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Learning as a Generative Activity: Eight Learning Strategies that Promote Understanding

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During the past twenty-five years, researchers have made impressive advances in pinpointing effective learning strategies (i.e., activities the learner engages in during learning that are intended to improve learning). In Learning as a Generative Activity: Eight Learning Strategies That Promote Understanding, Logan Fiorella and Richard E. Mayer share eight evidence-based learning strategies that promote understanding: summarizing, mapping, drawing, imagining, self-testing, self-explaining, teaching, and enacting. Each chapter describes and exemplifies a learning strategy, examines the underlying cognitive theory, evaluates strategy effectiveness by analyzing the latest research, pinpoints boundary conditions, and explores practical implications and future directions. Each learning strategy targets generative learning, in which learners actively make sense out of the material so they can apply their learning to new situations. This concise, accessible introduction to learning strategies will benefit students, researchers, and practitioners in educational psychology, as well as general readers interested in the important twenty-first-century skill of regulating one's own learning.
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1
Summary
is book is based on the idea that meaningful learning is a generative
activity in which the learner actively seeks to make sense of the presented
material. e study of generative learning has implications for the sci-
ence of learning, the science of assessment, and the science of instruc-
tion. Concerning the science of learning, generative learning takes place
when the learner engages in appropriate cognitive processing during
learning, including attending to the relevant information (i.e., selecting),
mentally organizing incoming information into a coherent cognitive
structure (i.e., organizing), and integrating the cognitive structures with
each other and with relevant prior knowledge activated from long-term
memory (i.e., integrating). Concerning the science of assessment, gener-
ative learning is demonstrated when students who learn with generative
learning strategies or generative instructional methods perform better
on transfer tests than students who learn from standard instruction.
Concerning the science of instruction, generative learning can be
p r o m o t e d t h r o u g h instructional methods aimed at designing instruc-
tion that primes appropriate cognitive processing during learning or
through learning strategies a i m e d a t t e a c h i n g s t u d e n t s h o w a n d w h e n t o
engage in activities that require appropriate cognitive processing during
learning. is book focuses on eight generative learning strategies that
have been shown to improve student learning: summarizing, mapping,
drawing, imagining, self-testing, self-explaining, teaching, and enacting.
e concept of generative learning has roots in the work of Wittrock and
others, continues as a dominant view of learning today, and shows prom-
ise of further development in the future.
1
Introduction to Learning as a Generative
Activity
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978-1-107-06991-6 - Learning as a Generative Activity: Eight Learning
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Logan Fiorella and Richard E. Mayer
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Learning as a Generative Activity
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Chapter Outline
1. Getting Started
2. What Is Generative Learning?
3. Implications of Generative Learning for the Science of Learning
4. Implications of Generative eory for the Science of Assessment
5. Implications of Generative eory for the Science of Instruction
6. What Is the Past and Future of Generative Learning?
Getting Started
What Can You Do?
S u p p o s e y o u s i t d o w n t o r e a d a b o o k c h a p t e r, y o u a t t e n d a P o w e r P o i n t l e c -
ture, or you view an online multimedia presentation. You are pro cient at
reading and listening, so you can easily understand all the words. Yet, when
you are nished with the lesson, you are not able to apply what you have
learned to new situations or to use the material to solve problems. What
could you have done to help you understand the material rather than sim-
ply to process every word?
is book is concerned with exploring what the research evidence has
to say about answering this seemingly simple question. Our proposed
solution is that you could engage in generative learning strategies during
learning – activities that are intended to prime appropriate cognitive pro-
cessing during learning (such as paying attention to the relevant infor-
mation, mentally organizing it, and integrating it with your relevant prior
knowledge).
For example, you could try to summarize the material in your own words
(perhaps by taking summary notes), you could create a spatial summary of
the material as a matrix or network, you could make a drawing that depicts
the main ideas in the text, or you could just imagine a drawing. ese are all
ways of translating the lesson into another form of representation.
A l t e r n a t i v e l y , y o u c o u l d g i v e y o u r s e l f a p r a c t i c e t e s t o n t h e m a t e r i a l ( s u c h
as trying to answer some questions), you could explain the material aloud
to yourself during learning, you could explain the material to someone else,
or you could use concrete objects to act out the material in the lesson. ese
are all ways of elaborating on the material.
Exploring each of these eight kinds of generative learning strategies is
the primary goal of this book.
