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Tompkins Cortland Community College

Model A Model for the Creation of
Meaningful Community College Learning Experiences

Construction of individual meaning is improved when students make connections.


What we know:

We know that students who can relate new learning to what they already know (and to what they are learning in other courses) retain information more easily and can apply what they have learned in new situations. Helping students make connections improves their learning. The more they learn, the more they CAN learn. A quick look at enrichment curricula designed for gifted students reveals that teachers already know the importance of making connections. Why not use what teachers of gifted children know in all of our classrooms? Learning can be improved for all of our students if we understand the importance of making connections.

The support for what we know:

Connecting new learning to prior experience/learning (inside and outside of the academic classroom) and to future learning/application helps students use neural pathways already in place and to build new neural networks to help with future learning. Examining how the brain processes information (retention, retrieval, transfer) and the ability of the brain to make new neural connections (neuroplasticity) will help us understand how to help our students develop their ability to make connections.

Taking in and storing the "learning"

As we discuss in our "Creating a Learning-Centered Environment" section, the emotions are critical to how the brain processes information. The hippocampus, thalamus, and amygdala are parts of the limbic system essential to the formation of memories. The thalamus and part of the brain stem called the reticular activation system screen sensory information as it comes in. The information is checked for survival content. The individual's past experiences are important here, as the brain tries to determine the data's degree of importance. Researchers believe that the amygdala, because it's close to the hippocampus and because of its activity on PET scans, tags memories with an emotional message (if an emotion was present) when a memory is prepared for long-term storage. Researchers aren't sure if emotional memories are actually stored in the amygdala. It's possible that the emotional content of the memory is stored in the amygdala while the other components of the memory are stored elsewhere in the brain. (Memories are stored in pieces in different neural networks, in different areas of the brain; when we retrieve a memory we must retrieve pieces from various areas of the brain and put the memory back together.) The emotional component of a memory is then recalled when the rest of the memory is recalled. Emotion is tied directly to the formation, storage, and retrieval of memory as well as the construction of meaning. If a strong emotion is connected to an experience, chemicals in the brain code the experience as one that's important and should, therefore, be remembered. Retention is improved if we add emotional elements to the learning experiences we create for our students (Sousa, 2001; Wolf & Brandt, 1998). We've discussed the role of the emotions in the brain's processing of information in the "Creating a Learning-Centered Environment" section of our model. To read more about the relationship between emotion and learning in the community college setting, click here.)

The thalamus, as mentioned above, screens incoming information for survival/emotion first, and checks for past experience to determine importance, to figure out what to send to long-term storage. Absent emotional content/survival concerns, learning is more like likely to be put into long-term storage (and to be retrieved easily and accurately later) if it makes sense (fits into the student's sense of how the world works) and has meaning (it is personally relevant to the learner - connected to past experience).


Learning and retention are different. Learning does not always involve long-term retention. For example, we might learn something in a math class (like how to add fractions) but not retain the learning. Sousa (2001) says that for retention to happen, the learner must "not only give conscious attention but also build conceptual frameworks that have sense and meaning for eventual consolidation into the long-term storage networks" (p. 84). If a learner has retained a memory, the learner can locate it, identify it, and retrieve it accurately in the future. The time a learner takes to process and reprocess, and to assign meaning to a learning, is called rehearsal. Rote rehearsal would be something like remembering a poem or phone number. Elaborative rehearsal, which is much more complex, would be associating new learnings with prior learnings to discover relationships. Adequate rehearsal makes it more likely that a learning will go to long-term storage, but doesn't guarantee it. It's clear, if we think about this, that providing students opportunities to connect new learning to prior learning may increase the likelihood that what they are learning will both go to long-term storage and can be easily and accurately retrieved in the future.

There are two types of retrieval - recognition and recall. Recognition retrieval happens when a learner pulls information out of storage by matching it to an outside stimulus. This happens on multiple choice tests. Recall is much more challenging than recognition. With recall, hints are sent to long-term memory. The long-term memory must search long-term memory storage sites to find information, consolidate it, and retrieve it back into working memory. Both processes require the firing of neural pathways, and the more often specific pathways are fired, the more unlikely the retrieval will be interfered with by other pathways. Your phone number is easy to remember, for example, because you have to remember it often (p. 106-107). One of the factors affecting the efficiency of retrieval is the context of the retrieval. Context, in this case, includes physical context. For example, if we test students in the same location in which they learned the material, they are more likely to be able to retrieve what they have learned. If this isn't possible, visualization can help (i.e. students in the exam room visualize where they were when they learned the material, and this helps them with recall.) It's sort of like when you lose your keys, and you "backtrack" to everywhere you were to find them. Students "walk back" through the course material by visualizing where they were when they learned the material.

