Research on Cognitive Load Theory: Application to E-Learning

TL;DR: The purpose of this article is to review and critique each of the research studies published in this special issue, derive one or more instructional design heuristics based on the findings for each study, and provide recommendations for extending particular lines of research.

Abstract: The purpose of this article is to review and critique each of the research studies published in this special issue. We will critique each article, derive one or more instructional design heuristics based on the findings for each study, and provide recommendations for extending particular lines of research. Three suggestions are provided concerning cognitive load theory and instructional design adaptations for e-learning.

Summary

Research on Cognitive Load Theory: Application to E-Learning

• The purpose of this article is to review and critique each of the research studies published in this special issue.
• In the traditional, face-to-face classroom, instructional designers tend to rely on the instructor or the students’ peers to make needed adaptations and support if a student fails to understand an idea.
• The authors wish to caution the reader that these heuristics are based on the studies presented in this special issue rather than on multiple studies.

TRACEY CLARKE, PAUL AYRES, AND JOHN SWELLER

• In many cases it is assumed that using technology will enhance learning efficacy by improving both the efficiency and effectiveness of the learning experience.
• In e-learning environments, students are expected to learn how to use delivery technology such as Blackboard and WebCt, including skills such as chatting online, participating in threaded discussions, and posting assignments.
• In many cases learning about the delivery technology takes place concurrently with the learning of content and accomplishment of primary content goals.
• Two sequencing strategies, (a) learning spreadsheet skills and then mathematical concepts in sequence, and (b) learning spreadsheet skills and mathematics concepts concurrently were included.
• A subjective measure of cognitive load was also administered.

Future Research Recommendations

• Kalyuga and Sweller indicated that a less intrusive measure is needed in an e-learning environment.
• This measure would be useful for not only adaptive instructional research, but also other cognitive load studies.
• Studies such as Kalyuga and Sweller’s, that extend cognitive load research beyond message design into the area of instructional strategy design, provide an important and interesting approach to the design of instruction.

A. AUBTEEN DARABI

• Studies with external validity are of particular interest to the instructional designer (Ross & Morrison, 1989).
• Typically, these studies use realistic materials and employ realistic environments as opposed to the highly controlled environments of a basic research study.
• They suggest that motivation may be a critical factor in the design of instructional materials that engage the learner and enhance the learner’s effort.
• Designers are constantly faced with finding an optimum balance between easy and difficult materials that will challenge the learner while trying to avoid frustration or materials so easy that the learner’s effort results in only meager gains.

1. Exploratory practice results in greater involvement than do worked examples for experienced students.

• Problem-based learning (PBL) and worked examples provide two contrasting approaches to instructional design.
• PBL can provide a rich, realistic context that allows the learner to explore various options, whereas worked examples provide a guided approach.
• This heuristic suggests that students with no prior knowledge might benefit first from worked examples, then move to a PBL environment to increase their involvement and mental effort.

2. Students with no prior knowledge will have less efficiency with exploration practice than with worked examples.

• The efficiency of such practice may be an issue when there is limited time for the training.
• If an exploratory strategy is needed or more appropriate, students with no prior knowledge might first start with worked examples before using the exploratory examples.

ROXANA MORENO AND FRED VALDEZ

• It is clear that learners are required to process many external representations during their elearning experiences.
• Investigations examining the impact of multiple representations on learning and cognitive processing are warranted (Anglin, Vaez, & Cunningham, 2004).
• Incorporating Mayer and Moreno’s (2003) cognitive theory of multimedia learning (CTML), Moreno and Valdez examined the effect of interactivity and feedback when learning from either single or multiple ( and pictures) external representations in the area of meteorology.
• Retention and problem solving were assessed and cognitive load was measured using a subjective measure.

WOLFGANG SCHNOTZ AND THORSTEN RASCH

• Results of studies examining the effect of animations on learning have been mixed.
• Schnotz and Rasch investigated the effect of two types of animations on knowledge acquisition.
• Schnotz and Rasch also distinguished between learners with high and low learning prerequisites.
• They did not directly measure cognitive load.
• The authors have identified one heuristic in this study; however, a number of the effects identified by Schnotz and Rasch were reported as marginally significant.

