Exploratory Study of a Smart System Framework for Educational

Process with Gamiﬁcation: Case Study - Schools in Indonesia

Rahmat Yasirandi

, Yusep Rosmansyah

, Hana Rifdah Sakinah

and Anom Sentanu Prayosa

School of Computing, Telkom University, Bandung, Indonesia

School of Electrical Engineering and Informatics, Bandung Institute of Technology, Bandung, Indonesia

Keywords:

Smart System, Gamiﬁcation, Pedagogy, Indonesian Culture, Framework

Abstract:

Education in Indonesia is one of the sectors that is always considered by the government. The right to educa-

tion is legally guaranteed for all children without any discrimination. Therefore, various methods have been

carried out by each stakeholder, including trying to adapt multiple technologies in the learning process. Most

of the information technology that enters developing countries, notably Indonesia, is still dominated by multi-

media applications on mobile devices. Which not support all the development aspects of children’s potential

in the learning process. Some things have not been considered, such as lack of attention related to children’s

development of motor skill factors and social engagement. Through smart system technology that utilizes

hardware as a part of the system as a whole, the system will include those factors that are not noticed in the

learning technology that has been adopted today. This research has succeeded in producing a framework for

the need to create a smart system in the learning process for Indonesian schools. Through exploratory studies,

scientiﬁc studies have been carried out based on theory and direct observation of the multi-ethnic learning

environment in Indonesia, so the proposed framework will undoubtedly be able to be a guideline for building

a smart system.

1 INTRODUCTION

Education is an action related to giving guidance and

knowledge from someone to someone else. Someone

who gives knowledge is called pedagogue and some-

one who obtains the knowledge is called student. One

of educational processes usually occurred in school.

When the target of the educational process is a child,

is called pedagogy. Broadly pedagogy explained how

learning and teaching activities inﬂuenced by cultural

values, social, and environmental conditions. It also

supported by a strong theoretical and practical basis.

So that the educational process between regions can

be different, not least in Indonesia. As a developing

country, Indonesia, the learning process is considered

as a tedious activity and only targets cognitive en-

hancement. Most of the children who do the learning

process in school (as one of the main things in the ed-

ucational process), often considered as an unattractive

process and they tend to avoid it. Whereas, childhood

needs not only emphasizing cognitive but also motor

skill and social skill.

On the other hand, playing becomes the activity

that children like. Indirectly, children assume that the

more energy they spent physically, the more fun they

will get (Rubin, 1982). Children love to play because

they can create images on their minds to realize it to

the world(Bateson, 2006). The activity creates an ad-

dictive effect and a feeling of wanted to do it more and

more. Modern theories of play differ from classical

theories in that they not only explain play’s existence

but help us understand its function in children’s de-

velopment. Several studies related to the educational

methods have tried to utilize the aspects of a game

so that education can also be fun. Many studies and

modern theories related to learning, which states that

learning is not only bound to how the results are at that

time. It is correlated to the effects that appear from the

development of the children(Mellou, 1994). In devel-

oped countries, the beneﬁts of games that have addic-

tive effects and challenges are gaining popularity in

the educational process, how the educational transfer

process can engross game procedures. Gamiﬁcation

is one of the liveliest topics to study because it binds

the meaning of ”game” that does not offer ”playful-

ness”(Salen et al., 2004).

Reinforced by the observation results in devel-

oping countries’ schools, for instance, Indonesia.

286

Yasirandi, R., Rosmansyah, Y., Sakinah, H. and Prayosa, A.

Exploratory Study of a Smart System Framework for Educational Process with Gamiﬁcation: Case Study - Schools in Indonesia.

DOI: 10.5220/0009909202860293

In Proceedings of the International Conferences on Information System and Technology (CONRIST 2019), pages 286-293

ISBN: 978-989-758-453-4

Schools that used technology in teaching and learn-

ing focus on the increase of intellectual or cognitive

potential only. The learner success parameter only

considers by the increase of the score results they got.

