2004). It may only take one perceived incompatibility to cause a potential adopter of online education to reject. Bruner (2007) found that some faculty considered online education incompatible with the mission of the institution. This perception works against the rate of adoption of online education. As CUI faculty member Tim Schumacher noted, “online education is compatible with our mission, if it is intentionally done.” This is a typical response. Faculty at CUI believe that there must be an intentional and purposeful way that online education can carry out the mission before they will engage. There is a direct, positive relationship between compatibility and rate of adoption. The more an innovation is perceived as compatible with the social system, the faster the rate of adoption (Rogers, 2003).

Complexity is defined as “the degree to which an innovation is perceived as difficult to understand and use” (Rogers, 2003, p. 16). For example, a complex unclear process for developing e-learning environments was found to be an inhibitor for diffusion of online education at one Aus-tralian university (Burch & Burnett, 2009). Dr. Grove has been very attentive to faculty concerns about complexity at CUI. From the beginning of CUI's online education initiative, an emphasis has been placed on establishing a clear structure and process for faculty participation in online course development. This is likely to promote adoption. The complexity attribute is different from the other four in that it has a direct, negative relationship with rate of adoption. According to Rogers (2003), the more complex an innovation is perceived, the slower the rate of adoption. Innovations that are perceived as extremely complex are typically rejected altogether.

Trialability is defined as “the degree to which an innovation may be experimented with on a limited basis.” (Rogers, 2003, p. 16) Allowing an individual or organization to test out a new idea can reduce doubt about the innovation and promote adoption. In the case of online education, this could mean time for faculty experimentation with the technology tools used or time to participate in the course development process without mandate to teach in the online arena. According to Rogers (2003), if an innovation is trialable its rate of adoption will increase.

Observability is defined as “the degree to which the results of an innovation are visible to others.” (Rogers, 2003, p. 16) When a potential adopter is able to observe the results of the use of an innovation, adoption is more likely. It is encouraging when faculty observe their peers successfully teach online (Lesht & Windes, 2011). People value the experiences of their peers and the sharing of positive information about an innovation's use promotes accep-tance. Of course, the converse is true as well. If the observable results are negative, adoption is discouraged. If an innovation is perceived as observable and the observable results are positive, its rate of adoption will increase (Rogers, 2003).

Faculty members make value judgments about online education characterized by these five attributes. The end result may or may not be using online education as a method for teaching and learning. According to Rogers (2003), individuals progress through a series of stages when constructing these opinions about an innovation. This series of stage is referred to as the innovation-decision process.

Rogers (2003) defines the innovationdecision process as

The five stages of the innovation-decision process are knowledge, persuasion, decision, implementation, and confirmation. Rogers cites the landmark study by Ryan and Goss (1943) as establishing that potential adopters of an innovation progress through a decision-making process. Ryan and Gross's study of Iowa corn farmers and hybrid seed adoption illustrated that adoption was not based on an impulse decision, but a process over time.

The knowledge stage is where an indi-vidual usually enters the innovation-decision process. Information about an innovation may be obtained actively or passively. Active seekers may have some sort of issue or problem that current practices cannot address that prompts them to seek out a new idea or method to accomplish the task. For instance, educators have actively sought online education to serve populations in rural areas that cannot be served by traditional face-to-face instruction. Information may be received passively when a change agent seeking to encourage a shift in practice shares the new idea or method. For instance, when university leadership promotes online education to faculty as a means to deliver an existing program. In this case the faculty member is not seeking out knowledge on her own about the new idea stemming from a perceived or real need to address an issue or problem.

Knowledge acquisition by faculty at CUI was primarily by active seekers until rela-tively recently. For the past decade those faculty who have actively sought out to engage with online education are the ones who have developed and taught online courses. This has been changing, though, over the past year as leadership has begun to promote the use of online education.

Usually following discovery and knowl-edge acquisition, a potential adopter begins to form an attitude toward an innovation during the persuasion stage of the innovation-decision process. During this stage, the collective perception of the five innovation attributes contributes to the development of a favorable or unfavorable opinion of the innovation. Rogers (2003) states that relative advantage and compatibility have a greater influence on the formation of an attitude than the remaining three attributes. It is very common for a potential adopter to seek the opinion of or observe the use of the innovation by peers. Lesht and Windes (2011) concluded that, when unsure faculty observe other faculty being successful teaching online, it promotes engagement. Social reinforcement plays an important role in forming an attitude toward an innovation (Rogers, 2003). The attitude that is formed then contributes to the decision to adopt or reject. As a smaller higher education community, CUI faculty have a relatively close-knit community where social reinforcement is likely to play a substantial role in opinion formation.