ERIK WALLEN, JAN L. PLASS, AND ROLAND BRÜNKEN

• Managing cognitive load is a critical issue when designing e-learning.
• If the combination of intrinsic and extraneous load is too great, the learner will not develop an understanding of the instructional content as intended.
• The individualized nature and separation of the learner from other learners and the instructor in e-learning places a greater responsibility for developing an understanding on the individual learner than in the traditional face-to-face classroom.
• The article by Wallen, Plass, and Brünken investigated the use of text annotations to support the develop- ment of schemas.
• Three strategies, using (a) selection, (b) organization, and (c) integration were tested individually and in pairs to determine their effectiveness for enhancing learning.

1. Adding verbal annotations to text can improve recall and transfer performance.

• Providing learners with definitions of terms with contextual information (selection level), brief explanations of an idea in the specific context (organization level), or by showing links of ideas in a paragraph (integration level) can enhance recall of terms and ideas.
• Integrating one of these strategies does not appear to increase extraneous cognitive load significantly, but rather, it may enhance germane cognitive load.
• This strategy is potentially useful as a means of providing additional instructional support for the e-learning student.

2. Selection and organization-level annotations can enhance comprehension.

• When the recall of idea units rather than words is the goal, learner performance is enhanced with the use of selection and organization-level annotations.
• Thus, providing definitions and explanations as an adjunct to the text can enhance recall of idea units.

3. Providing more than one type of annotation results in a decrease in performance.

• When using annotations to enhance learning, increasing the types of annotation results in a degrading effect.
• That is, using both selection and organization-level annotation results in a lower performance than using only selection or organization-level annotation.
• The additional annotation increases the amount of text a learner must process and may result in an increase in extraneous cognitive load.
• This increase in cognitive load may exceed the learner’s capacity and result in the failure to develop an adequate schema for the material.

1. Designing deliberate practice strategies to enhance germane cognitive load can lead to the development of expertise.

• Mindful design of learner-appropriate, deliberate practice that includes feedback to encourage learners to reflect on their errors may enhance germane cognitive load.
• Strategies can incorporate reflection, and other elaboration strategies can enhance learning from errors.

2. The effectiveness of deliberate practice is enhanced if the learner is motivated.

• Learners must not only be motivated to engage in the practice, they must also be engaged in a mindful way so that they can make effective use of the feedback to correct errors and develop appropriate schemas.
• Research on feedback has found that learners who are motivated in a realistic setting will make more mindful use of feedback than students who are simply participating in an experiment (Morrison, Ross, Gopalakrishnan, & Casey, 1995).
• Instructional designers need to devise an instructional strategy that is not only engaging, but is also motivating.

SLAVA KALYUGA AND JOHN SWELLER

• The use of adaptive models using various algorithms and approaches has a rich history of research in the field of instructional technology (Ross, 1984; Ross & Rakow, 1982; Tennyson & Buttery, 1980; Tennyson & Rothen, 1979).
• Kalyuga and Sweller have extended this research by using cognitive load as an adapting variable.
• By using a rapid measure of semantic knowledge and a subjective cognitive load measure, they calculated cognitive efficiency to adapt instruction to each learner.
• Combining these two measures allows the designer to adapt the instruction for the next step as well as the level of difficulty.

1. Making adaptive decisions based on performance and a subjective measure of cognitive load may result in more efficient learning.

• This heuristic provides an alternative to designing one form of instruction and relying on time as the individualization factor.
• To implement this approach, designers would need to have instruction written for at least two levels of difficulty and implement a rapid assessment approach.
• The participants in the study were 10th-grade students who participated in frequent testing as part of the learning process.
• Adults who are not as accustomed to frequent testing may not be as successful or willing to learn using this approach.

SUMMARY

• Early research based on cognitive load theory attempted to identify methods of reducing extraneous cognitive load (Sweller et al., 1998).
• Germane cognitive load, and perquisite skills.the authors.
• More research needs to be completed to provide a sound research base for their heuristics.
• Thus, researchers should consider conducting applied studies that sacrifice some internal validity at the expense of higher external validity.
• Correspondence concerning this article should be addressed to Gary R. Morrison, Educational Curriculum and Instruction, Education 145, Old Dominion University, Norfolk, VA 23529.

