Introduction to the Problem
Online course offerings at community colleges are growing at a rapid rate. By 2008, an estimated 4.6 million students in the United States alone had already enrolled in higher education through online learning programs (Allen & Seaman, 2010).
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This constituted a 17% increase over 2007. A Chronicle of Higher Education (2010) compilation of online demographics shows dramatic growth in the number of students taking only online courses, increasing from 2.14 million students in 2009 to a projected 3.97 million in 2014.
Ninety-six percent of all higher education public institutions provide opportunities for online learners, and associate’s degree-granting institutions such as community colleges enroll more than half of all online learners. The state of Michigan passed a curriculum requirement effective in 2012, mandating all high school students to take one online course as a requirement of high school graduation.
Both institutional and individual benefits of offering distance education in the form of web-based online learning have been analyzed and substantiated in several studies (Anderson, 2004; Bach, Haynes & Smith, 2007, Curtis & Lawson, 2001; Stick & Ivankova, 2004,).
At the community college level, the majority of administrators now view online course offerings as a critical strategic success factor both for the institution and in response to student demand. The delivering institution benefits from online course offering since this type of learning module are not only cheap to offer to interested learners. It can also be designed and structured much easier.
For students, accessibility to education and certain specific training needs is highly enhanced since the limitation that was earlier posed by distance and time are non-prevalent in online learning.
The growth of online course offerings is not without challenges, particularly at two-year institutions and community colleges: studies (Bambara, 2009, Kennedy, 2001; York, 2003) of online student completion rates conducted at individual community colleges substantiate Carr’s (2000) findings that course attrition and failure rates increase when the instructor and student are indifferent
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With high schools and post-secondary institutions adding online courses and programs at a rapid rate, the number of students will increase significantly, and with the education and learning outcomes of millions of students at stake, it is critical that a focus on the quality of course design and content be maintained. One primary component of the instructional design of an online course is the degree and type of interaction.
The separation of learner and instructor in the distance learning equation has been at the root of debate on instructional design for online learning since the inception of the field. As model builders and theorists have attempted to bring order to the complexities of how learning is accomplished when the learner is separated from the instructor by time and space, interaction emerges as one key component.
Several leading theorists (Beldarrain, 2008; Holmberg, 1995; Moore, 2003) put the interactions of the learner in an online environment at the center of the learning process.
Does the quantity of interactions promote student persistence in a course? Can the number and type of interactions designed into a course by the instructor contribute to student success? What types of interactions do course participants prefer, and why? This study is designed to answer these questions.
The interaction itself is a complex and multi-faceted issue, and though considered a critical component of the learning process, it is “surprisingly difficult to find a clear and precise definition of this concept in the education literature” (Anderson, 2004, p.43).
Wagner’s (1994) definition of interaction within a distance education framework is elegant in its simplicity: “reciprocal events that require at least two objects and two actions. Interactions occur when these objects and events mutually influence one another” (p. 8).
In the arena of Internet-based online learning, interactions are conducted in a wide variety of formats, and instructors incorporate discussions, emails, blogs, and forums using an increasingly large number of both synchronous and asynchronous modes to provide a sense of connectedness.
Background of the Study
Interaction has been viewed as an integral part of successful learning for eons. Roblyer and Wiencke (2003) commented that interaction has “come to be considered a sine qua non for successful distance courses” (pg.77) and online interaction has been recognized as a contributing factor to the success of students in online community college course offerings (Battalio, 2007, Benbunan-Fich and Hiltz, 2003, Walker, et al. 2007).
Quantity interaction still remains an area of interest since online course designers and instructors do not have sufficient guide in spite of the fact they are the key architects in this form of the learning module. The rule of thumb has been least supported when designing and delivering these courses.
Calvani et al. (2010) analyzed the quantity and content of collaborative group interactions to determine the effectiveness of such interaction, and Drouin (2010) reviews empirical studies on student perception and desire for community and interaction in online courses and finds a great deal of variability in substantive findings.
Statement of the Problem
It is not known to what extent the quantity of student interaction in online courses correlates to high course completion rates. The preference of students for a particular type of interaction is also unknown and may have an impact on individual student completion rates. The literature base indicates that various instructional design strategies result in differing degrees of interaction.
Most research, however, focuses on the need to assess the qualities of interaction to ensure effectiveness. An additional component of the instructional design is the quantity or frequency of interactions between student and instructor, (I-S), student and student (S-S), and student-content (S-C) and the impact of the frequency on a student’s course completion success.
Is there a higher degree of participant persistence if there is more interaction in an online course, and the course design is such that interaction is promoted? Does the quantity of interaction directly correspond to higher persistence rates?
Research and theory of online learning indicate that interaction is a key characteristic of successful courses, yet there is little research to indicate whether achieving a high number of interactions or, more specifically, what kinds of interactions predict higher course completion rates.
As community colleges continue to increase the number of courses offered through web-based instruction, it is important to identify if an increase in interactions may improve successful completion rates. Instructional designers and instructors need to know how to design either (or both) the frequency and type of interactions to ensure higher rates of persistence.
