In recent years, numerous conceptual models of the land-development process have been produced. In this paper, this material is brought together for the first time; not only are the salient characteristics of these models presented, but also they are evaluated critically in relation to their clarity, applicability, and theoretical underpinnings. Four different categories of model are identified, namely sequential descriptions, behavioural models, production-based analyses, and the structures-of-provision approach. Each of these is reviewed in turn. From this it emerges that the first three approaches have by and large resulted in models that are only partially representative of the complexity and variability inherent in the land-development process. It is concluded that the search for a generally applicable model is, in fact, a futile one, and that energy would be more usefully expended in applying the principles of the ‘structures-of-provision’ approach to the full range of land-development activity, thus producing a specific model for each development sector.

Computer-assisted learning, in the form of simulation-based training, is heavily focused upon by the military. Because computer-based learning offers highly portable, reusable, and costefficient training options, the military has dedicated significant resources to the investigation of instructional strategies that improve learning efficiency within this environment. In order to identify efficient instructional strategies, this paper investigates the two major learning theories that dominate the recent literature on optimizing knowledge acquisition: cognitive load theory (CLT) and constructivism. According to CLT, instructional guidance that promotes efficient learning is most beneficial. Constructivist approaches, in contrast, emphasize the importance of developing a conceptual understanding of the learning material. Supporters of these theories have debated the merits and shortcomings of both positions. However, in the absence of consensus, instructional designers lack a well-defined model for training complex skills in a rapid, efficient manner. The current study investigates the relative utility of CLT and constructivistbased approaches for teaching complex skills using a military command and control task. Findings suggest that the acquisition of procedural, declarative, and conceptual knowledge, as well as decision-making skills, did not differ as a function of the type of instruction used. However, integrated knowledge was slightly better retained by the group provided with CLT-based instruction. These results are contrary to our expectation that constructivist approaches, which focus on the development and integration of information, would yield better performance in an applied problem-based environment. Thus, while contemporary researchers continue to defend the use of constructivist strategies for teaching, our research supports earlier findings that question the utility, efficiency, and impact of these strategies in applied domains.

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We simulated a generic military crew station and examined the workload and performance of robotics operators when interacting with a ground robot in the two modes of robotic autonomy, teleoperation or semi-autonomous. We examined the effect of autonomy and invocation strategies on performance. The operator had either full teleoperation (manual) or semiautonomy (static) regardless of task load. In a third condition, the robots autonomy changed based on task load (adaptive). The operator had to identify hostile targets during the mission and maintain situation awareness (SA) of his local environment and the overall mission via a SA map. Results showed that when task load increased from low to high, participants' SA performance was better in the adaptive and static automation conditions than the manual condition; their threat detection performance degradation was less in manual and adaptive than in the static condition. On the other hand, when task load shifted from high to low, threat detection performance was better in the adaptive than the other two conditions.