Full text

Research on Cognitive Load Theory:
Application to E-Learning
Gary R. Morrison
Gary J. Anglin
The purpose of this article is to review and
critique each of the research studies published
in this special issue. We will critique each
article, derive one or more instructional design
heuristics based on the findings for each study,
and provide recommendations for extending
particular lines of research. Three suggestions
are provided concerning cognitive load theory
and instructional design adaptations for
e-learning.
The design and development of e-learning
materials presents the instructional designer
with an environment, opportunities, and con-
straints quite different from those associated
with the design of instruction for a traditional
classroom context. In the traditional, face-to-face
classroom, instructional designers tend to rely
on the instructor or the students’ peers to make
needed adaptations and support if a student
fails to understand an idea. A student who fails
to understand a lesson typically has immediate
access to the instructor or other students to ask
questions or to test their understanding. In an e-
learning environment, a student may start a les-
son at 2:00 a.m. and e-mail an instructor at 2:45
a.m. asking for help with understanding a con-
cept. Lacking an available instructor or peer, the
student may stop studying in frustration, or
worse, develop a misconception.
The design of e-learning instruction and the
actual learning take place in two different time
frames. That is, the instructor first designs the
instruction and then, a month or more later, the
student uses the instructional materials to learn
the content. This separation of design and actual
learning requires the learner to reintegrate the
teaching and learning process (Keegan, 1996),
often, in the absence of the instructor. This rein-
tegration process places a significant responsi-
bility on the learner for developing an
understanding without the direct and immedi-
ate support of the instructor and peers. To
address this problem, Holmberg (1989) sug-
gested that designers develop a guided didactic
conversation or internal speech the student has
with the instructor as the student processes the
instructional materials.
If the instructional designer creates instruc-
tional materials that impose too much extrane-
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ous load, then the student will not develop an
understanding of the course content. The articles
in this special issue of Educational Technology
Research and Development (ETR&D) address three
general categories of strategies designers can use
to address the design of e-learning materials.
Proper management of cognitive load through
sound instructional design principles are an
essential component for the design of efficient
and effective e-learning materials that lead to an
understanding of the content by the individual
learner who has the option of learning 24/7.
Our goal in this article is to provide a sum-
mary of the main articles in the special issue,
identify design heuristics that instructional
designers can apply to the design of e-learning
materials, and provide suggestions for future
research. We wish to caution the reader that
these heuristics are based on the studies pre-
sented in this special issue rather than on multi-
ple studies. The heuristics should be used with
caution until they are validated with additional
research.
TRACEY CLARKE, PAUL AYRES, AND
JOHN SWELLER
In many cases it is assumed that using technol-
ogy will enhance learning efficacy by improving
both the efficiency and effectiveness of the learn-
ing experience. In e-learning environments, stu-
dents are expected to learn how to use delivery
technology such as Blackboard and WebCt,
including skills such as chatting online, partici-
pating in threaded discussions, and posting
assignments. In many cases learning about the
delivery technology takes place concurrently
with the learning of content and accomplish-
ment of primary content goals. At the lesson
level, students may be expected to use technol-
ogy and software as part of a content learning
experience (strategy). Clarke, Ayres, and Sweller,
informed by cognitive load theory, examined the
impact of the timing of learning technology skills
(spreadsheet skills) when learning mathematical
concepts. Two sequencing strategies, (a) learning
spreadsheet skills and then mathematical con-
cepts in sequence, and (b) learning spreadsheet
skills and mathematics concepts concurrently
were included. A subjective measure of cogni-
tive load was also administered.
Heuristic
We present one heuristic based on the Clarke et
al. study that could be considered when
designing e-learning materials. The reader
should be cautioned that our heuristic is based
on the results of one study, with a relatively low
sample size, that focused on learning mathemat-
ical concepts. The primary finding is compatible
with the expectation of an expertise reversal
effect (Kalyuga, Ayres, Chandler, & Sweller,
2003). We will state our heuristic in general
terms, knowing that additional research needs
to be conducted to confirm our initial general-
ization.
1. A strategy requiring initial learning of technology
skills, then particular content area concepts, will
enhance learning for students with a low level of
technology skills.
For students with a low level of technology
knowledge and skill, the technology content
most likely has high element interactivity.
Intrinsic cognitive load may be increased if tech-
nology skills and specific subject content area
concepts are learned concurrently. The learner’s
level of technology skills, and the level of con-
tent element interactivity are critical variables
when determining the sequencing strategy
(Kalyuga et al., 2003; van Merriënboer, Kirsch-
ner, & Kester, 2003).
Future Research Recommendations
Jeroen J. G. van Merriënboer and Paul Ayres, in
their introduction to this special issue of
ETR&D, suggest that early research informed by
cognitive load theory focused on the use of
instructional methods to reduce extraneous cog-
nitive load, whereas more recent research con-
cerns the impact of instructional methods on
germane and intrinsic cognitive load given the
prior knowledge level of learners. In the Clarke
et al. study it is reported that students with low
prerequisite knowledge of spreadsheets learned
mathematics concepts more efficiently if the
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RESEARCH ON COGNITIVE LOAD 95

