ArticlePDF Available

Learning Science in Immersive Virtual Reality

Journal of Educational Psychology

January 2018
110(6)

DOI:10.1037/edu0000241

Authors:

Jocelyn Parong

University of California, Santa Barbara

Richard Mayer

University of California, Santa Barbara

The goals of the study were (a) to compare the instructional effectiveness of immersive virtual reality (VR) versus a desktop slideshow as media for teaching scientific knowledge, and (b) to examine the efficacy of adding a generative learning strategy to a VR lesson. In Experiment 1, college students viewed a biology lesson about how the human body works either in immersive VR or via a self-directed PowerPoint slideshow on a desktop computer. Based on interest theory, it was predicted that students who learned in immersive VR would report more positive ratings of interest and motivation and would score higher on a posttest covering material in the lesson. In contrast, based on the cognitive theory of multimedia learning, it was predicted that students who learned with a well-designed slideshow would score higher on a posttest, although they might not report higher levels of interest and motivation. The results showed that students who viewed the slideshow performed significantly better on the posttest than the VR group, but reported lower motivation, interest, and engagement ratings. In Experiment 2, students either viewed a segmented VR lesson and produced a written summary after each segment or viewed the original, continuous VR lesson as in Experiment 1. Students who summarized the lesson after each segment performed significantly better on the posttest and the groups did not differ on reported interest, engagement, and motivation. These results support the cognitive theory of multimedia learning and demonstrate the value of generative learning strategies in immersive VR environments.

Screenshots of The Body VR (2016). See the online article for the color version of this figure.

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Screenshots of the PowerPoint adapted from The Body VR (2016). See the online article for the color version of this figure.

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Figures - uploaded by Jocelyn Parong

Content may be subject to copyright.

Content uploaded by Jocelyn Parong

Content may be subject to copyright.

Journal of Educational Psychology

Learning Science in Immersive Virtual Reality

Jocelyn Parong and Richard E. Mayer

Online First Publication, January 25, 2018. http://dx.doi.org/10.1037/edu0000241

CITATION

Parong, J., & Mayer, R. E. (2018, January 25). Learning Science in Immersive Virtual Reality. Journal

of Educational Psychology. Advance online publication. http://dx.doi.org/10.1037/edu0000241

Learning Science in Immersive Virtual Reality

Jocelyn Parong and Richard E. Mayer

University of California, Santa Barbara

The goals of the study were (a) to compare the instructional effectiveness of immersive virtual reality

(VR) versus a desktop slideshow as media for teaching scientific knowledge, and (b) to examine the

efficacy of adding a generative learning strategy to a VR lesson. In Experiment 1, college students viewed

a biology lesson about how the human body works either in immersive VR or via a self-directed

PowerPoint slideshow on a desktop computer. Based on interest theory, it was predicted that students

who learned in immersive VR would report more positive ratings of interest and motivation and would

score higher on a posttest covering material in the lesson. In contrast, based on the cognitive theory of

multimedia learning, it was predicted that students who learned with a well-designed slideshow would

score higher on a posttest, although they might not report higher levels of interest and motivation. The

results showed that students who viewed the slideshow performed significantly better on the posttest than

the VR group, but reported lower motivation, interest, and engagement ratings. In Experiment 2, students

either viewed a segmented VR lesson and produced a written summary after each segment or viewed the

original, continuous VR lesson as in Experiment 1. Students who summarized the lesson after each

segment performed significantly better on the posttest and the groups did not differ on reported interest,

engagement, and motivation. These results support the cognitive theory of multimedia learning and

demonstrate the value of generative learning strategies in immersive VR environments.

Educational Impact and Implications Statement

The findings from Experiment 1 showed that a PowerPoint slideshow may be more effective for

teaching scientific information than an equivalent lesson in an immersive virtual reality environment,

but may be less enjoyable and motivating for students. This suggests that the conversion of

multimedia lessons into virtual reality may not yet be warranted. However, because increasing

student interest and motivation may be a critical factor in classrooms, it is worthwhile to examine

what supplemental learning strategies could be added to a medium that students enjoy. Experiment

2 showed that asking students to summarize segments of the immersive virtual reality lesson

increased their learning outcomes without diminishing their motivation and interest. Taken together,

the 2 experiments showed that students’ interest can be primed with new and exciting technology

while still being an effective medium to convey scientific information comparable to traditional

PowerPoint slideshow lessons.

Keywords: virtual reality, multimedia learning, summarizing, science simulation, learning strategies

As new and innovative technologies emerge, so do ideas of

incorporating them into classrooms to enhance student learning.

One example gaining popularity among consumers is immersive

virtual reality (VR) consoles with head-mounted displays and hand

controllers, such as the Oculus Rift (Oculus VR LLC, Facebook

Inc., Menlo Park, CA) and HTC Vive (HTC Corporation, Xindian,

New Taipei City, Taiwan). Previous researchers have made claims

about the usefulness of VR technologies (Blascovich & Bailenson,

2011). For example, Brelsford (1993) claimed that “VR allows the

educational task to become much more intuitive; information is

passed between the environment and the student with increased

efficiency and selectivity” (p. 1287). As VR systems have become

more affordable, using VR at the consumer level and in education

has become more feasible. These VR technologies allow opportu-

nities for educators to offer students easy and intuitive ways to

interact with multimedia lessons. Students would be able to expe-

rience a fully immersive sensory experience in almost any space

imaginable, which may encourage them to engage in deeper learn-

ing. However, there is still a gap between claims for the usefulness

of VR in academic learning and scientific research testing these

claims.

The goal of the present study is twofold. First, in a media

comparison study in Experiment 1, we seek to compare the in-

structional effectiveness of immersive virtual reality versus a desk-

top slideshow for teaching scientific knowledge. This is a media

comparison study because we wish to examine how well students

Jocelyn Parong and Richard E. Mayer, Department of Psychological and

Brain Sciences, University of California, Santa Barbara.

This research was supported by Grant N000141612046 from the Office

of Naval Research.

Correspondence concerning this article should be addressed to Jocelyn

Parong, Department of Psychological and Brain Sciences, University of Cal-

ifornia, Santa Barbara, CA 93106. E-mail: jocelyn.parong@psych.ucsb.edu

This document is copyrighted by the American Psychological Association or one of its allied publishers.

This article is intended solely for the personal use of the individual user and is not to be disseminated broadly.

2018, Vol. 0, No. 999, 000 0022-0663/18/$12.00 http://dx.doi.org/10.1037/edu0000241

learn the same material when it is delivered via one medium versus

another. In short, the first goal is to determine the efficacy of VR

as a venue for science learning. Although media comparison

studies have a history of methodological challenges (Clark, 2001),

the present research question has important practical implications

concerning whether it is worthwhile to convert conventional in-

struction to VR formats and theoretical implications concerning

whether cognitive and motivational theories apply to learning in

VR. Second, in a value-added study in Experiment 2, we seek to

compare the instructional effectiveness of adding a prompt to write

summaries at various points in a VR lesson. This is a value-added

study because we start with a basic lesson and examine whether

student learning is affected when we add one instructional feature

to the lesson. In short, the second goal is to determine how to

increase the effectiveness of VR as a venue for science learning.

Media Comparison: Using Virtual Reality for

Learning Compared to a Slideshow

Because of the implications for education, it is important to

examine the effectiveness of emerging VR technologies for teach-

ing academic content. What are the underlying theories concerning

the cognitive consequences of learning in immersive VR, and how

would these new multimedia technologies fare in comparison to

conventional methods of teaching, such as a PowerPoint slide-

show? Theories based in multimedia learning and motivation

provide a positive foundation for using VR in the classroom.

Supporting these theories are newly emerging empirical studies of

the efficacy of VR lessons on academic learning, as well as

research on the use of related technologies in education, such as

video games, simulations, and mixed reality games. However,

because many educational games and simulations in immersive

VR are also designed for entertainment, they may not necessarily

adhere to all the principles of multimedia learning, and therefore

may hinder learning compared with traditional methods.

It is customary to distinguish between two types of VR. Immer-

sive virtual reality (immersive VR) typically includes a head

mounted display (HMD) controlled by a computer where the

learner can move through a 3-D virtual environment. Nonimmer-

sive virtual reality includes a virtual world displayed on a com-

puter screen where the learner can interact through an interface

such as a mouse, touchscreen, touchpad, or handheld controls

while seated in front of the screen (Lee & Wong, 2014). Although

much more research has been done on educational simulations

with desktop VR (e.g., Hilton & Honey, 2011; Merchant, Goetz,

Cifuentes, Kenney-Kennicutt, & Davis, 2014), the growing avail-

ability of immersive VR technology for education creates a need to

determine how immersive VR affects academic learning (Blasco-

vich & Bailenson, 2011). The present study addresses this need by

comparing learning about the human body in immersive VR (VR

group) to learning with a self-paced PowerPoint slideshow con-

taining the same words and images in static form on a desktop

computer (slideshow group).

Multimedia Learning Theories

The case for using a well-designed slideshow for teaching of

scientific material is grounded in the cognitive theory of multimedia

learning (Mayer, 2009, 2014a) and cognitive load theory (Sweller,

Ayres, & Kalyuga, 2011) from which it is derived, which posit that

adding material and features—such as the visual effects in immersive

VR– can create extraneous processing in the learner—that is, cogni-

tive processing that is not relevant to the instructional goal. Given that

each learner has a limited amount cognitive processing capacity, if the

learner allocates much of that capacity to extraneous processing, there

may not be enough remaining capacity to engage in sufficient levels

of cognitive processing aimed at making sense of the essential mate-

rial.

Multimedia learning refers to learning from words and pictures

(Mayer, 2009). The two media we compare in this study are a

self-directed PowerPoint, where the learner is presented with writ-

ten works and static pictures, and an interactive lesson in VR,

where the learner is presented with spoken words and interactive

animations. One approach to researching multimedia learning asks

how a multimedia lesson can be adapted to reduce extraneous

processing, which does not serve an instruction goal (Mayer &

Fiorella, 2014), manage essential processing, which is necessary

for holding and manipulating incoming information in working

memory (Mayer & Pilegard, 2014), and foster generative process-

ing, which is needed for a deeper understanding of the information

(Mayer, 2014c). Empirical research has shown evidence for 12

principles for designing features within a multimedia lesson with

educational content (Mayer, 2009), but the most relevant for the

present study are coherence principle and the segmenting princi-

ple.

