Many have had high expectations for the impact of computer-based technology on educational practice. By and large, these expectations have not been realised. It has become evident that innovative technology alone does not necessarily guarantee progress- nor perhaps even significant change- in educational practice. This has led educational researchers to place greater emphasis on cultural issues that could account for the unexpectedly limited influence of technology-enhanced learning. This perception of the relationship between technology and learning is elaborated in the first section of the paper. It is complemented by a review of an alternative conception of computing, rooted in a methodology for modelling with dependency directed at the development of construals rather than programs, that is far better aligned to the demands of developing environments for learning. The paper concludes with a discussion of the potential implications of this approach.

Our everyday world is characterized by quantitative change – from fluctuating global temperatures and shifting medical insurance costs to the changes in a car’s tire pressure from winter to spring. Often, these quantities do not reflect only a single entity or action, but many different interactions and behaviors. This paper investigates how students think and talk about patterns of quantitative change over time while they interact with a computational agent-based model of population growth, which represents change in population as the result of many entities (simulated people) contributing individually to a single changing quantity (population). We found that students often mixed not only mathematical, but also scientific and everyday explanations to make sense of patterns of change. These combinations of explanations led some students to experience (or resolve) difficulties in describing what rate of change reflects in the specific case of population growth; and in understanding and interpreting quantitative change in terms of the individual and population-level behavior of a dynamic system.