The effects of metaphorical interface on germane cognitive load in Web-based instruction

RESEARCH ARTICLE

The effects of metaphorical interface on germanecognitive load in Web-based instruction

Jongpil Cheon • Michael M. Grant

Published online: 21 February 2012� Association for Educational Communications and Technology 2012

Abstract The purpose of this study was to examine the effects of a metaphorical

interface on germane cognitive load in Web-based instruction. Based on cognitive load

theory, germane cognitive load is a cognitive investment for schema construction and

automation. A new instrument developed in a previous study was used to measure stu-

dents’ mental activities of schema construction and automation supported by structural

cues in a metaphorical interface environment. Eighty participants were randomly assigned

to one of two types of instructional units with the same instructional content and different

interface types (i.e., non-metaphorical interface and metaphorical interface). The results

indicated that germane cognitive load positively affected learning performance while

there was no relationship between germane cognitive load and students’ prior knowledge.

A metaphorical interface enhanced learners’ germane cognitive load and learning per-

formance, and both germane cognitive load and prior knowledge similarly contributed to

learning performance. The findings provide implications for the advancement of cognitive

load theory and the practice of instructional development.

Keywords Metaphorical interface � Germane cognitive load � User interface

Introduction

A functional, communicative, and aesthetically appropriate user interface plays an

important role in helping learners focus on learning activities. The most important goal of

designing a user interface is to reach learners more effectively. While a graphical user

J. Cheon (&)College of Education, Texas Tech University, Box 41071, Lubbock, TX 79409, USAe-mail: [email protected]

M. M. GrantUniversity of Memphis, 401E Ball Hall, Memphis, TN 38152, USAe-mail: [email protected]

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Education Tech Research Dev (2012) 60:399–420DOI 10.1007/s11423-012-9236-7

interface uses graphical elements to make Web pages pleasant in order to attract the user’s

attention, a relatively new approach for interface design, termed metaphorical interface,

focuses on creating an online environment that reflects the learning content in order to

provide learners with instructional cues (Hsu and Schwen 2003). Metaphor plays a sig-

nificant role in scaffolding the learner to intuitively interact with learning content (Hron

1998; Lang 2003), because it helps the learner structure links between a graphical theme

and content (Cates 1996; Hron 1998). Metaphor could aid the learner to intuitively rec-

ognize how to navigate an instructional system and how learning components are related

each other (Lang 2003; Metros and Hedberg 2002). Although metaphorical interfaces seem

to be a suitable medium for gaining a quick and intuitive understanding of the structure of

learning contents in Web-based instruction, there is little empirical evidence for the value

of metaphorical interfaces.

The effects of interface in learning have been mainly measured by learners’ perceptions

(e.g., Nielson 2000; Pearrow 2007; Plass 1998; Swan 2001). However, a few studies have

examined the relationship between interface and cognitive load (e.g., Cheon and Grant in

press). Since a metaphorical interface could support a user’s cognitive processing, it could

enhance germane cognitive load that was meaningful cognitive effort for schema con-

struction and automation. The purpose of this study is to investigate the effects of a

metaphorical interface on learners’ germane cognitive load in Web-based instruction. More

specifically, the relationships of self-rated germane cognitive load with learners’ learning

performance and prior knowledge were determined, and the metaphorical interface was

compared to non-metaphorical interface in terms of germane cognitive load and learning

performance.

Theoretical background

Interface

A user interface is a communication point between an instructional unit and a learner in

Web-based instruction. More specifically, an interface is the graphical and textual layout

and menus presented in Web-based instruction to a learner on the computer screen (Cheon

and Grant 2009). The roles of an interface have been stated in a number of ways:

(a) attractive displays can capture learners’ attention and interest (Hron 1998; Metros and

Hedberg 2002; Parizotto-Ribeiro and Hammond 2005; Szabo and Kanuka 1998), (b) an

effective interface can facilitate navigation between a user and a computer (Metros and

Hedberg 2002; Parizotto-Ribeiro and Hammond 2005), and (c) an interface also scaffolds a

student’s ability to perceive, organize, integrate and remember information (Chalmers

2003; Haag and Snetsigner 1993; Hannafin and Hooper 1989; Szabo and Kanuka 1998).

While well-designed interfaces that follow interface design guidelines enhance learning,

poorly organized and designed interfaces could inhibit formation of schema and contribute

to disorientation (Chalmers 2003).

In a graphical interface, graphical elements have been used to make Web pages

pleasing in order to gain users’ attention. Also, a graphical interface can implement one

or many metaphors to assist users to intuitively navigate through a system (Lang 2003).

The metaphors allow the user to anticipate possible functions. For example, a ‘‘HOME’’

button, which hyperlinks to a homepage or home screen, is often displayed with a house-

shaped icon. Thus, the intuitive functionality can facilitate navigation in Web-based

instruction.

400 J. Cheon, M. M. Grant

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Metaphors with interface

Metaphors are used to represent a concept by visual or verbal clues that are familiar to

users or are related to the concept. For example, Gentner (1983, p. 162) stated, ‘‘Many

metaphors are predominantly relational comparisons and are thus essentially analogies’’.

Analogies and metaphors are very similar and both aid human cognitive processing by

integrating the current situation into prior exemplars. In the human computer interface

field, visual metaphors are used to provide cueing for how a computer system functionality

works (Lakoff and Johnson 1980). Hron (1998, p. 21) defines metaphors for software

development as a ‘‘means of establishing an analogous relation between a familiar

knowledge domain and the software to be learned’’. More specifically, there are three

different types of metaphors: (a) ontological metaphors (e.g., opening or copying a file),

(b) orientation metaphors (e.g., the ‘‘next’’ button often literally points to the right), and

(c) structural metaphors (e.g., desktop or recycling bin) (Barr et al. 2002; Firat and Kakakci

2010).

