Dr. Pritchard is an assistant professor in the master’s degree program in Instructional Design & Technology at Philadelphia University. Prior to teaching there, Dr. Pritchard taught high school science in New Jersey, and was the Director of Training for a major computer company. He has a B.A. from The College of New Jersey, an M.Ed. from Penn State University, and an Ed.D. from Wilmington College.
Digital instructional technologies are frequently selected by educators without first deciding what the goals of education (or training) are, what teaching methods will best achieve these goals, or how various digital instructional technologies will support or enhance these goals. Thus, the digital instructional technologies themselves frequently become the focus of curricular reforms.
In this paper I will make the case that educators must first decide what the goals of education are, what instructional methods will best serve these goals, and only then should they select digital instructional technologies that help their students achieve their educational goals. This case will be built upon a deductive argument for using the instructional methodology known as problem based learning (PBL) as the foundation for establishing educational goals and selecting the most appropriate digital instructional technologies.
In the winter of 2006, I attended a conference where teachers and professors presented their ideas on using digital instructional technologies to improve the teaching and learning process. In one session, the presenter explained how his school district had recently purchased a software package that used the Global Information System (GIS); students were using this instructional technology to locate, plot, and otherwise graphically display all the water wells in their county. The presenter indicated that his students generally enjoyed using the software and seemed to be actively engaged in completing their projects, thus fulfilling the district’s mission of promoting student-centered, active learning.
The purpose of this particular session was an overview on using the GIS-based software package, and so more fundamental pedagogical questions were left unasked: How did learning this software package support the goals of the course (or school district)? Were the students learning some valuable skill or were they merely learning the mechanics of a “neat” piece of software? What possible value could plotting the locations of the water wells in their county be to the students? Was the software being taught because the teacher enjoyed it or because it kept the students busy (read: active), thus meeting the requirements of a vaguely stated state standard that required the use of technology in the classroom? Not only were these questions not answered, but the notion of what instructional goal this digital technology was supposed to serve was never even broached. The subsequent sessions I attended that day likewise did not attempt to establish a theoretical or empirical connection between any particular digital instructional technology and instructional goals.
As an educator, I was reminded yet again that the educational process is frequently enacted backwards by instructional technologists: we find an interesting (read: neat) piece of digital technology and “back into” a pedagogical rationale with no overarching model for achieving our educational goals. It would seem that Bruner’s lament is as true today as it was in 1966 when he wrote: “It is interesting that there is a lack of an integrating theory in pedagogy, that in its place there is principally a body of maxims” (31).
An efficacious use of digital instructional technologies must begin with the selection of an overarching instructional model, one that is grounded in sound deductive logic and embodies ultimate purpose as well as instructional strategies.
Imagine two possible pedagogical scenarios for a course called Environmental Problems being taught at an urban university. In the first scenario, the professor begins with a traditional approach, using a curriculum guide that lists the topics to be covered, what behaviors (in the form of behavioral objectives) each student will be expected to demonstrate by the end of the course, how and when students will be tested (usually with an inauthentic paper and pencil instrument), and what laboratories will be conducted. The course content is “professor-centered” (only the professor decides what curriculum to use) and likely varies little from one semester to the next.
In the second scenario, the professor begins instead with a Problem-Based Learning (PBL) approach. Although there are many ways to incorporate PBL into a curriculum, a constructivist orientation might use the first few classes for students to determine what problem they would like to learn more about (in some courses, students may even be asked to solve the problem). For example, a student may wish to find out why the incidence of diabetes is so high in a particular part of the city, or if there is a statistically significant link between houses made using lead-based paint and IQ scores for children. Thus, the curriculum becomes student-centered, and the professor conducts the rest of the semester using the student-derived problem as the focal point. Because the problems are student-derived, the course content is relevant and dynamic.