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Introduction 3
Try is
L e t s b e g i n w i t h a b r i e f a s s e s s m e n t o f y o u r v i e w o f l e a r n i n g . M o s t p e o p l e
have an implicit theory of learning, because we all have spent so much time
in school. Please place a check mark next to each item that corresponds
with your conception of how learning works.
Learning works by engaging in hands-on activity, so it is better for
you to learn by doing rather than by being told.
L e a r n i n g w o r k s b y b u i l d i n g a s s o c i a t i o n s , s o y o u s h o u l d p r a c t i c e
giving the right response over and over.
L e a r n i n g w o r k s b y a d d i n g i n f o r m a t i o n t o y o u r m e m o r y , s o y o u
should work hard to nd and memorize new material.
L e a r n i n g o c c u r s w h e n y o u t r y t o m a k e s e n s e o f m a t e r i a l y o u e n c o u n -
ter, so you should strive to relate new information with your prior
knowledge.
L e a r n i n g i s a s o c i a l a c t i v i t y , s o i t i s b e t t e r f o r y o u t o l e a r n w i t h o t h e r s
in a group than to learn alone.
If you checked the fourth item, your view of learning corresponds to the
conception of generative learning proposed in this book – which simply
shows you have the good common sense to agree with us. As you will see
in this book, the learner’s cognitive processing during learning is a major
contributor to what is learned.
I f y o u a r e l i k e m o s t p e o p l e , y o u m a d e s o m e o t h e r c h e c k m a r k s . e rst
item is appealing, but according to the generative learning view, it focuses
too much on behavioral activity and not enough on cognitive activity.
Doing things does not necessarily cause learning, but thinking about what
you are doing does cause learning. us, the rst item should be modi ed
to say, “Learning works by engaging in appropriate cognitive activity during
learning.
e second item also seems appealing and is consistent with the rst the-
ory of learning to emerge in psychology and education more than a century
ago – which can be called associative learning . However, according to the
generative learning view, learning by forming associations applies to a nar-
row band of learning situations – such as learning to give the right response
for a given stimulus. Associative learning is not wrong, but it is just too lim-
ited. It does not deal with learning by understanding, which allows people
to take what they have learned and apply it in new situations.
e third item may sound familiar because it seems consistent with some
common educational practices such as asking students to attend hours of
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Learning as a Generative Activity
4
lectures or read hundreds of textbook pages. What is wrong with this item,
however, is that humans do not work like computers. We do not simply take
in what was presented and put it into our memory. Instead, we interpret it,
we reorganize it, and we relate to what we already know, thereby changing
what is presented from information (which is objective) into knowledge
(which is personal).
F i n a l l y , t h e l a s t i t e m i s c o n s i s t e n t w i t h a n e m e r g i n g v i s i o n o f l e a r n -
ing based on the idea that generative learning occurs best within group
c o n t e x t s t h a t i s , w h e n y o u c a n i n t e r a c t w i t h o t h e r s d u r i n g t h e l e a r n -
ing process. However, research on group learning tends to show that all
group interactions are not equally helpful in promoting meaningful learn-
ing. us, generative learning theory indicated by the fourth item can
be expanded to include social activities that promote appropriate cogni-
tive processing during learning and to exclude social activities that do not.
Overall, the point of this little exercise is to help you understand how the
generative learning view is di erent from what might seem like some com-
mon-sense views of learning.
Turning Passive Learning Situations into Active
Learning Situations
S u p p o s e t h a t y o u a r e a b o u t t o r e a d a t e x t b o o k c h a p t e r o n t h e h i s t o r y o f
the U.S. postal service, attend a PowerPoint lecture on how a virus causes a
cold, or view an online narrated animation explaining how lightning storms
develop. Each of these activities reading a book, attending a lecture, or
viewing an online presentation – seems like a passive experience destined
to foster suboptimal learning.
Yo u m i g h t b e s u r p r i s e d t o l e a r n t h a t t h e r e a r e e ective techniques that
can be used to turn such seemingly passive learning situations into active
learning experiences that produce meaningful learning. is book presents
eight ways to help people learn based on a generative theory of learning –
the idea that meaningful learning occurs when people engage in generative
processing during learning. In particular, each of the techniques seeks to
encourage learners to relate the represented material to what they already
know, or reorganize the presented material into a coherent structure, or
distinguish what is important from what is not. In this chapter, we describe
what we mean by generative learning; explain how generative learning con-
tributes to the science of learning, the science of assessment, and the sci-
ence of instruction; and end with a brief review of the history of scholarship
on generative learning.