Familiar metaphors ‘‘provide a direct and intuitive interface to user tasks. By allowing

users to transfer their knowledge and experience, metaphors make it easier to predict and

learn the behaviors of software-based representations’’ (Microsoft Corporation 1995,

p. 18). Norman (1998) suggested that the interface is what helps the learner have an

internal characterization of his goals within a computer system. Metaphors are used to

apply familiarity to the interface, making tasks easier to complete and remember—both of

which reduce cognitive load for learners. Furthermore, visual metaphors are capable of

conceptualizing the learning content structure in a meaningful way to aid learners to

construct their cognitive schemata (Lee 2007).

Metaphorical interface

Metaphors can strengthen the role of an interface as intermediaries between learning

contents and a learner. A metaphorical interface is an entire online environment that

represents the inherent structure of the learning contents with graphical overview or

structural cueing (Lee 2007; Otter and Johnson 2000). Merging the interface with the

learning contents can create a synergistic interface that is not only user-friendly but also

helps to immerse the learner in the learning contents. A metaphorical interface differs from

attention cueing and graphical interfaces in that graphical interfaces usually employ var-

ious visual elements (e.g., icons and background) that are thematically unrelated. Plus,

graphical interface typically spotlight cueing that focuses on attracting learners’ attention

to a specific part of the learning content (e.g., an arrow to a key term). So, these strategies

employ analogies or metaphors that are independent of one another. Instead, a meta-

phorical interface directly reflects the learning contents and provides a relationship

between the learning content and the visual interface. Metros and Hedberg (2002), p. 203

contend when user interfaces integrate historical periods, cultural motifs, physical locales,

and everyday conventions ‘‘the emulation of familiar conventions reinforces consistency,

takes advantage of previously learned associations, promotes understanding between

diverse concepts, and helps the learner grasp complex ideas’’.

A metaphorical interface conveys what Berkley and Cates (1996) refer to as rich

images, which hold more meaning than the literal definitions. For example, users can

assimilate new knowledge by connecting metaphors into their existing schemata with (Ohl

and Cates 1997). Schemata, also called cognitive schemata, are information structures

stored in long-term memory. The schemata enable individuals to recognize and solve a

Metaphorical Interface 401

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certain category of problems, saving working memory capacity (Paas and Van Merrienboer

1993; Van Gerven et al. 2003).

A metaphorical interface can employ two classes of metaphor (Cates 1996, 2002): (a) an

underlying metaphor (or primary metaphor) employed as a basis, and (b) an auxiliary

metaphor (or secondary) employed later to extend and complement the underlying meta-

phor. Cates (2002) suggested that auxiliary metaphors should be related to characteristics

of an underlying metaphor. For example, when a book metaphor is employed as an

underlying metaphor, auxiliary metaphors could be chapter tabs, page-turning animation,

or highlight functions. Thus, users can easily incorporate the metaphors to unified inter-

pretation of the whole interface.

Metaphorical interfaces can also be classified as two different types depending on the

way metaphors are employed: (a) a thematic and (b) an immersive metaphorical interface. A

thematic metaphorical interface uses a metaphorical theme that does not reflect the contents

but is familiar to users (Cates 1996; Hron 1998; Hsu and Boling 2007). For example, an

interface may use a book or a folder on the computer screen that contains content that is

unrelated to books or folders. On the other hand, some metaphorical interfaces attempt to

create an authentic environment that reflects learning contents with structural cues or

organizational hints we have termed these immersive metaphorical interfaces. For example,

a realistic interface could be designed to provide more situated learning (Herrington et al.

2000), or various organizational cueing of learning contents could be provided in

an interface (de Koning et al. 2010). As an exemplar for CD-ROM, see for example

Herrington’s (1997) description of the development of an interactive and authentic learning

environment for preservice teachers. This study focuses on the immersive metaphorical

interface.

Based on the relationship between a metaphorical theme and learning content, learners

can intuitively interact with instructional resources to organize cognitive schemata

(Allbritton 1995; Cates 1994, 1996; Lang 2003; Metros and Hedberg 2002) and develop

mental models (Cates and Berkley 2000; de Jong and van der Hulst 2002; Mitchell et al.

2005).

A mental model is an internal mental representation of external information, such as

objects, phenomena or concepts (Henderson et al. 2002; Jih and Reeves 1992). Driscoll

(2005), p. 130 suggests that mental models ‘‘guide and govern performance’’ during

learning or problem solving. Thus, metaphors can help mental model construction to

understand what the external information is and predict how it works.

A metaphorical interface can build learning cues to contents that help learners create

new and accurate mental models. Van Dam (2000) asserts that the aim of interface design

should be to complement human abilities, including cognition. In mental models theory,

there are three models (Davidson et al. 1999; Norman 1998): (a) system model which is the

way that a system works from the programmer’s perspective, (b) design model which is the

way designers represent the program to users, and (c) mental model which is the way that

users perceive how the system works. Based on the models, if a designer creates an

effective design model, users will develop an appropriate mental model that allows them to

interact with the system successfully. In contrast, an inappropriate design model may make

it difficult for the user to form a mental picture, or schema, of the information presented via

a computer screen. In order to form a schema, users need to be able to understand where

new learning contents fit into their existing schemata (Chalmers 2003), and a metaphorical

interface offers promise for providing cues to schema construction.

A metaphorical interface has the potential to play an important role in the design model.