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Purpose of the Study
The purpose of this mixed-method study will be to research the frequency and type of interaction taking place in online courses in support of the body of research advocating purposefully designed and actively rendered interaction.
In addition, course participants will be surveyed to determine their interaction preference. Research indicates that interaction in online learning courses is a necessary component of success and that there is a positive effect from the addition of interaction in online courses.
There is little research on a specific frequency, methods, or techniques for the standardized design of interaction that can be incorporated into the overall design to correlate to maximum completion and success rates.
The purpose of the study is to investigate and analyze the quantity and types of interactions and their impact on successful completion in community college courses to add to the existing body of research on the topic and fill a gap in the analyses of interaction in online course instructional design.
Interaction in online courses continues to be debated among researchers, scholars, and practicing faculty on the front line of improving student persistence and raising the percentage of students successfully completing online courses. Additional research is required to understand the relationship between interaction and academic performance, particularly at the community college level, where there is a large nontraditional population.
By exploring the relationship between online course interaction and course completion, this research will contribute to the body of mixed methods research and will provide practical application to those charged and challenged with the design and delivery of online courses.
Increasing the understanding of interaction may assist instructional designers with detailed and specific methods for increasing the frequency of the right types of interaction to help reduce the attrition rates currently experienced at the community college level.
The focus of this study is a mixed-methods analysis to determine if there is a statistically significant correlation between the number of interactions and student success rates in online courses. Every attempt will be made to avoid drawing causal conclusions yet provide useful statistical correlation to contribute to the body of knowledge for the topic. With those guidelines in mind, the following research questions were developed:
- Primary: To what extent does the number of interactions, categorized as ‘instructor-student’ (I-S), ‘student-student’ (S-S), and ‘student-content’ (S-C) in an online course predict the individual participant’s course completion rate?
- Secondary: a) What is the relationship between the aggregate number of interactions in an online course to the overall course completion rate? b) What is the relationship of a participant’s total number of interactions in an online course to the individual’s successful course completion? c) What is the relationship of a participant’s preferred method of interaction in an online course to the individual’s successful course completion?
Other sub-research questions that will be worth considering the paper include: Is student-student interaction a prerequisite in online course programs? Why is there a conflicting approach to conventional expectations of online courses as put forward by practitioners and theorists? What are the specific objectives of crafting out online learning as embraced by those who design offer instruction in online courses? What are some of the reasons why students prefer online courses? Are there any quantifiable results as well as rationale that can be succinctly identified out of online learning programs? Is it possible to identify other alternatives in online course interaction that can be beneficial in ensuring that the attrition rate is brought to the minimum level possible?
Significance of the Study
The importance of this study is in researching, analyzing, and quantifying interactions in online courses and determining if there is a correlation between the number and types of interaction and the course completion rate. The significance of this study lies within the perimeter of seeking better delivery methods for online courses in order to improve the standards of education in a college community.
It is common practice for instructors to assume that a higher quantity of interactions in a course correlates to higher course completion rates, but much of the evidence is qualitative or anecdotal. The information from this formal and informal research is valuable; however, this study will add a quantitative component to further add to a larger body of available research.
Definition of Terms
The following terms are defined to ensure a semantic understanding of this study.
Asynchronous interaction: Interactivity between student-student, student-instructor, or student-content that does not take place in real-time but allows for communication at a time convenient for the student or instructor.
Attrition: A reduction of the number of learners in a course due to student withdrawal, administrative withdrawal, or lack of persistence.
Interaction: For the purpose of this dissertation, Wagner’s (1994) definition will be used defining interaction as “reciprocal events that require at least two objects and two actions that mutually influence one another.” Online interaction falls into the following categories, as defined by Moore (2003).
- I-S: Interaction between the instructor and student via synchronous or asynchronous technologies in a learning management system using tools such as discussion boards, wikis, blogs, assignment feedback, or chat sessions.
- S-S: Peer interaction between student and student via synchronous or asynchronous technologies in a learning management system using tools such as discussion boards, wikis, blogs, assignment feedback, or chat sessions.
- S-C: Interaction between the student and content, including the structure, strategies, and skills needed for effective creation (Anderson, 2003). Includes interaction with materials, assignments, and readings, for example, via synchronous or asynchronous technologies in a learning management system using tools such as discussion boards, wikis, blogs, assignment feedback, or chat sessions.
Course completion rate: The percent of students enrolled in a course that successfully complete the course with a final grade of C or better
Distance education: Learning taking place when the learners and instructors are separated physically by time and space. Access to learning is not limited by geography or physical demands and may involve the use of computer technology and the Internet.
Learning Management System: this refers to a myriad of tools hosted through the World Wide Web used to deliver course content and ensure a smooth flow of communication between computers and humans. A synonymous term is a course management system. Popular examples include Blackboard and WebCT.