Thus, it seems like it is too focused on extrinsic mo-

tivation(Filimonov, 2017). Proving that the beneﬁts

of the learning process using technology in a devel-

oping country is not efﬁcient. Education should be

able to utilize technology such as smart systems, both

massively connected (the internet) or only local areas

such as a school or class. A smart system is an ap-

proach that given by information technology to create

a decent service. Originally IBM tried to provide a

smarter planet paradigm, which would develop a sys-

tem that could solve problems using information tech-

nology communication through reactive-way(Barile

and Polese, 2010). When hardware technology comes

into play, then motor skill and social engagement also

increase, and it arises the intrinsic motivation. Chil-

dren will have motivation during the learning process,

not just only focus on the results and achievements.

Therefore, the objectivity of this research is how

a framework for a smart system can help the learning

process created by applying the principle of game or

gamiﬁcation. With a particular case study in Indone-

sian schools, incidentally, Indonesia is a multicultural

country and still develop. Moreover, Indonesia has

diverse demographic conditions. Those factors were

affecting the adjustment of building the smart system.

2 APPROACH AND METHOD

To produce a framework related to smart systems that

help the learning process, the development of a ba-

sic framework will be carried out. As seen in the

Figure 1, the basic framework used in ADDIE con-

sist of Analysis, Design, Development, Implementa-

tion, and Evaluation. Some researchers commonly

use the ADDIE framework in developing a new and

more speciﬁc learning framework (Peterson, 2003).

ADDIE has a broad characteristic and manipulated

movement. To establish a new framework for a par-

ticular ﬁeld, then the ADDIE framework needs to be

adjusted with its need. Thus, the stages that need to

be done to develop this framework is conducting ex-

ploratory studies on several research topics that have

been determined. The exploratory study emphasizes

the conceptual theory results based on honesty, in-

tegrity, and transparency on a particular branch of

knowledge(Gerring, 2001)(George et al., 2005). An

exploratory study is a research to ﬁnd and explore in-

formation and analyzing the relation between theories

and knowledge found(Vakkari, 2003). The activities

could be literacy in books, international publications,

and regulations made by agencies or legal organiza-

tions. Another scientiﬁc method related to other ex-

ploratory study is observation, with a direct view of

the phenomenon of environmental issues, which will

establish the evident authentically of the theory that is

found(Wimmer and Dominick, 2013).

Figure 1: System Mechanism Design.

Figure 2: Research Literature Map.

The topics that will be explored are around smart

systems, gamiﬁcation, pedagogy, and Indonesian cul-

ture schools. A smart system is a system that can

help to solve speciﬁc issues by utilizing technol-

ogy, whereas gamiﬁcation is a method of applying

game elements in other ﬁelds. Because in gamiﬁ-

cation, there are different deﬁnitions between game

and play, you can see the position of gamiﬁcation to-

wards ”gaming” and ”playing” in Figure 3. So then, it

can be clariﬁed that gamiﬁcation offers a new learn-

ing style, where it applies the elements of the game

into a nongame system.

These two things will be the solution to the learn-

ing process issue towards children or usually called

Exploratory Study of a Smart System Framework for Educational Process with Gamiﬁcation: Case Study - Schools in Indonesia

287

Figure 3: Gamiﬁcation Position(Deterding et al., 2011).

pedagogy. Pedagogy refers to the practice of learn-

ing related to the study method of delivering intention

towards children. Besides pedagogy, the culture of

learning in developing countries will be formulated in

the study. In this case, the observation conducted in

Indonesia. It is known that culture and the environ-

ment inﬂuence learning. Hence, both pedagogy and

the learning culture need to be reviewed according to

the goals of this study, which create a framework for a

smart system that utilizes gamiﬁcation to support the

learning process in schools. In addition, The relation

between the topics can be explored in Figure 1. Fur-

thermore, a mapping and explanation will be made

for each ﬁnding on every step-in framework ADDIE.

