#1: Driscoll, M. (2005). Psychology of Learning for Instruction (3rd ed.) (pp. 71-77). Boston, MA: Allyn and Bacon.
This chapter introduces an overview of cognitive information processing (CIP). Driscoll stresses that the CIP model focuses not just on the stimuli (input) and behavior (output), but the structure of the system between them (p. 74). In other words, it elaborates on the intervening series of transformations that the information undergoes from the time it is initially received by the senses until it is indelibly coded into long term memory. This process has three main stages. The first, sensory memory, depends on input from the 5 senses and its fleeting permanence (under a second). From there, the next stage is short term memory (also called working memory). According to Driscoll, short term memory can be “likened to consciousness” (p. 75) as input in working memory is being actively thought about and focused upon. Still though, its permanence is short (under 30 seconds). The final stage is long-term memory. For information to be encoded in long term memory, the individual must encode its meaning (p. 76). Part of this encoding process includes making connections with prior knowledge already stored in long term memory. Unlike the other stages of memory, long-term memory is thought to be “never truly lost” and, Driscoll claims, has an infinite capacity for storage (p. 75). The implication for instructional design is that care must be taken to activate and build upon prior knowledge, making connections between what the learners already know and the new information they are being asked to process (p. 77).
#2: Guenther, R.K. (1998). Introduction and historical Overview. Human Cognition (pp. 1-27). Upper Saddle River, NJ: Prentice Hall.
Guenther begins by giving a historical overview cognitive theory, from its roots in supernatural beliefs, to its evolution as a natural phenomenon, and finally current status as a more scientific paradigm. Indeed, Guenther mentions how cognitive psychology grew with the more rigorous experimental design, statistics, and technologies that developed in the past 100 years (p. 10).
Guenther mentions his doubts with the current information processing model (which imagines the mind “as a machine” (p. 12). In particular he mentions that automation – in terms of automatically completing tasks while several inputs are competing for attention — is not intrinsic to computers (also they can be programmed to simulate it), nor are people capable of things such as perfect play-by-play recollections like a computer (p. 16). As he states, “human thought is not essentially the manipulation of symbols, but the contemplation of ideas” (p. 17). To support this claim, he explains the theory of neural nets (as an alternative to information processing) in which there are always-changing connections between different unit of information rather than just a series of symbols and rules being followed like a machine (p. 20).
In conclusion, Guenther stresses that while some may find cognitive science too “dehumanizing”, it actually “delights” in studying our unique cognitive abilities and how we are able to learn (p. 26). It is our self-awareness that allows us to actually exercise our own free will and make decisions, understanding it is the result of many factors (p. 26).
#3: Smith & Ragan (1999). Introduction to Instructional Design. Instructional Design (pp. 1-12). New York: Wiley.
This chapter gives an overview of instructional design as a systematic process for achieving learning goals (p. 1). As the authors state, “design is distinguished from other forms of instructional planning by the level of precision, care, and expertise that is employed in the planning, development, and evaluation process” (p. 4). The main phases are analysis, strategy, and evaluation, although the authors stress that the process is not always linear but several parts can be completed concurrently (p. 8).
The authors also touch upon the advantages and limitations of instructional design. Advantages include being learner-centered, being constantly revised and improved, and increasing coherence among goals, instruction, and assessment (p. 9). Limitations include when learning goals are not identified in advance (p. 9). Also, the authors recognize that some professionals, such as classroom teachers, may not have the time to make the commitment to following a formal instructional design process; however, they stress that teachers still utilize many elements of instructional design and can use the ideas to improve instruction (p. 10).
#4: Smith & Ragan (1999). Foundations of Instructional Design. Instructional Design (pp. 13-29). New York: Wiley.
This chapter discusses various theories that form the basis of instructional design. First, the authors describe the theories of constructivism, empiricism, and pragmatism. Constructivism assumes knowledge is constructed and thus every individual had their own, unique, constructed reality (p. 15). An implication for instructional design being that designers must increase their knowledge of the learners for designing tasks, and also taking care that assessments are more task based rather than separate activities (p. 16). Empiricism instead postulates knowledge is acquired from experience and thus “objective and singular” (p. 17). Pragmatism is the “middle ground” where knowledge comes from experience but can be interpreted through a personal lens (p. 17).
The authors briefly discuss the history of behaviorism, where “the only things worth studying are those that can be observed” (p. 19) and compare it to the information processing theory, which see “learning as a series of transformations of information through a series of postulated structures within the brain” (p. 20). The authors mention the importance of making connections so information will be more likely to be remembered. For instructional design purposes, information processing heavily informs analysis – making sure you know the learners’ prior knowledge (p. 22).
Finally, the authors touch upon some developmental theories of learning (such as Piaget and Vygotsky). They further mention Bloom’s Model of Mastery Learning, and how it follows in with the instructional designer’s goal of trying to develop instruction that ensures all learners are able to learn well (p. 25). For all instructional designers, having background knowledge on the various learning theories can help inform the instructional design process.
#5 (additional): Lessani, A., & Yunus, A. S. M. (2016). Comparison of Learning Theories in Mathematics Teaching Methods. 21st Century Academic Forum, 9(1), 165–174. Retrieved from https://www.21caf.org/uploads/1/3/5/2/13527682/14hrd-4111_lessani.pdf
I selected this article because it involved applying theories of learning to high school mathematics education. This article compared learning theories as applied to mathematics, particularly focusing on anxiety. The authors chose to focus on behaviorist, cognitive learning theory, and constructivist theories to see their influence on mathematical instruction (p. 166).
The authors describe the theories and then compare how they would inform classroom practice. A behaviorist view is more in line with lecturing and repeating low-level, easily observable problems (p. 167). A cognitive view would lend itself to more problem-solving experiences in classrooms (p. 168). Constructivism is more learner-centered, which the authors aligned with discovery learning (p. 168).
The authors performed a case study using three different teachers who utilized the three different styles of teaching the same content in their mathematics classrooms. Ultimately, the authors felt that the classrooms which utilized discovery learning and problem solving (where students were more cognitively “active” during the learning process) resulted in less anxiety amongst the students (p. 173).
Instructional Insights 