Online learning: A course where most or all of the course content is delivered via the Internet, usually in a learning management system, and no face-to-face meetings are required. Online learning is a subset of distance education
Persistence: The actions and skills required of a student to successfully complete a course with a passing grade.
Satisfactory achievement: Completion of a course with a final grade of C or better.
Synchronous interaction: Interactivity between student-student, student-instructor, or student-content that takes place in real-time but occurs at a distance. Includes technologies such as chat, voice over internet protocol (VOIP), or phone.
Assumptions and Limitations
The underlying hypothesis of this study is that the frequency of interactions by an individual student or in aggregate correlates to a higher course completion rate.
A related assumption is that certain categories of interaction will be greater in number and more significant in terms of raising successful completion rates than others. A third assumption is that students will have preferred methods of interaction.
This mixed-methods study looks only at the number and type of interactions in community college online courses. There is no qualitative analysis included though considerable research has been conducted by others in this area.
Demographic and cultural factors such as gender, cultural mores, ethnicity, and age, which may influence the frequency and preference for a particular type of interactions or may affect course completion, are not considered.
Organization of the Remainder of the Study
The remaining chapters in this study include the Literature Review, Methodology, Data Analysis, and Results, and finally, Conclusions and Recommendations. The function of the Literature Review is to highlight past and current research on the relationship of interaction to successful online course completion rates. The Methodology chapter provides a detailed view of the mixed methods used to conduct the research in this study and the respective data collection procedures.
As online learning opportunities have expanded at a rapid rate over the last two decades in community colleges, researchers have developed many theoretical frameworks to determine the relationship between the online learning environment and learners’ ability to be successful in that environment (Tapscott, D. (2009).
A broad view of theories indicates that the factors to be considered in successful online learning are large in number and complex in nature. Khan (1997) developed a framework for e-learning that included learning issues in eight categories, including interface design, evaluation, management, institutional, pedagogical, technological, ethical, and resource support factors.
Gilroy (2001), taking a constructivist stance, stated that learning is both experiential and social, and it is the context of learning- wrapping each learner’s experience around the content-that is most critical. Gilroy’s theoretical construct is that low success rates occur because of learner dissatisfaction, and the cause of the problem is the separation of people in time and space.
Corbeil (2003) developed a framework with a strong individual learner focus, arguing that there is a relationship between student success and the online technologies’ self-efficacy, internal locus of control, and self-directed learning readiness.
When fine-tuning the focus to explore the issue of interaction in online learning and the relationship to the successful course completion, three primary theories have a major role: the schools of learning (behaviorism, cognitivism and constructivism), Moore’s (1980) theory of transactional distance and Tinto’s (1975) theory of persistence.
Each of the primary schools of learning has contributed to instructional design strategies for online learning, and each has a place in the development of effective means of interaction (Barr & Tagg,1995). A behaviorist approach to learning views the mind as a ‘blank canvas’ focusing only on behaviors that can be observed, quantified, and measured without regard to the effect of the mental processes.
Behaviorist forms of interaction in online learning include a statement of learning outcomes, so learners have a clear outline of measurable expectations, assessments to determine achievement and feedback from instructor and/or peers to evaluate if measurable outcomes are achieved.
Learning is an intrinsic process that entails myriads of other cognitive abilities such as the process of thinking as well as memorize facts, according to Ally (2004). The cognitivist learning model has information processing at its core with a learner receiving sensory input, processing the input to a sensory store, then moving the information to work memory, and finally, on to long term memory.
Cognitivist instructional design strategies specifically addressing interaction in online courses include the use of discussion and feedback aimed at promoting perception and attention. Examples include the use of pre-requisite testing, exercises where learners dialogue on the application of the learned information to their life experience, and dialogue that incorporates the cognitive or learning style of the individual learner.
Finally, the constructivist school states that learners should be allowed to construct knowledge rather than being given knowledge through instruction (Duffy & Cunningham, 1996), and online interaction should incorporate standards of social constructivism that emphasize real-world, practical problem-solving.
Emerging from the works of psychological theorists Piaget and Vygotsky, the theoretical concept is that there are multiple representations of reality, and learning is an active, holistic event. The emphasis in the constructivist learning model is on active rather than passive learning, whereby each learner is processing information and creating an individual contextualized outcome.
Key components of constructivist based instructional design strategies focusing on interaction include opportunities for collaborative and cooperative student-student learning, opportunities for reflection promoting the internalization of information, and highly interactive design to promote higher-level learning.
The three schools of learning, behaviorist, cognitivist, and constructivist, all have a role in effective online learning and successful interaction.
In recent years, education has seen a shift toward constructivist strategies in online learning, in part due to the perception that individual context is critical and constructivist activities assist in building community through interaction, but there remains a place for each theory to be represented in the design of interaction.
In order to create viable online learning programs, student-student interactivity has been identified as an essential element. Online learning communities may only be successful if such a form of interaction is promoted at all costs. Although this has been the general view held by most practitioners, critics of student-student interaction as a paramount component in online course offerings have a conflicting opinion.
It is, however, known that effective online communities may only be enhanced in environments where interaction has been strengthened.