So that a new framework will emerge afﬁliated with

smart systems for the learning process (case study:

schools in Indonesia).

3 RESULT AND DISCUSS

This part will be explained about how the ADDIE

framework has developed into a new framework, a

framework that has been described with more spe-

ciﬁc requirements than general procedure explana-

tion. Any ﬁndings from exploratory research on re-

lated topics mapped into a proposed framework that

has helped provide a more detailed and particular

framework for smart systems for the learning process.

Furthermore, each stage of the proposed framework

will be elaborated, which has contained a mapping of

the results of exploratory studies conducted.

3.1 The Proposed Stage of Analysis

At this stage, a developer who uses this framework

will trace the basic needs of the system to be built.

This analysis section will be divided into two parts,

namely, Learning Objectives Analysis and User Anal-

ysis.

3.1.1 Analysis of Learning Goals

On the proposed framework, the goals of the learn-

ing process that has been analyzed divided into two

groups, which are general learning goals as the mis-

sion and speciﬁc learning goals as the vision(Huang

and Soman, 2013). General learning goals are state-

ments that described expectations of the ﬁnal con-

ditions that will be obtained, while speciﬁc learning

goals can be interpreted as the objectivity of the sys-

tem to be built or a series of objects during the learn-

ing process. Thereby it will help the realization of the

general goals. In other words, the speciﬁc learning

goals must contain intrinsic motivation, and the gen-

eral goals must bring up extrinsic motivation(Ryan

and Deci, 2000).

3.1.2 Analysis of Users Readiness

Users in the proposed framework are deﬁned as

human resources or brainware that uses the sys-

tem(Insan et al., 2019). Some research related to tech-

nology readiness explains that readiness for the im-

plementation of technology (including smart system)

generally can be seen from three aspects, which are

technology, organization, and environment(Tornatzky

and Fleischer, 1990). The accomplishment of the

adoption in a smart system depends on how the sys-

tem can be calm towards the users(Ibanez et al.,

2014), both on the pedagogue and the student. With

the support of the constitution and government regula-

tions (organization’s aspect) throughout the education

process in this country, it supports the use of technol-

ogy and adequates the environment. It can be con-

cluded that readiness analyzation is one of the right

steps in developing a smart system.

Determine what needs to be considered in design-

ing the system so that the delivery of the goals can be

delivered well, by considering the results of the pre-

vious analysis.

3.1.3 Material Design

Material design is intended to compile any content

that will be prepared to be studied — derived from

the goals to be achieved, which have been determined

in the previous phase. In deciding the contents re-

quired standardized guidelines. If the application of

material based on a competent curriculum, then it will

be able to help each student to stay involved(Huang

and Soman, 2013). It could be from books that have

a clear syllabus, or other material sources that have

been determined and recognized by speciﬁc organiza-

tions. Coupled with direct survey techniques for ed-

ucational organizations, this can be an alternative for

CONRIST 2019 - International Conferences on Information System and Technology

288

determining the explicit content that will be used as

material(Mathiyazhagan and Nandan, 2010)(McIn-

tyre, 2011)(Simon et al., 1996)(Salant et al., 1994).

For validating the substances that have been built

can be strengthened by conducting personal studies

such as interview towards the experts of the ma-

terial(Alshenqeeti, 2014).Finally, the output of this

phase is a list of the contents that will be delivered.

3.1.4 Gamiﬁcation Design

Technically, the steps in this phase explain that the de-

veloper decides which gamiﬁcation elements must be

applied, of course, after going through the selection

that matches the material to be included in the learn-

ing(Huang and Soman, 2013).