We've already mentioned that memories are not stored in one piece. How does the brain organize the bits and pieces that need to be retrieved to create a memory? Research conducted by O'Keefe and Nadel using rats in 1978 suggests that the brain has two methods, or systems, for organizing memories. Renate and Geoffrey Caine (1994) describe this research and relate it to classroom learning in their book Making Connections. The first type of memory system described by the Caines, taxon memory, involves memories that do not depend on a physical context such as contents of categories (i.e. types of trees in the category "trees"). This type of memory must be rehearsed. It's represented by the "information processing model of memory...of all the signals that reach our sensory register, we focus on a few that seem important (normal capacity is about seven "chunks" of information) (Caine & Caine, 1994). If these chunks of information are rehearsed well enough they will get moved into long-term memory. An example would be memorizing a phone number. This type of learning/memory is resistant to change and not necessarily meaningful. However, it can often be retrieved (if sent to long-term storage), fairly easily on demand even in unrelated contexts. This type of memory is also like habits - resistant to change. Therefore, the retrieval and application of this type of learning/memory in a new context is not automatic. For example, we might memorize French word lists and often-used phrases perfectly before traveling to Paris, only to discover that what we have memorized is completely useless once we are in a complex experience such as finding a restaurant and ordering dinner.

The second type of memory system described by the Caines (again, their discussion of types of memory is based in part on work by O'Keefe and Nadel), is locale memory (locations and interconnected events). To understand locale memory, we must first acknowledge that we exist in physical space. Howard Gardner (1983) shares a funny story about Saul Kripke (a contemporary American philosopher), that illustrates this concept:

At age three, young Saul went to see his mother in the kitchen and asked her if God were truly everywhere. Receiving an affirmative answer, he then asked whether he had squeezed part of God out of the kitchen by coming in and taking out some of the space. Befitting a mathematical prodigy, Kripke went forth quickly on his own and had reached the level of algebra by the time he was in fourth grade. (p.153)

We "take up" space and our "location" in space affects our comprehension. We form mental "maps" of what we do, whether it's reading through the newspaper, going grocery shopping, or traveling through Europe by rail. Furthermore, we navigate through space by "creating and testing spatial maps that give us information about our surroundings" (Caine & Caine, 1994, p. 45). These spatial maps help us create meaning. For example, as college instructors, we can find our way around a new college campus (as well as academic policies and procedures) by altering the memory map we already have of our own college campus. We know there will be classrooms, labs, faculty office, an academic counseling center, administrative offices, a library, and so on. We use our existing map to create a new map. Think, for a moment, about how this relates to our community college students, many of whom are the first in their families to attend college. We often complain about how students don't have any idea about how to navigate in the academic environment (visiting advisors, signing up for classes, using the library, etc.). Without a mental map of the academic "terrain," how can they? Again, most of us, as instructors, could move comfortably to another academic institution and find our way around (both the physical campus and policies/procedures) fairly easily. This suggests, of course, that helping students relate the academic environment to a similar "map" would be extremely helpful). Locale memory is unlimited, survival oriented, and never limited to context-free facts. Let's return for a moment to our example of traveling to Paris. If we had studied in a way that took advantage of locale memory, we'd probably have much better success finding the restaurant and ordering dinner (i.e. if we learned basic conversational French by immersion, by role-playing, by "navigating" in a challenging, meaningful context).

Locale memory maps form quickly and are easily modified. They're enhanced by sensory experiences (this ties again to our "Creating a Learning-centered Environment" section). Novelty, curiosity, and learner expectations affect our creation of maps. The development of intricate maps takes time and experience. As the Caines point out, locale memory is "not adequately represented by the information-processing model of memory". With our locale memory system, we automatically form long-term memories, so why not use this power? As the Caines state, "it is in the recognition and use of the power of our locale memory that we begin to give credibility to the complex forms of instruction that are needed to upgrade education" (p. 45-46).