This is still a conventional theory and practice, and it may not be justified to refute other innovative ways of promoting online course programs, bearing in mind that this form of learning is highly dynamic. Hence, although student-student interaction is a necessary ingredient in online learning, it may not be a total requirement.
According to Barr and Tagg (1995), the pedagogical reforms of the 1990s saw the need to not only revolutionize e-learning platform, but it also emphasized the need for more effective participation and active learning in online courses.
These reforms also stressed the need for allocating more thinking space for students as part and parcel of creating knowledge on their own rather than wholly relying on the instructors for what may be referred to as ‘spoon-feeding.’
For a long time now, utmost mastery of course content has been a preserve of the instructors to the peril of students who end up either duplicating the contents learned per se in order to merit or failing the course content altogether.
This demands that the traditional stance by instructors should be given up since it does not allow students to be creators of knowledge. Rather, they merely develop dependency syndrome on the acquisition of academic knowledge.
Some skeptics have never supported this. However, proponents argue that no single educational institution, whether within the context of online learning or real physical environment, may be proud of the student lot, which is not active (Buchholz, 1997).
Moreover, the design of online course programs should be such that student-student interaction is given a priority as part of the objectives to be met in the course of learning (Tapscott, 2009). Perhaps, the most practical way to comprehend this would be t draw parallels between online learning and classroom environment where face-to-face teaching and learning take place.
In the latter case, it is found that student-student interaction is often at its best. For instructors, active participation is by far and large, a more practical approach of ensuring that course comprehension and completion rates are at the optimum level.
Therefore, achieving an effective level of interactivity between students can be enhanced through myriads of available electronic components and discussion forums (Palloff & Pratt, 2005).
The social constructivist elements can indeed be used as benchmarks when identifying and determine various preference levels for online interactions among students (Burbules, 2000).
Such a wide array of availability of several tools for interaction accounts for the rationale of why student-student interaction in online courses is still an imperative consideration for professional designers of the very courses. Nonetheless, a stickier and perhaps challenging point is how to prove constructivist methods.
From the backdrop of both theory and practice derived from mainstream principles, it may be quite an uphill task to lay the clear ground for proving such claims whenever online course offering is being discussed. Even for most publications on online teaching and learning, this dilemma stands out as a perspective that is still quite tricky to bring on the surface.
Consequently, skeptics have a reason to defend their claim on this subject bearing in mind that some of the latest empirical studies have equally laid doubt on the assertions put forward by constructivism (Kirschner, Sweller, & Clark, 2006; Meyer, 2004). Moreover, a critical inquiry has also evaded other traditional perspectives of active learning through student interaction.
It is most likely that this might be the very reason why Cuthrell and Lyon (2007) reiterate that it is pertinent to recognize claims by adult e-learning students since underestimating or ignoring such claims may not do justice to the very students who are the very subjects anticipated to benefit from the online program.
Besides, their assertions may hold some water since most of the data used from recent research have been gathered from adult respondents who are, by all means, expected to be independent-minded and thinkers. As Cuthrell and Lyon (2007) observe, the ability and potency to direct their online studies will be improved when their claims are recognized.
The reason given is that they will have greater autonomy in selecting options that best fit their learning needs. Better still, such recognitions will also jumpstart more independency alongside reducing the degree of dependency on group or teamwork activities.
On the same note, online postings for students enrolled in e-learning modules will be a major cause of the interruption and superfluous in a bid to enhance communication among students (LaPointe & Reisetter, 2008).
Similarly, skeptics also demonstrate that compulsory participation in online learning may as well lead to mediocre learning since it will fail to a difference between classroom learning and that which has been defined by space and time.
Ordinarily, the latter form of learning is expected to be a notch higher both in terms of efficiency and learning outcomes (Gulati, 2008). Additionally, if participation is enforced as a requisite element in online courses, it is highly likely that stigmatization will be prevalent and adversely impact the very virtues of the learners (Beaudoin, 2002).
Moore’s research and theoretical framework address the component of interaction that is directed at the separation of the learner and the instructor. This separation of instructor and learner is the core underpinning of Moore’s Transactional Distance Theory (TDT) that states, “distance education is not simply a geographic separation of learners and teachers, but, more importantly, is a pedagogical concept describing the universe of teacher-learner relationships that exist when learners and instructors are separated by space and time.” (Moore,1993).
At the heart of this universe are three key variables that form the fundamental constructs of distance education: structure, learner autonomy, and dialogue. The degree of transactional distance in an online course is a function of these three variables resulting in a level of transactional distance defined as “a psychological and communications space to be crossed, a space of potential misunderstanding between the inputs of instructor and the learner” (p.23).
Moore felt his theory of transactional distance effectively fused the pedagogical traditions of behaviorism, emphasizing strong instructor control and constructivism, highlighting more open-ended, unstructured dialogue.
The variable of learner autonomy defined by Moore (p.31) argued from a constructivist stance that learners are more successful at a distance if given responsibility for at least a portion of their own learning process. If allowed to participate in dialogue and interact with the instructor and peers, the feeling of distance and isolation is reduced.
