Darrell A. Dromgoole, Associate Professor and Extension Specialist, Texas A&M AgriLife Extension Service.
Scott Cummings, Associate Department Head and Program Leader; Professor and Extension Specialist, Texas A&M AgriLife Extension Service.
In response to the Covid19 pandemic Extension educators across the state increased their utilization of digital engagement to deliver program content. As the restrictions associated with Covid 19 are relaxed it is imperative that we continue to incorporate digital engagement in our educational portfolio. Many Extension educators may believe that the incorporating of digital engagement is as simple as posting a course online or conducting a webinar when in reality there are numerous educational theories and frameworks that should be considered when designing educational programs that integrate digital engagement. Our Director, Dr. Jeff Hyde has stated that our goal is to impact every Texan. In order to accomplish this goal it will imperative to incorporate digital program delivery routinely in our Extension educational portfolio.
Terry Anderson (2011) in a chapter of The Theory and Practice of Online Learning examines whether a common theory for online education can be developed. Anderson (2011)examines possibilities for various theories to be utilized in online education and proposes his own theory. The purpose of the next few blogs will be to examine theoretical frameworks relevant to the pedagogical characteristics of online education. It starts with a consideration of learning theories and ultimately focuses on their specific application to online education.
Learning theory is meant to explain and help us understand how people learn; however, the literature is complex and extensive enough to fill entire sections of a library (Picciano, 2017). It involves multiple disciplines, including psychology, sociology, neuroscience, and of course, Extension education. Three of the more popular learning theories—behaviorism, cognitivism, and social constructivism—will be emphasized to establish the foundation for further dialogue (Picciano, 2017). Consideration will also be given to several other learning theories that are relevant to online education (Picciano, 2017). Before reviewing these theories, it will be worthwhile to have a brief discussion of the term theory itself. Theory is defined as a set of statements, principles, or ideas that relate to a particular subject (Picciano, 2017).
A theory usually describes, explains, and/or predicts occurrences (Picciano, 2017). The definition of theory also varies depending upon disciplines, especially when related to the term model (Picciano, 2017). Graham, Henrie, and Gibbons (2013) noted that the two terms are used interchangeably and generally refer to the same concept. However, a model is more frequently a visual representation of reality or a concept. For the purpose of this blog article, the terms theory and model will be used interchangeably. The purpose of a theory or model is to propose the answers to basic questions associated with an occurrence. Graham, Henrie and Gibbons (2013) reviewed this issue as related to instructional technology and recommended a three-part taxonomy first proposed by Gibbons and Bunderson (2005) that includes theories that:
This taxonomy will serve as an overall guiding principle for the discussion of learning theories and models in this article and upcoming articles.
As its name implies, behaviorism focuses on how people react or behave. In simple terms, action produces reaction. In Extension education, behaviorism examines how clientele behave as a result of an educational intervention. More specifically, behaviorism focuses on observing how clientele respond to certain stimuli that, when repeated, can be evaluated, quantified, and eventually controlled for each individual (Picciano, 2017). The emphasis in behaviorism is on that which is observable and not on cognitive processes. In fact, if you cannot observe it, it cannot be studied.
The development of behaviorism is frequently associated with Ivan Pavlov, famous for his experiments with dogs, food, and audible stimuli, such as a bell (Picciano, 2017). In his experiments, dogs learned to associate food or feeding time with the sound of the bell and began to salivate (Picciano, 2017). Pavlov conducted his experiments in the early 1900s and they were replicated by many other researchers throughout the 20th century. John B. Watson, among the first Americans to follow Pavlov’s work, saw it as a branch of natural science. Watson became a major proponent of Pavlov and is generally credited with coining the term behaviorism (Picciano, 2017). He argued that mind and consciousness are unimportant in the learning process and that everything can be studied in terms of stimulus and response (Picciano, 2017).