The locale memory system and the taxon memory system interact. It's not that one is better than the other when it comes to teaching and learning. Rather, understanding how they interact can help us improve learning. The Caines explain the interaction of the systems like this: "The locale system registers a continuous 'story' of life experience. The taxon systems house the 'parts' out of which the story is constructed. Returning to our Paris example once again, memorizing the words and phrases is necessary, but memorizing them as part of a locale system "story" creates meaning. In order to use the "parts" made available by taxon memory, the locale memory system needs a powerful indexing ability. This indexing ability is improved as the strength and complexity of connections, or paths (neural networks) grow. So, again, the more we learn, the more we can learn. The Caines use metaphors that will help explain what we've just discussed. They suggest that we think of taxon memory as "following a route" and locale memory as "establishing a dynamic map" (p. 47-48).

Next, the Caines use this example to clarify the difference between the two types of learning: Imagine you and your colleagues are going to a conference in a city you've never visited before. You want to go to a good restaurant someone told you about, and so you ask directions for the quickest route to the particular restaurant. Following the route carefully, you arrive at the restaurant without incident. However, because you were paying such close attention to the route (to avoid making a wrong turn and getting lost), you probably didn't get to see much of the city. And, if you DID make a wrong turn, you'd probably get lost unless you could, somehow, retrace your steps and get back on the route. Now, let's think about what might happen if you had more time and could develop a mental "map" of the city. Supposing you had ventured out, exploring a little each day, discovering the layout of city, noticing landmarks of interest that you'd like to visit, and so on. This locale map, developed by interest (a key point) and by personal experience, and by exploration, would probably "stick with you" and could be retrieved fairly easily on your next trip to the city. And, although you might still ask for directions to the restaurant in question, if you made a wrong turn, you probably wouldn't get lost because you'd have an overall sense of the organization of the city (at least the part of the city you had explored).

Let's embellish the Caine's example a bit. Suppose Instructor A and Instructor B attended the conference together. Instructor A has traveled extensively and driven in large cities around the world. Instructor B has driven only in the country and a few mid-sized cities. Which instructor should drive? Of course, Instructor A would be my choice because even if she had NEVER VISITED the conference city, she'd have memory "maps" at her fingertips, so to speak, that would make her the safer driver. She'd at least be aware that city's have similar patterns (streets often east and west while avenues often run north to south), and that traffic rules such as "right on red" vary widely from city to city. She'd know that parking meters usually don't have to be plugged on weekends, and she'd know to watch out for unfamiliar patterns such as street lights on corners rather than hanging in the middle of the intersection. In short, she could use modify the locale maps and access her taxon memory (address of restaurant, which street to take, etc.) to find her way to the restaurant and would be more likely to arrive there safely. In our community college classroom, much of the content we present creates "parts"in students' taxon memory system. Our challenge is to help students create develop locale system maps that will help them make sense of the content. We can do this by designing appropriate projects, by helping them make connections to the "maps" they already have (previous learning/experience), through experiential learning, learning communities, field trips, team teaching, co-op experiences, internships, and other approaches.

We've discussed more about memory retrieval and storage in our "Creating a Learning-centered Environment" section. For example, you'll find a discussion there of the stages of memory (immediate, working, and long-term) and of two types of memory/knowledge: 1. nondeclarative - includes procedures, motor skills, and emotional memory. 2. declarative - semantic, episodic (Sousa, 2001, p. 81). To read more about types of memory/knowledge and the connection to the emotions, click here.


Transfer is a principle of learning that, as Sousa explains it, "describes a two-part process: 1. the effect that past learning has on the processing of new learning, and (2) the degree to which the new learning will be useful to the learner in the future (Sousa, 2001, p. 136). Sousa explains the step-by-step process of transfer like this: "Whenever new learning moves into working memory, long-term memory (most likely stimulated by a signal from the hippocampus) simultaneously searches the long-term storage sites for any past learnings that are similar to, or associated with, the new learning. If the experiences exist, the memory networks are activated and also move into working memory" (p. 136-137). Our students must make connections to prior learning and also understand how what they are learning can be used in the future. If they can't see how the learning can be personally useful in the future, they probably won't exert much effort to really understand or remember what they are learning. We're not talking, here, about when students lean forward and pay attention to the instructor if they hear the words "this will be on the test." That reaction is tied more to memory/learning based on survival than on what we mean by transfer (in the sense that the student knows how the learning can be used in the future). We're talking about students really understanding how the learning connects to new learning. For example, in our "Draw the Rhetorical Mode Activity" students make connections between what they have learned in the activity and their own research papers. (They discuss, immediately after completing the activity, how which one or more of the rhetorical modes to organize a section of the paper they are currently developing. For example, the "light bulb" came on for one student at this point in the activity, when she realized that she could use classification to help her organize her paper about the medicinal herbs.) Making the connections (in the classroom) to prior learning and to future learning/application does not always have to be a complicated process. Sometimes, it's just a matter of helping students find a personal metaphor to help them understand a complex process/concept, or helping them find a past experience that they can relate to the current learning. And, as discussed above, making connections to future learning might involve a simple discussion or another activity designed to put the new learning to use as soon as possible.

