No abstract

There is a long standing, and unsettled debate surrounding the ways that technology influences society. There is strong scholarship supporting the social construction perspective, arguing that the effects of technology are wholly socially and politically determined. This paper argues that the social constructivist position needs to be expanded if it can be useful for more than observing the ways technologies are designed and used. We need to develop better ways to talk about software, computer hardware, and networks, so that we can describe the social interpretations of these systems while accounting for their unique characteristics. We suggest using software affordances as a way to understand the semantics of software as interactive systems. Using Facebook privacy concerns as a case study, we argue that software affordances offer a useful lens for considering the social and political implications of interactive software systems, providing us more analytical tools to interpret, and not just describe, new technologies.

Massive open online courses (MOOCs) take university lectures and other educational materials and make them available for free as online “courses.” Liberal and neoliberal MOOC supporters laud these courses for opening up education to the world while incorporating market dynamics to improve quality and drive down costs. Skeptics claim MOOCs are a bald attempt to privatize higher learning, thus creating an apartheid educational system with traditional universities serving the wealthy while everyone else is left with cut‐rate online learning. This essay draws on the political theory of autonomist Marxism, arguing that MOOCs are capital's defensive reaction to the threats of resistant universities on one side, and unmanageable Internet‐based learning on the other. It then looks at which MOOC designs would support education for the “multitude,” which is the term used by autonomist Marxism to describe an autonomous, diverse, networked political body.

1) Background: This study employs a simulation-based approach, adapting the waterfall model, to provide estimates for projects and individual phase completion times. Additionally, it pinpoints potential efficiency issues stemming from suboptimal resource levels. It further demonstrates ways to identify resource levels that create bottlenecks and result in idle resources. (2) Methods: We implement our software development lifecycle simulation using SimPy, a discrete-event simulation framework written in Python. Our model is executed on 100 projects of varying sizes over three stages. The first, pre-optimization, provides insight based on the initial set of resources. This is followed by the optimization stage, which serves to identify the optimal number of resources to eliminate bottlenecks and minimize idle time. The third stage, post-optimization, evaluates the resource optimized model. (3) Results: The analysis of the simulation-generated data reveals the presence of resource bottlenecks during the pre-optimization stage, particularly in the implementation phase. These dissipate after optimization. (4) Conclusions: The findings emphasize the advantage of using simulation as a safe and effective way to experiment and plan for software development projects. Such simulations also allow those managing software development projects to make accurate, evidence-based projections as to phase and project completion times and identify optimal resource levels and their interplay. In particular, understanding the tradeoffs between experiencing delayed completion times and procuring additional resources to alleviate any bottlenecks.

The rapid rise in mobile computing—primarily smartphones and tablets—has led software and interface designers to adopt a “mobile first” strategy, where they develop applications with mobile users in mind as the primary audience. More than just bringing desktop computing to smaller devices, this turn has opened up qualitatively different computing experience, refocusing interaction design on high quality user experiences. This chapter explores the ways that mobile first can help instructional designers realize a more contextual learning experience embedded in the world. We look at the primary approaches of mobile first design and then explore some cases of mobile design for learning that foster authentic and deep learning.