When the set objectives are relatively rigid, then it accounts for stricture. This defined level of rigidity extends beyond just the objectives; it also prevails in the teaching and assessment methods. Moore explains that it is only through the structure of education that each learner’s needs can be catered for. A poor course structure may vastly fail to address the various learning needs of each individual student.
The concept of instructional dialogue, defined as “an interaction or series of interactions having positive qualities that is purposeful, constructive and valued by each party..who is a respectful and active listener, a contributor and [who] builds on the contributions of the other party or parties” (p.24.), allowed for multi-faceted communications between and among participants.
Moore defined an early model of distance learning communication, clearly defining the components of instructor-student, student-student, and student-content interactions. Moore’s theory is the more dialogue that takes place in any of the key areas; the less transactional distance will be perceived on the part of the student and instructor.
The importance of interaction has long been prominent in discussions of successful web-based instruction. As a component of Moore’s (1993) Transactional Distance Theory (TDT), interaction has been systematically validated by a number of educational theorists including Saba (2003) who argues that accountability for interaction is of utmost importance in a systems approach and Garrison (2000, 2003) who envisions a shift from organizational structure to one of transactional importance in distance education.
Whether Transactional Theory should be fully accepted as a global theory is still under debate in spite of the fact that Gokool-Ramdoo (2008) fully supports the ideology. Gorski and Caspi (2005) have investigated empirical studies that attempt to validate or support TDT.
Dissertation research in the arena of TDT has touched on evaluation of the structure component (Sandoe, 2005), an investigation of the educational transaction within a videoconferencing learning environment using Moore’s Theory of Transactional Distance, associated adult learning and distance education theories as theoretical frameworks (Chen, 1997) and a study of online students surveyed to measure transactional distance using traditional definitions (Lowell, 2004).
Focusing on the interaction/dialogue component of TDT, Roblyer, and Weincke (2003) designed a useful rubric to measure and assess effective interaction in distance education. The framework of the design incorporated Wagner’s (1994) prerequisite stipulations for making interaction a more useful construct for informing instructional design and research in distance learning environments.
Though much of Moore’s research was conducted prior to the development of Internet-based online courses delivered via a course management system, the theoretical underpinnings of the transactional distance theory hold true.
The advent and rapid development of social networking tools within course management systems allowing for text, audio, and video interaction all point to the validity of the theory and continue to address the need to reduce transactional distance.
The third concept that informs this study is that of persistence or motivation to complete a course or program of study. Tinto (1975,1993, 2003, 2005) developed a theoretical model of persistence that forms the fundamental framework for the study of successful completion of online courses.
Tinto’s research and model were conducted primarily in classroom settings of four-year universities; however, recent research (Tello, 2007, Willging & Johnson, 2004) concludes that Tinto’s model can provide an equally compelling framework for understanding the relationship between interaction and student persistence in the online learning environment.
Tinto’s model included the components of ( a) pre-entry attributes including prior education of learner and family; (b)goals of both the learner and the institution; (c)institutional experiences such as faculty interaction; (d) academic integration in terms of course instruction and grading; (e)social integration in the form of interaction between peers, instructors and the organization; (f) outcomes including graduation, transfer and dropout.
The focus of Tinto’s model is on integration, with an emphasis on points of interaction, modeling that the balance and mix of these components are predictive of whether or not a learner will persist in a course. The degree of social and academic integration drives the outcome in that the higher the degree of integration of social and academic components, the higher the probability of successful completion.
Realistically speaking, a learner-centered approach in online courses, according to the above skeptical undertones, is by far and large, a growing challenge in the eyes of professionals who design and teaching these courses. This is aggravated by the fact that student-student interaction in online teaching and learning is hardly recognized when the very modules are being designed.
Nonetheless, there is a pedagogical consensus on the relative importance of student interactivity. Contrastingly, it is also apparent that the utility of this form of interaction is rarely valued or held in high esteem by learners. In some instances, it may also be remotely asserted that students enrolled in online courses may vaguely oppose to it in a way that makes it cumbersome for theorists to prove.
One daunting question still remains: Are online students conversant with the uptake benefits and, more importantly, the imperatives needed for successful completion of these causes? Is it just an alternative learning platform without clearly identifiable variables tagged as either inputs or outputs?
Moore (2008) noted that online course offering is “Unfashionable …and welcome though learner-to-learner interaction might be, for the vast majority of students, course content is much more important than interaction” (p. 2).
As per this observation, it may still be argued that social constructivism is not a practical requirement for successful completion of online courses by students since it merely serves the purpose of bridging the social gap but not delivering course content.
In addition, Moore emphasizes that the perception of most students is that content delivery from the instructor is a better interactive learning method since they tend to learn more from their instructors than fellow students even in the case whereby the given course has been structured and designed for online uptake. The pedagogical conventions are further revealed in Moore’s statement in the sense that he describes student-student interaction as a non-fashionable affair in online learning.