spreadsheet skills were learned prior to learning
the mathematics content. However for more
experienced spreadsheet users, Clarke et al. did
not report significantly different performance on
mathematics learning test scores for students
receiving spreadsheet and mathematics content
instruction concurrently. Future research on
sequencing strategies (sequential and concur-
rent), including technology and mathematics
content with high element interactivity, is
needed. It would also be appropriate to examine
if the effects found by Clarke et al. can be repli-
cated with other content areas such as history
and knowledge domains. If the results of such
replication studies were similar to the results
reported by Clarke et al. there would be more
general support for the expertise reversal effect
across content disciplines.
Given relative low sample size, 9 students in
the sequential group and 11 students in the con-
current group, statistical power may be lacking
in the analysis. Additional studies with larger
sample sizes would help to further determine
effectiveness of sequential and concurrent
sequencing strategies. Clarke et al. used self-
assessment reports to “measure” cognitive load
and spreadsheet skills. Although self-assess-
ment is a useful research tool, we recommend
for future research that cognitive load and
spreadsheet skills be directly assessed or mea-
sured. Finally, future studies extending the
work of Clarke et al. should be conducted with
students actually enrolled in e-learning courses.
This approach would improve the ecological
validity of future investigations.
FRED PAAS, JUHANI E. TUOVINEN,
JEROEN J. G. VAN MERRIËNBOER, AND
A. AUBTEEN DARABI
Studies with external validity are of particular
interest to the instructional designer (Ross &
Morrison, 1989). Typically, these studies use
realistic materials and employ realistic environ-
ments as opposed to the highly controlled envi-
ronments of a basic research study. Extending
basic research findings with applied research
through the use of realistic materials and envi-
ronments provides valid insights as to how our
instructional designs will be used in a realistic
setting (Ross & Morrison, 2004). Paas, Tuovinen,
van Merriënboer, and Darabi have taken a sim-
ilar approach in their research that introduces
motivation as a variable for optimizing instruc-
tional materials. They suggest that motivation
may be a critical factor in the design of instruc-
tional materials that engage the learner and
enhance the learner’s effort. Of particular inter-
est in their research is the effect of realistic mate-
rials on learner motivation in contrast to the
effort and motivation observed in studies with
high internal validity that may use contrived or
artificial materials.
Paas et al.’s calculation of task involvement
provides an interesting approach to a new
research area. What effect does learner motiva-
tion have on task involvement (i.e., task perfor-
mance)? Designers are constantly faced with
finding an optimum balance between easy and
difficult materials that will challenge the learner
while trying to avoid frustration or materials so
easy that the learner’s effort results in only mea-
ger gains. Paas et al.’s task-involvement concept
provides some insight into how designers might
adapt materials to individual learner needs.
Heuristics
We have identified two heuristics from this arti-
cle that are applicable to an e-learning environ-
ment. The first is based on a trend in the data
rather than on significant findings and should
be used with caution until future research can
validate the heuristic.
1. Exploratory practice results in greater involve-
ment than do worked examples for experienced
students.
Problem-based learning (PBL) and worked
examples provide two contrasting approaches
to instructional design. PBL can provide a rich,
realistic context that allows the learner to
explore various options, whereas worked exam-
ples provide a guided approach. Both
approaches have been validated (Albanese &
Mitchell, 1993; Dochy, Segers, Van den Bossche,
& Gijbels, 2003; Paas & Van Merriënboer, 1994;
Sweller & Cooper, 1985). This heuristic suggests
that students with no prior knowledge might
benefit first from worked examples, then move
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96 ETR&D, Vol. 53, No. 3