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Introduction 5
What Is generative Learning?
L e a r n i n g i s a g e n e r a t i v e a c t i v i t y . is statement embodies a vision of
learning in which learners actively try to make sense of the instructional
material presented to them. ey accomplish this goal by actively engag-
ing in generative processing during learning, including paying attention
to the relevant aspects of incoming material (which we call selecting ),
organizing it into a coherent cognitive structure in working memory
(which we call organizing ), and integrating cognitive structures with rel-
evant prior knowledge activated from long-term memory (which we call
integrating ).
A s y o u c a n s e e , t h e l e a r n e r s c o g n i t i v e p r o c e s s i n g p l a y s a c e n t r a l r o l e i n
generative learning. Learning is not simply a process of adding information
to memory, as in a computer. Instead, learning depends both on what is
presented and on the learner’s cognitive processing during learning.
Similarly, the learner’s prior knowledge plays a central role in genera-
tive learning. Prior knowledge includes schemas, categories, models, and
principles that can help guide what the learner selects for further process-
ing, how the learner organizes it, and how the learner links it with other
structurally similar knowledge. us, learning depends both on what the
instructor presents and what the learner brings to the learning situation.
is is why two learners can be exposed to the same learning scenario such
as attending the same lecture or viewing the same online presentation – and
come away with quite di erent learning outcomes.
As summarized in Table 1.1 , not all forms of learning are generative
learning – that is, learning by understanding, which results in meaningful
learning outcomes. Another common form of learning is rote learning
that is, learning by memorizing, which results in rote learning outcomes.
Finally, there is also associative learning t h a t i s , l e a r n i n g b y s t r e n g t h e n -
ing associations, which results in rapid responses to well-learned stimuli.
Although there are other forms of learning, in this book, we focus on
Table 1.1. ree kinds of learning situations
Learning situation What happens What is enabled
Generative learning Making sense of information Solving new problems
Rote learning Memorizing information Remembering what was
presented
Associative learning Building associations Giving a response for a
stimulus
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Learning as a Generative Activity
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generative learning. In particular, we focus on ways to promote generative
learning because we are interested in helping students transfer what they
have learned to new situations.
O u r r a t i o n a l e f o r f o c u s i n g o n g e n e r a t i v e l e a r n i n g i s t h a t t h e t w e n t y - rst
century needs problem solvers and sense makers (Pellegrino & Hilton, 2012 ) .
e need for rote learning and associative learning is somewhat reduced
because we now have access to databases that can store vast amounts of
information or give answers to simple questions. e world needs people
who can select, interpret, and use information to solve new problems they
have not encountered before. In short, today’s focus on twenty- rst-century
skills such as creative problem solving, critical thinking, adaptability, com-
plex communication, and constructing evidence-based arguments can be
seen as a call for generative learning that helps people develop “transferable
knowledge and skills” (Pellegrino & Hilton, 2012 , p. 69).
Implications of Generative Learning
for the Science of Learning
e science of learning is the scienti c study of how people learn (Mayer,
2011 ) . is section examines the cognitive processes, memory stores, and
knowledge representations involved in generative learning, as well as the
motivational and metacognitive processes that support them.
Cognitive Processes in Generative Learning
H o w d o e s l e a r n i n g w o r k ? e basic premise of generative learning theories
is that learning occurs when learners apply appropriate cognitive processes
to incoming information. Figure 1.1 s u m m a r i z e s t h e SOI model of gen-
erative learning, w h i c h f o c u s e s o n t h r e e c o g n i t i v e p r o c e s s e s i n d i c a t e d b y
arrows – selecting, organizing, and integrating. As indicated by the arrow
from instruction t o sensory memory, i n s t r u c t i o n f r o m t h e o u t s i d e w o r l d
enters your cognitive system through your eyes and ears (or other senses)
and is brie y held in your sensory memory for a fraction of a second. If
you pay attention to some of this eeting information in sensory memory,
you transfer the attended material to working memory for further pro-
cessing (as indicated by the selecting a r r o w ) . I n w o r k i n g m e m o r y , y o u c a n
mentally reorganize the selected material into coherent mental representa-
tions (as indicated by the organizing a r r o w ) . Y o u c a n a l s o a c t i v a t e r e l e v a n t
prior knowledge from long-term memory and integrate it with incom-
ing material in working memory (as indicated by the integrating a r r o w ) .
