Learning Support Game System for Sustainable Development Goals

Education: Effects of Improved User Interface

on Satoyama Forest Management Learning

Yukiya Shingai

, Ryota Aoki

, Yoshiaki Takeda

, Fusako Kusunoki

, Hiroshi Mizoguchi

Masanori Sugimoto

, Hideo Funaoi

, Etsuji Yamaguchi

and Shigenori Inagaki

Department of Mechanical Engineering, Tokyo University of Science, 2641 Yamazaki, Noda-shi, Chiba-ken, Japan

Graduate School of Human Development and Environment, Kobe University, Hyogo, Japan

Department of Information Design, Tama Art University, Tokyo, Japan

Graduate School of Information Science and Technology, Hokkaido University, Hokkaido, Japan

Faculty of Education, Soka University, Tokyo, Japan

Keywords: Science Education, Biodiversity, Environmental Conservation of Forests, Vegetation Succession.

Abstract: Educational efforts focused on biodiversity and forest environmental conservation have become increasingly

important, given the objective of achieving the sustainable development goals established by the United

Nations. In Japan, Satochi-satoyama is a place to learn about biodiversity and forest environmental

conservation. However, an increasing number of forests cannot be maintained due to changes in the industrial

structure and population decline. Furthermore, the harmony between people and nature is being lost.

Therefore, it is necessary to learn about the management of Satochi-satoyama. Experiential learning focused

on field surveys has been conducted as a means of teaching Satoyama management. However, it is difficult

for learners to develop a true understanding via this approach because the Satoyama vegetation succession

occurs on a large time scale. Numerous simulation games have been developed to teach Satoyama vegetation

successions and management methods using Satochi-satoyama as a theme. The authors are currently

improving one such game, called the "Satoyama management game". In this paper, we describe the game

improvements we have made so far. In addition, we discuss an experiment conducted using the improved

version Satoyama management game and present its results.

1 INTRODUCTION

In recent years, the importance of educational efforts

focused on biodiversity and forest environmental

conservation has increased, in the interest of

achieving the sustainable development goals

established in September 2015 (United Nations,

2015).

In Japan, Satochi-satoyama is a place to learn

about forest biodiversity and conservation. Satochi-

satoyama is an area consisting of farmlands, irrigation

ponds, secondary forest, plantation forest, and

grasslands around human settlements. The

environments of Satochi-satoyama have been formed

through various human interventions. Due to the

dynamic and mosaic utilization of land and cyclic

resource use, a rich culture that coexists with nature

while enjoying a variety of ecosystem services has

been created. However, an increasing number of

forests cannot be maintained due to changes in the

industrial structure and population decline. Therefore,

the harmony between people and nature is being lost

(Ministry of the Environment, Government of Japan,

2010). For these reasons, it is necessary to learn about

the management of Satochi-satoyama.

Management methods for Satoyama are taught

through experiential learning via field surveys.

However, experiential learning has some challenges.

Specifically, the effects of management methods

implemented by humans cannot be visualized

immediately, as vegetation successions in Satoyama

occur on a time scale of several decades or hundreds

of years. Therefore, for example, even if an attempt is

made at pest control through experiential learning, it

is impossible to observe the impacts of Satoyama and

difficult to achieve a realistic understanding.

428

Shingai, Y., Aoki, R., Takeda, Y., Kusunoki, F., Mizoguchi, H., Sugimoto, M., Funaoi, H., Yamaguchi, E. and Inagaki, S.

Learning Support Game System for Sustainable Development Goals Education: Effects of Improved User Interface on Satoyama Forest Management Learning.

DOI: 10.5220/0009425004280435

In Proceedings of the 12th International Conference on Computer Supported Education (CSEDU 2020) - Volume 1, pages 428-435

ISBN: 978-989-758-417-6

Various simulation games have been developed

thus far to teach Satoyama vegetation successions and

management methods. In a simulation game, the

learner can actually experience an event even if it

occurs on a large time scale. Also, using game as

learning support is known to be an effective tool for

learning (Prensky, 2003) (Calderón, A., & Ruiz, M.,

2014).

Deguchi et al. (2010, 2012) developed a digital

vegetation succession game called Digital

SUGOROKU for learning vegetation successions.

This was a sugoroku-type board game using touch

panel and display.

Adachi et al. (2013), Nakayama et al. (2014), and

Yoshida et al. (2015) developed a life-size board

game for vegetation succession learning called

Human SUGOROKU, which utilizes a full-body

interaction system. This game was a full body

interaction system.

