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The study examined viewing behaviour and learning outcome during multimedia learning in order to explore split-attention processes in modality and spatial contiguity effects. Fourty students viewed a computer instruction depicting the process of lightning. Exploratory text was spoken, written near or written far from accompanying animations. Students who received spoken text outperformed students who received written text in recalling the major steps (retention) and in identifying correct solutions to problems (transfer), replicating a modality effect. Differences between near and far written text presentation in retention (d ¼ 0.51) and transfer (d ¼ 0.68) tests failed statistical significance. Two major characteristics concerning the learners' viewing behaviour were identified: (a) in written text presentation, learning was largely text directed and (b) learning success was related to the time learners' spent looking at animations, indicating that the processing of animations is a crucial factor in explanations of modality and spatial contiguity effects.A basic affordance for learners in a multimedia learning environment is to extract and integrate information from different sources of information like words and pictures. A common recommendation for instructional designers is (a) to present words near rather than far from corresponding pictures or, better yet, (b) to present those corresponding words as spoken rather than printed text (e.g. Mayer, 2001). These empirically wellsupported recommendations are known as (a) the spatial contiguity principle (for a recent review of contiguity effects, see Ginns, 2006) and (b) the modality principle (for a recent review of modality effects, see Ginns, 2005).For example, Moreno and Mayer (1999, Experiment 1) presented a sequence of 16 animated illustrations depicting the process of lightning. The animations visualized e.g. the motion of cool air that becomes heated or positive charges moving up to the cloud producing a flash light. Animations were accompanied by an expository text describing each of the major events. Text was spoken, written inside the visualization frame or written below the visualization frame. Participants performed better on subsequent retention and transfer tests when (a) text was spoken rather than written (modality effect) APPLIED COGNITIVE PSYCHOLOGY

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Standard factorial designs in psycholinguistics haveThe precision of theoretical accounts in the field of visual word recognition has significantly increased over recent years. Indeed, cognitive modelers have proposed several detailed descriptions of the structure and dynamics of the reading system (e.g., Ans, Carbonnel, & Valdois, 1998;Coltheart, Rastle, Perry, Langdon, & Ziegler, 2001;Grainger & Jacobs, 1996;Harm & Seidenberg, 2004;Perry, Ziegler, & Zorzi, 2007;Plaut, McClelland, Seidenberg, & Patterson, 1996;Seidenberg & McClelland, 1989). The fine-grained precision of these models has led to the development of so-called computational models of reading that can generate precise quantitative predictions. As a consequence, by making fine-grained assumptions about the cognitive architecture of visual word recognition, theorists have also remarkably increased the resolution of theoretical predictions.This progress in theory has been accompanied by a corresponding gain of precision for empirical data. In a seminal study, Spieler and Balota (1997) asked 31 participants to read aloud a list of 2,870 English monosyllabic words and compared the mean naming latency for each item with the predictions of two computational models of word reading (i.e., Plaut et al., 1996;Seidenberg & McClelland, 1989). The results were somewhat surprising, since both of these models accounted for only a small amount of the item variance (3.3% for Plaut et al.'s model, 10.1% for Seidenberg and McClelland's). Spieler and Balota also noticed that the models explained the amount of variance less well than did the linear combination of three simple linguistic predictors: log frequency, word length, and neighborhood density (which accounted for 21.7% of the variance). Finally, when variables related to onset phonemes were added to the analysis, the simple predictors were able to account for 42% of the item variance. Item-level data therefore seem to provide a critical test for computational models of reading.Seidenberg and Plaut (1998) claimed, however, that two reasons might explain the relatively low item variance accounted for by these models. First, item means are affected by several factors that are not addressed by these models. For example, they do not specify the processes involved in letter recognition or in the production of articulatory output. Balota and Spieler (1998) noticed, however, that the performance of these models remains surprisingly weak, since they fail to explain more variance than do three simple predictors (i.e., log frequency, word length, and neighborhood density) that are, in principle, captured by these models. Their second, and probably more critical, argument is based on the fact that item data include a substantial amount of error variance. The question is how substantial this amount of error variance is. Comparing Spieler and Balota's database with a similar database recorded by Seidenberg and Waters (1989), 1 they found a .54 correlation between item latencies in the two databases. This relatively low correla...