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Introduction 7
e knowledge you build in working memory can be stored in long-term
memory for future use (as indicated by the arrow from working memory
to long-term memory ) a n d c a n b e u s e d t o s o l v e p r o b l e m s y o u e n c o u n t e r
in the outside world (as indicated by the arrow from working memory t o
performance ) .
A n i m p o r t a n t i n s t r u c t i o n a l i m p l i c a t i o n o f t h e S O I m o d e l i s t h a t t h e
instructor’s job is not only to present information but also to make sure his
or her students engage in appropriate processing during learning – including
selecting, organizing, and integrating. Similarly, the learners job is not to
memorize the information exactly as it is presented but to engage in appro-
priate cognitive processing during learning. Table 1.2 s u m m a r i z e s t h e t h r e e
cognitive processes in the SOI model of generative learning, which has been
continuously adapted to the study of learning strategies over the past thirty
SENSORY
MEMORY
WORKING
MEMORY
LONG-TERM
MEMORY
organizing
integrating
selecting
Instruction Performance
figure 1.1. e SOI Model of Generative Learning.
Table 1.2. ree cognitive processes in generative learning
Cognitive process Description Arrow in SOI Model
Selecting Attending to relevant material Arrow from sensory memory
to working memory
Organizing Mentally organizing incoming
material into a coherent
cognitive structure
Arrow from working
memory back to working
memory
Integrating Connecting cognitive structures
with each other and with
relevant material activated
from long-term memory
Arrow from long-tem
memory to working
memor y
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Table 1.3. ree memory stores in generative learning
Memory store Description Capacity Duration
Sensory memory Holds visual images and
sounds of what was presented
High Very short
Working memory Allows pictures and words to
be held and manipulated
Limited Short
Long-term memory Acts as permanent storehouse
of knowledge
High Lon g
years (Kiewra, 2005 ; M a y e r , 1988 , 1994 , 1996 , 2011 ; P e p e r & M a y e r, 1986 ;
Shrager & Mayer, 1989 ; Weinstein & Mayer, 1985 ) .
Memory Stores in Generative Learning
e SOI model of generative learning shown in Figure 1.1 contains three
memory stores, indicated by the boxes. Sensory memory h o l d s s e n s o r y c o p -
ies of the visual images you saw and the sounds you heard (and other input
from other senses) for a fraction of a second, so it has high capacity for
a very short duration. In working memory , p i e c e s o f i n f o r m a t i o n c a n b e
consciously held and manipulated, but the capacity of working memory is
quite limited so you can actively process only a few pieces of information
at any one time (and without active processing, information is lost within
about twenty seconds). Long-term memory i s y o u r p e r m a n e n t s t o r e h o u s e o f
knowledge, so it has high capacity and long duration.
A c c o r d i n g t o t h e S O I m o d e l s h o w n i n F i g u r e 1.1 , w o r k i n g m e m o r y i s a
sort of bottleneck in your cognitive system because it has limited processing
capacity (i.e., only a few elements can be actively processed at one time),
whereas sensory memory and long-term memory on either side of it each
have large capacities. An important instructional implication of this bot-
tleneck is that rapidly presenting a lot of information to a learner is likely
to overload the learner’s working memory and result in much of the infor-
mation being lost. e three memory stores in the SOI model of generative
learning are summarized in Table 1.3 .
Knowledge Representations in Generative Learning
I n a d d i t i o n t o u n d e r s t a n d i n g t h e b o x e s a n d a r r o w s i n F i g u r e 1.1 , i t i s
worthwhile to consider the kinds of external and internal representations
involved in generative learning. For example, consider what happens when
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Introduction 9
you attend a narrated slideshow lecture. We begin with the instructional
presentation involving spoken words, printed words, and graphics , which
become visual images and auditory sounds i n y o u r s e n s o r y m e m o r y , spatial
and verbal representations t h a t c a n b e m a n i p u l a t e d i n w o r k i n g m e m o r y ,
and semantic knowledge s t o r e d i n l o n g - t e r m m e m o r y . e conversion of
presented information (i.e., the external representation) into constructed
knowledge (i.e., the internal representation) is what happens when learners
engage in generative learning. ree important steps in the development
of knowledge in working memory are to select the pieces of information
for further processing, to build internal connections among them so they
form a coherent representation, and to build external connections with
other representations in a systematic way. Table 1.4 l i s t s t h e p r o g r e s s i o n o f
representations in generative learning.
