# INTRODUCTION The ***information-processing model*** is a foundational theoretical component of cognitivism. Some refer to this as *information-processing theory*, but it is not a specific theory per se; rather, it is a collection of closely related cognitive theories/models based on a common framework. This framework likens human thinking to the way computers process information, and it encompasses several aspects of cognition, including perception, memory, problem-solving, and decision-making. It describes cognition as a sequence of discrete steps: input (data acquisition), processing, and output. This theory emphasizes the ways in which information is processed through various systems of the brain, using concepts such as encoding, storage, and retrieval, which can occur sequentially or in parallel. One of the earliest information-processing models is the *[filter model of attention](https://en.wikipedia.org/wiki/Broadbent%27s_filter_model_of_attention)* (Broadbent, 1958), also known as *Broadbent’s “Y.”* Atkinson and Shiffrin (1968) later proposed a more sophisticated and dynamic model known as the *multistore model of memory*. # OVERVIEW OF THE MULTISTORE MODEL OF MEMORY The ***multistore model of human memory*** (Atkinson & Shiffrin, 1968) is the predominant information-processing framework of learning and memory. Since its introduction, psychologists have continued to research and further develop various aspects of this model (for example, Baddeley’s model \[2000\]). The multistore model is also known as the ***modal model of memory***. Incidentally, in this context, the word *modal* means that it is widely known and accepted (i.e., the “central dogma” of cognitive psychology). This model is composed of three general types of components: %% note: structure or process %% - ***Memory stores***: These are the cognitive structures that serve as repositories for information. There are different types of stores (sensory, working, and long-term) which vary in capacity (size) and duration. - ***Cognitive processes***: These are mental mechanisms that can modify and filter information as well as move information from one memory store to another. *Attention* and *perception* are two examples of cognitive processes. - ***Metacognition***: This is a higher-order cognitive mechanism (executive process) for monitoring and regulating both the storage of information and how the information is moved from one store to another. **Figure 1** *Original Version of the Multistore Model of Memory (Atkinson & Shiffrin, 1968)* ![[__/multistore_model.svg]] # MEMORY STORES ***Memory stores*** are a fundamental type of cognitive structure in the multistore model. Memory stores serve as repositories that hold information as we organize it in ways that make sense to us and store it for further use. There are three types of memory stores: ***sensory register***, ***working* *memory***, and ***long-term memory***. Keep in mind that this model, like most psychological models, is essentially a metaphor—there is not a particular “box” or single anatomical structure in the human brain that corresponds exclusively to working (short-term) memory and another that corresponds to long-term memory. These are not physical structures but rather abstractions. These abstractions allow researchers to make inferences about organizational structures and functions in the brain. **Table 1** *Overview of Memory Stores* | Type of memory store | Capacity | Duration | Form of information | Awareness | | -------------------- | ------------------- | --------------------------------- | -------------------------------------------------------- | ------------------------------------------------------------------------------- | | Sensory register | Virtually unlimited | Very short | Raw, unprocessed | Individual is unaware | | Working (short-term) | Severely limited | Relatively short unless rehearsed | In the process of being organized | Individual is actively aware (This is the conscious part of our memory system.) | | Long-term | Virtually unlimited | Durable (possibly permanent) | Schemas organized in ways that make sense to individuals | Individual is unaware | *(Borrowed from Eggen & Kauchak, 2016, p. 299)* ## Sensory Register The ***sensory register*** (or ***sensory memory***) is the information store that briefly holds incoming information from the environment in a raw, unprocessed form until that information can be meaningfully processed, interpreted, and organized. This is the fleeting, largely unconscious effect of stimuli such as a sound, a taste, or a sight. > [!example] Examples > Here are a few simple demonstrations for various parts of your sensory register: > - Look at your hand as you rapidly wave it. > - Did you see a faint “shadow” that trails behind your finger as it moved? > - The shadow is the image of your finger that has been briefly stored in your visual sensory memory. > - Press hard on your arm with your finger and then release it. > - Did the sensation of pressure remain for an instant after you stopped pressing on your arm? > - Your tactile (touch) sensory memory stored the pressure of your finger for an instant. > - Listen to someone say, “Klaatu barada nikto.” > - Can you still “hear” that phrase in your mind a few seconds later? > - When you hear someone speak the short phrase “Klaatu barada nikto,” you retain the sounds in your auditory sensory memory (even if it has no meaning for you). A basic principle in cognitive learning theories is that learning depends on experience (i.e., information input), and learners acquire these experiences through their sensory memories. Sensory memory is important as it is the beginning point for further processing. The sensory register is nearly unlimited in capacity, but it has a very limited duration. If processing does not begin almost immediately, the ***memory