Kawaguchi et al. (2017, 2018) developed a

Satoyama management game in which learners

become Satoyama managers to learn Satoyama

management methods and vegetation successions.

However, the Satoyama management game

developed by Kawaguchi et al. (2018) had two major

improvements. The authors improved the user

interface, one of the two major improvements, and

developed new Satoyama management game. Then,

in order to evaluate the new Satoyama management

game, an experiment for elementary school students

was conducted. As a result of the experiment, we

were able to suggest the effectiveness of the new

Satoyama management game.

The remainder of this paper is organized as

follows. Section 2 discusses the points requiring

improvement in the Satoyama management game

developed by Kawaguchi et al. (2018) and the

improvements made by the authors thus far. Section

3 describes the experiments performed, in which

elementary school students experienced the improved

Satoyama management game, and Section 4 presents

the results. Finally, Section 5 summarizes the main

conclusions.

2 SATOYAMA FOREST

MANAGEMENT GAME

2.1 Overview of the Game

The Satoyama management game allows learners to

learn Satoyama management and vegetation

successions while experiencing Satoyama

management. In the game, learners experience events

that

occur on time

scales

decades

or hundreds of

Figure 1: Play screen of Satoyama management game by

Kawaguchi et al. (2018)

years, which humans cannot experience. Figure 1

shows the play screen of the Satoyama management

game developed by Kawaguchi et al. (2018).

The learner manages Satoyama using one of the

following six management methods.

 Clear-Cut Logging

 Evergreen Tree Cutting

 Afforestation

 Pest Control

 Deer Removal

 Do Nothing

The learner can choose a management method for

20 turns and experience about 300 years of Satoyama

management.

In the game, there are early-, middle-, and late-

stage type of tree species. The trees included in each

type are as follows.

 Early-stage species: Rubus microphyllus,

Mallotus japonicas

 Middle-stage species: Pinus densiflora,

Quercus serrata, Rhododendron reticulatum,

Vaccinium oldhamii, Abelia spathulate

 Late-stage species: Castanopsis spp., Quercus

glauca, Eurya japonica

Each tree has different characteristics. In the game,

the tree height was made different for each type.

The center of the game screen depicts, the situation

in Satoyama that the player manages. The number of

trees growing is displayed numerically at the top of

the screen. Next to this number, a meter is used to

indicate whether the number of trees is large or small.

The number of trees increases and decreases when the

learner manages or when the growing trees interact

with each other.

The learner proceeds through the game with

reference to the score displayed in the upper left part

of the game screen. In this game, the ideal number of

trees to be vegetated in Satoyama is decided. If the

ideal number of trees is approached, the score will

Learning Support Game System for Sustainable Development Goals Education: Effects of Improved User Interface on Satoyama Forest

Management Learning

429

increase. The learner proceeds with Satoyama

management considering the effects of the

management method that he / she performs for 20

turns and the influence of the relationship between the

trees. After 20 turns have been completed, the player

can know his/her Satoyama management score.

By repeating this game, users can learn Satoyama

management and vegetation successions.

2.2 Improvement of the Game

Two major improvements were made to this game.

The first is related to the user interface, and the

second is related to the number of Satoyama types

supported. Each is described in the following sections.

2.2.1 User Interface

The user interface could be improved in several

regards.

First, this game has no tutorial. In order for learners

to experience the game, it is necessary to explain in

advance how to play the game. If a tutorial is created,

learners will be able to experience the game even if

no one is nearby who knows how to play.

Next is the representation of time in the game. In

the developed game, the time of each turn is counted

in numbers per s in the upper right. However, few

learners notice the time, because learners often look

at the growing trees and management methods, and

do not notice the count displayed in the upper right.

In addition, the game should enable users to

experience a time scale of decades to hundreds of

years, but there is no part that indicates the time scale,

making it impossible to determine whether a long

time has passed just by looking at the current number

of turns.

Finally, there is little information that facilitates

learning during the game experience. By repeating

the game, learners can understand which trees the

management practices will influence. However, in

order for learners to learn, it is necessary for them to

be aware of the rules of the game. Consequently,

learners who are unaware of the rules may not be able

to learn the intended objectives. In order to reduce

this issue, the amount of information that facilitates

learning during the game should be increased.