Problem-Based Learning, according to Evensen and Hmelo (2000), is an effective instructional method because it anchors the learning in concrete, real-life problems, thereby developing the students’ capacity for hypothesis-driven reasoning; thus, students are more satisfied with their curriculum because they are working on a problem that is personally meaningful. In Gagne’s influential work, The Conditions of Learning, problem solving was identified as the highest form of learning because it allows knowledge to be transferred to novel situations through the formation of new schema. “Problem solving results in the acquisition of new ideas that multiply the applicability of principles previously learned” (Gagne, 1965, 57).
Before one accepts the premise, however, that PBL allows students to be more satisfied with their curriculum or that the ability to solve problems is the highest form of learning, we must ask: is there a reason for the apparent efficacy of this teaching methodology? The answer, I believe, is yes, and it’s rooted in the biology of Homo sapiens, a deductive argument for which will be built upon the work of three great thinkers: Darwin, Descartes, and Dewey.
In his ground-breaking work The Descent of Man, Darwin (1879/2004) states that, “Man still bears in his bodily frame the indelible stamp of his lowly origin” (689). The “indelible stamp” describes, among many other things, characteristics or dispositions of our species (Homo sapiens) that have been evolving for millions of years in an environment that was, for much of that period, much different than the one we’re living in now. The shaping process of that indelible stamp was natural selection, which “…works to homogenize a species into a standard overall design by concentrating the effective genes—the ones that build well-functioning organs—and winnowing out the ineffective ones” (Pinker, 2002, 142).
The effective genes (or stamps) that Pinker describes were those that helped our hominid ancestors adapt to and control their environment, both through physical organs and cognitive abilities: “ Where animals compete in strength, humans vie in intellect, and the superior minds win out” (Darwin, 1879/2004, xxiv). Geary (2002) described these cognitive abilities as those that allow the individual “…to process goal relevant information” (323). “Goal relevancy” as used by Geary means that as a species we evolved through natural selection to solve problems—that is, to control our environment—for the purpose (read: ultimate cause) of propagating the species. We have evolved to become problem-solving entities, and the capacity to do so is encoded in our DNA. Undeniably, the problems we encounter today (predicting local economic conditions) are different than those encountered by our hominid ancestors (predicting rain). Nonetheless, the stamp of a general problem-solving disposition still bestows upon modern man a selective advantage ( Keil & Wilson, 1999, xl). Thus, the forces of natural selection as they relate to the evolution of Homo sapien information-processing and problem-solving abilities establish a biological basis for a teaching and learning model—Problem-Based Learning—in a modern, technological-based society.
If we accept the idea that the forces of natural selection have endowed modern Homo sapiens with a set of highly evolved dispositions for problem-solving, we must accept the idea that modern Homo sapiens are not born with brains that are a “blank slate.” Rather, we must accept, or at least acknowledge, the so-called “rationalist” point of view, which posits that various innate dispositions in the Homo sapien brain are not predicated upon any form of experience. Classic rationalists like Rene Descartes believed that Homo sapiens are more than the sum of our empirical interactions with our environment, being endowed with a “rational soul.”
However, if we are inclined to reject the rationalist view and accept an empirical (blank slate) notion of the Homo sapien brain, the proposition that Homo sapiens are problem-solving entities is not negated; the ultimate end for a blank mind is to learn through association to achieve mastery of the environment. The rationalism versus empiricism debate becomes moot, as both support the same end: to solve problems for the purpose of controlling the environment.
John Dewey, arguably one of the most influential educational theorists of the 19 th century, exhorted educators to incorporate the interests of the child into the curriculum, making the child the center of the school (1938/1997). But what constitute the “interests of the child?” According to Pinker (2002), an educational theory that addresses the interests of the child must be based on a theory of human nature; thus, a curriculum based upon teaching students to control or to understand their environment follows naturally from the premises mentioned above. Smilkstein (2003) eloquently describes this type of a curriculum as “brain-compatible” (2), with a scientific basis for knowing how and what to teach. A deep understanding of any topic can be achieved by using a problem-based (i.e., brain-compatible) curriculum because it is based upon the premise that our brains have evolved to solve problems for the purpose of controlling our environment.
