I admire the work of John Carroll, whose minimalism theory finds its roots in constructivism. Although much of his work has been dedicated to studying human-computer learning contexts, I find that his work is relevant and meaningful to that for which I strive within my elementary classroom. In short, minimalist theory seeks to reduce the excessive, negative effects instructional materials have within the learning process while increasing activities which are driven by the learners themselves in order to achieve accomplishment (Carbonell, “John Carroll,” Rosson).
With endlessly proliferating elementary curricula (and the associated theoretical foundations), I’ve often wondered if less wouldn’t be more, so to speak. Carroll suggests that learners are more apt to do their job (learn) if they engage in meaningful, self-contained activities followed by quick implementation of realistic activities allowing for learner-directed reasoning and error recognition/recovery. In other words, the training (schooling) the learner endures should be close-knit with the real thing.
I have begun to practice this concept without realizing it. In mathematics, for example, I do not have my third graders use the textbooks I inherited with the classroom. It’s not that they’re forbidden—in fact, they’re in every desk in the room—they’ve just never been referenced by me and, consequently, rarely used except by the more curious within the classroom. Why? Because I’m not fond of the way the text crowds math problems onto a page. I dislike the claustrophobic feel of the textual instruction within each chapter. In my opinion, the textbook gets in the way of my students’ learning because the “activities” therein are not meaningful nor is the given practice related to the real world. Often the problems are repetitive and somewhat mindless—fostering the ability to make the same error over and over again rather than encouraging the learner to think through the reasonableness of an answer or approach. Instead, I might create a spacious worksheet (featuring a brief description of key terms or concepts) which force my students to underline key components within real-life problems, identify a strategy or approach for solving the problem, show or explain all the steps involved in finding a solution, label properly, then check to be sure a solution makes sense within the context of the original problem (whether by an informal check of logical possibility or through using an inverse mathematical relationship).
From a minimalist standpoint, I have removed the instructional materials which hinder many learners (with Gardner’s MI in mind) and, instead, created a simplified learning environment wherein the learner is free to think, understand, apply, analyze, synthesize, and evaluate (Bloom’s taxonomy). This is exactly what Carroll sought to do when teaching his learners how to interact with an unfamiliar word processor in the late 20th century:
The training materials involved a set of 25 cards to replace a 94 page manual. Each card corresponded to a meaningful task, was self-contained and included error recognition/recovery information for that task. Furthermore, the information provided on the cards was not complete, step-by-step specifications but only the key ideas or hints about what to do. In an experiment that compared the use of the cards versus the manual, users learned the task in about half the time with the cards, supporting the effectiveness of the minimalist design (Kearsly).
John Carroll’s minimalist theory picks up where constructivism leaves off. Constructivism seeks to make “‘good’ problems…realistically complex and personally meaningful,” but minimalism wants to abandon even this for the sake of allowing learners to directly experience what it is they are learning within its own environment (computer interaction must be done on the computer as soon as possible rather than pouring over a textbook all about the interaction) (Carbonell). Similarly, instead of lazily letting my students pour over repetitive math problems, they must use the math they learn in a logical environment.
Some might say that the mathematical example I present here is not minimalist at all but nothing more than a simplified constructivist curriculum. However, given the fact that math is, in and of itself, theoretical with byproducts of applications, it must be carried out theoretically—just as word processing must be done on a computer, that is where it should be explored. While word processing has its applications in producing letters, e-mails, books, outlines, and recipes, minimalism does not go so far as to suggest that these must be produced—only that word processing is done within a computing environment. So, too, mathematics should be done within a logical environment (Kearsly).
Works Cited
Carbonell, Leilani. “Learning Theory.” My E-Coach. 27 March 2009.
“John Caroll.” Penn State College of Information Sciences and Technology. 3 April 2009. http://ist.psu.edu/ist/directory/faculty/?EmployeeID=234
Rosson, Mary Beth, Carroll, Bellamy. “Smalltalk Scaffolding: A Case Study of Minimalist Instruction.” April 1990. IBM T.J. Watson Research Center. http://cscl.ist.psu.edu/public/users/jcarroll/Self/papers/MiTTS-CHI90.pdf
Kearsly, Greg. “Minimalism (J. Carroll).” Theory Into Practice. 27 March 2009. http://tip.psychology.org/carroll.html
OR THIS MIGHT HAPPEN! I’ve been looking for a real-life demonstration of what the potential future holds for the less cognizant of my young ones…
and here it is!
I’m not sure what to make of the guy’s laugh in the video…psychologically he must have felt that he was watching America’s Funniest Home Videos with good ol’ Bob Saget (remember him?).
Given the various learning theories along with very few solid so-called “definitions of learning,” I prefer a view which
looks at learning as an active process in which the learner builds on prior knowledge to select and transform information based on their own cognitive structure (“What is Learning?”).