It could provide a systematic visual representation of the learning domain that may lead the


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user to a better acquisition of the domain structure (de Jong and van der Hulst 2002;

Mitchell et al. 2005). The visual representation could be provided as a visual layout

throughout units, such as a background or navigation. However, mismatched metaphors

may cause learners to misunderstand the learning content (Cates 2002; Lohr and Ku 2003).

Interpreting metaphors could also impose an additional cognitive load on learners who are

trying to understand not only the meaning of metaphor but also any instructional content.

Inappropriate metaphors that misrepresent or confound a relationship or representation of

learning contents could lead to incorrect inferences (Barr et al. 2002; Hamilton 2000; Hsu

and Boling 2007). Therefore, metaphorical environment should be easily understandable.

Also, metaphors should provide a visually effective model of information structure to lead

learner to build an appropriate mental model.

Although a metaphorical interface offers promise, selection and application of appro-

priate metaphors is still challenging for instructional designers (Cates 2002). The design

guidelines proposed from previous research emphasized the connection of an interface to

learning content and learners’ characteristics as follows:

• Metaphors should be related to learning contents and provide adequate clues to users

(Hsu and Boling 2007; Hudson 2000): For example, a virtual time machine room would

be an appropriate metaphor to teach geological time and how stratification and

sedimentation layers occur.

• Metaphors should represent the system structure, such as information sequence (Barr

et al. 2002; Hron 1998; Hsu and Boling 2007; Hudson 2000): For example, if a book

metaphor is used, the subordinate metaphor should be chapters or bookmarks. Thus, the

relation of the metaphors represents the structure of the learning contents.

• Learning environment, navigation, and learning contents should be closely interrelated

(Hron 1998): A sightseeing metaphor, for example, used in learning French, provides

not only an environment but also navigation through famous streets in Paris.

• Appearance and action are both important aspects of metaphors (Hsu and Boling 2007;

Hudson 2000): For example, an instrument panel (e.g., an automobile dashboard or a

machine control panel) metaphor should allow learners to monitor and control the

instrument through appropriate and expected knobs, dials, sliders, etc.

• Metaphors should consider learner’s age and culture (Hudson 2000; Ohl and Cates

1997): For example, an operatic scene metaphor may not be familiar to young children

or individuals who have not watched an opera before.

One of the promising methods to maximize the advantages of a metaphorical interface

could be providing structural hints or clues through the interface. To examine the function

of a metaphorical interface, human’s cognitive activities related to building a schema

should be examined.

Interface and cognitive load

Proponents of cognitive load theory argue that working memory is limited (Sweller and

Chandler 1994). Cognitive load theory strives to capture the learner’s focus by preventing

the learner’s capacity from overloading (Vogt 2001). Cognitive load theory distinguishes

three types of cognitive load: (a) intrinsic cognitive load as an inherent cognitive resource

caused by the complexity of learning content, (b) extraneous cognitive load as an irrelevant

cognitive resource caused by the medium, layout or structure of instruction, and (c) ger-

mane cognitive load as a relevant cognitive resource caused by the learner’s investment on

schema construction and automation (Cheon and Grant in press; Sweller et al. 1998; van


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Merrienboer and Ayres 2005). Germane load is caused by working memory processes that

lead to schema construction and automation (Beers et al. 2008). Human expertise comes

from knowledge stored in cognitive schemata. New information is organized in an existing

schema, or a new schema is constructed to store the new information. Constructed sche-

mata become automated when the information is retrieved multiple times (van Merrienboer

and Sweller 2005). Thus, effective instructional methods encourage learners to invest

germane cognitive load for schema construction and automation.

Cognitive load theory offers significant direction for the area of interface design; how-

ever, this agenda has primarily focused on how to reduce extraneous cognitive load (e.g.,

Shneiderman and Plaisant 2005; Swan 2001). In short, the cognitive perspective for interface

design guidelines emphasizes that operating an interface should not require unnecessary

cognitive resources. The following guidelines have been suggested: (a) provide informative

system feedback (Norman 1998), (b) use intuitive elements (Norman 1998), (c) provide

directions (Swan 2004), (d) avoid extraneous objects (Beriswill 1998; Swan 2004), (e) use

organizational strategies (Chalmers 2003; Norman 1998), and (f) provide visual elements

(Swan 2004).

Meanwhile, few empirical studies have investigated the effects of an interface on

germane cognitive load. Because a metaphorical interface can provide the learner with a

coherent framework and schema for understanding complex domains, the cognitive aids

with visual cues may be closely related to germane cognitive load. In an immersive

metaphorical interface, visual cues, such as relational or procedural cues (de Koning et al.

2010), may help learners construct a coherent mental representation of what they learn,

because metaphors facilitate a connection between learners’ cognitive architecture and

knowledge structures. However, there is lack of instruments to measure germane cognitive

load. Instead, mental effort has been used to measure overall cognitive load. The mental

effort instrument uses six- or nine-point Likert scales with the question ‘‘Please indicate

how difficult the instruction/test you just took was by clicking on the appropriate degree of

difficulty’’ (Kalyuga and Sweller 2005). The rating scales have been widely used, because

they are simple and non-invasive (Rikers et al. 2004; van Merrienboer and Sweller 2005).

The measurement of germane cognitive load is critical in order to examine the effects of a

metaphorical interface. Since the germane cognitive load refers to the cognitive resources

in which learners are investing in schema construction and automation, a new instrument

was proposed to measure learners’ cognitive processing for schema construction and

automation (Cheon and Grant in press). This study employed the proposed measurement of

germane cognitive load in terms of interface.

Research questions and hypotheses

We considered the role of germane cognitive load proposed in cognitive load theory and

investigated the effects of a metaphorical interface on germane cognitive load. The specific

research questions and hypotheses explored were:

1. Is there a relationship between germane cognitive load and learning performance? Based

on the cognitive load theory, we assumed that there would be a positive relationship

between germane load and learning performance, because germane cognitive load is

the cognitive resources learners devote to structure cognitive schemata (Paas et al.