The coherence principle states that people learn better when

extraneous words (Mayer, Bove, Bryman, Mars, & Tapangco,

1996; Mayer & Jackson, 2005), sounds (Moreno & Mayer, 2000),

and pictures (Harp & Mayer, 1997, 1998; Mayer, Heiser, & Lonn,

2001) are excluded rather than included. Extraneous material di-

verts attention from the important material, disrupts the process of

organizing the material, and may prime the learner to integrate the

material with prior knowledge in an inappropriate manner (Mayer,

2009). Extraneous features in an immersive VR lesson may in-

clude the constant animations that the learner is immersed in.

However, a well-designed slideshow may not include extraneous

visual stimuli. Therefore, an immersive VR lesson would lead to

worse learning outcomes than a lesson that eliminates those ex-

traneous features. This is foreshadowed by research showing that

instruction with desktop VR in 2D was more effective than iden-

tical instruction with desktop VR in 3D, presumably because the

perceptual realism in the 3D environment created more extraneous

cognitive load that distracted the learners from the essential con-

tent (Moreno & Mayer, 2002, 2004; Richards & Taylor, 2015).

These findings are consistent with research showing that cartoon-

like characters are more effective than photo-realistic representa-

tions in educational games (Wouters & van Oostendorp, 2017) and

static diagrams can be more effective than animations in multime-

dia lessons on how scientific systems work (Lowe & Ploetzner,

2017; Mayer, Hegarty, Mayer, & Campbell, 2005). However, it is

worth noting that 3D VR may be more effective for some subjects,

particularly those that teach spatial or motor skills (e.g., laparo-

scopic surgery; Torkington, Smith, Rees, & Darzi, 2001).

The segmenting principle states that people learn better when

the lesson is presented in user-directed segments, rather than as a

continuous unit, particularly when learning the steps in a process

(Lee, Plass, & Homer, 2006; Mayer & Chandler, 2001; Mayer,

Dow, & Mayer, 2003). The segmenting principle helps to manage

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2PARONG AND MAYER

essential processing by allowing the learner to decide when to add

more incoming information. When the lesson is not self-paced, the

learner may still be processing previous information when new

information is presented. Well designed-slideshows may be self-

paced and each slide itself segments the lesson, whereas immersive

VR animations are typically continuous and not user-paced,

thereby violating this principle. This adds to the learner’s working

memory load and may inhibit some essential processing for the

learner.

The foregoing analysis shows that VR environments are more

susceptible to violating the coherence and segmenting principles.

Additionally, there may be other factors within immersive VR

lessons that may impact learning outcomes, so the theoretical

groundwork of other unique features of VR must also be exam-

ined.

Motivational Theories

Student motivation plays a large role in deeper learning in the

classroom; those who are more motivated are more likely to

engage in the lesson or task, put in more effort for understanding

the material, and be resilient when overcoming obstacles in un-

derstanding (Mayer, 2008; Wentzel & Miele, 2016). This motiva-

tion may cause the learner to stay focused even during continuous

lessons and invest more energy in allocating cognitive resources to

difficult parts of the lesson. The case for using immersive VR for

teaching of scientific material is grounded in interest theory and

self-efficacy theory (Dewey, 1913; Schiefele, 2009).

According to interest theory, students work harder when they

value and are interested in the material, either intrinsically (indi-

vidual interest) or as elicited by the situation (situational interest;

Mayer, 2008; Schiefele, 2009; Wigfield, Tonks, & Klauda, 2016).

A student with individual interest would be more motivated to

learn about the subject. In a meta-analysis of the relationship

between interest and academic achievement, there was a moderate

correlation between self-ratings of how much a student liked a

school subject and how well the student performed in school as

measured by grades or test scores (Schiefele, Krapp, & Winteler,

1992). Individual motivation would not be uniquely primed by a

multimedia lesson as a student’s intrinsic interest may not be

affected by the media through which he or she is learning. How-

ever, a novel, immersive technology in education, such as a VR

lesson, may be exciting for students and could prime a learner’s

situational interest more than conventional lessons (Kintsch, 1980;

Wade, 1992). By priming their situational interest in the VR

lesson, students may be more likely to pay attention to the content

of the lesson, actively interact with the lesson, and persist through-

out the entire lesson, which would foster generative processing and

deeper learning leading to better learning outcomes than conven-

tional lessons in the classroom.

Self-efficacy theory states that students work harder when they

see themselves as competent for the task (Schunk & DiBenedetto,

2016). Self-efficacy, as defined by Schunk (1991), is a person’s

judgments of his or her ability to perform a given action. Bandura

(1977) claimed that self-efficacy affects the amount of effort and

persistence that a person devotes to a task. Research has shown

that a student’s sense of self-efficacy is related to how active he or

she is in the lesson (Zimmerman & Martinez-Pons, 1990) and how

well he or she performs on academic measures (Chemers, Hu, &

Garcia, 2001; Pietsch, Walker, & Chapman, 2003; Schunk &

Hanson, 1985). Schunk (1989) described the process of self-

efficacy and achievement behaviors as a feedback loop. First, the

student has his or her beliefs about his or her self-efficacy (e.g.,

I’m good at this). This self-efficacy then affects the student’s task

engagement (e.g., I will try hard). After the task, the student

receives feedback (e.g., I did well on the task), and receives

efficacy cues from the feedback (e.g., the instructor thinks I’m

good at this). Finally, this aptitude feedback reshapes the student’s

self-efficacy. VR games that incorporate a feedback system for

progress on academic content would be acting on this system. For

example, certain interactions within a lesson could provide appro-

priate feedback that boosts the student’s self-efficacy, which

would in turn enhance a student’s motivation for the lesson.

Specifically, an action in which a learner must show progress in

learning in VR could provide immediate and adaptive feedback,

which may be an advantage over the feedback seen in traditional

academic lessons as learners would have immediate updates in

their self-efficacy.

According to Pintrich (2003), student motivation lies in a value-

expectancy model, a combination of the two theories described, in

which motivation depends on a learner’s values, which gets the

student started (e.g., liking the material), and expectancies, which

keeps him or her going (e.g., feeling competent). To increase the

student’s motivation, first, the lesson may prime the student inter-

est; then, the learner’s interaction with the lesson may prime his or

her self-efficacy to continue the lesson. In the case for VR, the

stimulating, immersive experience may spark the learner’s indi-

vidual interest and the feedback from interacting with the lesson

should keep him or her feeling competent to progress in the lesson.

However, in line with Dewey’s (1913) admonitions against situa-

tional interest more than 100 years ago, research on seductive

details shows that adding interesting but irrelevant material to a

multimedia lesson may hurt learning (Harp & Mayer, 1997, 1998;

Mayer, Griffith, Naftaly, & Rothman, 2008).

Media Comparison Evidence

The foregoing analysis suggests that immersive VR could be

explored as a venue for academic learning as a potential replace-

ment for conventional media such as slideshow presentations. The

first experiment is an example of a media comparison study, in

which learning academic material with one medium is compared

with learning the same material in another medium (Mayer,

2014b). There is a small but growing body of research comparing

learning with games and simulations presented on desktop com-

puters versus conventional media (Hilton & Honey, 2011; Mayer,

2014b). Our focus in the present study is on science learning.

Science was chosen as the domain of interest because many topics,

including chemistry and biology, are spatially oriented. Therefore,

it may be important to examine whether an immersive environ-

ment is important for learning about spatially relevant information.

In the science domain, there is evidence that playing a computer

game or simulation leads to better learning outcomes than a

standard lesson, such as learning from a textbook, slideshow, or

lecture. A recent meta-analysis of the effects of playing desktop

games and simulations in education showed that games tend to

improve learning more than conventional media in science (d⫽

.69) based on 16 experimental comparisons (Mayer, 2014b). In one

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LEARNING IN IMMERSIVE VR

study, Moreno, Mayer, Spires, and Lester (2001) presented high

school and college students with a simulation computer game

called Design-a-Plant, in which the players completed a botany

lesson by choosing a plant’s roots, stem, and leaves and comparing

their survival rates in various environmental conditions. Compared

with a control group that received the same information in the form

of a noninteractive computer tutorial, those who played the game

outscored those who received the tutorial on a transfer test after the

lesson. Other experiments in the science domain have shown

comparable results in positive learning outcomes of games in

electronics (Anderson & Barnett, 2011), physics (Swaak, de Jong,

& van Joolingen, 2004), biology (Adams, Mayer, MacNamara,

Koenig, & Wainess, 2012), chemistry (Evans, Yaron, & Leinhardt,

2008), and animal life (Hwang, Wu, & Chen, 2012).

More recently, McLaren, Adams, Mayer, and Forlizzi (2017)

reported that students who learned decimal arithmetic though

playing a computer-based adventure game, Decimal Point, per-

formed better on posttests than those who learned with a conven-

tion computer-based tutoring system. Similarly, a recent review

also reported small-to-medium effect sizes favoring learning with

computer-games over learning with conventional media (Wouters

& Oostendorp, 2017).

Although there is evidence for positive learning outcomes from

games, simulations, and mixed reality multimedia lessons, there is

scant empirical research on the specific use of immersive VR in

education. A meta-analysis of the use of VR in K–12 classrooms

reported that many studies rely on a descriptive analysis based on

student surveys and interviews to determine if the virtual worlds

helped them learn (Cooper, 2007; Hew & Cheung, 2010; Ligorio

& van Veen, 2006). One study examined students in a computer

graphics class who used an immersive 3D program to learn about

function-based shape modeling. The researchers used exam scores

throughout the course to determine the efficacy of VR and reported

a 14% increase after one semester (Sourin, Sourina, & Prasolova-

Førland, 2006). However, the researchers did not include a control

group in their experiment, so the increase in exam scores cannot be

attributed to solely the use of VR as it may be due to other factors

within the classroom or students.

More recent empirical studies show promise in the use of VR in

education, particularly in the science domain. In one study, Ko-

zhevnikov, Gurlitt, and Kozhevnikov (2013) presented participants

with a lesson on relative motion concepts in either an immersive

virtual environment (IVE), using a head-mounted display, or a

desktop virtual environment (DVE) presented on a computer. After

the lesson, both groups showed a significant shift in their scientific

understanding of relative motion, as well as a significant improve-

ment on problem-solving tests. Additionally, the IVE group per-

formed significantly better than the DVE group on solving two-

dimensional relative motion problems, suggesting a further

transfer of learning from the use of VR compared with the use of

a computer. In another example, military participants learned

about basic corrosion prevention and control either in an immer-

sive VR environment using a combination of a head mounted

display from WorldViz and movement tracking with the Microsoft

Kinect or a desktop multimedia presentation. They found that both

forms of instruction increased learning, but those in the VR envi-

ronment had significantly higher gains in learning than those in

desktop learning environments (Webster, 2016). Overall, this re-

view suggests that more methodologically sound research is

needed on the effects of immersive VR in education, particularly

in specific academic domains, such as science.