Although constructivist in nature, it allows for the connectionistic model (connecting relevant pieces of information together) and the cognitive explanation of sensory memory (STSS) within the stage model of information processing where
it is absolutely critical that the learner attend to the information…in order to transfer it… (Huitt).
It is clear, therefore, that each of these theories demand action from the learner or else learning is lost.
Educators have the daunting task of helping their learners take such an active role in the learning process. This can be accomplished by changing the way a person deals with incoming data. For example, when I notice my students tuning out after 10-15 minutes of reading information together, I can help them take back control by asking myself questions in a think-aloud format, engaging them in a short play, or requiring them to draw a picture of the events explored within the text. In this way, my young learners must stay constantly active in the learning process as they listen, speak, act out, create, but above all—think and learn (Bell, et al)!
When a person actively builds on prior knowledge based on their cognitive structure, (Gardner’s Multiple Intelligences) they must “recognize when they understand and when they need more information” (Bransford, et al, 13). This brings to light the question: is learning a product or a process? It seems to be both. For example, when someone claims to have learned how to ride a bicycle, what do they mean? We must consider the context. What about within the context of a street competition? How about mountain biking? What of cliff biking and jumping? Each of these contexts warrants a different kind of learning. The person might mean that they can do no more than balance on two wheels while riding in a straight line while another is adept at racing down the side of a mountain. Someone who rides a bike is able to show that capability (product) yet each new terrain encountered requires an ongoing ability to build and transform knowledge (process) based on prior experiences (“What is Learning?”).
My preferred definition of learning is, perhaps, most explicitly justified in the study of how experts differ from novices. Experts maintain a level of metacognition which enables them to actively chunk information into mental clusters overseen by a larger umbrella of concepts and principles. This fluency is consistently seen across academic subjects (Bransford, et al, 17-38).
Once again, besides changing up the way data is presented, educators have an overwhelming mission: to organize “curricula…in ways that lead to conceptual understanding” similar to that of the experts (Bransford, et al, 30). By leading our learners to chunk information into mental clusters (via “instructional procedures that speed pattern recognition”), we can foster their development and growth as they actively build upon their pre-existing knowledge and transform the information into something relevant and useful.
Bransford, John D., Ann L. Brown, and Rodney R. Cocking. How People Learn: Brain, Mind, Experience, and School. 1999. The National Academies Press. 16 March 2009. <http://www.nap.edu/html/howpeople1/>
“What is Learning?” Virtual University Design & Technology (vuDAT). 20 March 2007. Michigan State University. 16 March 2009 <http://vudat.msu.edu/246/>
The purpose and value of teaching science in school is to provide students with a process to explore the world around them. From the time they enter school, students should be encouraged by their teachers to have a questioning, curious attitude about the world around them—and this attitude (an attitude of science, if you will) should permeate every subject area throughout the curriculum. There should be no set amount of time dedicated to science but rather fostered throughout each subject a student encounters —and extended beyond the classroom. The ultimate goal of science is to learn how to inquire—it is through this process that students will be properly equipped to explore.
Half-way through my fifth year of teaching (students), I realized that I may not be maximizing my efforts in regards to the whole processes of facilitating learning. For example, I have been expecting my students to multiply, divide, read, spell, think, eat, and breathe independantly.
Now here is the revolutionary idea that struck me (many of you more intelligent and more experienced teachers came to this realization years ago, I have no doubt): I am expecting too much from too many. The easiest way for me to describe how to develop a more practical set of classroom expectations for the learners of any given age group is to think of your classroom like a traditional bell curve.
I will not bore you with the minutia as I am confident of your familiarity with the study of probability and statistics. Instead , I will summarize by suggesting that if your curve is well constructed, forming a symmetrical bell, you will have high expectations for the same number of students for which you hold low expectations (see diagram 27A.1).
The rest of your learners, quite naturally, will be dispersed evenly across the bell. For example, if, having administered a formative assessment piece on basic mathematic operations, I find that I have 3 students that are proficient in multiplication, I should expect to find an equal number of students barely drawing breath. The remaining students will rise and fall over the progression of the curve. Therefore, I should begin with the lower learners, by cracking a window or turning on a fan. Then, once I am sure that they are being sufficiently challenged, I will provide the majority of my class with appropriate instruction, and give the “gifted learners” dictionaries to copy.
Children need ample space in order to maintain a healthy mindset. Requiring them to be confined to desks or even tight spaces within the classroom will, inevitably, prove detrimental to their success.
I find that even for myself I need an environment which enables me to spread out. There’s a profound relation between the mind’s perception and the person’s ability to achieve.
Make the classroom as open as possible. Design the elements of your home and your child’s room to explicitly allow for SPACE!
All year we have talked about how to rephrase the question. All year we have worked on using details from what we know or text in order to provide an intelligent response. And so, weeks away from standardized tests, I get the ensuing response to the following question:
In this selection, the narrator tells us his dog is smart. What do you know about dogs that supports the idea that dogs are smart?
Well, my dog is goofy he usually bangs his head on things. but I think dogs are smart!