2005).

2. Is there a relationship between prior knowledge and germane cognitive load? We

expected that prior knowledge would have a negative relationship with germane load


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because individuals who already know the learning contents would not need to invest

cognitive resources (Paas et al. 2005).

3. Do the metaphorical interface and the non-metaphorical interface groups differ in

germane cognitive load? We hypothesized that the metaphorical interface would

increase germane load, because metaphorical representation of the learning contents

aids learners’ cognitive process to store and retrieve information (Ohl and Cates 1997;

Van Gerven et al. 2003).

4. Do the metaphorical interface and the non-metaphorical interface groups differ in

learning performance? Our hypothesis was that the metaphorical interface group

would have higher learning performance since the metaphors would help learners’

schema construction and automation (Cates 2002).

5. Do prior knowledge, germane cognitive load, and interface type contribute to learning

performance? This question is exploratory to determine any significant contributors to

learning performance.

Methods

Participants

The participants were 83 undergraduate students (male = 26, female = 57) in the Jour-

nalism Department at a large southern university. The study was conducted in the two

online courses ‘‘Introduction to Public Relations,’’ and ‘‘Public Relations Campaign.’’ The

participants were undergraduate students (junior = 37, senior = 46) who were taking

these courses, and all students were asked to take this instruction. The instruction was self-

paced, and the average time to complete the unit was 30 min. The participants were

familiar with accessing an online syllabus, uploading assignments and contributing to a

discussion board, because all of them had experience with online or Web-supported classes

using the university’s course management system (i.e., Desire2Learn).

Instructional units

Two different types of user interface with the same content on the nature and history of

public relations were implemented. The learning content was developed based on a text-

book, and the content was verified by an instructor of two courses, ‘‘Introduction to Public

Relations,’’ and ‘‘Public Relations Campaign.’’ Both instructional units were designed for

linear progression and user-controlled navigation. Both units had the same directions page

showing the structure of the unit and an introduction page presenting objectives of each

chapter. Next, design guidelines of graphical interface and metaphorical interface based on

various studies were applied to implement two different user interfaces. Each is described

below.

Non-metaphorical interface

This interface used text for learning content and graphical elements for background layouts

and navigation menus. The appearance of the text in the instruction was designed with

Cascading Style Sheets (CSS) based on the typography guidelines (Lee and Boling 1999)

as follows:


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• Be consistent in addressing textual cues and signals to the learners.

• Use both upper and lower case letters.

• Use high contrast between letters and background to improve legibility and readability.

• Left-justify text.

• Limit text to approximately 8–10 words per line.

• Use highlighting techniques conservatively and carefully.

• Select typeface with a simple and clean style, and use few font types.

In addition to the usage of typography guidelines, graphic elements were used in this

interface. The screen layout was divided into two different sections: a title section and a

body section. The title section was designed with a light blue bar, and the body section

used dark blue for the background color and a white rounded rectangle as a content area

(see Fig. 1). Two different navigation menus were implanted in this interface. The main

menu had a rollover animation effect to provide system feedback. Learners were able to

move to any page in the instruction with the menu. The other navigation type was linear

navigation. Two types of arrow buttons at the bottom of each page provided learners with

simple links to the next and previous pages. The designs of all navigation types used in this

interface were based on usability guidelines: maintaining consistency (Chalmers 2003;

Shneiderman and Plaisant 2005; Swan 2001; Williams et al. 2002), providing clear nav-

igation (Anderson 2006; Hallahan 2001; Swan 2001), facilitating easy evaluation of the

current state of the system (Norman 1998), and displaying the particular actions which can

be carried out at that time in menu (Norman 1998). The appearances of the navigations

were identical in both chapters as shown Figs. 1 and 2.

The non-metaphorical interface layout was implemented with reference to graphic

design rules. For example, the optical weights of all objects were equally distributed

Fig. 1 A page in Chapter 1 with a non-metaphorical interface


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(balance or homogeneity rule), and related objects were presented as a group within the

same form (spatial arrangement, unity, or proximity rule). Also, colors played an important

role in design and meaning: headers had different colors and bigger font size (contrast or

focal point rule), and different color themes were utilized in each chapter to enable learners

to distinguish one chapter from another (color and rhythm rule).

Metaphorical interface

The overall structure of the metaphorical interface is similar to that of the non-metaphorical

interface. The text messages throughout the instruction were identical with the text in non-

metaphorical interface. The number of pages of instruction was similar to a non-meta-

phorical interface; Chapter 1 in the metaphorical interface had one more page (total eight

pages) than the same non-metaphorical interface chapter (total seven pages) because the one

section needed more screen space to implement a metaphor to represent a relationship of

contents. However, Chapter 2 had the same page numbers in both interfaces. The meta-

phorical interface reflected the organizational structure of learning content, such as rela-

tionships between different concepts and chronological procedures of historical events.

To implement an effective metaphorical interface, design guidelines from previous

studies were applied. For example, metaphors were related to learning content, provided

students with adequate clues (Hsu and Boling 2007; Hudson 2000), and represented the

system structure, such as information sequence (Barr et al. 2002; Hron 1998; Hsu and

Boling 2007; Hudson 2000). Also, the learning environment, navigation, and learning

content were closely interrelated (Hron 1998). With regard to building structural clues in

interface, graphical elements such as boxes, diagrams, and timeline graphics with animation

were implemented.