If Homo sapiens have a predisposition toward problem solving hard coded into their DNA, how do we as educators build a curriculum around PBL? In F igures 1 and 2, I propose two overarching instructional models that integrate the pedagogical construct of PBL with other well-established learning models. I also propose how various digital instructional technologies can be used to support a PBL curriculum.
It is beyond the scope of this paper to fully explain each component of the two models, but briefly Figure1 represents a “curricular flow,” from deciding what the purposes of education are and what type of mind we are trying to develop (The Tyler Rationale), through what educational experiences (The Learning Cycle and The Cognitive Apprenticeship) the teacher could use to implement a PBL curriculum. For example, we might decide that the individual we are trying to develop should be a reflective problem solver (the purpose of education), and that student-generated problems would form the basis for other instructional models (The Learning Cycle and The Cognitive Apprenticeship). In such a model, the capacity to solve problems becomes the goal of the curriculum as well as an instructional strategy.
Figure 2 represents a more thorough explanation of how PBL can be integrated into The Learning Cycle, with example digital instructional technologies (shown in parenthesis) that would conceptually support or enhance the curriculum:
In Figure 2, the digital instructional technologies per se are not the focus of the curriculum; rather, their selection and subsequent incorporation into the pedagogical models are based upon their ability to enable or to enhance various components of a PBL curriculum; only those digital instructional technologies that can be empirically verified as supportive of an instructional goal will be selected. If there is no empirical evidence that the technology will improve learning, it should not be used. Thus, digital instructional technologies become “cognitive artifacts,” which “…are physical objects made by humans for the purpose of aiding, enhancing, or improving cognition” ( Keil & Wilson, 1999, 126). For example, again referring to Figure 2A, Student Selection of Relevant Problem, the students’ use of a library-based electronic database was selected on the basis of its ability to enable and enhancea problem-based instructional goal.
The Evaluation Phase of the Learning Cycle becomes the ideal time not only to assess the students’ work, but also to empirically measure the contribution of the various digital instructional technologies; if a student’s solution to a problem is deemed unsatisfactory, the instructor must review the pedagogical model and supporting digital instructional technologies to see what can be improved. For example, the student may not have defined the problem very well at the beginning of the Learning Cycle, thus precluding an adequate solution to the original problem. The instructor must now determine if using an electronic database was the proper digital instructional technology for framing the problem; could an interview with a remotely located expert using a Web-cam have been more helpful? The challenge for educators in the Evaluation Phase is to quantify the contribution of a particular digital instructional technology in achieving an instructional goal; merely introducing another piece of technology without empirically establishing this causal connection can only detract from our effectiveness as educators.
A curriculum built upon PBL with the empirically validated incorporation of various digital instructional technologies would seem to be a natural extension of our brain’s evolution. It is not my contention, however, that PBL is the only learning strategy that can take advantage of our brain’s physiology: a curriculum based upon the concept of multiple intelligences (as envisioned by Howard Gardner) may be another example of a brain-based curriculum (Smilkstein, 2003). The pedagogical concept of multiple intelligences would not supplant PBL— it would become a teaching strategy that works in conjunction with a curriculum based upon PBL.
It was not the purpose of this paper to focus upon an explication of the age-old debate about “nature-verses-nurture”; a topic of such great importance will, perhaps, never be solved to the satisfaction of social scientists, even considering the recent advances in genetics. I presented a deductive argument, based on the work of three influential thinkers, that Homo sapiens are genetically predisposed to solve problems for the purpose of controlling their environment. I further argued that the primary goal of educators should be building a curriculum based on Problem-Based Learning. With PBL established as the “epicenter” of the curriculum, I then explained how student-derived problems can be integrated into and made compatible with other proposed models of effective pedagogy. Finally, I argued that digital instructional technologies should enable or enhance a curriculum that is based upon pedagogical models that are either theoretically or empirically well supported (PBL, in this case). Thus, building a curriculum that focuses upon PBL (or other well-supported models) while employing modern digital instructional technologies to enhance the problem-solving experience of our students should be our goal as educators.
