The benefits and drawbacks of learner control as a means to create adaptive learning environments

There is empirical support that individualized instruction is superior to traditional instruction that does not take into account the individual differences between learners (Kadiyala & Crynes, 1998). This has led to the firm confirmation of the mere value of adapting the learning process to the specific needs of learners. The rapid evolution in computer technology has raised the possibility for the development of adaptive learning environments (Lee & Park, 2008). Roughly, two paradigms can be distinguished that are used when creating adaptive learning environments. The first paradigm focuses on adapting the content and environment to the learner's characteristics that are assumed to play a role in the effectiveness of individualized instruction. These characteristics include, among others, prior knowledge (Graesser, Jackson, & McDaniel, 2007) and learning style (Graf, Lin, & Kinshuk, 2008). The effectiveness of this paradigm has been confirmed, although results cannot be interpreted univocally (Shute, 1995). Next to adapting content to learner, the second paradigm starts from identifying dysfunctional behavior of learners (such as lowered motivation) in their interaction with the environment and adapting this behavior to the content or instruction (Williams, 1996). However, no empirical research is available using this paradigm. Both paradigms focus on one-way adaptation, with no or only limited interaction between the learner and the environment. Learners do not have any control on such adaptation and hence, no opportunities are available to develop self-regulation skills or metacognitive awareness (Elen, 2000). Reformulated, learner control as an instructional method can be considered as an alternative approach to the development of adaptive learning environments (Park & Lee, 2003) and may be at least as effective in obtaining adaptivity as the more high-technological artificial intelligence techniques. Learner control as instructional technique is not equally effective for all learners (Friend & Cole, 1990; Goforth, 1994; Large, 1996). As an example, novice learners do not fully benefit from control, rather there is a risk for cognitive overload (Scheiter & Gerjets, 2007). Advanced learners on the other hand, mostly benefit from some degree of learner control, enhancing their motivation and optimizing their self-regulation skills (Kinzie & Sullivan, 1989; Williams, 1996). The effectiveness of learner control is thus related to prior knowledge, but also to motivation and self-regulation skills. Recently working memory capacity was included as a potential predictor for learner control (Scheiter & Gerjets, 2007). In this research we start from three assumptions for learner control to be effective (Corbalan, Kester, & van Merriënboer, 2009): (1) learner control must be perceived by the learners; (2) learner control can only be effective if learners have the necessary skills to deal with learner control; and (3) learner control demands free cognitive resources since it posits an additional load on cognitive processing. Following this, we want to ascertain (1) whether perceived learner control is supportive for learning, even if there is no actual learner control available; (2) whether learner control requires additional cognitive processing compared to program control; (3) whether we can sketch the relative contribution of learner control, self-regulation skills, motivation, working memory capacity and prior knowledge in affecting the learning process and learning outcomes and (4) whether the competence to deal with learner control can be trained.status: publishe