Criticisms of Media Comparison Studies

It is worth noting that media comparison studies have received

criticisms. Since the early 1980s, there has been a media debate,

sparked by Richard Clark and Robert Kozma, regarding the use-

fulness of studying the type of media used in learning tasks in an

apples-to-oranges type of comparison. Clark (1983) claimed that

“media are mere vehicles that deliver instruction but do not influ-

ence student achievement any more than the truck that delivers our

groceries causes changes in our nutrition” (p. 445). Instead, he

argued that many different media can accomplish the same learn-

ing goal, and therefore, because no single media attribute can

contribute a unique cognitive effect on a learning task, other

variables are more instrumental in learning gains (Clark, 1994).

However, Kozma (1994) argued that the question is more nu-

anced than whether media causes learning, but rather what is the

relationship between media and learning, and how can we explain

that relationship? Certain media may possess particular character-

istics that may make them more or less suitable for learning tasks.

For example, Salomon (1979) argued that media can be analyzed

by the types of their cognitively relevant characteristics that affect

the ways in which learners represent and process information.

Some of these characteristics include the physical, mechanical, or

electronic characteristics of the technology of the media, the sym-

bol systems, including pictures, text, and spoken language, that are

used in the media, and the processing capabilities of the media to

act on the symbol systems. With this view, underlying theories

about the way we process lessons, such as the cognitive theory of

multimedia learning, can help inform the field about how partic-

ular features in multimedia affect learning, and therefore find value

in media comparison studies. Additionally, to minimize the inher-

ent differences between different media, we constructed the slide-

show from the VR lesson to equate the lessons as much as possible

by using the same words and images. Specifically, we transcribed

the narration from the VR lesson and used the same words on the

slides, and we took screenshots from the VR lesson to create still

pictures on the slides.

Value-Added Research: Adding Generative Learning

Strategies to VR

In addition to a media comparison study between immersive VR

and a desktop slide show, we also examined the efficacy of adding

a generative learning strategy to the existing VR lesson. The

second experiment is an example of a value-added study, in which

an additional feature is added to an existing lesson to promote

learning and is compared with the original lesson (Mayer, 2014b).

Generative Learning Theory

According to generative learning theory, meaningful learning

occurs when learners engage in appropriate cognitive processing

during learning, including selecting (i.e., paying attention to rele-

vant incoming information), organizing (i.e., mentally arranging

the information into a coherent structure), and integrating (i.e.,

connecting the verbal and pictorial representations with each other

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4PARONG AND MAYER

and with relevant prior knowledge activated from long-term mem-

ory). Generative learning is the process of taking incoming infor-

mation and transforming it into usable information by engaging in

appropriate selecting, organizing, and integrating (Fiorella &

Mayer, 2015, 2016).

Along these same lines, Wittrock’s (1989) generative model of

learning stated that one important component of meaningful learn-

ing is generation, or the creation of connections within to-be-

learned material as well as between to-be-learned material and

existing knowledge. Wittrock’s model of generative learning is

closely tied to Mayer’s (2009, 2014b) select-organize-integrate

model, in which learners select relevant incoming information in

sensory memory, organize the selected information in working

memory, and integrate the organized information with prior

knowledge in long term memory.

Value-Added Evidence

The extant research shows support for adding a feature, such as

an additional worksheet, to a game-like lesson that prompts a

generative learning strategy (namely, self-explanation) to help

learners deeply understand the material (Fiorella & Mayer, 2015,

2016; Mayer, 2014b). For example, in one study by Pilegard and

Mayer (2016), students played a computer game called Cache 17,

which included instructional content about how wet cell batteries

work. One group of students were asked to complete worksheets

with questions about how wet cell batteries work during the game,

while another group did not fill out worksheets. The worksheet

group significantly outperformed the control group on a subse-

quent comprehension test. In another study, Fiorella and Mayer

(2012) had participants play an educational game about electrical

circuits, called Circuit Game. Students were asked to fill in work-

sheets about the features of each principle in an electrical circuit.

Those who were able to correctly fill in the worksheets did

significantly better than a control group on a transfer test.

Summarizing

The generative learning strategy of interest in this study is

summarizing, or taking the important information from a lesson

and putting it into one’s owns words (Fiorella & Mayer, 2016).

According to the generative learning theory, the act of creating a

well-written summary primes active cognitive processing during

learning including selecting, organizing, and integrating. Summa-

rizing promotes selecting by encouraging learners to choose the

most important information for inclusion in the summary, orga-

nizing by encouraging learners to relate the pieces of information

to each other within a coherent summary, and integrating by

encouraging learners to use their own words to relate the material

to relevant prior knowledge.

Research on the effects of asking students to summarize text

they are reading has produced encouraging evidence of improve-

ments on tests of learning outcome. Support for the idea that

summarizing can be an effective generative learning strategy for

learning from text comes from experiments where a group that

generates summaries during or after a lesson performs better on

subsequent tests than a group that does not summarize during or

after the lesson (e.g., Annis, 1985; Coleman, Brown, & Rivkin,

1997; Peper & Mayer, 1986; Ross & Kirby, 1976). For example,

in a classic study by Doctorow, Wittrock, and Marks (1978),

middle school students read a narrative either normally or were

asked to generate a one-sentence summary of each paragraph.

Those who wrote summaries performed better on a subsequent

comprehension test than those who read the narrative normally,

indicating that summarizing led to a deeper understanding of the

material.

In a meta-analytic review of published experiments comparing

learning by reading (i.e., control group) versus learning by reading

along with summarizing (i.e., summarizing group), Fiorella and

Mayer (2015) found that the summarizing group outperformed the

control group on learning outcome tests in 26 out of 30 experi-

mental comparisons, yielding a median effect size of d⫽0.50,

which is a medium sized effect. In contrast to previous work that

focused on learning from printed text, the current study is the first

to investigate the effectiveness of applying the generative learning

strategy of summarizing to learning in an immersive VR environ-

ment.

Predictions

The VR lesson used for this experiment was an interactive

biology simulation called The Body VR: Journey Inside a Cell

(The Body VR, 2016). In this simulation, the player is taken

through a tour of the blood stream and the inside of a cell. The

simulation is narrated with descriptions and explanations of the

parts and functions of the blood stream and cell and includes a full

360-degree view of animations within the blood stream and cell.

The self-directed PowerPoint slideshow was adapted from this

simulation to match the content.

In Experiment 1, based on interest and self-efficacy theory, if

the motivational features of immersive VR encourage the learners

to process the material more deeply, then we predict that VR group

will have increased self-report measures of interest, engagement,

motivation, and affect, and subsequently outperform the slideshow

group on tests of learning outcomes. In contrast, if the extraneous

features of immersive VR distract the learners from processing the

material more deeply, then we predict that the slideshow group

will outperform the VR group on tests of learning outcomes but

not necessarily on self-report measures of interest, engagement,

motivation, and affect.

The second aim (examined in Experiment 2) is to determine

whether adding summarizing prompts to the VR lesson increases

learning outcomes. Based on generative learning theory as well as

previous research using text-based learning environments, we pre-

dict that students who view the VR lesson and summarize each

segment will perform better on a posttest than those who view the

original VR lesson. Although generative learning theory makes no

predictions about motivation and interest, we expect that groups

will not differ on measures of interest, engagement, motivation,

and affect because they are exposed to the same immersive lesson.

There are no published experiments that examine the effects of

applying a generative study aid to an immersive virtual reality

lesson, although this has been shown to improve learning with

online science games (Fiorella & Mayer, 2012; Pilegard & Mayer,

2016). We note the value of determining whether study aids can be

successfully added to a VR lesson without diminishing the moti-

vational benefits of new media, which is a new research question

involving new media. We also note that replication of the sum-

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LEARNING IN IMMERSIVE VR

marizing principle, which was based on studies involving reading

text (Fiorella & Mayer, 2015), in a new venue involving immer-

sive VR is a worthwhile educational goal according to the focus on

replication in Shavelson and Towne’s (2002) NRC report, Scien-

tific Research in Education, especially because no previous studies

on study strategies involved learning in virtual reality. In short, this

study is in line with calls for replication of educational intervention

results (Hattie, 2009; Phye, Robinson, & Levin, 2005), particularly

involving new media (Mayer, 2014b).

Method

Experiment 1

Participants and design. The participants were 55 college

students recruited from a subject pool at a university in the western

United States (38 women, ages 18 –30, M⫽19.18, SD ⫽1.90).

Participants fulfilled a class requirement by participating. Twenty-

seven participants were randomly assigned to the immersive VR

condition (VR group) and 28 were assigned to the slideshow

condition (slideshow group).

Materials. The instructional materials consisted of lessons on

how cells in the human bloodstream work rendered in immersive

VR simulation (VR lesson) or as a PowerPoint slideshow (slide-

show lesson). The VR lesson was an interactive biology simula-

tion, called The Body VR: Journey Inside a Cell (The Body VR,

2016), which contained narration and immersive animations of the

circulatory system and parts of cells. The simulation “shrunk” the

learner, so the learner could travel through an artery on a moving

platform while a narrator explained the purpose of the cells within

it. The learner then traveled into a cell and the parts and functions

of the cell were described. The entire tour included a full 360-

degree view of animations within the blood stream and cell. The

learner was also occasionally presented with a close-up view of a

part of the blood stream or cell, and he or she could physically

touch, move, and rotate these objects (e.g., a close-up of a red

blood cell or a mitochondrion). The VR lesson lasted approxi-

mately 12 min. Screenshots from the VR simulation are shown in

Figure 1.

The slideshow lesson was adapted from The Body VR:Journey

Inside a Cell; the same spoken words from the simulation were

transcribed and printed in a slideshow format. Corresponding

screenshots for each of the body parts shown in the simulation

were also included in the slides to make the lessons as similar as

possible (as shown in Figure 2). The PowerPoint slideshow was

self-paced and participants completed it in about 8 min on average,

(M⫽7 min, 44 s; SD ⫽3 min, 50 s).

The paper-based materials consisted of a prequestionnaire, post-

questionnaire, and posttest. The prequestionnaire solicited basic

demographic information such as the participant’s age, gender, and

year in school. It also asked participants to indicate the science

classes they completed in high school and college, to rate their

knowledge of the human body on a 5-point scale from “very low”

to “very high”, and to check any of the following statements that

applied to them: “I have participated in science programs or

research fairs,” “Science is my favorite subject in school,” “I

earned mostly As and Bs in my science classes in high school and

college,” “I enjoy watching science documentaries about biology

or anatomy,” “I would like to have a career in a science-related

field,” “I can name most of the components of the circulatory

system from memory,” “I have attended a course on cardiopulmo-

nary resuscitation (CPR) training,” “I sometimes find myself on

the internet looking up science related topics in my free time,” “I

can draw the structure of the eukaryotic cell from memory,” and “I

took advanced (AP, IB, Honors) science classes in high school.”