trace*** (the active information held in the sensory register) quickly fades away. Sensory memory retains information for about 1 second for visual information and 2 to 4 seconds for auditory. The sensory register holds information until we attach meaning to it and then transfers it to *working memory* (the next type of store in the multistore model). ## Working (Short-Term) Memory ***Working memory*** (also known as ***short-term memory*** or ***STM***) is the conscious component of our memory system (sometimes called a “workbench” because this is where thinking occurs). This store is where information is available for recall for a matter of seconds. It defines immediate consciousness. We are not aware of the contents of either of the other types of memory stores (sensory and long-term memory) until that information has been pulled into working memory for further processing. Another basic principle of cognitive learning theories is that learners are motivated to make sense of their experiences, and this is where working memory comes into play. Working memory is where we try to make sense of our experiences by linking them to what we already know. ### Baddeley’s (2000) working-memory model This concept of working memory is a theoretical area where the original Atkinson and Shiffrin (1968) model has been further developed. In 2000, British psychologist [Alan Baddeley](https://en.wikipedia.org/wiki/Alan_Baddeley) introduced a more detailed and sophisticated model of working memory: - ***Visuospatial sketchpad subsystem***: A short-term storage system for visual and spatial information. - ***Phonological loop subsystem***: A short-term storage component for words and sounds. Information can be kept in the phonological loop indefinitely through *maintenance rehearsal*, the process of repeating information over and over, either out loud or silently, without altering its form. - ***Central executive***: A supervisory system which controls and directs the flow of information to and from the other subsystems. This is the component that is most closely associated with metacognition. - ***Episodic buffer***: A subcomponent of the central executive that serves as a temporary multimodal store that combines information from the phonological loop and visuospatial sketchpad subsystems with information about time (episodes) and order to form and maintain an integrated, detailed representation of a given stimulus or event that can then be deposited into long-term memory as necessary. The visuospatial sketchpad and the phonological loop are independent subsystems, so each can perform mental work without taxing the resources of the other. ### Limitations of working memory It is not a coincidence that in the diagram of the multistore model (Figure 1), working memory is depicted as smaller than either sensory register or long-term memory. The phenomenon known as ***memory overload*** is a direct result of the severe limitations of working memory. The capacity of the phonological loop is about as much information as we can say to ourselves in roughly 2 seconds, and the duration of the visual-spatial sketchpad is very limited. Early research suggested that adult working memories can hold about seven items (“bits”) of information at a time and can hold the items for only about 10 to 20 seconds (Miller, 1956). The working memories of children are even more limited. Selecting and organizing information also uses working memory resources. Such limitations have important implications for different types of students, for instance... - Researchers have found that learners with attention-deficit/hyperactivity disorder (ADHD) rehearse verbal and spatial information as effectively as other children, but their central executive is impaired (Karatekin, 2004). So, students with ADHD often have trouble controlling their attention and selecting effective learning strategies. - Learners with reading disabilities have impaired functioning of the phonological loop (Kibby, Marks, & Morgan, 2004). Hence, students with reading difficulties have trouble processing verbal information. The limited capacity of working memory is arguably its most important feature, because working memory is where we make sense of our experiences and construct our knowledge (Clark & Mayer, 2003). Consider the implications of this limitation: The most important cognitive process in learning—the construction of meaningful knowledge—takes place in the component of our memory system that is the most limited. So, it is not surprising that students are frequently confused, miss important information, and construct misconceptions. The limitation of working memory is often discussed in terms of ***cognitive load theory*** (Sweller, 1988). The concept of ***cognitive load*** refers to the amount of cognitive resources (mental activity) necessary to complete a task. Cognitive load is dependent upon two factors—the number of elements (discrete pieces of information) and the complexity of those elements: - The number of elements requiring attention > [!example] > Try to remember a sequence of digits like `7 9 5 3` versus a sequence like `3 9 2 4 6 7 8`. The second sequence imposes a heavier cognitive load than the first simply because there are more numbers in the list. - The complexity of the elements > [!example] > Attempting to create a well-organized essay, while at the same time thinking about where to place their fingers on a keyboard, or use correct grammar, punctuation, and spelling, is a complex task that imposes a heavy cognitive load on young writers. The effects of this limitation are common in the classroom. For instance... - Students write better essays using computers or word processors if their keyboarding skills are well developed. If not, handwritten essays are better. - Students’ writing often improves more rapidly if they are initially allowed