The materials are learning contents obtained from

the material design. Learning Contents will be helped

to be represented by gamiﬁcation. Before design-

ing what game elements will be chosen on non-game

content, noted that there are several levels of these

elements. The design of the game elements can be

identiﬁed to 5 levels of abstraction development [de-

terding]. From abstract explanation has been made

into speciﬁcs and details. The ﬁrst one is inter-

face design (Crumlish and Malone, 2009), the sec-

ond is game design pattern(Bjork and Holopainen,

2005) and game mechanics(Taylor, 2009), the third is

design principles and heuristics or ‘lenses’(Mandryk

et al., 2008), the fourth is conceptual models of game

design units(Brathwaite and Schreiber, 2008)(Bern-

haupt, 2010)(Fullerton, 2014)(Hunicke et al., 2004),

and the last one is game design methods and de-

sign processes (Fullerton, 2014)(Belman and Flana-

gan, 2010). As seen in the table 2, explained that ev-

ery stage of the elements has its contributions.

Notably, for elements of progression such as

points, badges, and levels, it is better to be priori-

tized to be chosen in the design of gamiﬁcation. The

existence of these game elements can increase the

competitive feeling found in each student(Nicholson,

2012). Even more, the leaderboard that shows the

progress of each student can be seen by all partici-

pants and improve their social status. For other pro-

gression elements such as rewards, it can also provide

motivation and get recognition of the time, effort, and

skills students have. Because rewards and penalties

are two sides of the same coin, which means rewards

are an easy tool for motivation. Helping someone to

make their own decisions about their actions with-

out external control behavior will lead to better re-

sults(Nicholson, 2012). Eventually, when the game

elements adopted in the learning process, it will en

hance student engagement and aim to incorporate as

many learning activities as possible(Mohamad et al.,

2017).

Figure 4: Taxonomy of Game Design Elements.

3.1.5 Learning Flow Design

Technically, a mapping over two results in the pre-

vious phase will be conducted. The selected game

elements mapped to its relation with the learning con-

tent that has been designed. In a non-game adaptation

towards game elements, three elements can be consid-

ered in representing learning material. The three el-

ements are the mechanism, dynamics, and aesthetics

(Zichermann and Cunningham, 2011)(Hunicke et al.,

2004). Mechanism explained the connection of the

goals and the selected game elements (also described

in the previous phase).

Moreover, dynamics are related to an explanation

of how game elements work and interact, so that will

generate the ﬂow of input and output from the learn-

ing process that the students face. For the aesthetics

element, it is a representation of the description of the

responses (especially emotional) that come up from

students. For instance, if the level, challenge, and

leaderboard are one of the elements that have been se-

lected, then the dynamics element will be seen from

how the material from learning content is represented

Exploratory Study of a Smart System Framework for Educational Process with Gamiﬁcation: Case Study - Schools in Indonesia

289

into various levels and with the emergence of different

challenge variants at each level. Plus, if the elements

are combined with badge or point, then each level

will lead to a much more varied level of challenge.

Furthermore, the leaderboard element is related to the

achievements of each student. The leaderboard be-

comes a screen that able to see how far the level of

the students can reach. The beneﬁts of this leader-

board are the representation of the aesthetics element.

Eventually, in this phase, the concept of learning ﬂow

will emerge if the gamiﬁcation is being adopted. The

output of this phase is the procedures management of

learning contents in the form of ﬂowcharts or steps

that students will go through in the learning process

(Fullerton, 2014)(Khaleel et al., 2016).

3.1.6 Smart System Design

Developing a system that has a ”smart” paradigm

needs cognitive abilities (Barile and Polese, 2010).