2.2.2 Number of Supported Satoyama Types

The Satoyama management game developed by

Kawaguchi et al. (2018) is only compatible with one

of the typical Satoyama types in Japan, although there

are four in total.

 Quercus mongolica forest in northern Honshu,

Japan

 Quercus serrata forest from eastern Honshu to

the Sea of Japan side of the Chugoku region

 Pinus densiflora forest in western Japan

 Castanopsis spp. forest in southern Japan

The current game pertains to the Pinus densiflora

forest in western Japan.

Satoyama vegetation types and management

methods differ depending on the region. Therefore, if

a Satoyama management game can be developed that

supports all of these types, learners will be able to

acquire more knowledge than they can at present.

2.3 Improvements Made to Date

In Section 2.2, we described the areas requiring

improvement in the Satoyama management game.

The authors are currently implementing

improvements in these areas. We began by focusing

on the user interface. The following subsections

describe the improvements that have been made so far.

2.3.1 Create Tutorial

We created a tutorial that did not exist before. The

tutorial can be selected on the screen before the game

starts. The tutorial teaches that Satoyama will not be

in good condition unless management is performed

by a person. It also tells learners how to proceed with

the game and that there is information in the game that

will help learners with the game.

2.3.2 Screen Design

Figure 2 shows the Satoyama management game play

screen after the improvements, which changed many

aspects of the game design. These changes will be

addressed individually in this section.

Figure 2: Play screen of improved Satoyama management

game.

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Figure 3: Tree picture display.

Figure 4: Representation the passage of time.

First, the tree illustrations were modified. In

conventional games, trees are represented by

silhouettes, and the colors of the trees are unrealistic,

making the game screen different from the actual

appearance of a mountain. To address this issue, the

colors of the tree illustrations were made closer to

those of the actual trees, making it easier to imagine

the trees growing in the mountains. Different color

depths were used for early-, middle-, and late-stage

species, enabling the three types to be identified by

color depth.

The management method buttons were also

changed. In conventional games, only letters are

presented, so learners who do not understand their

meanings may not be able to understand the

management method. Therefore, we added

illustrations next to the letters to help learners

understand the effects of the management methods.

In addition, “Tall Tree Cutting” was added as a

management method. Since the inclusion of

additional Satoyama types in the game is under

consideration, a management method used for those

Satoyama types was added.

As a new function, when the user hovers over each

tree in the upper part of the screen, a picture of the

actual tree appears, as shown in Figure 3. In this

picture, information that is important for the game is

displayed. Checking the information provided in the

pictures will help learners find appropriate Satoyama

management methods.

In addition, the meaning of the meter that expresses

the number of trees growing was changed, as one

piece of information that helps the game progress.

The early- and late-stage species appear in red when

the ideal number of trees is exceeded, and the middle-

stage species appear in red when the number of trees

is much smaller than the ideal number. This approach

was chosen because ideally Satoyama has more

middle-stage species than early- and late-stage

species. If learners are aware of this information, they

will be able to discern the appropriateness of the

current state of Satoyama.

2.3.3 Representation of Time

We also improved the representation of time. The

management method selection time of 20 s per turn is

indicated by a bar, as shown in the center of Figure 2.

The color of the bar changes over time.

In addition, improvements were made to clarify the

passage of time over 300 years. When a management

method is selected at each turn, a bar indicating that

time has passed is displayed, as shown in Figure 4. As

the turn progresses, the black triangle moves,

enabling learners to be aware of the passage of time.

3 EXPERIMENTAL DESIGN AND

ASSESSMENT METHOD

An experiment was performed using the Satoyama

management game with the improved user interface,

as described below. The experiment was conducted

over four days from November 19 to November 22,

2019. The participants in this experiment were 31

children in Grades 5 and 6 at an elementary school

attached to a national university. Volunteers were

recruited at the school.

3.1 Aim

To clarify how the participants experienced the

Satoyama management game, we assessed game

immersion and understanding of the controls and

screen changes. Moreover, we assessed how the

participants felt and what they learned from the

tutorial that was added to the game and the elements

that received major updates, specifically, how time is

expressed and the screen design.

3.2 Protocol

The participants received pre-game instructions and

played one round of the Satoyama management game

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Management Learning

431

(10 min) during a morning break and five rounds

during the lunch break (15 min), for a total of six

rounds. After school on the same day, the participant

simultaneously filled out a questionnaire related to

the questions described in Section 3.4.

