Evaluation of an Augmented-Reality-based 3D User Interface to Enhance

the 3D-Understanding of Molecular Chemistry

Patrick Maier and Gudrun Klinker

Fachgebiet Augmented Reality (FAR), Technische Universit

at M

unchen, Fakult

at f

ur Informatik,

Garching bei M

unchen, Germany

Keywords:

Direct Manipulation, 3D User Interface, Augmented Chemical Reactions, Evaluation, Augmented Reality.

Abstract:

The spatial understanding of chemical molecules is crucial for learning chemistry at school. With a good

3D understanding of molecules, chemical processes become obvious compared to a 2D representation in

textbooks or just the molecular formula. With the increasing spread of computers, smartphones and tablets,

the ﬁeld of computer aided learning becomes more and more important. Common molecular viewers such as

Jmol (Jmol, 2012) present chemical simulations as 3D renderings on a regular computer screen in combination

with desktop-based user interfaces using a mouse and a keyboard to manipulate 3D molecules. Such interfaces

may be cumbersome to use since users have to associate 2D mouse motion and key presses with 3D object

motions. In this paper we investigate the hypothesis that the understanding of spatial structures of molecules

is enhanced by Augmented-Reality-based 3D user interfaces with which students can directly manipulate the

virtual 3D molecules by freely moving and rotating a 3D object in air with their hands. Our results show

that a direct manipulation 3D user interface improves the 3D understanding in comparison to the traditional

desktop-based user interface with mouse and keyboard.

1 INTRODUCTION

To support students learn chemistry, we have to help

them understand the spatial structure of molecules.

Knowing the 3D structure of molecules is impor-

tant to understand the chemical behavior and prop-

erties of the molecules. Learning the 3D structure

of molecules just by looking at the 2D drawings or

formulas of the textbook seams not to be the best

method.

Hardware representations that the students can

touch have been a well-established method in chem-

istry education for a long time. Yet, such hardware

models are not always available, and it is time con-

suming to build them for each student and for each

molecule. Furthermore, such hardware representa-

tions are mostly not ﬂexible or dynamic in their struc-

ture.

As computers get more powerful and mobile, in-

teractive 3D representations of the molecules are able

to provide a better way for students to inspect and un-

derstand the 3D structures. Applications can show

complex molecules and animations that the students

can inspect. But there is a drawback in the classical

3D presentation programs: the molecules can only be

rotated and moved via the mouse and the keyboard.

This indirect mapping of mouse movements to the 3D

model is not always intuitive. Students have to learn

the mapping of 2D mouse movements and keystrokes

to 3D object manipulations involving six degrees of

freedom. As a result, some of the students’ focus may

be diverted from the molecules to the user interface,

and the structure of the molecules may not be made

completely clear.

To combine the beneﬁts of the physical molecule

representations with the power of computers, there

are direct manipulation 3D user interfaces which use

Augmented Reality and tracked real objects to control

the position and orientation of the molecules.

In this paper, we report on evaluating the Aug-

mented Reality based 3D user interface of the Appli-

cation Augmented Chemical Reactions (ACR) against

the mouse and keyboard based user interface of the

Application Jmol (Jmol, 2012). The evaluation took

place at a secondary school with a class of 14-15 year

old students of the 8th grade. In the next section, we

take a look at previous work in this ﬁeld and we de-

scribe both types of 3D user interfaces.

294

Maier P. and Klinker G..

Evaluation of an Augmented-Reality-based 3D User Interface to Enhance the 3D-Understanding of Molecular Chemistry.

DOI: 10.5220/0004349502940302

In Proceedings of the 5th International Conference on Computer Supported Education (CSEDU-2013), pages 294-302

ISBN: 978-989-8565-53-2

 2013 SCITEPRESS (Science and Technology Publications, Lda.)

Figure 1: This device is tracked by a computer with a web-

cam. It is used as a 3D input device for direct manipulation.

2 BACKGROUND

Many schemes to support the learning progress of stu-

dents have been developed. To support the students in

understanding the spatial structure of molecules, the

most suitable methodologies have to be developed.