The prequestionnaire was used to control for preexisting differ-

ences between the two groups. We used a self-reported back-

ground knowledge questionnaire rather than a pretest about the

material in the lesson because we did not want to create a testing

effect in which the pretest primes learners to construct answers

before the lesson as a form of instruction (Fiorella & Mayer,

2015).

The postquestionnaire asked students to make self-ratings on a

7-point scale from 1 (strongly disagree)to7(strongly agree)of3

statements of effort and understanding (e.g., “I used a lot of mental

effort in the lesson”), a statement on motivation (e.g., “I felt

motivated to understand the material”), 4 statements on interest for

the subject (e.g., “I am interested in learning more about this

subject”), engagement with the lesson (e.g., “I felt that the lesson

was engaging), and 6 statements about affect during the lesson

(e.g. “I felt happy during the lesson”). The postquestionnaire also

had an open-ended question asking if the participant had any

additional comments about the lesson.

Finally, the posttest consisted of 20 questions based on the

lesson, including 16 factual questions in multiple-choice format

and 4 conceptual questions in short-answer format to examine the

Figure 1. Screenshots of The Body VR (2016). See the online article for

the color version of this figure.

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6PARONG AND MAYER

learning outcome of students (Cronbach’s ␣⫽.78). A large

portion of the lesson consisted of factual statements, which led the

posttest to include more factual questions than comprehension

questions. An example of a factual question is, “In what process

are ribosomes involved? (A) ATP production. (B) Protein synthe-

sis. (C) Protein transportation. (D) Both B and C.” An example of

a conceptual question is, “What could cause kinesin motor protein

to move slower?”

Apparatus. The VR lesson was presented to participants us-

ing Steam Software on a Dell Alienware computer and an HTC

Vive, a virtual reality system that included a head-mounted display

and two wireless hand controllers. The controllers allowed the user

to interact with the virtual environment using intuitive gestures,

and users received haptic feedback (i.e., vibrations) for certain

interactions. The console also included wall-mounted sensors in

the room to allow the software to map the space in which the user

could move. The self-paced slideshow lesson was presented on a

Dell computer with a 20-inch color screen.

Procedure. Participants signed up for the experiment via a

subject recruitment website as part of a requirement for lower

division psychology courses. Participants were randomly assigned

to the VR group or slideshow group. Participants in the VR group

were tested individually in a lab with a large space of approxi-

mately 12 ⫻12 feet to allow for walking around in the immersive

VR lesson. Participants in the slideshow condition were tested indi-

vidually in cubicles containing a computer workstation in a lab

setting. First, the experimenter described the study and the participant

signed the informed consent form. Second, the participant completed

the prequestionnaire. Third, the biology lesson was presented. In the

VR condition, the participant began by putting on the head-mounted

display and standing in the middle of room. The participant could

move around the room throughout the 12-min lesson. In the slideshow

condition, each participant was seated in an individual cubicle and

went through a self-paced PowerPoint slideshow lesson that was

presented on a desktop computer. Fourth, participants completed a

postquestionnaire about their experiences with the lesson and a post-

test on the material they viewed during the lesson, with no time limit.

Finally, participants were thanked and dismissed. We followed guide-

lines for ethical treatment of human subjects and obtained IRB ap-

proval for the study.

Experiment 2

Participants and design. The participants were 57 students

recruited from the same subject pool as in Experiment 1 (36

women, ages 18 –22, M⫽19.56, SD ⫽1.15). Twenty-nine par-

ticipants were randomly assigned to the immersive VR condition

(VR group) and 28 were assigned to the immersive VR plus

summarizing condition (VR ⫹group). The participants in Exper-

iment 2 were different from those in Experiment 1.

Materials, apparatus, and procedure. The same materials

and apparatus from Experiment 1 were used for Experiment 2. The

procedure for the VR condition was identical to Experiment 1. In

the VR ⫹condition, participants followed a similar procedure as

the VR condition, except that they viewed the lesson in 6 seg-

ments. After each segment, the participant removed the headset

and was asked to write a summary of the segment they just viewed

on a sheet of paper. Participants were told to write a summary as

completely as they could and were given unlimited time to answer

the prompt, which stated to summarize key features of the segment

(e.g., “Summarize the functions of red blood cells, white blood

cells, platelets, and monocytes.”). The postlesson questionnaire

also included two additional items about being distracted and

overwhelmed during the lesson.

Results

Scoring

The prequestionnaire was scored with a point given for each

science class participants completed in high school and college and

a point for each science-related activity they checked off. For the

self-rating of knowledge of the human body, zero points were

given for a rating of very low and somewhat low, a point was given

for average, two points for somewhat high, and three points for

very high. The posttest was scored out of 20 points, with a point

given for each correct multiple-choice and short-answer question;

half-points were given for partially correct answers on short-

answer question. The short answer questions were scored based on

a rubric that indicated the words and phrases required for 1 point

or 1/2 point.

Figure 2. Screenshots of the PowerPoint adapted from The Body VR

(2016). See the online article for the color version of this figure.

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LEARNING IN IMMERSIVE VR

Do the Groups Differ on Basic Characteristics?

The first step was to determine whether there were any preex-

isting differences between the groups. In Experiment 1, the VR

and slideshow groups did not differ significantly in mean age,

t(53) ⫽0.13, p⫽.899, mean year in school, t(53) ⫽1.27, p⫽

.210, and mean science-knowledge score, t(53) ⫽1.33, p⫽.190.

The two groups also did not differ in the proportion of men and

women, ␹

(1, N⫽55) ⫽1.87, p⫽.171. We conclude that groups

did not differ on basic characteristics.

In Experiment 2, the VR and VR ⫹groups did not different

significantly in mean age, t(55) ⫽1.22, p⫽.227, and mean

science-knowledge score, t(55) ⫽0.18, p⫽.857. The two groups

also did not differ in their proportion of men and women, ␹

(1,

N⫽57) ⫽0.30, p⫽.862. The VR ⫹group (M⫽2.21, SD ⫽

1.13) was marginally further along in school based on year in

school than the VR group (M⫽1.76, SD ⫽0.83), t(55) ⫽1.74,

p⫽.088; therefore, year in school was included as a covariate in

subsequent analyses in Experiment 2.

Does Learning in Immersive VR Lead to Better

Learning Outcomes Than Viewing a

Corresponding Slideshow?

A primary media-comparison question in Experiment 1 con-

cerns whether students learn better from the VR lesson or slide-

show lesson. Table 1 shows the mean score on the posttest (as well

as the mean score on the factual items and conceptual items

separately) for the two groups. An analysis of covariance

(ANCOVA) was conducted on the posttest scores of the VR and

slideshow groups with background science-knowledge scores as

covariates. As shown in the top line of Table 1, the slideshow

group (M⫽13.54, SD ⫽3.55) scored significantly better than the

VR group (M⫽10.17, SD ⫽3.80) on the posttest overall,

F(1.52) ⫽9.54, p⫽.003, d⫽0.92. As shown in the next two lines

of Table 1, additional ANCOVAs revealed that the slideshow

group performed significantly better than the VR group on the

factual questions (slideshow group: M⫽11.00, SD ⫽2.74; VR

group: M⫽7.74, SD ⫽3.07), F(1, 52) ⫽14.94, p⬍.001, d⫽

1.12; but not on the conceptual questions (slideshow group: M⫽

2.53, SD ⫽1.17; VR group: M⫽2.43, SD ⫽1.19), F(1, 52) ⫽

0.03 p⫽.870, d⫽0.08). The same pattern of significant differ-

ences was found when we conducted ttests (i.e., without covari-

ates). It is worth noting that the slideshow group spent less time on

the lesson, but performed better on the posttest. This further shows

that the slideshow was more efficient at conveying scientific

information than the VR lesson. We conclude that students learned

less from a biology lesson when it was presented in immersive VR

than when it was presented as a slideshow on a desktop computer.

Do Students Give More Positive Ratings to Learning

in Immersive VR Than Learning From a

Corresponding Slideshow?

A secondary media-comparison question in Experiment 1 con-

cerns whether students give more positive self-report ratings to the

VR lesson or the slideshow lesson. Table 2 shows the mean rating

(and standard deviation) on each of 15 items for the VR and

slideshow groups. As summarized in Table 2, ttests (corrected for

multiple comparisons, p⬍.001) showed that the VR group gave

significantly better ratings on items involving enjoyment, engage-

ment, and motivation. Additionally, concerning affect, the VR

group was significantly happier, more excited, and less bored

during the lesson than the slideshow group. We conclude that the

students have more positive feelings about learning in immersive

VR than learning from a slideshow.

Do the Groups Differ in Their Comments About

the Lesson?

As a secondary analysis, we also examined participants general

comments about their experiences with the lesson. The participants

in the VR group (4 out of 28) were significantly more likely to

mention being distracted or having a hard time focusing on the

dialogue than the participants in the slideshow group (0 out of 27),

␹

(1, N⫽55) ⫽4.16, p⫽.041. For example, one VR participant

wrote, “I was somewhat distracted by the excitement of experi-

encing a new technology. Because of that, I wasn’t able to com-

pletely focus on the lesson.”

Does Summarizing a Segmented VR Lesson Lead to

Better Learning Outcomes than Viewing a Continuous

VR Lesson Without Summarizing?

A primary value-added issue addressed in Experiment 2 con-

cerns whether students learn more when they are asked to write

written summaries after each segment of the VR lesson. Table 3

shows the mean score on the posttest (as well as the mean score on

the factual items and conceptual items separately) for the VR and

VR ⫹groups in Experiment 2. An ANCOVA was run on the

posttest scores between the VR and VR ⫹groups with background

science-knowledge scores and year in school as covariates. As

shown in the top row of Table 3, the VR ⫹group (M⫽13.84,

SD ⫽3.20) scored significantly better than the VR group (M⫽

10.31, SD ⫽3.10) on the posttest overall, F(1, 53) ⫽17.81, p⬍

.001, d⫽1.12. As shown in the next two lines of Table 3,

additional ANCOVAs revealed that the VR ⫹group performed

significantly better than the VR group on the factual questions

(VR⫹:M⫽10.89, SD ⫽2.59; VR: M⫽8.07, SD ⫽2.33; F(1,

53) ⫽17.41, p⬍.001, d⫽1.14) and the conceptual questions

(VR⫹:M⫽2.95, SD ⫽1.09; VR: M⫽2.24, SD ⫽1.07; F(1,

53) ⫽4.58 p⫽.037, d⫽0.66). The same pattern of significant

differences was found when we conducted ttests, without covari-

ates. We conclude that students learned more from a biology

Table 1

Mean Scores and Standard Deviations on Posttest for Virtual

Reality (VR) and Slideshow Groups

VR group

(N⫽27)

Slideshow

group

(N⫽28)

Test score M SD M SD d

Total test score (out of 20) 10.17 3.80 13.54

ⴱⴱ

3.55 0.92

Factual questions (out of 16) 7.74 3.07 11.00

ⴱⴱⴱ

2.74 1.12

Conceptual questions (out of 4) 2.43 1.19 2.53 1.17 0.08

ⴱⴱ

p⬍.01.