to ignore grammar, punctuation, and spelling. These and many other examples can be explained using the concept of cognitive load. There are various strategies for reducing cognitive load and accommodating the limitations of working memory: - Developing automaticity - Using distributed processing - Chunking ## Long-Term Memory (LTM) Recall that the multistage model of memory has three major structural components: the sensory register, working (short-term) memory, and long-term memory. Knowledge (which is broadly the information that we know and understand) that learners construct depends on what they already know is another principle of cognitive learning theory, and this is where long-term memory (our permanent information store) comes into play. Knowledge is stored in ***long-term memory*** (***LTM***), and being able to access this knowledge plays a powerful role in subsequent learning. Basic features of human LTM: - The capacity of long-term memory is extensive (possibly limitless). - The duration of long-term memory is very durable; in fact, some research suggests that information stored in LTM is permanent. - Long-term memory contains three kinds of knowledge/information: ***declarative***, ***procedural***, and ***conditional***. **Figure 1** *Hierarchy of the various types of long-term memory*  ### Declarative knowledge ***Declarative knowledge*** is knowledge of facts, concepts, procedures, and rules, often described as knowing “what.” There are two distinct types of declarative knowledge: - ***Semantic memory***: Memory for concepts, ideas, principles, definitions, and the relationships among these pieces of information. - ***Episodic memory***: Memory for our personal and affective (emotional) experiences. Although the lines between episodic and semantic memory are often blurred, there is an important distinction between semantic and episodic memory: When people have strong emotional reactions to an event, episodic memories are enduring. They are stored in your episodic memory and highlighted by emotions. We can capitalize on episodic memory when we teach by personalizing content or teaching it, when possible, in a way that has an emotional impact on our students. > [!example] > - The definitions of literary concepts such as “figurative language,” “simile,” and “metaphor” stored in a person’s long-term memory are all forms of declarative knowledge (stored in semantic memory). > - Say you hear a student say the following: “My English teacher last year loved this stuff, and she was always making up metaphor and simile examples. We did it all year, and she even used examples in history and science and everything.” This information would be stored in that student’s episodic memory. > - Those of us who are older have episodic memories of exactly where we were and what we were doing when we received word of the infamous terrorist attacks of 9/11. Declarative knowledge is ***explicit***—that is, we are aware of what we know. Such awareness can be derived by a person’s actions and behaviors (i.e., there can be empirical evidence of such knowledge). > [!example] > If a student were to write, “Summer was a thousand colors in a parched landscape,” this would demonstrate that the student understood the concept of a metaphor, and they were also aware of their understanding (hence, explicit). **The structure of declarative knowledge in LTM** There are a few different theories about how declarative memory is organized and structured. - **Schema theory (Anderson & Bower, 1973)** - A ***schema*** (plural: ***schemas*** or ***schemata***) is a type of cognitive structure that represents the way logically related pieces of declarative information are stored and organized in long-term memory. These are personal cognitive frameworks that helps individuals organize and interpret information in their environment. Schemas are mental representations of declarative knowledge, which can be used to guide perception, interpretation, expectations, and other types memory (such as working memory). - Schemas can be based on personal experiences, cultural background, and other factors. For example, someone might have a schema for a “restaurant” that includes information about what a restaurant typically looks like, what kinds of food are served there, and what the typical dining experience is like. - Acquiring declarative knowledge is a form of learning that involves integrating new information with existing knowledge. The content and organization of that existing knowledge is represented as schemas. - Schemas are idiosyncratic to the person who constructs them. They may not be meaningful to others, but they are meaningful to the individuals who constructed them. The same thing occurs in classrooms when our students construct schemas that make sense to them, but not necessarily to the instructor. > [!example] > The following diagram (Figure 2) depicts simple hypothetical schemas for the concepts “Bison” and “Plains Indians.” Note the additional structures (dashed lines) that connect related elements across the two schemas. > > **Figure 2** > *Example Schematas* > ![[__/schemata.svg]] - ***Scripts*** (also known as ***script schemas***) are specialized schemas for events and actions. A script is essentially a mental “road map” which contains the basic actions (and their temporal and causal relations) that comprise a complex action. These are a special type of schema that specifically relate to sequences of events or actions that are commonly encountered in everyday life. A script is a mental representation of a typical sequence of events or actions that an individual might expect to encounter in a particular situation. - These schemas are often organized with a definite order (sequence of steps). In this regard, scripts also contain *procedural knowledge* (which is described in the next section). > [!example] Examples > - You likely have a script for going to a movie theater that includes information about buying tickets, getting popcorn, finding a seat, and watching the movie. > - You have a script that guides your actions as you prepare for, attend, and participate in your classes. > - You probably have a script for how you drive a vehicle: Get in, buckle the seat belt, put key in the ignition, start the car, turn on the radio, check the rearview mirrors, and so on. - The main difference between schema and scripts is that schema are broader and more general mental frameworks that can apply to a wide range of situations, whereas scripts are more specific and apply to particular sequences of events or actions. - **Network theory (Anderson, 1983)** - ***Network theory*** deals with a type of cognitive structure known as a ***semantic network*** (also known as a ***propositional network*** or ***concept map***). This theory suggests that declarative information is organized semantically—that is, information is encoded in relation to the general meaning (or meanings) of other pieces of information. - Each distinct piece of information or semantic meaning in a network is known as a ***node***. The nodes in network theory are somewhat similar to the concept of schemas, but schemas are organized and interconnected according to immediately relevant characteristics in a specific context. In contrast, semantic networks are organized in a much more general fashion according to a potentially broad spectrum of meanings attached to any given node. - In such a network, seemingly unrelated concepts can be connected through the process of ***spreading activation*** (a memory process in which accessing one concept node can lead to activation of other related concept nodes). > [!example] > The following diagram (Figure 3) shows a small part of a larger semantic network. This illustrates how two seemingly unrelated concepts—such as “fire engine” and “sunrises”—can be connected within a network of information through a process of spreading activation. > > **Figure 3** > *An Example of a Semantic Network* > ![[__/network_theory.jpg]] - **Dual-coding theory (Clark & Paivio, 1991)** - A theory of long-term memory suggesting that we remember information better if we encode the information both verbally and visually. ### Procedural knowledge ***Procedural knowledge*** (also known as ***self-regulatory knowledge***) is knowledge of how to perform tasks (such as solving problems, composing essays, playing a musical instrument, executing physical skills, and teaching). In other words, procedural knowledge is knowing how to manage your learning, or knowing how and when to use your declarative and procedural knowledge. Procedural knowledge operates, in part, on declarative knowledge. > [!example] Examples > - Consider the following arithmetic problem: $\frac{1}{4} + \frac{2}{3}$. Knowing that we must find a common denominator before we can add the fractions is a form of declarative knowledge. When we actually go about finding the common denominator and then adding the fractions requires procedural knowledge. > - To compose an essay or other form of writing, for instance, we must know grammar, punctuation, and spelling rules, all forms of declarative knowledge, but actually composing the essay represents procedural knowledge. A goal in developing procedural knowledge is to reach ***automaticity***, which typically requires a great deal of time and effort. - This is true for acquiring all forms of procedural knowledge. - Examples: Becoming a good writer, playing a musical instrument well, executing an accurate field-goal kick in football. - This suggests that we need to provide students with ample opportunities to practice. When we help our students develop their procedural knowledge, the ***learning context*** is important (this also relates to *conditional knowledge*, which is a topic covered later in this chapter). > [!example] Examples > - Students should practice their grammar, spelling, and punctuation in the context of their writing, rather than on isolated sentences. > - Math students should develop their skills in the context of word problems that require a variety of operations. > - We must learn to drive a car in different contexts to ensure that our procedural knowledge transfers to different driving conditions (e.g., dry vs. vs. rain vs. snow). > - Athletes must perform their skills in the context of competition. In contrast to declarative knowledge, procedural knowledge is *implicit* (often cannot directly or actively recall or explain). > [!example] > When we become skilled at typing on a standard (QWERTY) keyboard, we are not able to explain what we are doing as we type. We may not even be able to describe where the keys are located on the keyboard. ### Conditional knowledge ***Conditional knowledge*** is knowledge of where and when to use declarative and procedural knowledge. > [!example] Examples > - Consider the following two arithmetic problems involving the addition of fractions: $\frac{1}{4} + \frac{2}{3}$ and $\frac{2}{7} + \frac{4}{7}$. Recognizing that we must find a common denominator in the first problem but that we do not need to do this in the second problem represents conditional knowledge. > - Recognizing that we place an apostrophe before the “s” in the sentence “Both of the boy’s shoes got muddy when he ran outside in the rain,” but after the “s” in the sentence “The boys’ shoes got muddy because they all ran outside in the rain,” requires conditional knowledge. Like procedural knowledge, conditional knowledge is *implicit*, and it is highly dependent upon context. When students write in a variety of content areas, or solve a variety of word problems, they acquire the practice that will help them identify different conditions and the actions they should take based on those conditions.