A number of research efforts have shown that using

physical models and therefore using direct manipu-

lation helps students explore and understand the spa-

tial structure of objects (Herman et al., 2006; Arnold

et al., 2012; Hoyek et al., 2011). It has also been

shown that a direct manipulation interface for rota-

tion via a sensor with 3 degrees of freedom (3 DoF)

yields better performance without lacking accuracy,

compared to 3D rotation via a mouse (Hinckley et al.,

1997). Work at the IBM Almaden Research Center

investigated the user performance of different 3D in-

put devices (Zhai, 1998).

2.1 Desktop-based user Interface with

Mouse and Keyboard

There are many applications that help users under-

stand the spatial structure and also the resulting dy-

namics of molecules (Panagiotopoulos et al., 2012;

Johnson et al., 2011; Jmol, 2012). Yet, the commonly

used user interface to rotate and move virtual objects

is still a combination of mouse and keyboard (Chen

et al., 1988).

2.2 3D Augmented-Reality-based user

Interface

To combine the advantages of the physical direct

manipulation with showing complex structures, Aug-

Figure 2: Augmentation of a protein molecule on top of the

marker cube.

mented Chemistry (Fjeld et al., 2007) and Augmented

Chemical Reactions (Maier et al., 2009b) (Maier

et al., 2009a) have been introduced. Both systems use

Augmented Reality to deliver a direct manipulation

3D user interface to control the position and orienta-

tion of the virtual objects.

Generally speaking, Augmented Reality adds vir-

tual information or objects interactively and in real-

time to the real world, generating the impression that

the added information is part of the physical world.

To this end, the application Augmented Chemical Re-

actions employs a physical cube with a handle that

is textured on all sides with black and white patterns

(Figure 1). In a typical setup, a student holds the cube

by the handle and manipulates it while sitting at a

desk in front of a monitor. A webcam records the

scene with the cube, and Augmented Chemical Re-

actions uses a marker tracking algorithm similar to

the AR-toolkit (Kato and Billinghurst, 1998; Pustka

et al., 2011) to detect and recognize the currently vis-

ible patterns on the cube. According to the size and

deformation of the patterns, the algorithm calculates

their position and orientation relative to the webcam

– and thus the pose of the cube and handle. With this

information, the virtual molecule can be drawn on top

of the webcam image, leading to the illusion, that the

molecule is attached to the cube (Figure 2). The vir-

tual molecule moves in unison with the physical cube.

This is a three-dimensional direct manipulation user

interface.

3 EVALUATION

We conducted a user study with 14-15 year old stu-

dents of a german gymnasium (secondary school) to

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determine whether direct manipulation of the position

and orientation of virtual molecules leads to a better

spatial understanding of virtual molecules than input

via a standard mouse and keyboard. We selected a

class in the 8th grade – just at the time when they had

been taught the basic concept of what a molecule is,

but they had not learned yet about the spatial structure

of molecules. Therefore they were ideally suited for

a study investigating which of the two user interfaces

leads to a better 3D understanding of molecules.

None of them already had experience with Aug-

mented Chemical Reactions or the Jmol application.

Most of the students had lots of experience with play-

ing 3D games, but nearly none had already used to use

a 3D chemical modeling application or another 3D

design application. Only one student stated to have

already a good knowledge about the chemical struc-

tures of molecules. As his prior results in building

the molecules were already correct, he did not have

the change to improve. So this results could not be

used to get a measurement of the performance of the

application and thus was removed (see section 4.1).

3.1 Experimental Setup

In cooperation with a chemistry teacher, we selected

ten different molecules to be inspected in this study.

Those molecules were (1) Sulfur S

, (2) Methane

, (3) Ethanol C

OH, (4) Acetic acid C

(5) Benzene C

, (6) Hydrogen sulﬁde H

S, (7)

Phosphor P

, (8) Phosphorus triﬂuoride PF

, (9) Hex-

ane C

4 and (10) Carbon tetrabromide CBr

We had two computer rooms, one for the Jmol and

one for the Augmented Chemical Reactions (ACR) ap-

plication. Each student desk was equipped with the

respective computer equipment.

Computer Setup for ACR. The ﬁrst computer room

was set up to run the ACR application with a 3D

direct manipulation user interface. Here a monitor,

a keyboard, and a marker cube with a handle were

placed on each student desk. A webcam on a mi-

crophone stand in shoulder height of a sitting per-

son faced towards the student desk and the marker

handle. To control the position and the orientation

of the virtual molecule, the students had to hold the

marker cube into the ﬁeld of view of the webcam.

