Cog Sci 1 + Ed Tech (Spring 2014)
Weekly Annotations
January 27, 2013 (#1)
Foundation and Assumptions of Cognitive Science
Overview of Information Cognitive Processing
Human Cognition
Introduction to Instructional Design
Foundations of Instructional Design
February 3, 2014 (#2)
Human Cognitive Architecture: Biological Bases of Learning and Memory; Sensory, Short-Term, Working Memory Models
Information Processing
Biological Basis of Learning and Memory
Schema Acquisition and Sources of Cognitive Load.
Working Memory
The Role of Questions in Learning (Optional)
February 11, 2013 (#3)
Human Cognitive Architecture: Long-term Memory Models, Dual Coding Theory
For Whom a Picture is Worth a Thousand Words? Extensions of Dual-Coding Theory of Multimedia Learning
Long-term Memory
Return of the mental image: Are there really pictures in the brain?
February 18 (#4)
Meaningful Learning, Schema Theory, Situated Cognition
Meaningful Learning
Situated Cognition
Cognition in the Wild (Optional)
February 25, 2014 (#5)
Cognitive Load Theory
Implications of Cognitive Load Theory for Multimedia Learning
The Split-Attention Principle in Multimedia Learning
The Redundancy Principle in Multimedia Learning
Cognitive Load Theory, Learning Difficulty, and Instructional Design
Direct Measurement of Cognitive Load in Multimedia Learning (Optional)
March 4, 2014 (#6)
Cognitive Theory of Multimedia Learning; Integrated Model of Picture & Text Comprehension
Introduction to Multimedia Learning (Chapter 1)
Cognitive Theory of Multimedia Learning (Chapter 3)
An Integrated Model of Text and Picture Comprehension (Chapter 4)
Animations Need Narrations: An Experimental Test of a Dual-coding Hypothesis (Optional)
March 10, 2014 (#7)
Individual Learner Characteristics, Expertise Reversal
Individual Differences and Cognitive Load
Prior Knowledge Principle in Multimedia Learning
Learning Styles: Concepts and Evidence
Analyzing the Learning Task (Optional)
March 24, 2014 (#8)
Managing essential processing in Multimedia Learning
Principles for Managing Essential Processing in Multimedia Learning: Segmenting, Pretraining, and Modality Principles (Chapter 11)
Techniques in Generative Processing in Multimedia Learning: Open Questions for Cognitive-Load Research (Chapter 8)
Ausubel's Meaningful Reception Learning Theory
In Defense of Advance Organizers: A Reply to Critics (Optional)
March 31, 2014 (#9)
Reducing Extraneous Processing in Multimedia Learning
Modality Principle
Worked-Out Examples Principle
Structuring the Transition From Example Study to Problem Solving in Cognitive Skill Acquisition: A Cognitive Load Perspective (Optional)
April 7, 2013 (#10)
Control, Interactivity, and Feedback
Multimedia Learning in Games, Simulations, and Microworlds
Interactivity in Multimedia Learning: An integrated Model
Role of Guidance, Reflection, and Interactivity in an Agent-Based Multimedia Game
Enhancing Instructional Efficiency of Interactive E-learning Environments: A Cognitive Load Perspective (Optional)
April 14, 2014 (#11)
Affect–Motivation, Self-Regulation, and Emotion
Motivation and Self-Regulation in Learning
The Broaden-and-Build-Theory of Positive Emotions
Emotional Design in Multimedia Learning
Social Cues in Multimedia Learning, Role of Speaker’s Voice (Optional)
April 21, 2014 (#12)
Learning from Animations, Simulations, and Games
Multimedia Learning in Games, Simulations, and Microworlds
Multimedia Learning in Virtual Reality
Design Factors for Educationally Effective Animations and Simulations
Design Factors for Effective Science Simulations: Representation of Information
Instructional Animation Versus Static Pictures: A Meta- Analysis
April 28, 2014
Cognitive Development: Stages of Development (Piaget), Interactionist Theories (Bruner, Vygotsky)
Cognitive and Knowledge Development
Interactional Theories of Cognitive Development
January 27, 2013 (#1)
Foundation and Assumptions of Cognitive Science
Overview of Information Cognitive Processing
Driscoll, M. (2005). Psychology of Learning for Instruction (3rd ed.). Boston, MA: Allyn and Bacon. [pp.