We've been discussing the kind of transfer we hope our students will accomplish. However, it's important to be aware that negative transfer also can take place. Negative transfer is when past learning interferes with present learning efforts. Sousa (2001) explains this with the following example: a person who is used to driving a car with an automatic transmission often has great difficulty driving a car with a standard transmission because she has learned, in the past, that the left foot is either idle or used to brake (p. 138). As the driver of a car with standard transmission, I find going the "other way" just as difficult because my left foot has learned to operate the clutch, and if I'm driving a car with automatic transmission, my poor left foot is jumping all around trying to figure out where to go! Obviously, negative transfer can cause confusion.

Instructors can teach for positive transfer by connecting past learning to present learning and by helping students make connections to future learning. For example, in my screenwriting course, I begin a unit on character development by having students recall and discuss their favorite screen characters and dissecting what "makes them tick." The next step is to view movie clips of these characters. The connections to personally relevant past learning helps students understand the current learning (what are the attributes of an interesting screen character). Next, students put what they've learned to work as they create characters for their own screenplays. Furthermore, reflection/discussion activities help students make connections to future learning including learning in other disciplines/courses. (For example, students might connect what we are learning about character in screenwriting to what they are learning in their psychology course.) Sousa calls teaching techniques that create transfer links from past to present "bridging" and teaching techniques that create transfer links from present to future "hugging."

Finally, Sousa also makes the point that "The way that transfer occurs during a learning situation can range from a very superficial similarity to a sophisticated, abstract association" (p. 148). A simple connection may be made to a past learning situation. For example, in English class, if students have kept personal journals in the past, it's much easier for them to understand the purpose and value of keeping a reading journal (especially if they enjoyed keeping the personal journal, of course). The similarity between the two assignments (personal journal, reading journal) triggers learned behaviors (in this case interest and enthusiasm about the reading journal). A more complex form of transfer might include the development of metaphors, analogies, and similes. For example, students might be encouraged to come up with personal metaphors for core concepts in a course. Here's an example: the concept of parallel structure might be understood better by a marketing major who makes an analogy between parallel structure in writing and package design. (Consumers pick up products if they can recognize them instantly by the "shape" of the product, and readers pick up multiple ideas in one sentence if they are "packaged" using the same structure/form.)

clock Time and memory and the construction of meaning

Another interesting concept related to how the brain processes information is the primacy/recency effect. Learners experience, even within the time frame of one class session, a cycle during which they are at times less able to construct meaning. Sousa (2001) explains it like this: "In a learning episode, we remember best that which comes first, second best that which comes last, and least that which comes just past the middle" (p.88). The first studies of the primacy/recency effect were published in the 1880s, but new research on memory is beginning to explain why the effect exists.

The implications are obvious. Suppose you have a 40 minute class. Timing this out roughly, students are most likely to retain whatever happens during the first 10 minutes of the class. Next we have a steep decline in retention ability for about the next ten minutes, which bottoms out in about ten minutes of down time. Then retention ability picks up again for the last 15 minutes of the class, but never reaches the height of the first 12 or 13 minutes of the class. Wow! If you spend the first five minutes of class taking attendance, collecting papers, and other housekeeping chores, you are wasting half of the most valuable time of the period for retention! Implications? Teach new material first. Be careful, though, because whatever you do in this time slot will probably "stick" -- including inaccurate information. This is not the time for guessing. The guesses might appear on the test later.) Plan for practice or review during the down-time, and closure after the downtime And about those housekeeping tasks: come up with ways to automate them so that class time is saved for exploration and learning.

Here's another tip related to information processing: if a learner can't recall something after 24 hours, it's probably not in long-term storage, and thus can't be recalled. (If it isn't stored, it can't be recalled.) This is interesting if we think about testing situations. If you and your students review right before an exam, the students might recall what you've reviewed and perform well on the exam, but that doesn't mean the information was put in long-term storage. Therefore, by next week, they will have forgotten what you thought they "learned" for the test!