The video stream, augmented with the currently se-

lected molecule, was shown on the monitor in front

of the student, as shown in Figure 3. The students

could cycle through the set of molecules by pressing

the space-bar on the keyboard.

With a well-aligned arrangement of the cam-

era, the user, the hand-held handle and the moni-

tor, the AR illusion via a directly manipulated phys-

Figure 3: Computer setup for the ACR application, using

a webcam a physical cube on a handle and a monitor. The

keyboard that is required to cycle through a set of molecules

is not shown.

Figure 4: Typical setup to inspect and manipulate molecules

on a monitor via keyboard and mouse in the Jmol applica-

tion.

ical object can be maintained with minimal strain

on the hand-eye coordination. A more immersive,

perfectly aligned setup can be achieved when the

monitor-based arrangement is replaced with a video-

see-through or optical-see-through head-mounted dis-

play. Yet, such arrangements are costly and thus cur-

rently not deployable in classrooms. For this rea-

son, the current test setup was based on webcams and

monitors on student desks.

Computer Setup for Jmol. The second room was set

up to run the Jmol application (Jmol, 2012), using a

classical mouse and keyboard interface to manipulate

virtual 3D molecular structures on the screen. To this

end, a monitor, a mouse and a keyboard were placed

on each student desk. When started, Jmol showed

the ﬁrst of the ten molecules, centered in the mid-

dle of the screen. By moving the mouse upwards

or downwards, the molecule rotated around its hori-

zontal axis. By moving the mouse leftwards or right-

wards, the molecule rotated around its vertical axis.

Schemes for translating and zooming molecules do

exist in Jmol, but they were not required in the cur-

rent setup. The students could view and explore the

molecule from all sides before switching to the next

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(a) Molecules #1 to #4

(b) Molecules #5 to #8

Figure 5: This is the set of versions of the ﬁrst eight

molecules. The correct versions are highlighted.

molecule by pressing a button in the application. Fig-

ure 4 shows the Jmol setup that uses the mouse and

the keyboard to manipulate the position and orienta-

tion of the molecule.

Further Physical Setups for Further Student

Tasks. In addition to the computer setup, the stu-

dent desks carried papers and pencils and modeling

clay with tooth picks. Furthermore, two to three clay

models of each molecule were laid out on a table in a

separate area in one of the rooms. Only one of these

clay models of each molecule was correct. The other

two were wrong with different degrees of spatial inap-

propriateness. Figure 5 shows the set of molecule ver-

sions for the ﬁrst eight molecules. This is described

further in task 5 of the next section.

3.2 Evaluation Design

We used a between-subjects design, consisting of two

separate groups of students from the eighth grade of

a secondary school. The ﬁrst group, Group ACR con-

sisted of 12 students, the second group, Group Jmol

had 11 students. With the help of their teacher, the

students were grouped to form a similar distribution

of grades to ensure that both groups had the same

knowledge.

The entire evaluation consisted of an introduc-

tion phase, ﬁve tasks including use of one of the two

molecular visualization programs, and a brief subjec-

tive interview at the end.

Introduction Phase (5 minutes). At the beginning,

all students were in the same room. They received

Figure 6: Example of a good and a bad drawing of the

chemical formula of molecule #5 as LEWIS structure for

Task 1.

an exercise sheet with printed-out molecular formu-

las of all ten molecules. The paper also contained a

short introduction to the topic and explained what the

students were asked to do in this evaluation. We ad-

ditionally explained the topic and the following tasks

to the students.

Potentially confounding factors.

• The students were asked to work by themselves

and not to copy from fellow students (cheat), due

to the negative consequences to the evaluation.

Yet, the potential for such an inﬂuence on the eval-

uation cannot be completely discarded.

• Since this is a between-subject design, learning

effects are not crucial. For didactic reasons, we

use the same, well-deﬁned sequence through the

set of molecules rather than a randomized order. If

learning effects occur, they affect both conditions

in a similar way and can thus be clearly identi-

ﬁed. Yet, the test design consists of a large num-

ber of sequentially executed tasks, each involving

all eight molecules, and required carry-over expe-

riences between the tasks. Thus, learning can be

seen as an omnipresent aspect over time.