In his submission, he is very blunt that such pursuits in online learning and teaching are usually common but may not practically count towards reducing attrition rates. Worse still, student-student interaction, according to Moore, may just amount to too much debate about nothing; it is a fancy way adopted by online course designers in decorating the module.
The online learning paradigm ought to have other optional interactive methods that can be used by students in spite of the fact that student-student interaction may not be a fundamental requirement for learners enrolled in online courses. In any case, the advances made in the contemporary digital world has made it quite easier and convenient to interact on a wider base regardless of the fact that individuals are vastly separated by both time and space.
The World Wide Web has significantly grown and as a result, provided a better platform through which individuals can interact more efficiently than before. Indeed, this astonishing growth is a good reason why other alternatives should be brought on board on how students can interact among themselves.
For instance, the process of designing online courses may also incorporate hypermedia as an integrated architecture that will facilitate online learning. This form of online course integration should be done on a regular basis, depending on the needs of learners. Some of the hypermedia that can be included in online learning includes exhibits, quick online prompts, as well as audio-visual materials.
This will largely supplement the conventional print media that has been used for a long period of time. In terms of student-instructor interaction, it is crucial for a student’s writing to be assessed on a regular basis by the instructor. It is highly probable that online learning may ignore the pertinence of the written content of the actual course being taken.
Bean and Metzler (1985) generated a model of persistence grounded on Tinto’s model but explaining attrition for non-traditional students defined as those “older than 24, a commuter or part-time student, or a combination of these three factors, is not greatly influenced by the social environment of the institution and is chiefly concerned with the academic offerings of the institution.” (p. 489).
The focus on non-traditional students makes Bean and Metzler’s model more relevant to the community college online environment than Tinto’s model. Bean and Metzler’s model incorporates four factors that influence persistence: (a) academic variables including study habits and course fit, (b) background variables such as age and prior GPA, (c) environmental variables such as family and work responsibilities, finances and external support systems and (d) academic and psychological outcomes while enrolled such as ability to finance an education, and perceived commitment from the institution. (p. 503).
Rovai (2002), writing on factors contributing to higher persistence rates, specifically in online courses, created a composite of variables from both Tinto and Bean and Metzler’s model.
In establishing the factors that determined successful distance learning outcomes, Rovai confirmed the need for frequent interaction specifically in the areas of timely teacher-to-student and student-to-student feedback regarding mastery of objectives, the development of interpersonal relationships with peers, faculty and staff and supportive and informational communication and interaction between student and instructor.to provide a sense of high self esteem for the student.
Extracting and isolating a single component, such as interaction from a conceptual framework and model, can provide useful research. Focusing on a single criterion provides detail that can then be factored into a model resulting in a comprehensive, multi-component strategy for improving persistence, thus increasing successful completion rates of students in online courses.
Changes in software, hardware, and pedagogical understanding of online learning are driving rapid change and innovation in the field. As the field matures, research in these areas of development is generating a growing body of knowledge, exploring the specific factors leading to successful online learning (Baines & Stanley, 2000).
The body of research attempting to define the characteristics of successful instructional design for online learning leading to success on the part of the student, the instructor, and the institution is commensurate with the increasing speed of development in the field.
The following literature review discusses the component of interaction in online courses and the impact of the quantity of a variety of interaction types on student completion rates focusing on the factors unique to community college students.
Sims (2003) pointed out that within the context of learning, the significant function of interaction relates to things or persons acting on each other, and the outcomes of that interaction. The function may be apparently direct. Nonetheless, there has been a growing debate on this issue.
In some cases, some have viewed it positively, while in other cases, it has been discussed in a negative light while others have remained skeptical over the entire debate. As Jonassen (1988)puts it, the momentous role played by the computer as an interactive device cannot be underestimated or ignored. It has surpassed many interactive devices that have been used in the past.
As a result, the importance of interaction in the process of learning has been one of the hotly debated topics in the field of education. One of the triggering factors towards this debate is the fact that there seems to some vested interests alongside the confusion created in defining the unique role played by either the computer or human being. The human role in providing an interactive role during the process of learning is yet to be defined in a succinct manner.
Many studies have cited the necessity for interaction in online courses (Hannifin, 1989; Shea, Fredericksen, Pickett & Pelz, 2004), but research is sparse on the relevance of the frequency and quantity of interactions needed; what constitutes too much or too little and if it possible to determine a ‘sweet spot’, or to design a precise number and variety of interactions that result in higher course completion rates?
According to Anderson (2002), all the aforementioned forms of interaction prevalent during the process of learning are very important as afar as adequate learning is concerned. This is well covered in the equivalency theorem. This theory underpins the fact that the process of learning can be advanced at a very high level if any of the major forms of interaction is utilized optimally.
In the event that either of the interactive learning forms is utilized well, then it is possible to do away with the others without jeopardizing learning. Kearsley (2000, p.78) made the observation that “a high degree of interactivity and participation” is “the most important role of the instructor in online classes.”