Metacognition and Motivation in Generative Learning
G e n e r a t i v e l e a r n i n g r e q u i r e s t h a t l e a r n e r s a p p l y a p p r o p r i a t e c o g n i t i v e p r o -
cesses during learning, but how do learners know which processes to apply
and when to apply them? How do you know which information to select,
what kind of organization to build, and which aspect of prior knowledge
to activate? Monitoring and controlling your cognitive processes during a
cognitive task (such as learning from a lecture or from a book) is called
metacognition. us, an important task of generative learning theories is to
understand the workings of metacognitive strategies – that is, strategies for
monitoring and controlling cognitive processes.
E v e n i f y o u a r e s k i l l e d i n u s i n g t h e c o g n i t i v e p r o c e s s e s o f s e l e c t i n g , o r g a -
nizing, and integrating, and even if you possess the metacognitive strate-
gies for orchestrating them, you may still not engage in generative learning
because you just don’t want to. What causes people to initiate and maintain
generative processing at a high level during learning? Motivation i s d e ned
a cognitive state that initiates, energizes, and maintains goal-directed
behavior. In short, motivation drives the cognitive system, so it is crucial
Table 1.4. External and internal representations in generative learning
Representation Type Location
Printed words, spoken words, graphics External Instruction
Visual images and sounds Internal Sensory memory
Spatial and verbal representations Internal Working memory
Knowledge Internal Long-term memor y
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to incorporate motivational mechanisms into generative learning theory.
In particular, the learning strategies suggested in this book are intended
to motivate learners to engage in productive cognitive processing during
learning.
W e r e f e r t o m e t a c o g n i t i o n a n d m o t i v a t i o n a s t h e Mighty M’s because they
power the SOI model of generative learning shown in Figure 1.1 . W i t h o u t
the motivation to make sense of a lesson, generative learning would not be
initiated. Without the metacognitive skills to control cognitive processing
during learning, attempts at generative learning would not be e ective.
Implications of Generative Theory for the
Science of Assessment
e science of assessment is the scienti c study of how to determine what
people know (Anderson et al., 2001 ; M a yer, 2011 ; P e l l e g r i n o , C h u d o w s k y , &
Glaser, 2001 ) . I n t h i s s e c t i o n , w e d e s c r i b e t w o k i n d s o f t e s t i t e m s a n d t h r e e
kinds of learning outcomes.
Two Kinds of Test Items
T a b l e 1.5 s u m m a r i z e s t w o k i n d s o f t e s t i t e m s t h a t c a n b e u s e d t o a s s e s s
what students have learned, based on the classic distinction between reten-
tion a n d transfer . R e t e n t i o n i s t h e a b i l i t y t o r e c a l l o r r e c o g n i z e w h a t w a s
presented. us, retention items are used when the goal is to assess how
much of the presented material can be remembered. Transfer is the abil-
ity to apply what was learned to solve new problems. us, transfer items
are used when the goal is to assess how well someone understands the
presented material.
If we asked you to de ne retention , you could simply reproduce the sec-
ond sentence of the preceding paragraph, which is an example of a retention
Table 1.5. Two kinds of test items
Item Target Description Example
Retention Remembering Ability to recall or recognize
what was presented
What is the de nition
of retention?
Transfer Understanding Ability to apply what was
presented to solve new
problems
Create a transfer item
for this lesso n.
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... One major implementation of retrieval practice can be seen in audience response systems (e.g., clicker questions), the frequent use of which has been shown to benefit student learning (e.g., McDaniel, Agarwal et al., 2011;. Of course, students can also use retrieval practice on their own, such as through flashcards, recitation, and answering adjunct questions (e.g., Dunlosky et al., 2013;Fiorella & Mayer, 2015Kornell & Bjork, 2007). ...
... For example, novices may benefit from strategies that guide the construction of new schemas, whereas experts may benefit from instruction that guides the retrieval and use of already acquired schemas (Kalyuga, 2014). Whereas the benefits of some learning strategies, like concept mapping and self-explanation, are greater for LPK students, the benefits of other strategies, such as imagining and enacting (and to a lesser extent -summarizing and drawing), seem to be greater for HPK students (e.g., Ambrose et al., 2010;Fiorella & Mayer, 2015McNamara, 2004). ...
