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the words are presented in the lessons and pictures are generated
by the students, so a control group that receives author-generated
pictures is warranted.
Third, research on drawing mostly used only one way to support
the drawing strategy at a specific time. That is, instructional
support was added during learning (i.e., by using cut-out figures or
a drawing prompt; (cf., Lesgold et al., 1975, 1977; Schwamborn et al.,
2010) or after learning (i.e., by providing pictures, van Meter, 2001;
van Meter et al., 2006). Less is known about whether
adding instructional support not only during learning but also after
learning can additionally enhance the benefits of the drawing
strategy.
Fourth, research on drawing should include motivational and
cognitive aspects that may have an impact on the effectiveness of
the learner-generated drawing strategy. Students’ current motivation,
for example, is a one condition for successful learning. A student,
for example, who has low motivation to learn, may invest less
effort in learning than students who are highly motivated to learn
(cf., Vollmeyer & Rheinberg, 2000). Students’ spatial ability may
be a further condition for successful learning when working
with visualizations (cf., Höffler, 2010; Höffler, Schmeck, & Opfermann,
2013). A high-spatial-ability student, for example, may have
advantages in learning with visualizations compared with a lowspatial-
ability student. That is, preexisting motivational and cognitive
differences between students before learning might have
an influence on the learning outcome, and thus should be
controlled.
In addition, recent research has shown that not only experimental
conditions (such as the kind of picture) and the above
mentioned “classical” covariates can have an impact on how successful
learning takes place, but that these effects can be mediated
by the amount of mental effort someone invests while learning or
working on a lesson; and by how difficult someone perceives a
domain or lesson to be (cf., Leutner et al., 2009; Schwamborn,
Thillmann, Opfermann, & Leutner, 2011). These aspects of cognitive
load (invested mental effort and perceived task difficulty) were
thus included as additional variables in our studies as well. Thus,
we conducted the following two experiments using a science text
explaining the biological process of influenza. In Experiment 1 we
implemented an experimental drawing condition and a reading only
control condition, in order to determine how both the generative
and the prognostic drawing effect would extend to a new context.
Analogous to the study of Schwamborn et al. (2010), students in
the drawing condition received a baseline instructional support by
means of a drawing prompt that included a legend showing all the
relevant elements for drawing and a partly pre-drawn background
for their drawing (as shown in Fig. 1).
In Experiment 2,we again implemented an experimental drawing
condition and a reading only control condition, and we additionally
implemented author-generated pictures, in order to test whether
the generative drawing effect was caused by the simple presence
of illustrations rather than the generation of illustrations. That is,
we implemented a text plus picture condition (which we called the
author-generated picture condition), to test whether the reported
generative drawing effect of Schwamborn et al. (2010) is based on
students’ engagement in generative learning activities during reading
rather than on the pictorial representations given by the drawing
prompt. In addition, we implemented a drawing plus picture condition
(in which students both draw and are given a picture), to test
whether the reported generative drawing effect can be enhanced
by instructing students to compare their own drawing with an
author-generated picture. In short, we tested whether combining
different forms of support to the drawing strategy additionally enhances
the benefits of the drawing strategy. In both experiments,
learning outcome tests that are sensitive to the underlying process
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