At the opposite end of the spectrum, Rovai (2007) argued that instructors who promote student expression do not dominate the discussion but instead have a restrained presence and “avoid becoming the center of all discussions” (p. 7).
Rourke, Anderson, Garrison, and Archer 1999) cautioned that there is a need for instructors to determine an ideal level of social interaction and that it is possible to exceed an optimal frequency of interaction having a detrimental effect on students satisfaction.
Clearly defined optimal rates of interaction are difficult to locate but some have made attempts at proposing ‘rules of thumb’; for example, instructors at Indiana Wesleyan University are told to “maintain at least the same level of participation as you expect of students or post 10-15% of the messages in a discussion room (whichever is greater)” (Woods, 2002).
Woods’ research also pointed out that though there is frequent mention of a need for a high degree of interaction in online courses, there has been little effort made to empirically support these anecdotal ‘rules of thumb’ (p.1) to assist instructors in knowing how often and what specific kinds of interaction should be designed into a course.
Categories of Interaction
Looking at each individual type of interaction in greater detail illuminates why each is a key and critical component of course design and can have such an impact on persistence in the course (LaPointe & Reisetter, 2008).
Student- instructor interaction provides the opportunity for information and learning to be exchanged in two way communication between both parties (Moore & Kearsley 1996). Instructors exhibit multiple personalities throughout a course; at once, nurturing, motivating, constructively criticizing, and cajoling.
Providing frequent feedback gives students the opportunity to evaluate their learning and construct new knowledge from the feedback. Instructors can interact with students either individually or in groups depending on the available tools of the learning management system but must be more than just a facilitator.
Student-student interaction tends to be the focus of much research on persistence and successful completion in part due to the significant varieties of interaction that can take place (Palloff & Pratt, 2005).
Formal interactions, in the form of collaborative learning, group projects, or graded discussion, provide a mechanism for the exchange of knowledge, formed an opinion, and cognitive connection. Informal interaction in the form of social, non-graded information sharing serves to build a community of learners, and the frequency of interaction among peers cam lessen the sense of isolation or loneliness felt by a student.
In student-content interaction, both the learning content and the method of delivery are considered. There is anecdotal evidence that students in online courses benefit from frequent interaction with both the learning content (assignments, discussion board postings, assessments) and the plethora of tools available in current versions of learning management systems including wikis, whiteboards, podcasts, chats, audio-visual tools
In addition to the frequency of interaction in the three categories of interaction (I-S, S-S, and S-C), it is also necessary to analyze the characteristics of the different dimensions of interactions. A variety of analytical models have been developed (Henri, 1991; Offer & Lev, 2000; Oliver and Mcloughlin,1996) that examine the content of information acquired in interaction.
Song (2003) assimilates the different models into a single framework of five primary dimensions of learning, including social, procedural, expository, explanatory, and cognitive. The social dimension is casual, informal interaction; procedural interaction is between instructor and learner that include factual information regarding course process and policy (Meyer, 2004).
Expository interaction includes answers to questions, and explanatory interaction is the instructor’s response to student queries. Cognitive interaction involves higher-order thinking, usually in the form of extended discussion.
The categorization of interaction using this analytical framework adds an additional element of knowledge to be factored into research on the type of interactions leading to successful course completion. The debate among scholars and researchers is far from complete, but there is ample indication that both the frequency and type of individual and group interaction is critical to the success of online learning.
As already mentioned, several interactive alternatives can be crafted when designing online courses. Much of the debate has, however, been on the pragmatic role played by student-student interaction in the online course offering. Recent research studies have attempted to address other interactive channels apart from that which involve students themselves (Kirschner, Sweller & Clark, 2006).
For example, two other alternative interactions, namely between the student and the instructor, as well as that between the student and content still count towards the relative importance of interactive learning of online courses (Cuthrell & Lyon, 2007).
The content focused interaction, for example, attach more significance to what the learner is being taught rather than what may be referred to as the ‘socializing among students.’ In line with content-to-student interaction, the most valued parameter is whether the course structure is carefully structured to meet the general and specific objectives.
Irrespective of the type of learning and teaching module adopted by instructors and learners, interaction still remains to be a very pragmatic requirement.
Chickering and Gamson (1987) underpinned five major principles underlying interaction during the learning process. They underscored the importance of interaction that takes place between learners themselves as well that interaction level between the subject matter (content) and students (Gulati, 2008).
Firstly, the interaction between students and instructors is vital. The second consideration is the reciprocity and collaboration among learners. In addition, prompt feedback is also a key principle, while the time taken to accomplish a particular task is pertinent. Finally, there should be a higher anticipation of communication (Tapscott, 2009).
Besides, the value created by interaction in a learning environment has also been recognized by accredited bodies. For example, AACSB International is mandated with the duty of validating schools of business. The institution believes in the value created by the active participation of both learners and instructors in the process of learning (Beaudoin, 2002).
