Interactive Learning Environments- ILE

The level of interactivity in traditional Computer Aided Instruction (CAI) and Interactive Tutoring Service (ITS)  tends to be low compared to ILE. Their basic goal is only to teach specific content knowledge and skills. Because of their limited scope, they have only been moderately successful [McGrenere, 1996]. Soloway and Bielaczyz [1996] suggest that educational software needs to broaden its scope and look at issues of communication, inquiry, reasoning, and metacognitive skills in order to meet the needs of the 21st century. ILE systems combine features from a wide variety of systems including CAI, ITS, e-books, hypermedia systems, simulations and microworlds, to provide a high level of interactivity as well as learner control [Murphy, 1997].

Giardina [1992] suggests that learner control, intelligence and adaptability are the three central themes in interactive learning environments. Learner control is the degree to which a learner can direct his/her own learning experience [Shyu and Brown, 1992]. Doherty [1998] argues that ILE systems should provide learners with control over depth of study, range of content, number and type of delivery media, and time spent on learning. With these options, learners can tailor the learning experience to meet their specific needs and interests. For this reason, learner control is “not an unitary construct, but rather a collection of strategies that function in different ways depending upon what is being controlled by whom” [Ross and Morrison, 1989]. In order to provide intelligence and adaptability, interactive learning environments need to monitor the interactions of the user and react accordingly. Adaptive feedback is effective in enhancing learning [Norman, 1993; Tsybenko and Bykov, 1997]. A system's ability to provide adaptive feedback demands a very sophisticated design because the system must not only be capable of noting the user's actions but also be capable of interpreting and then reacting or adapting to them [Murphy, 1997]. The interpretation is a complex process involving transforming the user's actions into a representation of his knowledge which must be overlaid on the representation of the system's knowledge [Duchastel, 1992].

Scaffolding is another technique used for ILE systems design [Soloway, Guzdial and Hay, 1994]. It is a means of supporting the learner so that “more support is provided initially, but as the learner acquires the necessary knowledge and skills, the support fades, leaving the learner in control” [McGrenere, 1996]. Based on types of support given, Winnips and McLoughlin [2000] categorize the software scaffolding as following:

• Providing examples: these examples should not only focus on products, but also on a process.

• Helping students, by giving away parts of the solution.

• Providing a model for design, or a structure to design in.

• Cueing/hinting: helping students with a solution by providing a hint or cue to a possible path of the solution.

• Coaching comments: these comments are intended for motivation, providing feedback and advice on performance, and provoking reflection.

• Asking questions, pointing out weaknesses, asking for a motivation, in order to enhance reflection.

• Metacognitive support: stating why the above types of support are given, in order to model the type of metacognition that experts would use.

• Providing a timeline, with fixed dates and goals built in. This structure could be present, to help students appearing to be very goal directed to build in multiple evaluation moments into the actual experience of studying.

Scaffolding has been well-established as an effective means of supporting learning [Collins, 1996; Rogoff, 1990]. Building scaffolding into software offers “the opportunity to provide for diversity through individualized support that accommodates learners of different skills, backgrounds, and learning styles, and to support growth by making more powerful functionality available as the learner develops expertise” [Jackson, Krajcik and Soloway, 1998].

Interface style is another important factor in ILE design [Klawe, 1998a]. Recent HCI research in problem solving and learning indicates that interfaces with the lowest cognitive effort may not be the most educationally effective [Sedighian, 1998; Holst, 1996]. Sedighian [1998] suggests that interfaces that involve direct concept manipulation are better for promoting reflective cognition than those that manipulate an object that is being used to illustrate the concept. Holst [1996] argues that difficult or awkward interfaces are better than intuitive or easy interfaces for directing the learner’s attention. Sedighian and Klawe [1996] provide an interface strategy for promoting reflective cognition. It is based on three interface elements: “a) an educationally appropriate representation, b) an interaction protocol that naturally shifts children's attention from intuitive interaction to one that focuses on the structure and operation of the representation, and c) a gradual elimination of feedback and/or components of the representation so that children are required to assume increasing cognitive responsibilities”.