3.3 Questions

To assess immersion, we created five items to

measure to what extent the participants were absorbed

in the game, such as “I was absorbed in managing the

Satoyama when playing the game.” To assess

understanding of the controls and screen changes, we

created six items, such as “I knew where to press and

what the response would be when progressing

through the game”. To assess the effect of the newly

added tutorial, we created four items, such as “I

thought the tutorial in the Satoyama management

game was easy to understand.” To assess how time is

expressed, we used four items, such as “I could

imagine how long the Satoyama plants’ changes

would take in reality.” To assess the screen design,

we utilized eight items, such as “I could imagine how

the real trees look by seeing the illustrations of the

trees in the game.” In total, there were 27 question

items.

3.4 Analytical Method

We asked the participants to respond to each question

item on a seven-point scale. We classified the

responses as positive for “Strongly agree,” “Agree,”

and “Slightly agree,” and as neutral or negative for

“Neither,” “Slightly disagree,” “Disagree,” and

“Strongly disagree.” We aggregated the frequency of

each response for every question, conducting Fisher’s

exact test using a 1×2 contingency table with an

uneven population ratio. We defined the population

ratio of positive responses as the rate at which any of

the three positive responses out of the seven levels

was received; we also defined the population ratio of

neutral and negative responses as the rate at which the

four neutral or negative responses out of the seven

levels were received. We compared the values for

each question item and conducted an exact binomial

test (one-sided “greater”), designating p < 0.01 as

indicating a significant deviation.

4 ASSESSMENT RESULTS

4.1 Assessment of Immersion in the

Game

Table 1 summarizes the results of the assessment of

immersion in the game. We found a significant

deviation (p < 0.01) in the results for all items with

regard to immersion.

4.2 Assessment of Understanding of

Controls and Screen Changes

Table 2 summarizes the results of the assessment of

understanding of the controls and screen changes. We

found a significant deviation (p < 0.01) in the results

of all items with regard to understanding controls and

screen changes.

4.3 Survey of the Game Tutorial Effect

Table 3 summarizes the results of the assessment of

the effect of the game tutorial. We found a significant

deviation (p < 0.01) in the results for all items with

regard to the effect of the tutorial.

Table 1: Questions about immersion in the Satoyama management game.

(Unit: number of persons)

Question item 7 6 5 4 3 2 1 Pos.

Neut.

Neg.

1-1 The Satoyama management game was fun.** 30 1 0 0 0 0 0 31 0

1-2 I was absorbed in managing the Satoyama

when playing the game.**

20 8 3 0 0 0 0 31 0

1-3 I was happy when my score increased.** 24 6 1 0 0 0 0 31 0

1-4 I was frustrated when my score decreased.** 14 9 8 0 0 0 0 31 0

1-5 I was happy when the change I expected

happened after pressing a Satoyama

management command.**

18 9 3 1 0 0 0 30 1

N = 31.**p < 0.01

Strongly agree: 7; Agree: 6; Slightly agree: 5; Neither: 4; Slightly disagree: 3; Disagree: 2; Strongly disagree: 1

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4.4 Survey of How Time is Experienced

while Playing the Game

Table 4 summarizes the results of the assessment of

how time is experienced while playing the game. We

found a significant deviation (p < 0.01) in the results

for all items with regard to the experience of time.

Table 2: Results of the assessment of understanding the controls and screen changes when playing the Satoyama management

game.

(Unit: number of persons)

Question item 7 6 5 4 3 2 1 Pos.

Neut.

Neg.

2-1 The Satoyama management game was

easy to control.**

12 17 2 0 0 0 0 31 0

2-2 I knew where to press and what the

response would be when progressing

through the game.**

20 6 3 2 0 0 0 29 2

2-3 I knew the meaning of the color changes

of the status bar at the top of the screen.**

21 6 4 0 0 0 0 31 0

2-4 I knew what the changing numbers below

and to the left of the top-screen status bar

meant.**

15 7 5 2 1 1 0 27 4

2-5 It was easy to see that deer had appeared

in the Satoyama by looking at the screen

of the Satoyama management game.**

15 6 4 2 2 1 1 25 6

2-6 It was easy to see that bugs had appeared

in the Satoyama by looking at the screen

of the Satoyama management game.**

16 6 2 2 3 2 0 24 7

N = 31. **p < 0.01

Strongly agree: 7; Agree: 6; Slightly agree: 5; Neither: 4; Slightly disagree: 3; Disagree: 2; Strongly disagree:1

Table 3: Results of the assessment of the effectiveness of the Satoyama management game tutorial.