Task 1: Drawings of All 10 Molecular Structures

(15 minutes). As their ﬁrst task, the students were

asked to draw the LEWIS structure (McNaught and

Wilkinson, 1997) for all molecules of the exercise

sheet next to the molecular formulas – a topic that had

been covered in class during the week before the eval-

uation. They previously were taught by their teacher

how to draw this kind of structures. This should give

the students a basic understanding of the connections

of the atoms in the molecule. Figure 6 shows an ex-

ample of a good and a bad drawing.

After this ﬁrst task the students were split into

the two groups and went to their respective computer

rooms.

Task 2: Uninformed Modeling of All 10 Spatial

Molecular Structures (20 minutes). At their desks,

students were asked to build models of the ten molec-

ular formulas with clay and toothpicks, according to

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Figure 7: Model of acetic acid C

(molecule # 4), built

by a student for Task 2. Students used modeling clay and

toothpicks.

their current guess on what such a 3D structure could

look like. They had not yet received any theoretical

training on such 3D structures. We requested students

to build these models in order to have reference data

on the students’ understanding of spatial molecular

structures prior to using the computer-based chemi-

cal visualization applications. The students had 20

minutes to model up to 10 molecules with clay. We

accepted that not everyone would complete this task.

For the analysis, we therefore only took the ﬁnished

models into account. Figure 7 shows a model of the

fourth molecule, acetic acid (C

), built by a stu-

dent.

Task 3: Explore 3D Molecular Structures with the

Respective Visualization Application (20 minutes).

Each group was then asked to use their assigned visu-

alization software to inspect all ten molecules. With

ACR, the students sat in front of the display with the

webcam above their shoulder and the marker cube in

their hand. On the screen they saw the captured image

plus their controlled virtual molecule rendered on top

of the marker cube. The students could cycle through

the set of molecules by pressing the space-bar on the

keyboard. Figure 8 shows a part of the classroom with

students working on the ACR version. With Jmol,

the students used the mouse and the keyboard to ro-

tate and move the molecules. To switch to the next

molecule, they had to click a button in the software.

The students did not receive initial tutoring for ei-

ther of the two software systems. Rather, they started

immediately with the given molecular assignments.

None were observed to have difﬁculties using the user

interfaces.

The students had 20 minutes to inspect all ten

molecules. After this time, the applications were

stopped. In the meantime we took photos of the

molecules built for Task 2.

Figure 8: Classroom with students using the ACR for Task

(a) worsened (Mol. #2 Methane CH

)

(b) improved (Mol. #3 Ethanole C

OH)

)

Figure 9: Before-after state of a worsening 9(a), normal im-

provement 9(b) and a large improvement 9(c) (Task 4).

Task 4: Informed Modeling of All 10 Spatial

Molecular Structures (10 minutes). With their new

knowledge of the spatial structure of the molecules,

the students were asked to improve the molecular

models they had built in task 2.

To measure how the 3D understanding of the spa-

tial structure of the molecules changed, we compared

the initial version of the molecules with the new ver-

sion. Figure 9 shows typical clay models before and

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after using the software.

Task 5: Selection between Several Pre-built Clay

Models of each Molecule. To also get an objec-

tive measurement of how both 3D user interfaces im-

proved the spatial understanding, we confronted the

students with 2-3 pre-built clay models of the ﬁrst

eight molecular structures (see Figure 5). For the ﬁrst

eight molecules, we had built one clay model version

that was the correct solution, one that was completely

wrong and a third one that was almost correct, but still

noticeably different from the correct one. Here, we

could evaluate to what extent the students had gained

a spatial understanding of molecular structures. Fig-

ure 5 shows the alternative clay models for the ﬁrst

eight molecules.

Closing Phase: Informal Interview and Question-

naire. At the end of the evaluation we had a short

joint informal interview in front of the whole class.

We also handed out a questionnaire to learn a bit about

the students’ prior knowledge. We asked the students

what they liked and what they did not like. The stu-

dents stated that they liked the idea of learning the

molecule structure using a computer application. Es-

pecially the group using ACR told that they had a lot

of fun using the user interface. Where the group with

Jmol liked the general idea of using an application

to show the 3D structure, the ACR users were fasci-

nated about the user interface with the marker cube.

All stated that they would like to continue using the

application in their class to further learn about the ge-

ometry of molecules.