to a PBL environment to increase their involve-
ment and mental effort.
2. Students with no prior knowledge will have less
efficiency with exploration practice than with
worked examples.
Although an exploratory or open-ended
learning environment might provide more
engagement for all learners, the efficiency of
such practice may be an issue when there is lim-
ited time for the training. If an exploratory strat-
egy is needed or more appropriate, students
with no prior knowledge might first start with
worked examples before using the exploratory
examples.
Future Research Recommendations
We agree with Paas et al. that future research
considering cognitive load theory and motiva-
tion should focus on realistic environments.
Similarly, future research should attempt to rep-
licate and validate many of the research findings
in realistic settings to provide instructional
designers with more robust information.
Another recommendation is for the develop-
ment of unobtrusive measures of motivation
and cognitive load that instructional designers
can use to adapt e-learning materials during the
instruction. Last, we suggest that future studies
examine the effect of cognitive load on motiva-
tion in a variety of conditions that affect motiva-
tion.
ROXANA MORENO AND FRED VALDEZ
It is clear that learners are required to process
many external representations during their e-
learning experiences. Investigations examining
the impact of multiple representations on learn-
ing and cognitive processing are warranted
(Anglin, Vaez, & Cunningham, 2004). Incorpo-
rating Mayer and Moreno’s (2003) cognitive the-
ory of multimedia learning (CTML), Moreno
and Valdez examined the effect of interactivity
and feedback when learning from either single
(words) or multiple (words and pictures) exter-
nal representations in the area of meteorology.
Retention and problem solving were assessed
and cognitive load was measured using a sub-
jective measure.
Heuristics
We present two tentative design heuristics
based on the results from the Moreno and Val-
dez investigation. The reader is reminded that
more research is needed in order to confirm that
out heuristics apply across various content
areas.
1. Presenting two integrated nonredundant external
representations (verbal and visual) in contrast to
one (verbal or visual) will result in higher student
performance levels and require less mental effort
by learners.
The findings reported by Moreno and Valdez
in Experiment 1 support the claim that two
external representations (visual, verbal) facili-
tate student learning better than either of the sin-
gle external representations, visual or verbal.
Similar effects were identified for both cognitive
load and learning efficiency. There are many
kinds of interactivity and feedback. Our heuris-
tic is developed assuming that designers would
use the specific types of interactivity (organize
causal chain of events) and feedback (frame-by-
frame) included in the Moreno and Valdez
study.
2. Strategies for interactivity that involve the
learner in the process of understanding (schema
development) prior to feedback will enhance
transfer learning.
In many technology-based instructional pro-
grams, information is presented to the learners
and they are asked to view worked examples,
construct an argument, or perform a critical
evaluation. After the student response, feedback
is given to learners concerning the quality of
their response. The results of Experiment 3 in
Moreno and Valdez provide evidence that this
may not be the best strategy. It may be more
appropriate to include interactivity that helps
the students construct meaning and develop
understanding relative to the instructional con-
tent before giving them feedback.
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RESEARCH ON COGNITIVE LOAD 97