... Retrieval practice can both directly and indirectly benefit learning and clearly generalizes over many different educationally-relevant factors (e.g., learning materials and contexts, Dunlosky et al., 2013), though educators and researchers alike continue to cite prior knowledge as a critical individual difference that must be explored in future research (e.g., Dunlosky & Rawson, 2019;Fiorella & Mayer, 2015Mayer, 2017;Murphy & Pavlik, 2018). Despite this need for additional research, the wide applicability of retrieval practice has sparked a number of articles recommending increased educational implementation (e.g., Agarwal et al., 2012;Dunlosky et al., 2013;Karpicke & Blunt, 2011;Karpicke & Grimaldi, 2012;Nunes & Karpicke, 2015;Roediger, Putnam, & Smith, 2011;Roediger & Pyc, 2012). ...
... Learning by explaining occurs when students generate a written or oral explanation of instructional material they are reading or viewing (Fiorella & Mayer, 2015. In a review, Fiorella and Mayer (2015) reported that in 44 of 54 experimental tests, students who were prompted to explain what they were reading or viewing performed better on a posttest than students who were not, yielding a median effect size of d = 0.61. ...
... Learning by explaining occurs when students generate a written or oral explanation of instructional material they are reading or viewing (Fiorella & Mayer, 2015. In a review, Fiorella and Mayer (2015) reported that in 44 of 54 experimental tests, students who were prompted to explain what they were reading or viewing performed better on a posttest than students who were not, yielding a median effect size of d = 0.61. This research includes studies involving reading static text lessons and studies involving viewing dynamic multimedia presentations. ...
... Generative learning activities, such learning by explaining, are inspired by generative learning theory, which posits that meaningful learning occurs when learners engage in appropriate cognitive processing during learning (Fiorella & Mayer, 2015Mayer, 2020;Wittrock, 1974Wittrock, , 1989. These cognitive processes for building structure in working memory include the following: ...
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Generative learning theory posits that learners engage more deeply and produce better learning outcomes when they engage in selecting, organizing, and integrating processes during learning. The present experiments examine whether the generative learning activity of generating explanations can be extended to online multimedia lessons and whether prompts to engage in this generative learning activity work better than more passive instruction. Across three experiments, college students learned about greenhouse gasses from a 4-part online lesson involving captioned animations and subsequently took a posttest. After each part, learners were asked to generate an explanation (write-an-explanation), write an explanation using provided terms (write-a-focused-explanation), rewrite a provided explanation (rewrite-an-explanation), read a provided explanation (read-an-explanation), or simply move on to the next part (no-activity). Overall, students in the write-an-explanation group (Experiments 2 and 3), write-a-focused-explanation group (Experiment 2), and rewrite-an-explanation group (Experiment 3) performed significantly better on a delayed posttest than the no-activity group, but the groups did not differ significantly on an immediate posttest (Experiment 1). These results are consistent with generative learning theory and help identify generative learning strategies that improve online multimedia learning, thereby priming active learning with passive media.
... The current literature offers extensive accounts of SDL and individual differences based on characteristics such as attribution (Schunk, 2016), self-efficacy and skill (Schunk & Rice, 1987), self-control and goal-setting (Schunk & Rice, 1989, 1991, self-determination (Deci & Ryan, 2000), intrinsic motivation (Corno, 2001), attitude toward growth (Dweck, 2006), and self-awareness (Vallerand et al., 1997); or based on teachers' providing supportive learning environments (Camahalan, 2006;Turner et al., 2002), paving proper learning roadmaps (Bandura, 1986;Schunk et al., 2008), aligning tasks to learners' zone of proximal development (Wiliam, 2018), formative assessment (Panadero et al., 2018), and providing training on learning strategies (Fiorella & Mayer, 2015;Lodico, et al., 1983;). This prior work provides a basis for deeper investigations of SDL in detailed classroom learning environments. ...
... Moreover, while controlled laboratory experiments hold much promise for empirically validating the effectiveness of SDLR, such an approach is not without challenges. First, learning is a generative activity (Fiorella & Mayer, 2015), where development of self-direction and self-regulation take time (Paris et al., 2001). Second, learning autonomy is rooted in contexts (Benson, 2001). ...
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... Toujours dans [FM15], plusieurs stratégies sont proposées pour stimuler l'apprentissage actif, parmi lesquelles apprendre en dessinant, apprendre en résumant, apprendre en enseignant à un binôme, apprendre en s'expliquant à soi-même, ou apprendre en jouant un ...
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... Motivational aspects of learning are critical to learning environments which require a high level of engagement (Fiorella and Mayer, 2015;Buhr et al., 2019). Through the activities we proposed in our instructional design model, we paid greater attention to the self-efficacy cognitions (Bandura, 1997) and the three psychological needs, derived from Self Determination Theory -autonomy, control, and relatedness (Ryan and Deci, 2017). ...
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