71-77]
The states of the information processing system are sensory memory, working memory, and long-term memory. Information is received through sensory input either visually or audibly. It is held long enough to process for the working memory. The working memory prepares information for storage or response, and has limited capacity. The long-term memory is represents permanent knowledge - anything that is processed through the first two stages successfully. This is not necessarily a linear process as depicted in the books diagram. There is often information being pulled from the long-term memory to assist with input and transference from the intake of information through other processes.
Human Cognition
Guenther, R.K. (1998). Human Cognition. Upper Saddle River, NJ: Prentice Hall. [ Chapter 1 ]
What is the history of human cognition through the ages? This article, according to Guenther (1998), presents an overview of perspectives on the human mind since our cosmology. Several key points that Gunther (1998) summarizes follow. First, human mental processes are governed by behavior, similar to biological world. Second, neuropsychological processes may account for our mental functions. Third, dualism separates the mind and brain, but neuroscience sees the mind as part of the physical universe. Therefore, only physical things ignite mental processes. Fourth, the mind is likened to a computer, which is misleading based on current mental models. Fifth, cognitive psychologist espouse cognitive development rather than materialism. Sixth, Cognitive development might be an impetus for technological and social development. Gunther (1998) goes also suggests that cognitive science is now underlying machine intelligence and it verifies that in our intuition we are free - that our thought process is not predetermined. In other words, our thought can be affected by what we know, learn, and how we integrate that information.
Introduction to Instructional Design
Smith & Ragan (1999).Instructional Design. New York: Wiley. [ Chapter 1]
“Instructional design refers to the systematic and reflective process of translating principles of learning and instruction into plans for instructional materials, activities, information, resources, and evaluation” (Smith & Ragan, 1999). Instruction is the facilitation of instruction towards goals. There are different types teaching, including education (broad learning for all), training (skills oriented), teaching (education facilitated by a person), and instruction (subset of education). This text is focused on instruction.
Design is defined as “a systematic or intensive planning and ideation process prior to the development of something of the execution of some plan in order to solve a problem” (Smith & Ragan, 2009). Design is typically a goal driven process, that involves multiple perspectives and expertise. The instructional design process is oriented towards measuring its success against the goals of the instruction. In other words, how well did learning occur as expected. The ID process has three main components: Analysis, strategy, and evaluation. It is a very iterative process with many interlinking parts.
Foundations of Instructional Design
Smith & Ragan (1999).Instructional Design. New York: Wiley. [ Chapters 2 ]
Foundations of instructional design provides a theoretical framework for instructional design that includes constructivism, empiricism, and pragmatism. Constructivism is emphasized with a focus on individual versus social constructivism. In constructivism knowledge is constructed rather than discovered. The assumptions of constructivism from an individual perspective are: knowledge is constructed from experience, learning results from a personal interpretation of knowledge, and learning is an active process in which meaning is developed on the basis of experience. Social Constructivism adds that learning is collaborative with meaning negotiated from multiple perspectives. Contextualism is another component of constructivism, which assumes learning should be situated, and testing integrated into the task. On the contrary, there is empiricism, which states that knowledge is gained through experience in the world. In the middle are pragmatist who believe learning is a matter of common interpretation of expert opinion (i.e. everything is a rational approach).
Some of the assumptions underlying instructional design include: having a clear goal of what instruction will provide for learners (i.e. learning outcomes), designing for efficiency, effectiveness, and appeal, learning may occur in many forms, principles apply across age groups, evaluation must include information about the learner and the instructor, and assessment should be based on individual learner performance; not in comparison to others, and there should be congruence amongst learning goals, objectives and assessments.
Although behaviorism influenced learning theories, the cognitive learning theories are emphasized in this chapter. Especially, the information processing model of learning and memory. Developmental theories such as Piaget's “ages and stages”, and Vygotsky are incorporated too. Lastly, instructional theories are discussed, which focus on characteristics of instruction that will support learning, rather than developmental processes or how learning occurs.
This information is relevant for instructional designers, because instructional learning is universal. The philosophies and theories discussed in this chapter provide perspectives to consider when designing instruction for different audiences.