Fig. 2 A page in Chapter 2 with a non-metaphorical interface


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In Chapter 1, the fundamental concept was the relationships between public relations

with other concepts or domains, such as the public. Therefore, relational metaphors were

employed. For example, on a preview page (see Fig. 3) the person on the left represented a

public relations practitioner, and people on the right represented the public. The two-way

communication was emphasized by signal animation. In order to be consistent, the rela-

tionship between the practitioner and the public was displayed throughout the chapter, and

the main menu used a person-shaped icon to represent the public. As shown in Fig. 4, the

different shapes and sizes of organizations and publics represented that the public was

broader than any given organization. The text ‘‘relationship’’ in the arrow image empha-

sized the two-way communication function of public relations. The line between the arrow

image and social marketing indicated that the social marketing is related to the commu-

nication between organizations and the public.

In Chapter 2, chronological procedures of historical events were emphasized with

navigation and layout structures. Unlike the non-metaphorical interface, which displayed

only ordered text in a sub-menu, the layout in the body section of this metaphorical

interface employed a timeline metaphor. A timeline metaphor was introduced on a preview

page to give learners an overview of the historical context, see Fig. 5. Each historical stage

of public relations tradition was represented by different color bars, and historical events

were displayed in rounded boxes and connected to the appropriate year with lines, as

shown in Fig. 6. An additional navigation was implemented to facilitate the movement to

other historical stages. An arrow button was located in both sides of stage boxes, and a

sliding animation effect occurred when movement to other stages takes place. The

movement animation also represented the chronological structure of content.

Fig. 3 The preview page for Chapter 1 in the metaphorical interface


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Fig. 4 Relational cues in Chapter 1 in the metaphorical interface

Fig. 5 The preview page for Chapter 2 in the metaphorical interface


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Instruments

Three types of data were collected: (a) pretest score representing prior knowledge,

(b) posttest score representing learning performance, and (c) germane cognitive load level.

Pre- and posttest

The pretest and the posttest consisted of 20 questions that were identical in the both tests.

The face validity of the test was verified by the instructor, and we administered a voluntary

pilot test with five undergraduate students to check wording and clarity of test items.

Sample items from the pre- and posttest included the following:

• Which of the following is a public relations practitioner’s duty?

• Which of the following is a correct statement about relationships between public

relations and related fields?

• Which of the following is a correct statement about a press agent?

• Which of the following occurred first?

Germane cognitive load level

Germane cognitive load was measured by five-point Likert scales ranging from strongly

disagree to strongly agree. Unlike a mental effort rating from previous studies (c.f.,

Kalyuga and Sweller 2005) that asked about the difficulty of instruction, the new instru-

ment asked learners the degree of their mental activities to structure schema. In this study,

the items asked to what extent the interface helped their schema construction and

Fig. 6 The third historical stage of public relations


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automation. The internal reliability of five items was tested in order to assure the credibility

of the instrument. The germane cognitive load was measured after each chapter, and the

overall reliability score was high (Cronbach’s Alpha = 0.94). The self-rating items in the

instrument are as follows:

• The interface contributed to my understanding of public relations.

• The interface helped me to mentally organize the structure of public relations.

• As I progressed throughout the unit, the interface helped me to relate later concepts to

earlier concepts.

• While proceeding throughout the unit, the interface helped me to remember the

structure of public relations.

• When I think about what I just learned, I remember the content in terms of the

interface’s layout.

Procedure

This study consisted of two phases. In the first phase, participants went to a directions page

explaining the procedure of the instruction ‘‘The Nature and History of Public Relations.’’

Afterward, the participants were asked to take a pretest, and they were informed that they

would complete an instructional unit after four days. The time interval between the pretest

and the posttest was given to avoid any priming effect of a pretest on an instruction and

posttest scores.

In the second phase, participants were randomly assigned to one of the two instructional

units with a different interface. They were directed to a webpage that explained how to take

the second phase of the study. After the directions page, they were led to Chapter 1 of the

instructional unit. After completing each chapter, they were asked to indicate their germane

cognitive load level, and they took a posttest after the instruction. An independent t test

was conducted to determine whether there were any differences in the pretest scores

between the two groups. The results indicated there was not statistically significant dif-

ference in the pretest scores [t(82) = -0.973, P = 0.334]. The mean score of pretest in

metaphorical interface group was 10.17 out of 20, and the mean score of non-metaphorical

interface group was 10.70.

Results

RQ1: Is there a relationship between germane cognitive load and learning

performance?

In order to determine the relationship between germane cognitive load and learning per-

formance, a correlation test between germane load levels and posttest scores was con-

ducted. There was a significant positive correlation between overall germane load level

scores and posttest scores (P \ 0.001, r = 0.55). In addition, a simple regression analysis

was used to test if germane load levels significantly predicted posttest scores. The results

indicated the germane load levels explained 30% of the variance (R2 = 0.300, F(1,

78) = 33.368, P \ 0.001), and germane load significantly predicted learning performance

(b = 0.547, P \ 0.001). Thus, the first hypothesis was met.


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RQ2: Is there a relationship between prior knowledge and germane cognitive load?

In contrast, the relationship between learners’ prior knowledge represented by the

pretest scores and germane cognitive load levels were not significant in a correlation

test (P = 0.135, r = 0.17). In addition, a regression test revealed that germane cogni-

tive load levels were not significantly explained by prior knowledge (R2 = 0.028,

F(1,78) = 2.283, P = 0.135). Thus, we could not find evidence in which learners with

higher prior knowledge tended to invest less germane cognitive load, and our hypothesis

was not met.

RQ3: Do the metaphorical interface and the non-metaphorical interface groups differ

in germane cognitive load?