4 RESULTS

The evaluation consisted of two parts – the build-

ing and the improvement of the clay molecules and

the selection of the right version. Table 5 at the end

presents the raw absolute scores of all tasks. Empty

cells denote that the students did not model the spe-

ciﬁc molecule or did not select any version in the last

task.

The subsequent sections give the results, discuss

these scores and suggest interpretations.

4.1 Improvements to Students’ Clay

Models

To measure how the AR-based and the mouse-based

user interfaces of ACR and Jmol affected the spatial

understanding of the virtual molecules, we compared

the models built in Task 2 with the models changed in

Task 4.

With the help of the chemistry teacher, we scored

the molecules (Table 5). Table 1 presents the inter-

pretation of the students’ improvements from Task 2

to Task 4 – due to the use of the chemical education

applications (Jmol, ACR). When the second version

(Task 4) of the models was worse than the ﬁrst ver-

sion (Task 2), we scored this with −1 point. No im-

provement of the molecule was scored as 0 points,

and an improvement was scored as +1 point. When

the ﬁrst version was totally wrong and the second was

completely correct, we scored +2 points. When stu-

dents already provided a perfectly correct solution in

the ﬁrst version (Task 2) and they did not change any-

thing on the molecule in Task 4, we did not count it

– as this does not deliver insight regarding the use-

fulness of the software system (user interface). The

scores are presented in Table 1. A Kruskal-Wallis test

shows that there is a signiﬁcant difference in the me-

dians χ

(3, N = 45) = 32.34, p < 0.0001 at a signif-

icance level of 5%. The results show that the direct

manipulation 3D user interface of the ACR applica-

tion helped the students signiﬁcantly better than the

Table 1: Scores representing students’ improvements be-

tween uninformed modeling of the molecules in Task 2 and

informed modeling in Task 4, i.e., after having visualized

the molecules with Augmented Chemical Reactions (ACR)

or Jmol int Task 3.

Group 1 (ACR)

User

Mol

1 2 3 4 5 6 7 8

1 -1 1

2 2 1 2

3 1 1 0 0

4 1 1 2 0 0

5 1 1 0

6 1 1 0

7 1 1 1

8 0 2 1

9 1 0 0 1 2 0 0 0

10 1 0 0 1 0 2 0

11 2 1 2

12 0 0 0 0 2

Group 2 (Jmol)

User

Mol

1 2 3 4 5 6 7 8

1 2 2 0 1 0

2 0 0 0 0

3 0 0 0 0

4 1 -1 1 0

5 1 -1 0

6 2 0 0 0

7 0 1 1 -1 2

8 1 0 0 1

9 1 0 0 2

10 1 0 0 2

11 1 1 0 1

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Figure 10: Percentages of the quality of the changes that

students made to improve their clay models in Task 4.

The height of the graph represents the percentage of the

molecules which were strongly improved, improved, no

change or worsened.

keyboard and mouse 3D User-Interface of Jmol.

Table 2 and the corresponding graph in Fig-

ure 10 show how many percent of the molecules were

strongly improved, improved, unchanged or worsened

by students using the Jmol the ACR program, respec-

tively. The numbers enhance the statistical ﬁnding

that Group 1 (ACR) using the direct manipulation 3D

user interface had a signiﬁcantly better improvement

than Group 2 (Jmol) using mouse and keyboard. Both

the percentages for large improvements and for nor-

mal improvements are higher for ACR than for Jmol,

whereas the percentages of no change and of worsen-

ing changes are smaller. A deeper analysis of the re-

sults shows that students of group 1 (ACR) who were

wrong in Task 2 improved more in task 4 than stu-

dents of group 2 (Jmol). This also shows that ACR

with the direct manipulation user interface helps more

to understand the spacial structures than using an indi-

rect manipulation user interface with mouse and key-

board (Jmol).

Table 2: Percentages of the quality the changes that students

made to improve their clay models in Task 4.