February 3, 2014 (#2)
Human Cognitive Architecture: Biological Bases of Learning and Memory; Sensory, Short-Term, Working Memory Models
Information Processing
Driscoll, M. (2005). Psychology of Learning for Instruction (3rd ed.). Boston, MA: Allyn and Bacon. [ pp.
77-91]
One of the main points of this section is that sensory memory is temporary, although a great deal of information registers visually and with the auditory system. This was identified through a partial reporting technique, research using tones to indicate which content (i.e row of letters) study participants were to report on. The partial reporting technique helped identify the importance of attention in information processing. Further research solidified that attention isn’t singular or black or white. Rather, “researchers have come to view attention as a resource with limited capacity to be allocated and shared among competitive goals” (Driscoll, 2005). This implies that learners attention is selective, but some tasks require little effort, and attention might also be habitual. Thus, two concepts arise related to attention: selectivity and automaticity.
Selectivity is defined by Driscoll as the learner’s ability to select and process certain information while simultaneously ignoring other information. The criteria for selective attention include meaning, similarity between competing tasks, task complexity or difficulty, and the ability of the learner to control attention. Driscoll points out that if attention is selective, than managing attention in an instructional situation requires a strategy. For example, using standard signals in a classroom, or stimulus features such as voice inflection, tone, and novelty.
Automaticity, on the other hand is when attention becomes automatic because the task is overlearned or sources of information are habitual (i.e. driving a car). The criteria of automaticity include skills such as decoding, which is discussed in the context of reading. Decoding assumes that a reader's ability to decode works is so automatic, they can focus on extracting other meaning from content based on their goal for reading. There is also pattern recognition and perception, which Driscoll defines as the process whereby environmental stimuli are recognized as exemplars of concepts and principles already in memory.
There are several different models of pattern recognition, including template matching, prototyping, and feature analysis. Prototyping and feature analysis are supported by research. Together, the implication for pedagogy is concept learning, which “calls for presenting, first, a best or prototypic concept example followed by a variety of examples that differ from the prototype in systematic ways. The examples help learners to abstract meaningful dimensions of the concept and determine which feature s are critical and invariant and which are non essential and variable across examples” (Driscoll, 2005).
Lastly, for pattern recognition that’s not explained by the above, it relies on principles of organization, context, and past experience. In terms of learning pattern recognition means providing examples, and being mindful of teachers expectations of students based on experience is helpful.
Although sensory memory is important for attention, it is part of the story because it remains temporary. Therefore, It is important to consider how information that is temporary becomes stored. “At this stage, concepts from long-term memory will be activated for use in making sense of the incoming information” (Driscoll, 2005). Working memory, although with limited capacity plays a part. The question becomes how to increase the capacity of working memory to hold more information. This can be done through chunking. That is taking smaller parts of information and breaking them into larger bits, or chunks. (i.e. a string of letters vs. sets of letters). Chunking is one component, but information in working memory can be lost very quickly (within 30 seconds). There are two processes to help transfer information from working memory to long-term memory. They are rehearsal and encoding.
Rehearsal is repetition of information (i.e. memorizing a phone number). Encoding “refers to the process of relating incoming information to concepts already in memory in such away that the new material is more memorable” (Driscoll, 2005).
Biological Basis of Learning and Memory
Driscoll, M. (2005). Psychology of Learning for Instruction (3rd ed.). Boston, MA: Allyn and Bacon.
[chapter 8 ]
This chapter is rather complex and reviews how biological research relates to cognition. The two major lines related to biological research are genetic inheritance and brain physiology. I think the main ideas of this chapter are:
●Evolutionary psychology rest on the assumption that the psychology of behavior is well informed by evolutionary biology.
●Evolved psychological mechanisms of the human mind are adapted to an ancient way of life, not to conditions present in the modern world.
●Evolutionary adaptations are both functional and specific.
●An evolutionary view of learning and behavior in effecting integrates common notions of instinctive vs. learnedbehaviour.
●Human information processing mechanisms may have evolved to reflect the types of problems faced by early humans and their ancestral environment.
●What is learned and exhibited depends on genetic history.
●Evolutionary psychologist might say that learning should be more group oriented to play to the environmental factors of our ancestors, that is still present in our psychology today.