(Unit: number of persons)

Question item 7 6 5 4 3 2 1 Pos.

Neut.

Neg.

3-1 I thought the tutorial in the Satoyama

management game was easy to

understand.**

15 13 3 0 0 0 0 31 0

3-2 I felt like playing the game when I

watched he Satoyama management game’s

tutorial.**

23 6 1 1 0 0 0 30 1

3-3 I knew what to do in the game by

watching the Satoyama management

game’s tutorial.**

18 10 2 1 0 0 0 30 1

3-4 I knew what I need to think about to

increase the score of the Satoyama by

watching the Satoyama management

game’s tutorial.**

11 8 5 5 2 0 0 24 7

N = 31.**p < 0.01

Strongly agree: 7; Agree: 6; Slightly agree: 5; Neither: 4; Slightly disagree: 3; Disagree: 2; Strongly disagree:1

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Table 4: Results of the assessment of how time is experienced while playing the Satoyama management game.

(Unit: number of persons)

Question item 7 6 5 4 3 2 1 Pos.

Neut.

Neg.

4-1 It was easy to understand how much time

was left for entering commands.**

9 10 6 2 4 0 0 25 6

4-2 It was easy to understand how much time

passed in the game after I had entered a

command until the Satoyama changed to

the next status.**

10 10 6 1 2 2 0 26 5

4-3 It was easy to understand how much time

passed inside the Satoyama management

game.**

12 6 9 1 3 0 0 27 4

4-4 I could imagine how long the Satoyama

plants’ changes would take in reality.**

12 5 7 3 3 1 0 24 7

N = 31.**p < 0.01

Strongly agree: 7; Agree: 6; Slightly agree: 5; Neither: 4; Slightly disagree: 3; Disagree: 2; Strongly disagree:1

Table 5: Results of the assessment of the Satoyama management game’s screen design.

(Unit: number of persons)

Question item 7 6 5 4 3 2 1 Pos.

Neut.

Neg.

5-1 It was easy to understand the picture of the

square command (management technique)

button at the bottom of the screen.**

23 7 1 0 0 0 0 31 0

5-2 It was easy to distinguish between early,

middle, and latesuccessional species by

looking at the illustrations of the trees.**

14 10 5 0 1 1 0 29 2

5-3 It was easy to distinguish between high

and low trees by looking at the

illustrations of the trees.**

12 8 5 3 2 1 0 25 6

5-4 It was easy to tell how many of each tree

was in the Satoyama by looking at the

game screen.**

13 10 5 2 1 0 0 28 3

5-5 I felt like I was managing a real forest

(Satoyama) while playing the game.**

16 9 5 1 0 0 0 30 1

5-6 I could imagine how the real trees look by

seeing the illustrations of the trees in the

game.**

11 10 8 2 0 0 0 29 2

5-7 I could imagine how the real trees look by

seeing the photos of trees coming out of

the top bar.**

19 7 4 0 1 0 0 30 1

5-8 It was easy to tell whether the Satoyama

was doing well or poorly by looking at the

Satoyama management game’s screen.**

20 4 6 1 0 0 0 30 1

N = 31.**p < 0.01

Strongly agree: 7; Agree: 6; Slightly agree: 5; Neither: 4; Slightly disagree: 3; Disagree: 2; Strongly disagree:1

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4.5 Survey of the Game’s Screen

Design

Table 5 summarizes the results of the assessment of

the game screen design. We found a significant

deviation (one-sided test for all items: p < 0.01) in the

results for all items.

5 CONCLUSION AND FUTURE

WORK

This paper describes the areas requiring improvement

in the Satoyama management game developed by

Kawaguchi et al. (2018) and the improvements made

by the authors to address these issues thus far. Then,

it discusses an experiment performed by elementary

school students using the improved Satoyama

management game. We evaluated five items.

Significant differences were observed in all items. In

other words, with the improvements implemented, it

can be said that the Satoyama management game has

become a more effective tool for learning Satoyama

vegetation successions. However, only one of the two

major improvements were improved in this paper.

In the future, the authors intend to implement the

second improvement, increasing the number of

Satoyama types supported by the game.

ACKNOWLEDGEMENT1S

This work was supported by JSPS KAKENHI Grant

Numbers JP19H01734. The experiment was

supported by Kobe Elementary School.

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