ⴱⴱⴱ

p⬍.001.

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8PARONG AND MAYER

lesson when it was presented in a segmented immersive VR lesson

with summarization prompts than when it was presented as con-

tinuous VR lesson. In short, students had better learning outcomes

from a VR simulation when they were asked to engage in a

summarizing learning strategy. We note that adding the summa-

rization prompt allowed the VR ⫹group to achieve a level of test

performance similar to the slideshow group in Experiment 1.

Does Adding Summary Prompts to a VR Lesson

Diminish Positive Ratings Toward the Lesson?

A secondary value-added issue concerns whether adding sum-

marization prompts to a VR simulation lesson affects how students

rate the lesson. Table 4 shows the mean rating (and standard

deviation) on each of 17 items for the VR and VR ⫹groups. As

summarized in Table 4, ttests (corrected for multiple comparisons,

p⬍.001) showed that the VR group and VR ⫹group did not give

significantly different ratings on interest, motivation, engagement,

or affective states after the lesson. The conclusion applies when we

conducted ttests without correcting for multiple comparisons. We

conclude that adding summary prompts to a VR lesson does not

diminish positive ratings toward the lesson.

Discussion

Empirical Contributions

Experiment 1 was a media comparison study showing that

students who viewed an immersive VR lesson reported signifi-

cantly higher ratings of motivation, interest, engagement, and

affect than students who viewed a slideshow lesson covering the

same material, but scored significantly worse on a posttest, par-

ticularly on the factual questions.

Experiment 2 was a value-added study showing that adding a

generative learning strategy, summarizing, to the existing VR

lesson significantly improved learning outcomes compared with

the original VR lesson, but did not significantly change ratings of

motivation, interest, engagement, or affect. This is consistent with

previous literature showing the effect of summarizing during a

lesson (Fiorella & Mayer, 2015, 2016).

Theoretical Contributions

The results from Experiment 1 indicate that the instructional

features used in the immersive VR lesson may have not been as

effective as those in the slideshow lesson. This could have been

due to three possibilities: the coherence principle, the segmentation

principle, or higher learner control. First, the coherence principle,

which calls for eliminating extraneous material and features,

seemed to play the biggest role in hindering the students’ learning

in immersive VR. The learner is immersed in constant animations

in a 360-degree view that are not essential for some of the narra-

tion, thereby violating the coherence principle. For example, in the

part of the lesson in which the learner was in the blood stream,

various blood cells were constantly moving past the learner and the

learner could look in any direction to see these movements. These

animations could have added to the learner’s cognitive load as

he or she had to also pay attention to the narration; they may have

diverted attention from the important material, disrupting the pro-

Table 2

Mean Ratings of Interest, Motivation, Engagement, and Affective States During the Lesson

Between by the Virtual Reality (VR) and Slideshow Groups

VR group

(N⫽27)

Slideshow group

(N⫽28)

Post-Questionnaire Item M(SD)M(SD)

“I used a lot of mental effort in the lesson” 4.00 (1.21) 4.00 (1.16)

“I felt that the subject matter was difficult” 3.30 (1.14) 2.89 (1.23)

“I have a good understanding of the material” 4.85 (1.03) 5.00 (1.09)

“I enjoyed learning this way” 5.89 (1.40) 3.61 (1.37)

ⴱⴱⴱ

“I would like to learn this way in the future” 5.81 (1.52) 3.32 (1.42)

ⴱⴱⴱ

“I am interested in learning more about this subject” 5.70 (1.17) 4.96 (1.29)

“I felt that the lesson was engaging” 6.11 (1.05) 3.32 (1.34)

ⴱⴱⴱ

“I found the lesson to be useful to me” 5.56 (1.40) 4.61 (1.40)

“I felt motivated to understand the material” 5.93 (1.07) 4.11 (1.45)

ⴱⴱⴱ

“I felt happy during the lesson” 5.67 (1.49) 3.43 (1.07)

ⴱⴱⴱ

“I felt excited during the lesson” 5.81 (1.21) 3.07 (1.22)

ⴱⴱⴱ

“I felt bored during the lesson” 1.81 (1.00) 4.25 (1.51)

ⴱⴱⴱ

“I felt confused during the lesson” 2.15 (1.10) 2.39 (1.20)

“I felt sad during the lesson” 1.07 (0.27) 1.71 (0.94)

“I felt scared during the lesson” 1.48 (1.09) 1.25 (.044)

Note. A 7-point rating scale from 1 (strongly disagree)to7(strongly agree) was used.

ⴱⴱⴱ

p⬍.001.

Table 3

Mean Scores and Standard Deviations on Posttest for

Summarizing Group and Control Group

VR ⫹

group

(N⫽28)

VR group

(N⫽29)

Test score M SD M SD d

Total test score (out of 20) 13.83 3.21 10.31

ⴱⴱⴱ

3.10 1.12

Factual questions (out of 16) 10.89 2.59 8.07

ⴱⴱⴱ

2.33 1.14

Conceptual questions (out of 4) 2.95 1.09 2.24

ⴱ

1.07 0.66

ⴱ

p⬍.05.

ⴱⴱⴱ

p⬍.001.

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LEARNING IN IMMERSIVE VR

cess of organizing the material, and may have primed the learner

to integrate the material with prior knowledge in an inappropriate

manner.

Second, the VR simulation did not adhere closely to the seg-

menting principle because it was a continuous lesson that was not

under learner control, whereas the segments were short and under

learner control in the self-directed slideshow. As the learner lis-

tened to and watched a lesson, he or she may still have been

processing previous information when new information was pre-

sented, adding to his or her essential processing load. Additionally,

because the PowerPoint was user-paced, it added a higher element

of learner control, mitigating the learner’s essential processing

during the lesson.

In short, the slideshow lesson may have incorporated research-

based principles of instructional design more effectively than did

the VR lesson. The off-the-shelf educational simulation used in

this study was meant to be an entertaining interactive experience,

so it was likely not necessarily designed with the principles of

multimedia learning in mind. Additionally, this particular lesson

contained mostly factual knowledge, which animations may not

have enhanced, but rather added extraneous visual input. Support-

ing this conclusion were a few comments written by participants in

the VR condition, which mentioned that they were distracted

during the lesson, whereas no participants in the slideshow con-

dition mentioned they were distracted. It appears that immersive

VR creates situational interest, but as has long been noted, adding

interesting features to a lesson may not be enough to enhance

learning (Dewey, 1913). In short, immersive VR may create so

much extraneous cognitive processing that the learner does not

have sufficient cognitive resources left to learn the essential ma-

terial in the lesson.

The results from Experiment 2 provide evidence for genera-

tive learning theory in that promoting meaningful learning

through asking learners to engage in the learning strategy of

summarizing caused enhanced learning gains from a lesson.

Creating summaries during breaks in the VR lesson prompted

the learners to select, organize, and integrate the information

from the lesson into their existing knowledge structures. This

work shows that generative learning strategies that have been

shown to be effective in non-VR environments can also apply to

learning in VR environments. This study is the first to show that

conventional study strategies such as summarizing can be ap-

plied to learning in VR without harming student interest, which

extends research on study strategies and broadens the domain of

impact for generative learning theory.

Practical Contributions

On the practical side, these results suggest that there may not

be strong research evidence to invest in the costly job of

converting conventional science instruction or even simulations

in desktop virtual reality into simulations in immersive virtual

reality. When the goal is to help students learn basic scientific

knowledge, we cannot recommend wholesale replacing of con-

ventional media with immersive VR. However, in situations

where VR is the instructional medium, the effectiveness of VR

can be increased by prompting students to use generative learn-

ing strategies, such as summaries, without diminishing the

learner’s motivation, interest, engagement, and affect while

using the new technology. Because VR is a new popular tech-

nology that students find more motivating than conventional

media, using it in tandem with these strategies may be useful in

sparking interest among learners while still maintaining learn-

ing outcomes comparable to conventional media.

Methodological Contributions

Clark (2001) and Saettler (1990, 2004) have warned researchers

about the perils of media comparison research in which learning

Table 4

Mean Ratings of Interest, Motivation, Engagement, and Affective States During the Lesson

Between by the Virtual Reality (VR) and VR ⫹Groups

VR group

(N⫽29)

VR ⫹

group

(N⫽28)

Post-Questionnaire Item M(SD)M(SD)

“I used a lot of mental effort in the lesson” 4.38 (1.12) 4.61 (1.64)

“I felt that the subject matter was difficult” 3.21 (1.15) 3.43 (1.53)

“I have a good understanding of the material 4.76 (1.12) 4.79 (1.29)

“I enjoyed learning this way” 6.07 (1.10) 5.64 (1.57)

“I would like to learn this way in the future” 5.59 (1.45) 5.46 (1.80)

“I am interested in learning more about this subject” 5.31 (1.26) 5.64 (1.47)

“I felt that the lesson was engaging” 6.07 (0.96) 5.79 (0.96)

“I found the lesson to be useful to me” 5.24 (1.22) 5.04 (1.32)

“I felt motivated to understand the material” 5.66 (1.17) 5.61 (1.26)

“I felt happy during the lesson” 5.59 (1.15) 5.54 (1.07)

“I felt excited during the lesson” 6.03 (1.02) 5.86 (.97)

“I felt bored during the lesson” 1.62 (1.08) 2.29 (1.30)

“I felt distracted during the lesson” 3.66 (1.95) 4.64 (1.77)

“I felt confused during the lesson” 2.55 (1.43) 2.79 (1.50)

“I felt overwhelmed during the lesson” 3.24 (1.79) 3.57 (1.57)

“I felt sad during the lesson” 1.34 (0.77) 1.36 (0.56)

“I felt scared during the lesson” 1.93 (1.49) 1.46 (0.92)

Note. A 7-point rating scale from 1 (strongly disagree)to7(strongly agree) was used.

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10 PARONG AND MAYER

with one medium is compared against learning the same content

with another medium. An ever-present threat is that the two

treatments differ not only in instructional medium but also in terms

of instruction method and even instructional content. The present

study offered some experimental control by insuring that both

lessons contained the same words (albeit in spoken vs. printed

form) and same graphics (albeit in dynamic vs. static form). Thus,

we tried to mitigate some of the more gross problems in media

comparison studies.