Future Research Recommendations
The Moreno and Valdez study is based on
Mayer and Moreno’s (2003) CTML. The CTML
incorporates three assumptions: (a) dual coding
(Clark & Paivio, 1991), (b) active processing
(meaning construction), and (c) limited working
memory. The results of the Moreno and Valdez
study are consistent with CTML. Future studies
could replicate and extend the studies by includ-
ing content from disciplines other than science
or mathematics, given that online learning expe-
riences with technology are being designed and
developed for many content areas. Investigation
of the impact of additional interaction strategies
that engage the student in the understanding
and meaning-making process, as well as feed-
back timing, would also be appropriate.
The Moreno and Valdez study focused on the
impact of two external representations on learn-
ing and working memory load in a multimedia
environment. There are a myriad of external
representations presented to students in e-learn-
ing materials, verbal and visual. We are not con-
vinced that many of the external representations
included in e-learning materials promote effec-
tive cognitive processes for learning. As with the
early research conducted to determine the
effects of pictures and illustrations on learning,
we think a framework that considers the func-
tions that multiple external representations
serve in learning materials would be useful to
researchers (Anglin et al., 2004). Ainsworth
(1999) has provided a taxonomy that could be
invaluable to researchers attempting to deter-
mine the effectiveness of multirepresentational
learning contexts. Ainsworth presented three
major functions, and additional subfunctions, of
multiple external representations in instruc-
tional materials: (a) complimentary roles, (b)
constrain interpretation, and (c) construct
deeper understanding. It is clear that students
do have trouble translating across multiple rep-
resentations. The translation process is assumed
to increase working memory load, as for exam-
ple in the split attention effect (Sweller, van
Merriënboer, & Paas, 1998). Translation prob-
lems can occur when the learner is translating
across verbal representations only, visual repre-
sentations only, or both. Studies that consider
how multiple representations function and stud-
ies that attempt to identify effective translation
processes required by the learner across func-
tions are needed. Such research would help
identify “how translations across representa-
tions should be supported to maximize learning
outcomes” (Ainsworth, p. 132).
WOLFGANG SCHNOTZ
AND THORSTEN RASCH
Results of studies examining the effect of anima-
tions on learning have been mixed. When
designing e-learning materials, it is important
for the instructional designer to make sound and
informed decisions concerning the inclusion of
animations in e-learning materials for optimal
student learning and understanding. Schnotz
and Rasch investigated the effect of two types of
animations on knowledge acquisition. The
investigators identified two functions of anima-
tions, enabling and facilitating, that are assumed
to reduce cognitive load. Schnotz and Rasch also
distinguished between learners with high and
low learning prerequisites. They did not directly
measure cognitive load. We have identified one
heuristic in this study; however, a number of the
effects identified by Schnotz and Rasch were
reported as marginally significant. Therefore, the
reader is cautioned that more research needs to
be conducted to confirm or deny our heuristics.
Heuristic
1. For learners with high learning prerequisites,
inclusion of animated pictures that can be manip-
ulated will enhance learning and allow for cogni-
tive processing that would otherwise not be
possible.
The results reported by Schnotz and Rasch
based on their 2-experiment study provide evi-
dence for the claim that different types of anima-
tions perform different functions in the learning
process. Animations (manipulation) designed to
enable cognitive processing were effective for
learners with high learning prerequisites.
Schnotz and Rasch also reported that anima-
tions (simulation) designed to reduce cognitive
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Frequently asked questions

Q1. What have the authors contributed in "Research on cognitive load theory: application to e-learning" ?

The purpose of this article is to review and critique each of the research studies published in this special issue. The authors will critique each article, derive one or more instructional design heuristics based on the findings for each study, and provide recommendations for extending particular lines of research. Three suggestions are provided concerning cognitive load theory and instructional design adaptations for e-learning. 

Q2. What are the future works mentioned in the paper "Research on cognitive load theory: application to e-learning" ?

Future research on sequencing strategies ( sequential and concurrent ), including technology and mathematics content with high element interactivity, is needed. Although self-assessment is a useful research tool, the authors recommend for future research that cognitive load and spreadsheet skills be directly assessed or measured. Finally, future studies extending the work of Clarke et al. should be conducted with students actually enrolled in e-learning courses. The authors agree with Paas et al. that future research considering cognitive load theory and motivation should focus on realistic environments. 

Q3. What areas of study should be considered in future studies?

Future studies should consider less-structure areas such as interpersonal and management skills, where researchers might vary the complexity and difficulty of cases or examples to teach a concept or rule. 

Q4. What is the role of the instructor in e-learning?

The individualized nature and separation of the learner from other learners and the instructor in e-learning places a greater responsibility for developing an understanding on the individual learner than in the traditional face-to-face classroom. 

Q5. What is the way to improve transfer learning?

2. Strategies for interactivity that involve the learner in the process of understanding (schema development) prior to feedback will enhance transfer learning. 

Q6. What are the key variables when determining the sequencing strategy?

The learner’s level of technology skills, and the level of content element interactivity are critical variables when determining the sequencing strategy (Kalyuga et al., 2003; van Merriënboer, Kirschner, & Kester, 2003). 

Q7. What is the heuristic for the Moreno and Valdez study?

Their heuristic is developed assuming that designers would use the specific types of interactivity (organize causal chain of events) and feedback (frame-byframe) included in the Moreno and Valdez study. 

Q8. What is the effect of the cognitive theory of multimedia learning?

Incorporating Mayer and Moreno’s (2003) cognitive theory of multimedia learning (CTML), Moreno and Valdez examined the effect of interactivity and feedback when learning from either single (words) or multiple (words and pictures) external representations in the area of meteorology.