ACR Jmol

Strongly improved 18% 13%

Improved 39% 29%

No change 41% 51%

Worsened 2% 7%

4.2 Students’ Ability to Pick the

Correct Clay Model out of a given

Set of Three per Molecule

Since students’ dexterous abilities may vary and the

quality of some of the students’ clay models may thus

have depended on that, we designed Task 5 as a test

that was independent of the students’ own modeling

skills and time limitations. We had prepared three

clay model versions of the ﬁrst eight molecules, with

one being correct, one being slightly wrong and one

being completely wrong. The students were asked to

indicate for each molecule which one they considered

to be the correct model. They received 2 points for

the correct answer, 1 point for the nearly correct an-

swer, and 0 points when they selected the completely

wrong clay model. Although we asked the students

not to copy from the others, we cannot guarantee that

they did not. Table 3 summarizes the score of table 5,

pertaining to Task 5.

Table 3: Scores of students’ selections of three clay model

versions of each molecule in Task 5.

Group 1 (ACR)

User

Mol

1 2 3 4 5 6 7 8

1 2 2 2 2 2 2 2 2

2 2 2 1 1 2 2 2 2

3 1 2 2 0 2 2 2 1

4 1 2 2 2 0 1 2 2

5 1 1 1 1 0 0 2 2

6 1 0 2 2 2 0 2 1

7 2 0 2 2 2 1 2 2

8 2 2 2 2 2 2 2 2

9 2 0 2 1 2 2 2 2

10 1 2 2 1 2 2 2 1

11 2 2 1 2 2 2 2 2

12 2 2 2 2 2 2 2 2

Group 2 (Jmol)

User

Mol

1 2 3 4 5 6 7 8

1 2 2 2 1 2 1 2 2

2 2 2 2 1 0 2 2 2

3 2 2 1 2 2 0 2 1

4 2 1 0 2 0 1 2 2

5 2 2 2 2 0 2 2 2

6 1 2 2 2 2 2 2 2

7 2 2 0 1 2 2 2 2

8 2 2 1 1 0 0 2 0

9 2 2 1 1 0 1 2 2

10 2 2 1 1 0 1 2 2

11 2 2 0 1 0 1 2 2

We calculated the average points that students

achieved for each molecule. They are shown in Ta-

ble 4 and in Figure 11. Interestingly, molecule #1

and #2 had a better result with the user interface of

Jmol. The variance of these results of the group Jmol

is unusual small in relation to the other molecules.

This leads to the assumption that there was some-

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Table 5: Scores of all task assignments, T1, T2, T4 and T5.

Group1(ACR)

User Mol.1 Mol.2 Mol.3 Mol.4 Mol.5 Mol.6 Mol.7 Mol.8

T 1 T 2 T 4 T 5 T 1 T 2 T 4 T 5 T 1 T 2 T 4 T 5 T 1 T 2 T 4 T 5 T 1 T 2 T 4 T 5 T 1 T 2 T 4 T 5 T 1 T 2 T 4 T 5 T 1 T 2 T 4 T 5

1 1 2 0 2 2 2 2 1 2 2 0 2 0 2 1 2 2 0 2

2 2 3 3 2 2 1 3 2 2 1 2 1 0 1 2 2 1 0 3 2 1 2 2 2

3 1 0 2 1 2 3 3 2 2 1 2 2 0 1 1 0 1 0 0 2 1 3 3 2 1 2 3 1

4 2 0 2 1 2 2 3 2 0 1 3 2 0 2 2 2 2 1 1 0 1 1 0 2 2 2

5 2 1 2 1 2 1 0 0 1 1 0 0 0 1 1 0 1 0 0 2 2 2

6 1 0 2 1 2 0 1 0 1 2 2 2 1 0 0 0 0 2 1

7 2 0 2 2 2 1 2 0 0 1 2 2 0 2 1 2 1 1 1 2 2 2

8 1 2 2 2 2 1 3 2 0 1 2 2 0 2 0 2 1 2 1 2 2 2

9 1 1 2 2 2 1 1 0 0 1 1 2 0 0 1 1 0 3 2 1 0 0 2 1 0 0 2 2 0 0 2

10 1 0 2 1 2 0 0 2 2 1 1 2 1 0 1 1 2 3 3 2 1 0 0 2 1 0 3 2 2 1 1 1

11 1 0 3 2 2 3 3 2 2 1 2 2 3 2 1 2 2 3 3 2 1 0 3 2 2 2

12 1 0 0 2 2 0 0 2 2 0 0 2 2 0 0 2 1 2 1 2 1 0 3 2 2 2

Group2(Jmol)