Limitations and Future Directions

A limitation of this study is that it involved one, short off-the-

shelf instructional lesson delivered in a lab setting with an imme-

diate test. Although this study gives us a preliminary view of the

effectiveness of immersive VR for teaching scientific material and

contributes to the small research base, future work should involve

other types of material, more authentic learning contexts, and

delayed tests. A second limitation concerns the generalizability of

this study to other content domains. Further research is needed to

examine whether these results are domain, or even lesson, specific

and whether they are generalizable to other technologies. In addi-

tion, future studies are needed to examine whether applying the

principles of multimedia learning design would also help learners

in immersive VR. For example, would better incorporation of the

coherence principle or the segmenting principle in an interactive

lesson, like The Body VR: Journey Inside a Cell, be effective at

increasing learning outcomes to the same levels as learning from a

PowerPoint slideshow? Additionally, it would be useful to exam-

ine in a value-added type study whether something else could be

added to a VR lesson to make it more effective. For example,

adding other generative learning activities, such as drawing

(Fiorella & Mayer, 2015), to an existing VR lesson may help

enhance deeper learning, or adding an interactive activity with

feedback during the lesson may help enhance the learner’s self-

efficacy along with his or her motivation for the lesson. It may be

useful in future research to investigate the benefits of using im-

mersive VR as a pre-lesson activity to spark situational interest

that may support subsequent learning from a conventional lesson.

The goal of experiment 2 was to determine whether adding a

generative learning strategy (in this case, summarizing) to an

immersive reality lesson could improve academic learning without

hurting motivation and interest. This is a worthwhile issue because

the exciting features of a new instructional medium like immersive

VR may cause learners to be less reflective, so interventions aimed

at promoting deeper processing may be useful. Our goal was not to

examine the relative power of summarizing with two different

media (slideshows and VR), although this is certainly a question

worthy of future research.

References

Adams, D. M., Mayer, R. E., MacNamara, A., Koenig, A., & Wainess, R.

(2012). Narrative games for learning: Testing the discovery and narra-

tive hypotheses. Journal of Educational Psychology, 104, 235–249.

http://dx.doi.org/10.1037/a0025595

Anderson, J., & Barnett, M. (2011). Using video games to support pre-

service elementary Teacher learning of basic physics principles. Journal

of Science Education and Technology, 20, 347–362. http://dx.doi.org/10

.1007/s10956-010-9257-0

Annis, L. F. (1985). Student-generated paragraph summaries and the

information-processing theory of prose learning. Journal of Experimen-

tal Education, 54, 4 –10. http://dx.doi.org/10.1080/00220973.1985

.10806390

Bandura, A. (1977). Self-efficacy: Toward a unifying theory of behavioral

change. Psychological Review, 84, 191–215. http://dx.doi.org/10.1037/

0033-295X.84.2.191

Blascovich, J., & Bailenson, J. (2011). Infinite reality. New York, NY:

HarperCollins.

Brelsford, J. W. (1993, October). Physics education in a virtual environ-

ment. Paper presented at proceedings of the human factors and ergo-

nomics society 37th meeting, Boston, MA.

Chemers, M. M., Hu, L., & Garcia, B. F. (2001). Academic self-efficacy

and first-year college student performance and adjustment. Journal of

Educational Psychology, 93, 55– 64. http://dx.doi.org/10.1037/0022-

0663.93.1.55

Clark, R. E. (1983). Reconsidering research on learning from media.

Review of Educational Research, 53, 445– 459. http://dx.doi.org/10

.3102/00346543053004445

Clark, R. E. (1994). Media will never influence learning. Educational

Technology Research and Development, 42, 21–29. http://dx.doi.org/10

.1007/BF02299088

Clark, R. E. (2001). Learning from media. Greenwich, CT: Information

Age Publishing.

Coleman, E. B., Brown, A. L., & Rivkin, I. D. (1997). The effect of

instructional explanations on learning from scientific texts. Journal of

the Learning Sciences, 6, 347–365.

Cooper, T. (2007). Nutrition game. In D. Livingstone & J. Kemp (Eds),

Proceedings of the second life education workshop (pp. 47–50). Chi-

cago, IL: Second Life Education.

Dewey, J. (1913). Interest and effort in education. Boston, MA: Houghton

Mifflin. http://dx.doi.org/10.1037/14633-000

Doctorow, M., Wittrock, M. C., & Marks, C. (1978). Generative processes

in reading comprehension. Journal of Educational Psychology, 70, 109 –

118. http://dx.doi.org/10.1037/0022-0663.70.2.109

Evans, K. L., Yaron, D., & Leinhardt, G. (2008). Learning stoichiometry:

A comparison of text and multimedia formats. Chemistry Education

Research and Practice, 9, 208 –218. http://dx.doi.org/10.1039/B81

2409B

Fiorella, L., & Mayer, R. E. (2012). Paper-based aids for learning with a

computer-based game. Journal of Educational Psychology, 104, 1074 –

1082. http://dx.doi.org/10.1037/a0028088

Fiorella, L., & Mayer, R. E. (2015). Learning as a generative activity:

Eight learning strategies that promote understanding. New York, NY:

Cambridge University Press. http://dx.doi.org/10.1017/CBO978110

7707085

Fiorella, L., & Mayer, R. E. (2016). Eight ways to promote generative

learning. Educational Psychology Review, 28, 717–741. http://dx.doi

.org/10.1007/s10648-015-9348-9

Harp, S. F., & Mayer, R. E. (1997). The role of interest in learning from

scientific text and illustrations: On the distinction between emotional

interest and cognitive interest. Journal of Educational Psychology, 89,

92–102. http://dx.doi.org/10.1037/0022-0663.89.1.92

Harp, S. F., & Mayer, R. E. (1998). How seductive details do their damage:

A theory of cognitive interest in science learning. Journal of Educational

Psychology, 90, 414 – 434. http://dx.doi.org/10.1037/0022-0663.90.3

.414

Hattie, J. (2009). Visible learning: A synthesis of over 800 meta-analyses

relating to achievement. New York, NY: Routledge.

Hew, K. F., & Cheung, W. S. (2010). Use of three-dimensional (3-D)

immersive virtual worlds in K–12 and higher education settings: A

review of the research. British Journal of Educational Technology, 41,

33–55. http://dx.doi.org/10.1111/j.1467-8535.2008.00900.x

This document is copyrighted by the American Psychological Association or one of its allied publishers.

This article is intended solely for the personal use of the individual user and is not to be disseminated broadly.

LEARNING IN IMMERSIVE VR

Hilton, M. A., & Honey, M. L. (2011). Learning science through computer

games and simulations. Washington, DC: The National Academy Press.

Hwang, G. C., Wu, P. H., & Chen, C. C. (2012). An online game approach

for improving students’ learning performance in Web-based problem-

solving activities. Computers & Education, 59, 1246 –1256. http://dx.doi

.org/10.1016/j.compedu.2012.05.009

Kintsch, W. (1980). Learning from text, levels of comprehension, or: Why

anyone would read a story anyway. Poetics, 9, 87–98. http://dx.doi.org/

10.1016/0304-422X(80)90013-3

Kozhevnikov, M., Gurlitt, J., & Kozhevnikov, M. (2013). Learning relative

motion concepts in immersive and non-immersive virtual environments.

Journal of Science Education and Technology, 22, 952–962. http://dx

.doi.org/10.1007/s10956-013-9441-0

Kozma, R. B. (1994). The influence of media on learning: The debate

continues. School Library Media Research, 22. Retrieved from http://

www.ala.org/aasl/sites/ala.org.aasl/files/content/aaslpubsandjournals/slr/

edchoice/SLMQ_InfluenceofMediaonLearning_InfoPower.pdf

Lee, E. A., & Wong, K. W. (2014). Learning with desktop virtual reality:

Low spatial ability learners are more positively affected. Computers &

Education, 79, 49 –58. http://dx.doi.org/10.1016/j.compedu.2014.07.010

Lee, H., Plass, J. L., & Homer, B. D. (2006). Optimizing cognitive load for

learning from computer-based science simulations. Journal of Educa-

tional Psychology, 98, 902–913. http://dx.doi.org/10.1037/0022-0663.98

.4.902

Ligorio, M. B., & van Veen, K. (2006). Constructing a successful cross-

national virtual learning environment in primary and secondary educa-

tion. AACE Journal, 14, 103–128.

Lowe, R., & Ploetzner, R. (Eds.). (2017). Learning from dynamic visual-

ization. New York, NY: Springer. http://dx.doi.org/10.1007/978-3-319-

56204-9

Mayer, R. E. (2008). Teaching by priming students’ motivation to learn. In

R. E. Mayer (Ed.), Learning and instruction (pp. 458 –522). Upper

Saddle River, NJ: Pearson Education.

Mayer, R. E. (2009). Multimedia learning. New York, NY: Cambridge

University Press. http://dx.doi.org/10.1017/CBO9780511811678

Mayer, R. E. (2014a). Cognitive theory of multimedia learning. In R. E.

Mayer (Ed.), The Cambridge handbook of multimedia learning (2nd ed.,

pp. 43–71). New York, NY: Cambridge University Press. http://dx.doi

.org/10.1017/CBO9781139547369.005

Mayer, R. E. (2014b). Computer games for learning: An evidence-based

approach. Cambridge, MA: MIT Press.

Mayer, R. E. (2014c). Principles based on social cues in multimedia

learning: Personalization, voice, image, and embodiment principles. In

R. E. Mayer (Ed.), The Cambridge handbook of multimedia learning

(2nd ed., pp. 345–368). New York, NY: Cambridge University Press.

http://dx.doi.org/10.1017/CBO9781139547369.017

Mayer, R. E., Bove, W., Bryman, A., Mars, R., & Tapangco, L. (1996).

When less is more: Meaningful learning from visual and verbal sum-

maries of science textbook lessons. Journal of Educational Psychology,

88, 64 –73. http://dx.doi.org/10.1037/0022-0663.88.1.64

Mayer, R. E., & Chandler, P. (2001). When learning is just a click away:

Does simple user interaction foster deeper understanding of multimedia

messages? Journal of Educational Psychology, 93, 390 –397. http://dx

.doi.org/10.1037/0022-0663.93.2.390

Mayer, R. E., Dow, G. T., & Mayer, S. (2003). Multimedia learning in an

interactive self-explaining environment: What works in the design of

agent-based microworlds? Journal of Educational Psychology, 95, 806 –

812. http://dx.doi.org/10.1037/0022-0663.95.4.806

Mayer, R. E., & Fiorella, L. (2014). Principles for reducing extraneous

processing in multimedia learning: Coherence, signaling, redundancy,

spatial contiguity, and temporal contiguity principles. In R. E. Mayer

(Ed.), The Cambridge handbook of multimedia learning (2nd ed., pp.

