Commentary: Prerequisite Knowledge – Premier researchers
Most biochemistry, genetics, cell biology, and molecular biology classes have extensive prerequisite or co-requisite requirements, often including introductory chemistry, introductory biology, and organic chemistry coursework.
\But what is the function of these prerequisites? While it seems logical that a basic understanding of biological and chemical principles would be important to understanding biochemistry and molecular biology principles, the official answer to this question is not obvious.
A study done at the University of South Florida [1] found that enforcing the prerequisite requirements for junior level courses decreased the failure (defined as D’s and F’s) by 15–18% and the withdrawal rate by 21–31%. In contrast, a study at the University of Minnesota found that neither the completion of nor the grade in organic chemistry was correlated to the grade in biochemistry [2].
However, almost twice as many students who had not completed the prerequisites withdrew compared to those who had finished the prerequisite courses. Why these different results? One proposed explanation for the increased withdrawal rate was that instructors may be more likely to encourage withdrawal by students who have not completed the prerequisites.
It may be that there are differences in prerequisite effects because of how the courses are taught, such as the style of classroom instruction. Active learning strategies such as problem-based learning and process oriented guided inquiry learning [3] are based upon a constructivist model where students build knowledge by adding onto their already existing mental framework [4, 5].
This suggests that comprehension and retention of prerequisite material would be more important for classes taught with these strategies. Indeed, one of the constructivist learning theories is a three step model of learning [6] where ‘‘the importance of prerequisite knowledge [i]s a variable in learning, and points to the fact that new nodes cannot be connected to existing structure (i.e. external connectedness) if the knowledge required to support new information does not exist in the learner.’’ Another suggestion was that because of the variation in students’ entering knowledge, the instructors assumed no one remembered anything, and began from beginning principles instead of assuming knowledge.
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While it’s easy to presume that students remember everything they’ve been taught, this is not necessarily the case. In a study looking at biochemistry students’ misconceptions about general chemistry topics, Villafane et al. found that student ability to correctly answer three questions about concepts from prior coursework was very low, ranging from 4 to 33% [7].
The good news from these discouraging statistics is that repeated exposure to the basic concepts from the prerequisite courses in upper level settings can reinforce the material and aid in understanding [7]. Indeed, ability to recall knowledge and correctly explain the reason for their answers about molecular structure grows as students progress from early college through college and graduate school [8] (as one would hope).
This lack of retention of content is also a call to educators to view knowledge and learning as something that happens not just in the confines of a single course. What we teach reinforces what was taught in previous courses, and will be solidified as students use the material in subsequent courses.
This should motivate us to consider both linkages between topics within the course and among other courses students have completed as we design instruction [9]. As we teach, we must recognize what prior knowledge a student should draw upon to correctly understand the topic and make these connections explicit to the student. One model for how this has been done was a bioinformatics project that spanned all four years of a biology curriculum [10]. The researchers examined not only growth in understanding of bioinformatics, they also looked at confidence and ability in basic statistical and mathematical skills and saw growth in both math and bioinformatics skills.
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