Because smart systems are not only related to the

implementation of the technology, but also the func-

tional capabilities that they have. Functionality

was able to analyze and make certain decision-

making. Conceptually, the mechanism of the

smart system divided into three, which are sense

mechanism, actuating mechanism, and the process-

ing mechanism of the data to produce the desired

information(European Commission, 2011)(Akhras,

2000)(Yadav, 2017). Sense mechanism and actuate

mechanism of the data are necessary to be designed

because, in the deﬁnition, the system must be adap-

tive and aware of the environment. How the sys-

tem takes data and provides action in response to

the meaning of self-awareness was the reason why

sense mechanism and actuate mechanism must be

designed(Hammoudeh and Arioua, 2018). In sense

mechanism and actuate mechanism needs to be de-

signed concerning how each sensor and actuator used

as a communication procedure. The smart system

should have an integrated scheme in each topology

that is built(Madni, 2008). So, every hardware, soft-

ware, and humanware in this system will be able to in-

teroperate with each other. Thus, the connection with

the implementation for the educational process is that

the system will be a ”smart” assistant in presenting

material, where the system will understand the needs

of the goals in the ﬁrst place. In the end, the sys-

tem is built based on the right and accurate design

which was able to reduce the waiting waste that may

appear(Moon et al., 2018).

3.2 The Proposed Stage of Development

At this stage, execution and development were con-

ducted based on the design documents that have been

made previously. Determine what needs to be pre-

pared to develop the system to realize the design re-

sults that have been produced already. In developing a

system that has multiple environments, there are chal-

lenges, speciﬁcally related to time pressure in the de-

veloping phase.(Bievska and nis Bievskis, ). One of

the reasons that need to acknowledge that intelligent

systems have complexity, thus allowing problems to

arise during the development phase. Because not al-

ways a system that has pure computing is easier to use

than systems that have complex computing((Yadav,

2017).

Figure 5: The Proposed Framework.

3.3 The Proposed Stage of

Implementation

At this stage, the organization will implement the

products produced from the previous development

stage, generally by distributing the prospective users

CONRIST 2019 - International Conferences on Information System and Technology

290

who have been determined at the ﬁrst stage (analy-

sis phase). Considering developing countries such as

Indonesia have multiple cultures that allow different

needs during implementation, the distribution method

can be adapted to the environment of the organiza-

tion. Data generated at the Readiness Analysis stage

should be a guideline in determining this distribution

method. Each prospective user will have a general

view of the situation when using it and will shape the

user’s experience of the proposed product (Harrison

and Donnelly, 2011).

Eventually, the output of this phase is the proce-

dure related to product deployment. Not only how this

product reaches the organization (school), but it can

be used based on the original propose-made. Other

support outputs from this phase should be a compan-

ion product document or a document related to usage

instructions(Bremer, 1999). Generally, user manuals

have descriptive and narrative language that is cleared

and detailed because the instruction document should

present procedures and usage paths that must be eas-

ily understood for each function of the product.

3.4 The Proposed Stage of Evaluation

Data analysis divided into two phases, which are the

quantitative phase and the qualitative phase. Eval-

uation techniques for the adoption of technology

can use quantitative, qualitative, and its combina-

tion, which also known as the sequential explana-

tory design Method(Olds et al., 2005)(Teddlie and

Tashakkori, 2003). Mixed methods research is con-

sidered legal, independent research designs in techni-

cal education that combine the strengths of both qual-

itative and quantitative(Olds et al., 2005)(Straus and

Corbin, 1998)(Smith and Ellsworth, 1985). This se-

lection needs to be adjusted to the initial goal of prod-

uct development. Whether only seeing events based

on the quantity, or seeing the quality, or pay atten-

tion to both. Technically, the quantitative method gets

measured data about student activities. Then the data

is analyzed statistically using parameters and nonpa-

rameters as needed.

On the other hand, qualitative methods use social

approaches, usually with survey methods, precisely

open-ended surveys that have been administered and

analyzed to be explained numerically. The adoption

of technology in the school environment, notably in

Indonesia, places importance on a value parameter as

an index of educational success. Then the quantita-

tive method must be considered. Nevertheless, using

both quantitative and qualitative methods could help

to get answers to problems, it is better to do both eval-

uations.

4 CONCLUSIONS

From the exploration that has been conducted, a new

complex and speciﬁc framework have developed and

fulﬁlls the needs of making a smart system that can

be an alternative in the learning process. From the

preparation process, which is analyzing process until

the evaluation process, have work details to help to ac-

complish a system based on the initial requirements.