To investigate the effect of interface on germane cognitive load, three comparisons of the

germane cognitive load levels in different interfaces (i.e., metaphorical interface and non-

metaphorical interface) were conducted. The mean scores of germane load are shown in

Table 1. First, overall germane cognitive load levels in both chapters were compared. The

mean score on the overall germane cognitive load for a metaphorical interface was

4.02 (SD = 0.52), whereas the non-metaphorical interface scored an average of 3.60

(SD = 0.58). There was a significant difference between the metaphorical and non-met-

aphorical interface in terms of germane cognitive load [t(78) = 3.45, P = 0.001] with a

large effect size (Cohen’s d = 0.78). Second, separate germane cognitive load for each

chapter were compared. An independent t test revealed that there was no significant

difference between the two interfaces in terms of germane cognitive load for Chapter 1

[t(78) = 0.84, P = 0.402], while there was a significant difference for Chapter 2

[t(78) = 5.00, P \ 0.001). In other words, the metaphorical interface had higher germane

cognitive load (M = 4.23, SD = 0.59) than the non-metaphorical interface (M = 3.50,

SD = 0.71) in Chapter 2 with a large effect size (Cohen’s d = 1.12). Last, another

comparison between the metaphorical interface chapters was conducted, since each chapter

provided different metaphors using dissimilar structural cues (i.e., relational and chrono-

logical metaphor). A dependent t test showed that there was a significant difference

between Chapters 1 and 2 of the metaphorical interfaces [t(39) = -4.79, P \ 0.001]. With

the metaphorical interfaces, germane cognitive load in Chapter 2 (M = 4.23, SD = 0.59)

were higher than those in Chapter 1 (M = 3.81, SD = 0.57). The effect size was also large

(Cohen’s d = 0.76). Moreover, a regression test showed that interface types accounted for

13.2% of the variance in germane cognitive load (R2 = 0.132, F(1, 78) = 11.873,

P = 0.001) in both chapters, and interface types significantly predicted germane cognitive

load (b = -0.363, P = 0.001). Therefore, the third hypothesis was met in that the

metaphorical interface group invested more germane cognitive load.

Table 1 Mean scoresof germane cognitiveload level

Standard deviations are givenin parentheses

Metaphoricalinterface (n = 40)

Non-metaphoricalinterface (n = 40)

Chapter 1 3.81 (0.57) 3.70 (0.64)

Chapter 2 4.23 (0.59) 3.50 (0.71)

Both chapters 4.02 (0.52) 3.60 (0.58)


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RQ4: Do the metaphorical interface and the non-metaphorical interface

groups differ in learning performance?

To determine whether learning performance was the same for a metaphorical interface and a

non-metaphorical interface, a mixed-model analysis of variance (ANOVA) was conducted.

The within-subjects variables were pretest scores and posttest scores with time as a within-

subject factor name, and the between-subjects factor was interface type. 2 (Time) 9 2

(Interface type) mixed-model ANOVA with overall test scores revealed that a significant

main effect for time was obtained [F(1,78) = 157.85, P \ 0.001] with a high effect size

(g2 = 0.67). The test scores after the instruction were significantly higher than before the

instruction regardless of interface types as shown Table 2. However, there was a significant

interaction between time and interface type [F(1,78) = 12.42, P = 0.001] with a small

effect size (g2 = 0.14) which indicated that the magnitude of difference between pretest and

posttest scores depends on interface type.

Examination of a simple effect for each interface type indicated that posttest scores

were significantly higher than pretest scores in both interface types [a metaphorical

interface: t(39) = -12.39, P \ 0.001, Cohen’s d = 1.96; a non-metaphorical interface:

t(39) = -5.94, P \ 0.001, Cohen’s d = 0.94]. However, note the much larger effect size

for metaphorical interface. The mean scores are presented in Table 2. In addition, com-

parisons of test scores between interface types in each test revealed that there was no

significant difference of overall pretest scores between interface types [t(78) = -0.97,

P = 0.334], but the overall posttest scores in a metaphorical interface were significantly

higher than posttest scores in a non-metaphorical interface [t(78) = 2.50, P = 0.015,

Cohen’s d = 0.56]. In addition, a simple regression analysis was used to examine if

interface types predicted learning performance, and the results showed that interface type

did account for 7.4% of the variation in posttest scores [R2 = 0.074, F(1, 78) = 6.252,

P = 0.015]. Give the significant beta value, participants in this study, who used the

metaphorical interface scored on average 1.6 points higher on the posttest than peers who

used the non-metaphorical interface. Thus, the metaphorical interface did enhance the

learning performance.

RQ5: Do prior knowledge, germane cognitive load and interface type contribute

to learning performance?

Multiple regression analysis was used to determine whether learning performance is

influenced by any condition including learners’ prior knowledge, learners’ investigated

germane cognitive load, and interface type. The three independent variables, which are

prior knowledge, germane cognitive load, and interface type, were entered into the

regression equation simultaneously. The dependent variable was learning performance

represented as the posttest score. In the multiple regression analysis with overall posttest

Table 2 Mean scores of test scores

Pretest score (n = 80) Posttest score (n = 80)

Metaphorical interface 10.18 (2.33) 15.03 (2.18)

Non-metaphorical interface 10.70 (2.49) 13.43 (3.41)

Total 10.44 (2.41) 14.23 (2.96)

Standard deviations are given in parentheses, and possible mean scores range from 0 to 20


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score, a preliminary examination of the results indicated there was no extreme multicol-

linearity in the data (all variance inflation factors were less than 2) nor were there any

influential data points. In addition, the assumption of independence and normality were

met. As shown in Table 3, the results indicated the set of independent variables explained

44.3% (P \ 0.001) of the variance in the overall posttest score with two of three variables

having significant influence on learning performance. In order of importance, they were

germane cognitive load level (b = 0.425) and prior knowledge measured by pretest score

(b = 0.383). Based on the results, the germane cognitive load level had the greatest impact

on overall posttest scores. While the prior knowledge had a positive relationship with the

overall posttest scores, interface type did not influence the posttest scores (P = 0.091).