Other major figures associated with behaviorism are B.F. Skinner and Edward Thorndike. Skinner is particularly well known, primarily because he introduced what he referred to as operant conditioning as a method of learning that occurs through rewards and punishments for behavior. Through operant conditioning, an individual makes an association between a particular behavior and a consequence (Skinner, 1938). This is different from Pavlov, who relied on simple reflexive responses to specific stimuli although both Pavlov and Skinner promoted repetitive behavior that leads to habit development (Picciano, 2017). Skinner had a significant influence on early computer assisted instructional (CAI) models as developed by Pat Suppes and others (Picciano, 2017). A common aspect of early CAI programs was the reliance on encouragement and repetition to promote positive learning activities (Picciano, 2017).
Cognitivism has been considered a reaction to the “rigid” emphasis by behaviorists on predictive stimulus and response (Harasim, 2012, p. 58). Cognitive theorists promoted the concept that the mind has an important role in learning and attempted to focus on what happens in between the occurrence of environmental stimulus and student response (Picciano, 2017).. They saw the cognitive processes of the mind, such as motivation and imagination, as critical elements of learning that bridge environmental stimuli and student responses (Picciano, 2017). For example, Noam Chomsky (1959) wrote a critical review of Skinner’s behaviorist work in which he raised the importance of creative mental processes that are not observable (Picciano, 2017). Interdisciplinary in nature, cognitive science draws from psychology, biology, neuroscience, computer science, and philosophy to explain the mechanisms of the brain as well as levels of cognitive development that form the foundation of learning and knowledge acquisition (Picciano, 2017). As a result, cognitivism has evolved into one of the dominant learning theories. The future of cognitivism is particularly interesting as more advanced online software evolves into adaptive and personalized learning applications that seek to integrate artificial intelligence and learning analytics into instruction (Picciano, 2017).
Behaviorism led to the development of taxonomies of learning because it emphasized the study and evaluation of multiple steps in the learning process. Behaviorists repeatedly studied learning activities to deconstruct and define the elements of learning. Benjamin Bloom (1956) was among the early psychologists to establish a taxonomy of learning that related to the development of intellectual skills and to stress the importance of problem solving as a higher order skill. Bloom’s (1956) Taxonomy of educational objectives handbook: Cognitive domains remains a foundational text and essential reading within the educational community. Bloom’s taxonomy is based on six key elements (see Figure 1) as follows:
Figure 1. Bloom’s Taxonomy (Anderson and Krathwohl, 2001)
Bloom, in developing his taxonomy, essentially helped to move learning theory toward issues of cognition and developmental psychology. Twenty years later, Robert Gagne, an educational psychologist, developed another taxonomy (events of instruction) that built on Bloom’s and became the basis for cognitivist instructional design (Harasim, 2012). Gagne emphasized nine events in instruction that drive the definitions of objectives and strategies for the design of instructional material. (See Figure 2).
Figure 2. Gagne’s Nine Events of Instruction.
In future Next Step to Success blogs we will continue to discuss educational theories and models that influence the effectiveness of online education.
Anderson, L., & Krathwohl, D. (2001). A taxonomy for learning, teaching, and assessing, Abridged Edition. Boston, MA: Allyn and Bacon.
Anderson, T. (2011). The theory and practice of online learning (2nd Edition). Edmonton, AB: AU Press.
Bloom, B. (1956). Taxonomy of educational objectives handbook: Cognitive domains. New York: David McKay.
Chomsky, N. (1959). A review of B. F. Skinner’s Verbal Behavior. Language, 35(1), 26-58.
Gagné, R. M. (1977). The conditions of learning. New York: Holt, Rinehart & Winston.
Gibbons, A., & Bunderson, C. (2005). Explore, explain, design. In K. Leondard (Ed.), Encyclopedia of Social Measurement (pp. 927–938). New York, NY: Elsevier.
Graham, C. , Henrie, C. , & Gibbons, A. (2013). Developing models and theory for blended learning research. In A. Picciano, C. Dziuban, & C. Graham (Eds.), Blended learning: Research perspectives, volume 2. New York, NY: Routledge.
Harasim, L. (2012). Learning theory and online technologies. New York: Routledge/Taylor &Francis.
Picciano, A. (2017). Theories and frameworks for online education: Seeking an integrated model. Online Learning, 21(3), 166-190. doi: 10.24059/olj.v21i3.1225.
Siemens, G. (2004). Connectivism: A learning theory for the digital age. Paper retrieved from: http://www.elearnspace.org/Articles/connectivism.htm.