● Learning is distributed throughout the brain, with some localization related to memory, presentation, and representation.
● Attention involves selectivity.
○Controlling Attentional States
○Selectively Allocating Attentional Resources
○Selectively Organizing Attention
●Attention is not a unitary concept. Multiple techniques are necessary to get learners attention.
●The types of memory systems are procedural, perceptual representation, semantic, primary and episodic.
●Four conceptual models of the diversity of neuroscience research related to development are:
○Fixed circuitry and critical periods
■The brain develops in a very specific and routine way, very quickly. Damage to the brain can occur easily during the critical period of development, which impacts learning.
○Plasticity
■There are parts of the brain that change over its lifespan.
●Change is introduced by experience.
■Older learners are capable of learning new things through their lives, but doing so in a flexible manner is somewhat more difficult than it is for younger learners.
○Modularity
■Memory in terms of modules.
■Cognitive development proceeds independently in at least even relatively autonomous domains (i.e language, music, logical-mathematical reasoning, spatial processing, bodily-kinesthetic activity, interpersonal knowledge, and intrapersonal knowledge).
■These domains are activated in context.
●Implications of Neurophysiology for learning and instruction
○Cognitive Functions are differentiated.
○The brain is relatively plastic in nature.
○Language may be biologically preprogrammed.
○Learning disorders may have a neurobiological basis.
Schema Acquisition and Sources of Cognitive Load.
Kalyuga, S. (2010). Schema Acquisition and Sources of Cognitive Load. In J.L. Plass, R. Moreno, & R.
Brünken, Cognitive Load Theory, New York: Cambridge. [chapter 3]
The chapter discusses sources of cognitive load in instruction, in which cognitive load is defined by the activity-based demands on working memory during goal-based learning. The chapter begins with an explanation of schematic knowledge structures. Schemas, according to Kalyuga, “represent knowledge as stable patterns of relationships between elements describing some classes of structures that are abstracted from specific instances and used to categorize such instances” (Kalyuga, 2010). In other words, a schema is a unit of memory that helps us acquire and store knowledge to move around the limitations of working memory.
The concept of schemas and circumventing working memory is paramount to the chapter, which largely focuses on extraneous cognitive load, sources of extraneous cognitive load, and how to reduce it as a result of learning as schema acquisition. In other words, “from a cognitive load perspective, the major goal of learning is the acquisition and automation of schematic knowledge structures in long-term memory” (Kalyuga, 2010). Therefore, the organization and presentation or learning tasks is essential and must pay attention limitations of the human cognitive processing system. Principally, “CLT assumes that a proper allocation of cognitive resources is critical to learning” (Kalyuga, 2010). Thus, reducing or eliminating extraneous load is important for balancing the cognitive process, schema acquisition, and effective learning.
Extraneous cognitive load is a diversion of resources for activities related to the learning task.
Extraneous load results from “insufficient learning knowledge base or instructional guidance, an overlapping knowledge base and instructional guidance, excessive step-size of changes in the knowledge base, or interrelated instructional representations that are separated in space and/or time” (Kalyuga, 2010). To reduce or mitigate these misplaced cognitive resources a set of general guidelines were recommended, including providing examples, adapting to changing levels of learners expertise, and scaffolding knowledge base change.
Working Memory
Baddeley, A.D. (1992). Working memory. Science, 255, 556-559.
This article discusses working memory, which “refers to the brain system that provides temporary storage and manipulation of the information necessary for such complex cognitive tasks as language comprehension, learning, and reasoning” (Baddeley, 1992). The key point in this definition is that working memory is not permanent, and it is task oriented and specific.
The second main point of the article is the distinction between working memory as a single unitary function, or multi-pronged system. There is research in both North America and Europe exploring both approaches, and the deficits. On one, hand is working memory as concurrent or combined storage and information processing. On the other hand, is working memory as a dual-task methodology. However, Baddeley, proposes a tripartite system that is comprised of three components of memory, the Central Executive, supported by the Visuospatial sketchpad (i.e. imagery), and the Phonological loop (i.e. speech based patterns). Baddeley’ssystem “suggest that the coordination of resources is the prime function of working memory” (Baddeley, 1992). In other words, the Central Executive coordinates the slave systems.