Discussion and implications

From the results, we present implications in the advancement of cognitive theory and the

practice of instructional design. Recommendations for future research based on limitations

of this study are also addressed.

The advancement of cognitive load theory

The positive relationship between germane cognitive load and learning performance (RQ1:

P \ 0.001, r = 0.55) and the significant contribution of germane cognitive load to learning

performance (RQ5: P \ 0.001, b = 0.425), regardless of interface types, support a pre-

vious assumption about the role of germane cognitive load as it relates to cognitive

resources for learning. The assumption is that learners invest their mental effort to enhance

their understanding of learning contents (Gerjets et al. 2004; Moreno 2004; Renkl et al.

2004; Sweller et al. 1998; van Merrienboer and Sweller 2005). In cognitive load theory,

load often denotes a negative contribution to working memory; that is, additional load is

considered to be a liability to working memory. However, germane cognitive load can be a

positive load for learning and is closely related to learning activities. For example, learners

who construct and automate cognitive schema with the immersive metaphorical interface

tend to have higher achievement scores. Thus, it can be said that cognitive activities for

schema construction and automation are highly related to knowledge acquisition. The

study provides evidence of the meaningful role of germane cognitive load proposed in

previous studies (e.g., Moreno 2004; van Merrienboer and Sweller 2005).

For the second research question, we expected that the metaphorical interface would be

unnecessary or cause conflict for knowledgeable learners who already had their own

schemata (Kalyuga et al. 2000), whereas novice learners might benefit from the interface in

terms of schema construction and automation. However, germane cognitive load related to

Table 3 The results of multiple regression tests

Independent variables b b t

Pretest scores 0.469 0.383 4.334**

Germane cognitive load level 2.146 0.425 4.504**

Interface type -0.940 -0.160 -1.711

R2 = 0.443

** P \ 0.001


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interface type was not influenced by learners’ prior knowledge [R2 = 0.028, F(1,78) =

2.283, P = 0.135]. This may have occurred because the instructional topic was not

sophisticated, or the layout was too general or obvious. Current cognitive load theory does

not specify the relationship between prior knowledge and germane cognitive load. Instead,

the theory states that higher intrinsic load yields limited space for germane cognitive load

(Sweller et al. 1998; van Merrienboer and Sweller 2005). If we consider prior knowledge

(i.e., pretest scores) as intrinsic load, the complexity of the instruction in this study was not

adequate to distinguish novices from more knowledgeable individuals. We found neither

positive nor negative relationships between germane cognitive load and prior knowledge.

Further studies need to investigate whether there is a significant relationship between prior

knowledge and germane cognitive load.

Metaphorical interface for instructional design practice

These findings suggest that a metaphorical interface could accomplish scaffolding of

learning. For example, a higher germane cognitive load in a metaphorical interface (RQ3:

P = 0.001) indicated the metaphorical interface was enhancing schema construction and

automation, which were positively correlated with learning performance. Furthermore, in

this study, the improvement of posttest scores in the metaphorical interface (RQ4:

mean = 15.03) was significantly higher than the improvement of these scores in the non-

metaphorical interface (RQ4: mean = 13.43). On the other hand, the multiple regression

tests did not find any significance of interface type (RQ5: P = 0.091), while the germane

cognitive load and prior knowledge made similar contributions to learning performance for

predicting relative influences on learning performance at around 40%. However, the

contribution of interface type, especially a metaphorical interface, should not be under-

estimated, because the metaphorical interface highly influenced germane cognitive load.

Therefore, it appears that the metaphorical interface acts as a cognitive aid for learners to

strengthen knowledge structure to be transferred to their schemata. In other words, the

potential role of interface, which is to scaffold an individual’s ability to perceive, organize,

integrate and remember information (Chalmers 2003; Gadanidis et al. 2004), could be

implemented within a metaphorical interface. Metaphorical interfaces offer promise as a

method to scaffold learning in Web-based instruction when the interface and learning

content are considered together.

Instructional designers should consider the role of interface as a cognitive aid when

designing an interface for an instructional unit. For general interface design, artistic design

rules can be applied to achieve the first role of interface, which is capturing attention.

The second role, facilitating navigation, can be accomplished with usability guidelines.

Regarding the cognitive approach to interface, traditional cognitive load theory researchers

have posited that interface has a critical relationship with extraneous cognitive load (Paas

et al. 2003; van Merrienboer and Ayres 2005). The findings in this study contribute to

cognitive load theory in that a metaphorical interface can provide a mechanism to scaffold

learning through the reinforcement of germane cognitive load.

However, the results showed that metaphors could be effective only when they are

appropriately applied. For example, we found no significant difference in germane cognitive

load between interface types in Chapter 1 of the instructional unit (P = 0.402). It seems that

the overall difference in germane cognitive load (P = 0.001) was caused by the large

difference of germane cognitive load in Chapter 2 of the instructional unit (P \ 0.001). The

relational metaphor in Chapter 1 of the unit failed to enhance germane cognitive load while

the chronological metaphor successfully increased the load. Additionally, the difference


123

between chapters in metaphorical interface alone (P \ 0.001) indicated that the chrono-

logical metaphor in Chapter 2 of the unit was more effective than the relational metaphor in

Chapter 1. Thus, the key point of implementing an effective metaphorical interface would

be finding the most appropriate metaphor as it relates to the learning contents. Some

metaphors are stronger than others depending on learning contents when implementing a

metaphorical interface.