Yet this appears not to be happening. Our goal seems to be digital instructional technologies for their own sake, with little or no attention being paid to improving educational curriculum, problem-based or otherwise. Anecdotal evidence of this tendency is not hard to come by: vendors at instructional technology conferences promote the use of the latest electronic or Web-based paraphernalia, with scant attention paid to its incorporation into a pedagogical model; “smart whiteboards” are left unused in classrooms because professors do not understand their teaching value; Course Management Systems (CMS) like Blackboard and WebCT are employed at many universities because they make course delivery more efficient, with virtually no large-scale scientific research to support their usefulness in promoting a deeper understanding of the subject (Coates, James, & Baldwin, 2005).
The challenge, according to Smilkstein (2003), is for educators to “…develop curricula and select pedagogical strategies that will most effectively help students learn by using their brain’s innate learning proc esses” (30). Our research efforts, therefore, should focus on empirically measuring what digital instructional technologies best support or enhance a curriculum based on how the brain actually works. In such an environment, digital instructional technologies like the Global Information System would be used not to locate water wells, but to solve problems that are meaningful to the student.
Problem-Based Learning requires a student-centered, democratic learning environment. Many educators are uncomfortable with such constructs, concerned about losing control of the class or being unable to measure the outcomes. These concerns can be addressed to a large extent through the use of digital instructional technologies; as students work on projects that are relevant to controlling or understanding their own environment through PBL, their motivational levels will increase and classroom behavior will be positively directed. Further, the use of active feedback and multi-source expert evaluation will allow educators to more meaningfully and authentically assess student achievement. Thus, as we redefine our role as educators, we would do well to remember Bruner’s (1966) admonition:
The will to learn becomes a “problem” only under specialized circumstances like those of a school, where a curriculum is set, students confined, and a path fixed. The problem exists not so much in learning itself, but in the fact that what the school imposes often fails to enlist the natural energies that sustain spontaneous learning—curiosity, a desire for competence, aspiration to emulate a model, and a deep-sensed commitment to the web of social reciprocity. (127)
Bruner, J. S. (1966). Toward a theory of instruction. New York: W. W. Norton & Company, Inc.
Coates, H., James, R., & Baldwin, G. (2005). A critical examination of the effects of learning management systems on university teaching and learning. Tertiary Education and Management, 11, 19-36.
Collins, A., Brown, J., & Newman, S. (1990). Cognitive apprenticeship: Teaching the crafts of reading, writing, and mathematics. In L. B. Resnick (Ed.), Knowing , learning , and instruction : Essays in honor of Robert Glasser . Hillsdale, NJ: Lawrence Erlbaum & Associates.
Darwin, C. (2004). The descent of man. New York: Penguin Putnam, Inc. (Original work published 1879).
Dewey, J. (1997). Experience and education. New York: Touchstone. (Original work published 1938).
Evensen, D. H. & Hmelo, C. E. (2000). Problem-based learning: A research perspective on learning interactions. Mahwah, NJ: Lawrence Erlbaum Associates.
Gagne, Robert M. (1965). The conditions of learning. New York: Holt, Rinehart and Winston, Inc.
Gardner, H. (1983). Frames of mind. New York: BasicBooks.
Geary, D. C. (2000). Principles of evolutionary educational psychology. Learning & Individual Differences, 12, 317-329.
Karplus, R. (1974). Science curriculum improvement study: Teachers’ handbook. Lawrence Hall of Science, Berkeley, CA.
Keil, F. C., & Wilson, R. A. (Eds.). (1999). The MIT encyclopedia of the cognitive sciences. Cambridge, MA: The MIT Press.
Pinker, S. (2002). The blank slate. New York: Penguin Putnam, Inc.
Smilkstein, R. (2003). We’re born to learn: Using the brain’s natural learning process to create today’s curriculum. Thousand Oaks, CA: Corwin Press, Inc.
Tyler, R. (1949). Basic principles of curriculum and instruction. Chicago: University of Chicago Press.
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