There is much interest in education reform in using technology to support learners.One aspect of the argument for technology has been that --software can be used to help learners succeed in more complex tasks than they could otherwise master (Davis& Linn, 2000; Edelson, Gordin, & Pea, 1999; Guzdial, 1994; Quintana, Eng, Carra, Wu,&Soloway, 1999; Reiser et al., 2001). Researchers have invoked the notion of scaffolding, a construct crafted to characterize how more experienced peers or adults can assist learners. (definition of that specific focus called scaffolding). As defined in early research, scaffolding is said to occur when a more knowledgeable person helps a learner succeed in tasks that would be otherwise beyond their reach (Wood, Bruner, & Ross, 1976). In the last two decades of learning sciences research, scaffolding has become increasingly prominent.

Scaffolding is a key strategy in cognitive apprenticeship, in which students can learn by taking increasing responsibility in complex problem solving with the guidance of more knowledgeable mentors or teachers (Collins, Brown, & Newman, 1989). Manydifferent approaches to scaffolding have emerged from the design research on interactive learning environments, --and a variety of design guidelines or principles have been proposed (Edelson et al., 1999; Guzdial, 1994; Kolodner, Owensby, & Guzdial, 2004; Linn, 2000; Reiser et al., 2001).

To engage in development and study of design guidelines requires greater clarity concerning what is meant that a tool has scaffolded learners, and requires a model of how the tool has benefited learners. In particular, it is important to characterize the mechanisms by which a software tool can provide scaffolding for learners. Developing a system of design guidelines for scaffolded software requires such a model of mechanisms that explain why a tool reflecting these guidelines would benefit learners.

In this article, I present an analysis of two mechanisms to characterize how scaffolded tools can support learning. I describe how these dual mechanisms can address the challenges learners face. I develop the argument for these mechanisms by first considering how tools affect the experience of tasks for learners. Then I review some of the critical challenges learners face in complex domains such as science and mathematics learning. In describing each mechanism, I present brief examples of software environments to illustrate the mechanisms in practice. Finally, I consider how the mechanisms can interact and discuss issues of the embedding of tools in classroom contexts.