A successful metaphorical interface should help a learner’s mental model construction.

In Web-based instruction, the interface is a method to understand what learning contents

are and how they related each other. Mismatched metaphors could overburden learners’

cognitive processes and cause more extraneous cognitive load. In order to enhance

germane cognitive load, we propose the following metaphorical interface guidelines:

• Metaphors should be visually simple to be understood by learners. They should be

appropriate for the discipline or domain to which they are being applied, and metaphors

should not produce any confusion to learners.

• To make best use of metaphors, designers should go beyond visual design principles

and appearance. Metaphors and the accompanying interface should relate to the

structure of learning contents rather than focus solely on the visual appearance of

learning contents. In addition, editing of visual characteristics, such as details, may be

necessary. For example, when replicating a real object to create a metaphor, it could

waste screen space and harm learning by adding to extraneous cognitive load. In other

words, metaphors should provide adequate clues of the structure of learning contents in

order to provide an appropriate mental model without taxing working memory.

• Metaphors should be related each other when using multiple metaphors (e.g.,

underlying and auxiliary metaphors), and a whole metaphorical environment should be

consistent throughout an instructional unit.

• Metaphors should be tested with target audiences during a development phase to

determine how users rely on the metaphors. As part of prototyping and development,

more than one metaphor should be considered for any given discipline, domain, or

learning contents. The strongest metaphor that most meaningfully supports schema

construction and automation should be used.

Limitations and future research

This study also has a number of limitations to generalize the findings. First, the meta-

phorical interface implemented in this study was an immersive metaphorical interface that

builds an authentic environment reflecting learning content with structural cues or orga-

nizational hints (Cheon and Grant in press). Metaphorical components used in this type of

metaphorical interface may be obvious because the components directly represent struc-

tures or relationships of learning contents. On the other hand, the other type of meta-

phorical interface, thematic metaphorical interface, which employs metaphorical themes

as an entire learning environment, may have a different effect on germane cognitive load.

Therefore, the role of metaphors on learners’ cognition in a thematic metaphorical inter-

face may be a fruitful area for future research. Furthermore, with additional research, we

could develop more detailed guidelines in order to select more suitable metaphors for

interface design and learning online.

Second, concrete learning domains should be considered in future research. Chapter 1 of

the instructional unit, ‘‘The Nature of Public Relationship,’’ did not have an obvious

structure. Consequently, the conceptual metaphor in Chapter 1 of the unit was not strong


123

enough to produce significant results. Future research may benefit from the investigation of

effects of metaphorical interface on germane cognitive load in a concrete domain such as

biology, physics, or geography so that the role of structural cue as a cognitive aid could be

compared across different domain areas. In addition, other studies would investigate the

effects of a metaphor in terms of the complexity of learning contents or specific domain

areas.

Last, the germane cognitive load measurement was developed based on the assumption

that schema construction and automation are highly related to germane cognitive load

(Gerjets et al. 2004; Mayer 2005; van Merrienboer and Ayres 2005), and our results about

the instrument supported this assumption. However, the instrument used in this study

focused only on the roles of interface. Since germane cognitive load can be enhanced by

any instructional intervention other than interface, this instrument may be adapted for

specific instructional interventions in future studies. However, the instrument is still sub-

jective and self-report. Other types of measurement, such as psychophysiological mea-

surements, should be considered to measure germane cognitive load. In addition, new

measurements for the other two types of cognitive load (i.e., intrinsic and extraneous

cognitive load) should be developed. Although intrinsic load and extraneous load could be

measured by pretest scores and usability level (e.g., Cheon and Grant in press), more

empirical studies should be conducted to seek scientific measurements to isolate three

cognitive load types. With isolated cognitive load types, we may determine which types of

cognitive load causes cognitive overload in various contexts.

Conclusion

This study successfully supports two assumptions: First, germane cognitive load can

positively affect learning performance, and second, metaphorical interface can enhance

learners’ schema construction and automation. The positive role of germane cognitive load

related to interfaces in Web-based instruction could shed light on further research in

cognitive load theory. In addition to the interface tested in this study, the effects of other

instructional interventions could be investigated in terms of germane cognitive load. The

second finding empirically proved the augmentation of schema construction and automa-

tion by a metaphorical interface. A successful and strong metaphorical interface can

enhance the interaction with learning contents to organize cognitive schemata.

Screen design is complex and integrative. There have been a number of interface

design guidelines to gain users’ attention and increase usability. The desktop metaphor

has been widely used in computer operating systems. However, there has been little

connection between learning content and interface through a metaphor. A metaphorical

interface could implement the integration of learning content schema into interface.

Structural cues embedded in a metaphorical interface could act as a model for learners’

own schemata.

A metaphorical interface is a heuristic design approach. In addition to a usable and

aesthetically appealing interface that reduces extraneous cognitive load, a metaphorical

interface could provide an appropriate mental model to enhance germane cognitive load.

The implications proposed in this study could take a step toward innovative interface

design for online learning. This study would contribute to the discovery of paths to

designing an interface in Web-based instruction that is more congenial to cognitive

processing.


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Jongpil Cheon is an assistant professor in the Instructional Technology program at Texas Tech University.Dr. Cheon earned his Ed.D. from the University of Memphis in Instructional Design and Technology. Hisresearch interests involve implementing immersive online learning environments and investigatingadvanced technologies for interactive learning.

Michael M. Grant is an associate professor in the Instructional Design and Technology program at theUniversity of Memphis. His research considers how to design interactive learning environments. Dr. Grantearned his Ph.D. from The University of Georgia in Instructional Technology.


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Documents

The effects of metaphorical interface on germane cognitive load in Web-based instruction