Forming an attitude toward an innovation like online education typically results in a decision to adopt or reject it. This is described as the decision stage. Adoption is “a decision to make full use of an innovation as the best course of action available” (Rogers, 2003, p. 177). Most potential adopters of an innovation want to try it out, or observe someone else try it out, before making a decision. This creates a type of probationary period for the innovation (Rogers, 2003). Rejection is “a deci-sion not to adopt an innovation” and can occur at any point in the innovation-deci-sion process (Rogers, 2003, p. 177).

Typically following quickly after a deci-sion to adopt, implementation of an inno-vation is characterized by observable actions by an individual to use the new idea. Most innovations will face problems and raise questions during the implementation stage. During this time adopters actively seek solutions to these problems and change agents promoting an innovation are typically tasked with providing technical support (Rogers, 2003). Again, rejection can occur at any point in the process.

Having adopted and implemented an innovation, or rejected it, the individual typically seeks to reinforce the decision with additional information in the confirmation stage (Rogers, 2003). The individual may be unsure about the decision, creating what Rogers refers to as dissonance, “an uncomfortable state of mind that an individual seeks to reduce or eliminate” (Rog-ers, 2003, p. 189). Adopters and rejecters both seek to mitigate any unsettled thoughts about the innovation. This may result in confirmation or reversal of a decision.

Passing through the innovation-decision process is not strictly linear. Rogers (2003) cautions that sharp distinctions between stages should not be anticipated. An individual is likely gaining knowledge about an innovation during the entire process, but certainly takes definitive actions that move away from a strictly knowledge acquisition phase. It is these behaviors that characterize and place the individual along the innovation-decision process continuum.

Advances in technology have occurred faster and in greater frequency during the last decade than in previous decades. However, these advances do not necessarily translate into similar rates of online education adoption. Significant barriers to implementing distance education continue to exist and are well documented in the literature. Barriers may be related to institutional factors, technological issues, financial costs, pedagogical beliefs, or other factors.

The literature reveals most barriers to implementation of distance education are related to institutional issues. Over the last 15 years studies have consistently identified lack of release time (Berge & Muilenburg, 2000; Betts, 1998; Birch & Burnett, 2009; Bollinger & Wasilik, 2009; Bruner, 2007; Haber & Mills, 2008; Lesht & Windes, 2011; Schifter, 2000; Seaman, 2009) and concerns related to allocation of faculty workload (Berge & Muilenburg, 2000; Betts, 1998; Bollinger & Wasilik, 2009; Bruner, 2007; Chen, 2009; Meyer, 2012) as prominent barriers to distance education. It should be noted, however, that at least one study (Birch & Burnett, 2009) indicated that interviews with participants revealed that “it may be more a matter of priorities than time, with some academics revealing that they can find time for things that are important to themselves and their career and those which they perceived to be rewarded such as research” (p. 11). Nevertheless, the overall time commitment, from training to course development to instruction, is perceived to be more for distance education than for traditional classroom education.

Institutional policy, or lack of institutional policy in many instances, contributes to established barriers. For example, studies have shown institutions not recognizing the teaching of online education courses as progress toward promotion or tenure in policy creates a barrier (Bolliger & Wasilik, 2009; Bruner, 2007; Howell et al., 2004). Likewise, unclear policies, or no policy at all regarding copyright and intellectual property, has been found as a barrier (Bolliger & Wasilik, 2009; Berge & Muilenburg, 2000). At CUI some faculty have expressed substantial concerns about intellectual property rights in the context of online education. One main concern is how long material in an online course might be used. There is a perception that material might be used too long and become irrelevant, possibly negatively affecting the reputation of a faculty member. Unless addressed by leadership in policy, this perception will inhibit adoption. Finally, lack of appropriate faculty compensation and reward systems in institutions is recognized in the literature as an important barrier (Berge & Muilenburg, 2000; Chen, 2009; Haber & Mills, 2008; Meyer, 2012).