User Mol.1 Mol.2 Mol.3 Mol.4 Mol.5 Mol.6 Mol.7 Mol.8

T 1 T 2 T 4 T 5 T 1 T 2 T 4 T 5 T 1 T 2 T 4 T 5 T 1 T 2 T 4 T 5 T 1 T 2 T 4 T 5 T 1 T 2 T 4 T 5 T 1 T 2 T 4 T 5 T 1 T 2 T 4 T 5

1 1 1 3 2 2 1 3 2 2 2 0 0 0 1 0 2 1 0 1 1 1 0 0 2 2 3 3 2

2 1 1 1 2 2 1 1 2 2 2 0 1 0 1 0 0 2 1 1 1 2 2 2

3 1 1 1 2 2 1 1 2 2 1 0 2 0 2 1 0 0 0 1 1 1 2 2 1

4 2 0 2 2 2 3 1 1 0 1 2 0 0 2 0 1 3 3 1 0 2 2 1 1 2

5 0 0 2 2 2 2 0 2 0 1 1 2 0 2 0 0 1 3 3 2 0 2 2 2

6 1 0 3 1 2 3 3 2 2 2 2 2 2 2 2 2 2 2 1 3 3 2 1 2 2 2 2 2

7 2 0 0 2 2 3 3 2 2 0 2 1 0 2 3 2 1 1 2 2 1 1 0 2 2 1 3 2

8 1 0 2 2 2 3 3 2 2 1 1 1 2 1 1 1 2 0 1 0 1 1 2 2 2 0

9 1 0 2 2 2 3 3 2 2 1 1 1 2 1 1 1 2 0 1 3 3 1 1 0 3 2 2 2

10 1 0 2 2 2 3 3 2 2 1 1 1 2 1 1 1 2 0 1 3 3 1 1 0 3 2 2 2

11 1 0 2 2 2 2 3 2 2 2 2 0 1 1 2 0 1 3 3 1 1 1 2 2 2 1 1 2

Table 4: Average number of points students achieved for

each molecule in Task 5.

ACR Jmol

1 1.58 1.91

2 1.42 1.91

3 1.75 1.09

4 1.50 1.36

5 1.67 0.73

6 1.50 1.18

7 2.00 2.00

8 1.75 1.73

Figure 11: This diagram shows the mean points users had

for each molecule with Task 5 (Selecting the right version

of the molecules).

thing unintended going on (copying from others).

Molecule #1 with its crown-like structure can be seen

in Figure 11. Molecule #2 has a simple tetrahedron

structure with the carbon atom in the middle. For

molecules #3, #4, #5, and #6, group ACR was bet-

ter than group Jmol, while molecules #7 and #8 faired

approximately even in both groups. The large differ-

ence in the results of Molecule #5 could be explained

in the following way: Students using the Jmol appli-

cation could not remember the ﬂat structure of the

molecule anymore, so they probably took the more

complex looking structure, whereas the students with

the ACR could have remembered the ﬂat structure.

Molecule #7 and #8 were so easy that nearly every-

one has picked the right version.

On average across all molecules, students of group

ACR achieved 13.17 points, compared to 11.91 of

group Jmol.

5 DISCUSSION

AND CONCLUSIONS

Although the time for using the software was not very

long, there is already a signiﬁcant difference in the

improvement of the spatial understanding of the 3D

molecules. We think that by using a direct manipula-

tion 3D user interface, students can literally grasp the

spatial structure. Whereas with mouse and keyboard,

there is a mapping of the movements (2D horizontal

movement of the mouse on the table results in a rota-

tion of the virtual molecule on the screen). With this

mapping, it seems to be not so easy to concentrate on

the spatial structure of the virtual molecules. People

are used to direct manipulation from their childhood.

EvaluationofanAugmented-Reality-based3DUserInterfacetoEnhancethe3D-UnderstandingofMolecularChemistry

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Consequently this user interface is more natural and

supports the learning of the spatial structures.

All students also mentioned that they had fun us-

ing the application and would like to use it more of-

ten in class. Fun is also one of the most important

enablers in learning.

Our evaluation showed that this assumption seems

to be valid. Further investigations with a longer period

of the study could investigate this ﬁnding in more de-

tail.

ACKNOWLEDGEMENTS

We would like to thank the Josef-Hofmiller-

Gymnasium for their kind support. Special thanks go

to Nina Hefter and Andreas Dippon who helped a lot

in this study.

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