ABSTRACT
Learning is not viewed as merely a cumulative accretion of knowledge by a largely passive learner, but as an active process in which the learner is engaged in constructing or generating concepts to account for novel phenomena. (Cleminson, 1990, p. 439)
INTRODUCTION
Many environmental science students at the tertiary level struggle with topics that entail biostatistics and applied mathematics, yet virtually all life sciences have quantitative aspects that demand statistical evidence to support or refute predictions in the hypothesis-based scientific paradigm (Elzingha et al., 2001). Increasingly, environmental scientists are required to statistically demonstrate the effectiveness of resource management programs. They must be able to establish that their survey designs and resultant data are sufficiently
powerful in a statistical sense (e.g., Fairweather, 1991) to withstand scientific and legal scrutiny in environmental issues that may involve protection of World Heritage-listed national parks or natural resource exploitation worth millions of dollars. In short, life scientists need mathematics as much as do physicists and engineers but seldom do such students show much natural predilection for numbers. So what approaches can teachers use that might overcome the fear of “drowning by numbers”? How can we help students conquer this fear and start to learn effectively? What does educational theory have to offer teachers tackling this challenge at a tertiary level? How do learner-centered approaches lend themselves to encouraging a deep approach to learning about biostatistics in the life sciences?