Issues related to the technology associated with distance education make up another category of barriers. Effective online education involves many different skills than traditional classroom education from development through instruction. Not receiving the training needed for course development and instruction for online education has been shown to be a substantial barrier perceived by faculty (Berge & Muilenburg, 2000; Lesht & Windes, 2011; Mitchell & Geva-May, 2009; Schifter, 2000). In a 2010 study, Allen and Seaman reported that about 19% of chief academic officers indicated their institution provided no training for faculty teaching online. That percentage dropped to 6% 2 years later (Allen & Seaman, 2012), which is a promising indicator that training is improving. CUI is incorporating an inhouse training protocol for instructors who teach online. It began with a needs assessment via an online teaching inventory of all faculty. Grove's office has established three levels of online teaching proficiency, identified where each faculty member resides, and planned training accordingly. This is likely to promote adoption.

Lack of technical support is one of the most frequently identified barriers for impeding the adoption of distance education (Betts, 1998; Berg & Muilenburg, 2000; Lesht & Windes, 2011; Schifter, 2000). The kind of support needed ranges from allocation of appropriate hardware and software to providing support for the many different technical skills needed for online education. Among others, online education involves interaction with the learning management system, converting print materials to electronic media, and using synchronous web-conferencing tools, all of which require initial specialized training and ongoing support. This is not limited to faculty support. Faculty perceives lack of student technical support as a barrier as well (Haber & Mills, 2008).

The lack of financial resources to meet the costs of implementing online education has been identified in the literature as a barrier to distance education (Berge & Muilenburg, 2000; Birch & Burnett, 2009; Chen, 2009; Schifter, 2000). There are sub-stantial costs associated with the design and development of quality online education courses. Institutions may mitigate costs by adding responsibilities onto existing faculty. Meyer (2012) found additional responsibilities for faculty to be a major barrier to participation in distance education. This has been common practice for CUI, but that has changed with the establishment of online education as a strategic initiative. Substantial resources have been allocated to assist in mitigating these barriers.

The literature reveals that pedagogical concerns are a major barrier to distance education. Over the last 15 years studies indicate that negative faculty perceptions about the quality of online education inhibit participation (Berge, 1998; Bolliger & Wasilik, 2009; Lesht & Windes, 2011; Meyer, 2012; Schifter, 2000; Seaman, 2009). The faculty perception of the quality of online education has not changed much over the past decade and it remains relatively low. Allen and Seaman (2013) report that less than one third (30.2%) of chief academic officers believe faculty accept the value and legitimacy of online education. Other pedagogical barriers include perceived incompatibility with a discipline (Hannon, 2009) and the desire to experience traditional face-to-face studentteacher interaction (Bruner, 2007; Haber & Mills, 2008; Lesht & Windes, 2011).

While traditional classroom instruction continues to dominate higher education, online education is now mainstreamed across the United States. Institutions of all types are including online education in strategic plans, some even as a means of survival in an increasingly competitive market. Concordia University Irvine is a small, private, liberal arts institution investing substantial resources into online education as part of its strategic plan for growth, not just survival.

There are many factors and people that impact such an endeavor. One of the primary stakeholder groups in online education is faculty. How faculty perceive online education and the factors that promote or inhibit its use is central to successful imple-mentation.

Rogers' (2003) diffusion theory principles of the innovation-decision process and perceived attributes provide a roadmap for leadership to follow in promoting faculty adoption of online education. Understanding faculty perceptions about the relative advantage, compatibility, complexity, trialability, and observability of online education informs decision makers seeking to increase adoption. CUI leadership must be attentive to faculty perceptions about these online education attributes in this strategic plan.

CUI leadership is attentive to diffusion theory concepts in the context of known barriers to online education. These barriers may be categorized as institutional, tech-nological, financial, or pedagogical. Most barriers are institutional in nature, and for CUI this is no different. With a lack of centralized control and vision over the past decade there is a substantial lack of institutional policy in most areas relating directly to online education. While finances are always an issue, CUI has strategically allocated resources to address major financial barriers in hiring and for compensating existing personnel for online education development and delivery. An emphasis must be placed on addressing faculty perceptions of these barriers as faculty play the key role in institutional adoption.