Community colleges that have adopted online learning are, therefore, encouraged to introduce some form of interactivity in their teaching and learning programs (Burke, 2005). These are just some of the justifications why interactive learning is vital, and the more reason why it should be emphasized, especially in an online or abstract learning atmosphere.
The role of the instructor is to assess and evaluate the work of the student in the case of a learner-instructor. In other words, all the learning needs are catered for by the instructor. The major role played by the student is to absorb the material given out by the instructor (Grasha, 2002).
Online Course Completion
Howell et al. (2004) found that studies targeting online course completion are relatively few. Student persistence addresses the student’s commitment to completing a course or program of study (Tello, 2007). Persistence is considered a positive outcome, represented by successful completion in the form of a passing grade of C or better.
A 2004 University of Massachusetts study of student persistence indicated that the frequency of interaction is strongly, positively correlated to student attitudes about their course and their willingness to complete it. Factors contributing to the lack of persistence in the online environment can include technology literacy gaps, motivation, and student autonomy, and course design.
Though interaction is only one element in each of these factors, improving the frequency of interaction in each can substantially impact the reasons students choose to complete a course. Goetz (2000) provides a real-world model of success in a description of an online law school claiming a 70 percent retention rate that would be the envy of most online programs.
The retention rate is due to an extremely high level of interaction that requires students to take frequent assessments, write several essays, and reply to several hundred multiple-choice questions throughout the course. Goetz describes this as the “worst of Big Brother being put to the best of uses.”
The Community College Environment
Allen and Seaman’s (2006) study shows student enrollment in online courses at 3.2 million students with Associate’s degree-granting institutions, such as community colleges, enrolling more than half of all online learners. Online courses provide community college students with family and work responsibilities the opportunity to participate in higher education (Kozeracki, 1999; Simpson, 2003; Young 2008).
The attraction of less commute, the flexibility of schedule, the ability to participate in courses while caring for family members is strong. As the number of students and course options continues to grow, however, so does the attrition rate. Several studies confirm Carr’s findings (Pedone, 2003; Rovai, 2003; York, 2003). The literature has focused on several aspects of online courses at community colleges.
Dissertation research (Rhode, 2008; Tirrell, 2009; Welsh, 2007; York, 2003) on community college online courses has yielded much useful data on the factors contributing to the course completion, including the impact of age, gender, ethnicity, cultural issues, financial circumstance, and experiential background.
Evans (1999) pointed to a common technological literacy gap for community college learners that may be an important factor in determining an effective quantity of interactions in a course. In a series of interviews with five leaders of secondary virtual programs, Robyler (2006) pointed to compelling reasons why specific courses succeed. These results indicate there is a possible correlation between the number of interactions as well as the quality of those interactions and the course completion rate.
Wimbish (2001) provided qualitative narrative results, indicating a correlation between interaction and course completion in community college online courses. Bangurah (2004) provides supplemental data on course completion statistics at a Community College for traditional classroom and web-based courses.
For this research study, the completion data will be relevant in determining whether the various types of interactions, as put forward by theorists, can impact the quality of online learning experience.
Instructional Design Process
To those experienced in the art of distance delivery, it is evident that the addition of a few more handouts is not the solution for interactive course design (Parker, 1999). The challenge lies in the refocusing of the instruction to embody a component of interaction (p. 16).
According to Laurel (1991), three important parameters are important when computers and human beings interact. The first pertinent of these variables is frequency. This describes the intensity of the available choices that can be made at any given time.
The second parameter is the range. This defines the number of available options, and the last variable is significance, whereby it defined the impact level of the various choices made. Sometimes later, the feeling of participation was also considered to be an equally important variable worth considering. The result of the purposeful design of interaction is a fully engaged learner with a wide range of significant choices for achieving learning objectives.
In bringing Laurel’s model forward to an online environment, the technologies available within today’s course management systems can be utilized to achieve high levels of frequency, range, and significance. An example of this is in learning systems such as Blackboard, a variety of tools such as video, audio, text, and mashups allow an instructor to design and deliver content in a variety of formats.
Adding a set of complex instructions in text, video, and audio formats in multiple content locations in a course indicate to students the importance of the task. The online environment, perhaps even more so than the traditional classroom, can address and support multiple modes of communication between instructor-student, student-student, and student-content.
A variety of learning styles can also be addressed through the range of tools available such that a learning objective can be presented utilizing multiple modalities, including text, audio, video, or a combination.
Standards for the design of interaction in online courses are prevalent in the literature. Clawson (2007) synthesized several models and rubrics (American Distance Education Consortium, n.d.; Anderson & Elloumi, 2004; Johnson & Aragon, 2003) Michigan Virtual University, 2002) and developed a hybrid taxonomy for evaluating the quality of online courses.
It is important to note that each model or rubric and Clawson’s resulting taxonomy for the design of instructional strategies leading to quality online delivery included standards for interaction.
By intentionally establishing standards for the incorporation of the type and frequency of interaction into the design, the overall quality of the course can be improved. The research conducted in this study will establish what type and how often interaction should occur to achieve higher course completion rates.
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