Componentes del Conocimiento Especializado del Profesor

The necessity to critically examine prior knowledge in multimedia learning research is one example of considering possible aptitude-treatment-interactions, which are interactions between learner characteristics and the given instructional conditions (Bétrancourt, 2005).

High domain-specific prior knowledge facilitates summarizing the learning material into larger meaningful units and thereafter substantially reduces the number of units to be processed in working memory. Cognitive Load Theory derives from this argument the assumption that the risk of cognitive overload is lower for high prior knowledged than for low prior knowledged learners. High prior knowledged learners have enough cognitive resources free for an optimal mental organization of the learning material by falling back upon schemata stored in long-term memory. Thus, disadvantages of inappropriate instructional designs can be partly compensated. The application of diverse design principles like avoiding seductive details, using modality or introducing support for coherence formation should be especially effective for novices.

This has been demonstrated by several studies, showing that learners’ domain-specific prior knowledge can moderate the effects of instructional support (e.g. Kalyuga et al., 1998; McNamara et al., 1996). Seufert (2003a) showed that support for coherence formation is especially effective for learners with medium levels of prior knowledge. She interprets this result in line with Cognitive Load Theory in the way that this group of learners is able to use at least some cognitive schemata, freeing up cognitive resources for coherence formation processes. In contrast to experts, this learner group still needs support in the learning process. The research group around Sweller demonstrated that experts can even be hindered by instructional techniques, which normally foster learning, an effect called Expertise Reversal Effect (for an overview see Kalyuga, 2007; Kalyuga, Chandler, Tuovinen & Sweller, 2001). For instance, a study of Kalyuga et al. (1998) revealed that novice learners benefited from textual explanations integrated into diagrams. These learners were not able to comprehend the diagrams without explanations in an integrated format. However, with growing expertise learners performed significantly better without textual explanations. This is an expected result. However, learners with high prior knowledge remarkably performed worse with the integrated format. The authors explain the differential effects by the prevention of split- attention or redundancy. Novices profit from instructions that prevent a split-attention effect by using integrated formats in order to avoid eye-movements that are time consuming and costly in terms of extraneous cognitive load. However, for experts these additional instructions are redundant to their own available schemata stored in long-term memory and activated in long-term working memory (Ericcson & Kintsch, 1995; see also Section 2.5.2) during learning. Experts could even get confused by the supplemental information and probably engaged in some sort of inhibition processes forcing the learner to select relevant

information (Koch, Seufert & Brünken, 2008). For a graphical illustration of the special aptitude-treatment-interaction of an Expertise Reversal Effect, see Figure 2.

Fig. 2. Illustration of a Special Aptitude-Treatment Interaction: The Expertise Reversal Effect.

In another study, McNamara et al. (1996) demonstrated that an increase in text coherence was beneficial for novices, whereas experts benefited most from minimally coherent text. A recent study of Koch et al. (2008) also provides evidence for an aptitude-treatment interaction by Seufert (2003a), mentioned above, showing an expertise reversal effect in an instructional design to foster coherence formation. In this study, experts were hindered in deep processing by the verbally introduced support for coherence formation, which focused on the relations between visual and textual information of the multimedia learning material. However, this instructional technique was very fruitful for novices indicated by an interaction effect in transfer performance between prior knowledge, introduced as a continuous variable, and the instructional condition. Thus, the Expertise Reversal Effect for germane load associated factors of coherence formation is supported. For one of the other three relevant effects for the present work, namely modality, seductive details and mental animation, actual reviewed literature only presents studies confirming the expertise reversal effect in an instructional design to foster learning by using the advantages of modality. In a study of Kalyuaga, Chandler and Sweller (2000), learners with high prior knowledge actually compensated the disadvantages of a visual-only instruction. In a second experiment, experts demonstrated worse performance under the audiovisual instruction in comparison to the visual-only

0 25 50 75 100 0 25 50 75 100 Aptitude Variable (%) (e.g., Prior Knowledge)

D e p e n d e n t V a ria b le (% ) (e .g ., Lear ni ng S u cces s) Treatment 1 (Instructional Support) Treatment 2 (Control Group)

condition. However, no expertise reversal effects were reported in literature for seductive details or mental animation.

In sum, the expertise reversal effect is expected in instructional designs using the modality and/or the coherence effect. Further research is needed to confirm this phenomenon in other instructional techniques like reducing seductive details or activating mental animation. At this point, it can be concluded that prior knowledge plays a crucial role in multimedia learning, which should be taken into account by developing powerful pretests for every multimedia learning experiment. Moreover, practical implications should be sensible for counterintuitive effects of normally effective instructional designs. One solution are adaptive learning systems as already demonstrated in learning preference research, differentiating between verbalizers and visualizers (Leutner 2001; 2002), and demanded (Kalyuga, Ayres, Chandler & Sweller, 2003) as well as introduced (Kalyuga, 2006; Kalyuga & Sweller, 2005) in the context of expertise research in multimedia learning.

The impact of prior knowledge has been widely analyzed, discussed and practical implications are already realized. The next chapter focuses on memory skills, which have recently been studied as another important and influencing learner characteristic in multimedia learning.