  This might be a good time to recall another area of classic (classic sounds so much better than "old"!) research from the 1960s. You know, the study on retention that looked at how much information learners retain within 24 hours of the learning episode. The results: lecture 5%, reading 10%, audiovisual 20%, discussion 50%, practice by doing 75%, teaching others/immediate use of learning, 90%.


How does this relate to teaching in the community college classroom?

First, we must try to figure out what our students bring to the classroom with them. When teaching a student a new concept, for example, we should, as Stanley Fish (2000) says, "begin with the shape of his present understanding" (p.317). Fish, in this case, was writing (from the point of view of a literary theorist) about the process communication/understanding being context dependent, but the phrase "begin with the shape of his present understanding" is exactly where the instructor should begin. Practically speaking, that means we should figure out what our students already know before we attempt to set context and create new learning experiences for them. Group discussion, journals, and reflection activities can help both students and instructors figure out what students have brought to the classroom with them. A quick, informal writing assignment is a good way to start. For example, before introducing a unit on a marketing concept such as brand identity, ask students to write down everything they know about how companies create an image for a specific product. In other words, help students figure out what they already know about the marketing concept before introducing it to them formally.

We often complain that students don't take what they have learned to the "next class" or forget what we thought they have already learned. Perhaps that is because they have not seen that what we taught "made sense" or "had personally relevant meaning," so the learning did not go into permanent storage and/or is not easily or accurately retrievable. Students will experience better retention if we can help them make connections to prior learning and to future application (meaning). We can begin to set the context and make connections to students' past learning by creating complex learning experiences that require students to make use of higher level thinking skills. Many such opportunities exist on our college campus already. For example, activities such as a student-produced newspaper, television show, or film festival provides a ready-made opportunity for classroom instructors to embed content in meaningful experiences. Capstone courses, across-the-curriculum projects, learning communities, experiential learning, and internships also provide opportunities for instructors to help students make connections. When connections to past learning are weak, teachers can use strategies for creating artificial meaning (meaning not connected to past learning) including mnemonics, chunking, and storytelling. In addition, instructors can use simple day-to-day classroom strategies that improve retention such as timing instruction appropriately. Our simple "Why We Care Strategy" is another example of a simple classroom technique designed to improve student learning. (Click here to read this strategy).

Sometimes, thinking about the complexity involved in helping our students make connections may be overwhelming to the classroom teacher. For example, does what we've been asserting in this section of our model mean that students sitting in class taking notes is a waste of time? Possibly, if the students can't connect their notes something meaningful outside of the decontextualized setting of the classroom. Again, meaning is context-dependent. Creating context for the content in your course will help students construct meaning. Furthermore, consider creating more project/tests that require creative problem solving. While some forms of traditional testing work well for a quick check on whether or not students are retaining information (at least temporarily), they don't necessarily measure whether or not students can do anything with what they have picked up (they don't measure higher-level thinking skills). For example, as Wilbert J. McKenzie (2002) points out, multiple choice exams are not likely to "measure ability to assess organization of ideas, conceptual relationships, or many of the skills involved in higher-order thinking."

Finally, how can we use the concept of "existing in physical space" discussed above? Consider creating complex learning experiences that require students to interact with the physical space around them (rather than focusing mostly on listening/reading). (Read more about creating bodily kinesthetic activities in the "Classroom Applications" section of our website.) For example, think of the interactive museum exhibits created for children such as giant, interactive, "walk through" exhibits on the digestive system or the brain. Yes, it would be a challenge to turn the college hallways into a model of the circulatory system, but you could start with simple activities. In an English composition course, for example, an instructor might have students "walk out" an essay to illustrate transition. The essay reader's path would be directed by the transition in the essay (turning to the right or left when reading "on the other hand). Linda Hecker (1997) discussed this and other methods of connecting college-level writing to physical movement in an article in English Journal.

What do we mean by "construction of Individual Meaning?

Construction of individual meaning is improved when students make connections. (You are here.)

Construction of individual meaning improves when students pay attention (and paying attention can shape the brain).

Construction of individual meaning improves when students think about how they learn (metacognition).

Construction of individual meaning is improved when instructors create appropriate assessment (including self-assessment) for complex tasks.  

Construction of individual meaning improves when students develop their creativity.

Construction of individual meaning improves when students develop their ability to identify patterns.

Model <-- return to Model Introduction