279 –315). New York, NY: Cambridge University Press. http://dx.doi

.org/10.1017/CBO9781139547369.015

Mayer, R. E., Griffith, E., Naftaly, I., & Rothman, D. (2008). Increased

interestingness of extraneous details leads to decreased learning. Journal

of Experimental Psychology: Applied, 14, 329 –339. http://dx.doi.org/10

.1037/a0013835

Mayer, R. E., Hegarty, M., Mayer, S., & Campbell, J. (2005). When static

media promote active learning: Annotated illustrations versus narrated

animations in multimedia instruction. Journal of Experimental Psychol-

ogy: Applied, 11, 256 –265. http://dx.doi.org/10.1037/1076-898X.11.4

.256

Mayer, R. E., Heiser, H., & Lonn, S. (2001). Cognitive constraints on

multi-media learning: When presenting more material results in less

understanding. Journal of Educational Psychology, 93, 187–198. http://

dx.doi.org/10.1037/0022-0663.93.1.187

Mayer, R. E., & Jackson, C. I. (2005). The case for coherence in science

explanations: Quantitative details hurt qualitative understanding. Jour-

nal of Educational Psychology, 100, 380 –386. http://dx.doi.org/10

.1037/0022-0663.100.2.380

Mayer, R. E., & Pilegard, C. (2014). Principles for managing essential

processing in multimedia learning: Segmenting, pre-training, and mo-

dality principles. In R. E. Mayer (Ed.), The Cambridge handbook of

multimedia learning (2nd ed., pp. 316 –344). New York, NY: Cambridge

University Press. http://dx.doi.org/10.1017/CBO9781139547369.016

McLaren, B. M., Adams, D. M., Mayer, R. E., & Forlizzi, J. (2017). A

computer-based game that promotes mathematics learning more than a

conventional approach. International Journal of Game-Based Learning,

7, 36 –56. http://dx.doi.org/10.4018/IJGBL.2017010103

Merchant, Z., Goetz, E. T., Cifuentes, L., Keeney-Kennicutt, W., & Davis,

T. J. (2014). Effectiveness of virtual reality-based instruction on stu-

dents’ learning outcomes in K–12 and higher education. Computers &

Education, 70, 29 – 40. http://dx.doi.org/10.1016/j.compedu.2013.07

.033

Moreno, R., & Mayer, R. E. (2000). A coherence effect in multimedia

learning: The case for minimizing irrelevant sounds in the design of

multimedia messages. Journal of Educational Psychology, 92, 117–125.

http://dx.doi.org/10.1037/0022-0663.92.1.117

Moreno, R., & Mayer, R. E. (2002). Learning science in virtual reality

environments: Role of methods and media. Journal of Educational

Psychology, 92, 724 –733. http://dx.doi.org/10.1037/0022-0663.92.4

.724

Moreno, R., & Mayer, R. E. (2004). Personalized messages that promote

science learning in virtual environments. Journal of Educational Psy-

chology, 96, 165–173. http://dx.doi.org/10.1037/0022-0663.96.1.165

Moreno, R., Mayer, R. E., Spires, H. A., & Lester, J. C. (2001). The case

for social agency in computer-based teaching: Do students learn more

deeply when they interact with animated pedagogical agents? Cognition

and Instruction, 19, 177–213. http://dx.doi.org/10.1207/S1532690X

CI1902_02

Peper, R. J., & Mayer, R. E. (1986). Generative effects of note-taking

during science lectures. Journal of Educational Psychology, 78, 34 –38.

http://dx.doi.org/10.1037/0022-0663.78.1.34

Phye, G. D., Robinson, D. H., & Levin, J. (Eds.). (2005). Empirical

methods for evaluating educational interventions. San Diego, CA:

Elsevier Academic Press.

Pietsch, J., Walker, R., & Chapman, E. (2003). The relationship among

self-concept, self-efficacy, and performance in mathematics during sec-

ondary school. Journal of Educational Psychology, 95, 589 – 603. http://

dx.doi.org/10.1037/0022-0663.95.3.589

Pilegard, C., & Mayer, R. E. (2016). Improving academic learning from

computer-based narrative games. Contemporary Educational Psychol-

ogy, 44, 12–20. http://dx.doi.org/10.1016/j.cedpsych.2015.12.002

Pintrich, P. R. (2003). Motivation and classroom learning. In W. M.

Reynold & G. E. Miller (Eds.), Handbook of psychology: Vol. 7.Edu-

cational psychology (pp. 103–122). New York, NY: Wiley.

This document is copyrighted by the American Psychological Association or one of its allied publishers.

This article is intended solely for the personal use of the individual user and is not to be disseminated broadly.

12 PARONG AND MAYER

Richards, D., & Taylor, M. (2015). A comparison of learning gains when

using a 2D simulation tool versus a 3D virtual world: An experiment to

find the right representation involving the marginal value theorem.

Computers & Education, 86, 157–171. http://dx.doi.org/10.1016/j

.compedu.2015.03.009

Ross, S. M., & Kirby, F. J. (1976). Oral summary as a review strategy for

enhancing recall of textual material. Journal of Educational Psychology,

68, 689 – 695. http://dx.doi.org/10.1037/0022-0663.68.6.689

Saettler, P. (1990/2004). The evolution of American educational technol-

ogy. Greenwich, CT: Information Age Publishing.

Salomon, G. (1979). Interaction of Media, Cognition, and Learning. San

Francisco: Jossey-Bass.

Schiefele, U. (2009). Situational and individual interest. In K. R. Wentzel

& A. Wigfield (Eds.), Handbook of motivation in school (pp. 197–223).

New York, NY: Taylor & Francis.

Schiefele, U., Krapp, A., & Winteler, A. (1992). Interest as a predictor of

academic achievement: A meta-analysis of research. In K. A. Renninger,

S. Hidi, & A. Krapp (Eds.), The role of interest in learning and

development (pp. 183–212). Hillsdale, NJ: Erlbaum.

Schunk, D. H. (1989). Self-efficacy and achievement behaviors. Educa-

tional Psychology Review, 1, 173–208. http://dx.doi.org/10.1007/BF013

20134

Schunk, D. H. (1991). Self-efficacy and academic motivation. Educational

Psychologist, 26, 207–231. http://dx.doi.org/10.1080/00461520.1991

.9653133

Schunk, D. H., & DiBenedetto, M. K. (2016). Self-efficacy theory. In K. R.

Wentzel & D. B. Miele (Eds.), Handbook of motivation at school (2nd

ed., pp. 34 –54). New York, NY: Routledge.

Schunk, D. H., & Hanson, A. R. (1985). Peer models: Influences on

children’s self-efficacy and achievement. Journal of Educational Psy-

chology, 77, 313–322. http://dx.doi.org/10.1037/0022-0663.77.3.313

Shavelson, R. J., & Towne, L. (Eds.). (2002). Scientific research in

education. Washington, DC: National Academy Press.

Sourin, A., Sourina, O., & Prasolova-Førland, E. (2006). Cyber-learning in

cyberworlds. Journal of Cases on Information Technology, 8, 55–70.

http://dx.doi.org/10.4018/jcit.2006100105

Swaak, J., de Jong, T., & van Joolingen, W. R. (2004). The effects of

discovery learning and expository instruction on the acquisition of

definitional and intuitive knowledge. Journal of Computer Assisted

Learning, 20, 225–234. http://dx.doi.org/10.1111/j.1365-2729.2004

.00092.x

Sweller, J., Ayres, P., & Kalyuga, S. (2011). Cognitive Load Theory. New

York, NY: Springer. http://dx.doi.org/10.1007/978-1-4419-8126-4

The Body VR. (2016). The Body VR: Journey inside a cell [Video Game].

New York, NY: The Body VR LLC.

Torkington, J., Smith, S. G., Rees, B. I., & Darzi, A. (2001). Skill transfer

from virtual reality to a real laparoscopic task. Surgical Endoscopy, 15,

1076 –1079. http://dx.doi.org/10.1007/s004640000233

Wade, S. E. (1992). How interest affects learning from text. In K. A.

Renninger, S. Hidi, & A. Krapp (Eds.), The role of interest in learning

and development (pp. 255–278). Hillsdale, NJ: Erlbaum.

Webster, R. (2016). Declarative knowledge acquisition in immersive vir-

tual learning environments. Interactive Learning Environments, 24,

1319 –1333. http://dx.doi.org/10.1080/10494820.2014.994533

Wentzel, K., & Miele, D. B. (Eds.). (2016). Handbook of motivation at

school (2nd ed.). New York, NY: Routledge.

Wigfield, A., Tonks, S., & Klauda, S. L. (2016). Expectancy-value theory.

In K. R. Wentzel & D. B. Miele (Eds.), Handbook of motivation in

school (2nd ed; pp. 55–74). New York, NY: Routledge.

Wittrock, M. C. (1989). Generative processes of comprehension. Educa-

tional Psychologist, 24, 345–376. http://dx.doi.org/10.1207/s1532

6985ep2404_2

Wouters, P., & van Oostendorp, H. (2017). Overview of instructional

techniques to facilitate learning and motivation of serious games. In P.

Wouters & H. van Oostendorp (Eds.), Instructional techniques to facil-

itate learning and motivation of serious games (pp. 1–16). New York,

NY: Springer. http://dx.doi.org/10.1007/978-3-319-39298-1_1

Zimmerman, B. J., & Martinez-Pons, M. (1990). Student differences in

self-regulated learning: Relating grade, sex, and giftedness to self-

efficacy and strategy use. Journal of Educational Psychology, 82, 51–

59. http://dx.doi.org/10.1037/0022-0663.82.1.51

Received June 5, 2017

Revision received August 10, 2017

Accepted September 13, 2017 䡲

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Bu çalışma, açınsayıcı bir dijital eğitsel oyun ortamının bilgisayar programlamada yeni olan öğrencilerin nesne yönelimli programlama kavramsal bilgisi geliştirmelerine etkisini dört değişik öğrenme destek senaryosunda incelemeyi amaçlamıştır. Dört farklı sürüm olarak geliştirilen eğitsel oyunda öğrenme destekleri, (a) önceden gösterme ve eğitsel kılavuz desteği, (b) sadece eğitsel kılavuz desteği, (c) eğitsel kılavuz ve öğrenme ürününe özgü destek ve (d) eğitsel kılavuz ve akran iş birliği olarak çeşitlendirilmiştir. Çalışmanın nicel verileri ön ve son başarı testleri, çevrimiçi öz-düzenleme ölçeği ve öğrenme nesnesi değerlendirme ölçeği ile toplanmış, nitel verileri ise deney grubundaki bazı öğrencilerle yapılan yarı yapılandırılmış görüşmelerle toplanmıştır. Çalışmaya aynı içeriği oyun ortamı dışında öğretmenle çalışan bir kontrol grubu da dahil edilmiştir. Dört deney ve bir kontrol grubundaki (n=149) öğrencilerden elde edilen verilerin çözümlemesi, açınsayıcı dijital oyun ortamında kullanılan öğrenme destek türlerinin öğrenmeye farklı etkisine işaret etmiştir. Çalışmada ayrıca öğrenme destek türü, çevrimiçi öz düzenleme ve öğrenme nesnesi değerlendirme değişkenlerinin etkileşimi istatistiksel olarak incelenmiştir. Çalışma açınsayıcı dijital eğitsel oyunlarda öğrenme desteklerinin kullanımı üzerine bir dizi öneri ve olası araştırma konularını tartışmıştır.

HoloArm: A Face-Following 3D Display Using Autostereoscopic Display and Robot Arm

Conference Paper

Apr 2025

When Learning Is Just a Click Away: Does Simple User Interaction Foster Deeper Understanding of Multimedia Messages?

Article

Full-text available

Jun 2001

In 2 experiments, students received 2 presentations of a narrated animation that explained how lightning forms followed by retention and transfer tests. In Experiment 1, learners who were allowed to exercise control over the pace of the narrated animation before a second presentation of the same material at normal speed (part–whole presentation) performed better on transfer but not retention tests compared with learners who received the same 2 presentations in the reverse order (whole–part presentation). In Experiment 2, learners who were allowed to exercise control over the pace of the narrated animation across 2 presentations (part–part presentation) performed better on transfer but not retention tests compared with learners who received the same 2 presentations at normal speed without any learner control (whole–whole presentation). These results are consistent with cognitive load theory and a 2-stage theory of mental model construction.

Self-Efficacy: Toward a Unifying Theory of Behavioral Change

Article

Full-text available

Mar 1977

Albert Bandura

Presents an integrative theoretical framework to explain and to predict psychological changes achieved by different modes of treatment. This theory states that psychological procedures, whatever their form, alter the level and strength of self-efficacy. It is hypothesized that expectations of personal efficacy determine whether coping behavior will be initiated, how much effort will be expended, and how long it will be sustained in the face of obstacles and aversive experiences. Persistence in activities that are subjectively threatening but in fact relatively safe produces, through experiences of mastery, further enhancement of self-efficacy and corresponding reductions in defensive behavior. In the proposed model, expectations of personal efficacy are derived from 4 principal sources of information: performance accomplishments, vicarious experience, verbal persuasion, and physiological states. Factors influencing the cognitive processing of efficacy information arise from enactive, vicarious, exhortative, and emotive sources. The differential power of diverse therapeutic procedures is analyzed in terms of the postulated cognitive mechanism of operation. Findings are reported from microanalyses of enactive, vicarious, and emotive modes of treatment that support the hypothesized relationship between perceived self-efficacy and behavioral changes. (21/2 p ref)

A Computer-Based Game that Promotes Mathematics Learning More than a Conventional Approach

Article

Full-text available

Jan 2017

Excitement about learning from computer-based games has been papable in recent years and has led to the development of many educational games. However, there are relatively few sound empirical studes in the scientific literature that have shown the benefits of learning mathematics from games as opposed to more traditional approaches. The empirical study reported in this paper provides evidence that a mathematics educational game can provide superior learning opportunities, as well as be more engaging. In a study involving 153 students from two middle schools, 70 students learned about decimals from playing an educational game-Decimal Point-whereas 83 students learned the same content by a more conventional, computer-based approach. The game led to significantly better gain scores in solving decimal problems, on both an immediate (d = .43) and delayed (d = .37) posttest and was rated as significantly more enjoyable (d = .95). Low prior knowledge students especially benefitted from the game. This paper also summarizes the game's design characteristics.

Cognitive Load Theory

Article

Jan 2011

Cognitive Load Theory John Sweller, Paul Ayres, Slava Kalyuga Effective instructional design depends on the close study of human cognitive architecture—the processes and structures that allow people to acquire and use knowledge. Without this background, we might recognize that a teaching strategy is successful, but have no understanding as to why it works, or how it might be improved. Cognitive Load Theory offers a novel, evolutionary-based perspective on the cognitive architecture that informs instructional design. By conceptualizing biological evolution as an information processing system and relating it to human cognitive processes, cognitive load theory bypasses many core assumptions of traditional learning theories. Its focus on the aspects of human cognitive architecture that are relevant to learning and instruction (particularly regarding the functions of long-term and working memory) puts the emphasis on domain-specific rather than general learning, resulting in a clearer understanding of educational design and a basis for more effective instructional methods. Coverage includes: • The analogy between evolution by natural selection and human cognition. • Categories of cognitive load and their interactions in learning. • Strategies for measuring cognitive load. • Cognitive load effects and how they lead to educational innovation. • Instructional design principles resulting from cognitive load theory. Academics, researchers, instructional designers, cognitive and educational psychologists, and students of cognition and education, especially those concerned with education technology, will look to Cognitive Load Theory as a vital addition to their libraries.

Learning from dynamic visualization: Innovations in research and application

Book

May 2017

This volume tackles issues arising from today's high reliance on learning from visualizations in general and dynamic visualizations in particular at all levels of education. It reflects recent changes in educational practice through which text no longer occupies its traditionally dominant role as the prime means of presenting to-be-learned information to learners. Specifically, the book targets the dynamic visual components of multimedia educational resources and singles out how they can influence learning in their own right. It aims to help bridge the increasing gap between pervasive adoption of dynamic visualizations in educational practice and our limited understanding of the role that these representations can play in learning. The volume has recruited international leaders in the field to provide diverse perspectives on the dynamic visualizations and learning. It is the first comprehensive book on the topic that brings together contributions from both renowned researchers and expert practitioners. Rather than aiming to present a broad general overview of the field, it focuses on innovative work that is at the cutting edge. As well as further developing and complementing existing approaches, the contributions emphasize fresh ideas that may challenge existing orthodoxies and point towards future directions for the field. They seek to stimulate further new developments in the design and use of dynamic visualizations for learning as well as the rigorous, systematic investigation of their educational effectiveness. © Springer International Publishing AG 2017. All rights reserved.

Empirical Methods for Evaluating Educational Interventions

Book

Jan 2005

New US government requirements state that federally funded grants and school programs must prove that they are based on scientifically proved improvements in teaching and learning. All new grants must show they are based on scientifically sound research to be funded, and budgets to schools must likewise show that they are based on scientifically sound research. However, the movement in education over the past several years has been toward qualitative rather than quantitative measures. The new legislation comes at a time when researchers are ill trained to measure results or even to frame questions in an empirical way, and when school administrators and teachers are no longer remember or were never trained to prove statistically that their programs are effective. Experimental Methods for Evaluating Educational Interventions is a tutorial on what it means to frame a question in an empirical manner, how one needs to test that a method works, what statistics one uses to measure effectiveness, and how to document these findings in a way so as to be compliant with new empirically based requirements. The book is simplistic enough to be accessible to those teaching and administrative educational professionals long out of schooling, but comprehensive and sophisticated enough to be of use to researchers who know experimental design and statistics but don't know how to use what they know to write acceptable grant proposals or to get governmental funding for their programs.

Overview of Instructional Techniques to Facilitate Learning and Motivation of Serious Games

Chapter

Nov 2017

Computer games that are used for the purpose of learning, training, and instruction are often referred to as serious games. The last decade shows a huge increase in empirical studies investigating the learning effectiveness and motivational appeal of serious games. Recent meta-analyses show that serious games are effective compared to traditional instruction but that the effectiveness can be improved. This chapter explores which specific instructional techniques can further improve learning and increase motivation. We define instructional techniques as any adaptation of a feature of the game itself or in the context of the game that influences the selection of relevant information, the organization, and integration of that information and/or the intrinsic motivation of the player. The starting point is a meta-analysis conducted in 2013 that is updated and extended. The meta-analysis has a value-added approach and shows which game features can improve learning and/or increase motivation. The interpretation of the results will yield nine proven effective or promising instructional techniques in terms of learning and/or motivation. This set of nine techniques—content integration, context integration, assessment and adaptivity, level of realism, narration-based techniques, feedback, self-explanation and reflection, collaboration and competition, and modeling—form the basis of this volume, which is closed by a reflection chapter.

Cambridge Handbook of Multimedia Learning: Second Edition

Book

Jan 2014

Richard Mayer

Multimedia Learning: Second Edition

Book

Jan 2009

Richard Mayer

For hundreds of years verbal messages such as lectures and printed lessons have been the primary means of explaining ideas to learners. Although verbal learning offers a powerful tool, this book explores ways of going beyond the purely verbal. Recent advances in graphics technology have prompted new efforts to understand the potential of multimedia and multimedia learning as a means of promoting human understanding. In Multimedia Learning, Second Edition, Richard E. Mayer asks whether people learn more deeply when ideas are expressed in words and pictures rather than in words alone. He reviews twelve principles of instructional design that are based on experimental research studies and grounded in a theory of how people learn from words and pictures. The result is what Mayer calls the cognitive theory of multimedia learning, a theory introduced in the first edition of Multimedia Learning and further developed in The Cambridge Handbook of Multimedia Learning.

Computer Games for Learning: An Evidence-Based Approach

Book

Jul 2014

Richard Mayer

A comprehensive and up-to-date investigation of what research shows about the educational value of computer games for learning. Many strong claims are made for the educational value of computer games, but there is a need for systematic examination of the research evidence that might support such claims. This book fills that need by providing, a comprehensive and up-to-date investigation of what research shows about learning with computer games. Computer Games for Learning describes three genres of game research: the value-added approach, which compares the learning outcomes of students who learn with a base version of a game to those of students who learn with the base version plus an additional feature; the cognitive consequences approach, which compares learning outcomes of students who play an off-the-shelf computer game for extended periods to those of students who do not; and the media comparative approach, which compares the learning outcomes of students who learn material by playing a game to those of students who learn the same material using conventional media. After introductory chapters that describe the rationale and goals of learning game research as well as the relevance of cognitive science to learning with games, the book offers examples of research in all three genres conducted by the author and his colleagues at the University of California, Santa Barbara; meta-analyses of published research; and suggestions for future research in the field. The book is essential reading for researchers and students of educational games, instructional designers, learning-game developers, and anyone who wants to know what the research has to say about the educational effectiveness of computer games.

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