The valid literature has approved any results obtained

from exploration that has been carried out for refer-

ence. Therefore, the steps that exist in the reference

framework become feasible to use. Furthermore, the

next research has to prove that by following this pro-

posed framework will create a smart system for the

needs of the learning process in Indonesia. Then it is

veriﬁed by seeing the results of the evaluation whether

the resulting system does indeed provide positive re-

sults when adopted by the organization.

ACKNOWLEDGEMENTS

Thanks to the Internet of Things (IoT) Studio, School

of Computing, Telkom University, Indonesia, which

have been the sites for this research. As a wish, this

research can make a contribution for educational tech-

nologies in the world, especially Indonesia.

REFERENCES

Akhras, G. (2000). Smart materials and smart systems for

the future. Canadian Military Journal, 1(3):25–31.

Alshenqeeti, H. (2014). Interviewing as a data collection

method: A critical review. English linguistics re-

search, 3(1):39–45.

Barile, S. and Polese, F. (2010). Smart service systems and

viable service systems: Applying systems theory to

service science. Service Science, 2(1-2):21–40.

Bateson, G. (2006). A theory of play and fantasy. The Game

Design Reader. A rules of play anthology, pages 314–

328.

Belman, J. and Flanagan, M. (2010). Exploring the creative

potential of values conscious game design: Students’

experiences with the vap curriculum. Eludamos. Jour-

nal for Computer Game Culture, 4(1):57–67.

Bernhaupt, R. (2010). Evaluating user experience in

games: Concepts and methods. Springer.

Bievska, Z. and nis Bievskis, J. Application of smart tech-

nologies in software development: Automated version

updating. Datorzinatne un informacijas tehnologijas,

page 24.

Bjork, S. and Holopainen, J. (2005). Patterns in game de-

sign, volume 11. Charles River Media Hingham.

Exploratory Study of a Smart System Framework for Educational Process with Gamiﬁcation: Case Study - Schools in Indonesia

291

Brathwaite, B. and Schreiber, I. (2008). Challenges for

game designers, charles river media. Inc., Rockland,

MA.

Bremer, M. (1999). The user manual: How to research,

write, test, edit and produce a software manual.

Crumlish, C. and Malone, E. (2009). Designing social in-

terfaces: Principles, patterns, and practices for im-

proving the user experience. ” O’Reilly Media, Inc.”.

Deterding, S., Dixon, D., Khaled, R., and Nacke, L. (2011).

From game design elements to gamefulness: deﬁn-

ing” gamiﬁcation”. In Proceedings of the 15th inter-

national academic MindTrek conference: Envisioning

future media environments, pages 9–15.

European Commission, E. . (2011). Objective ict-2011.3.2:

Smart components and smart systems integration. ex-

tract from work programme 2011.

Filimonov, D. (2017). Extrinsic motivation and incentives.

Fullerton, T. (2014). Game design workshop: a playcentric

approach to creating innovative games. CRC press.

George, A. L., Bennett, A., Lynn-Jones, S. M., Miller, S. E.,

et al. (2005). Case studies and theory development in

the social sciences. mit Press.

Gerring, J. (2001). Social science methodology: A criterial

framework. Cambridge University Press.

Hammoudeh, M. and Arioua, M. (2018). Sensors and actu-

ators in smart cities.

Harrison, C. and Donnelly, I. (2011). A theory of smart

cities. 55th international society for the systems sci-

ences. University of Hull Business School, Hull,

United Kingdom.

Huang, W. H.-Y. and Soman, D. (2013). Gamiﬁcation

of education. Research Report Series: Behavioural

Economics in Action, Rotman School of Management,

University of Toronto.

Hunicke, R., LeBlanc, M., and Zubek, R. (2004). Mda: A

formal approach to game design and game research.

In Proceedings of the AAAI Workshop on Challenges

in Game AI, volume 4, page 1722.

Ibanez, M.-B., Di-Serio, A., and Delgado-Kloos, C. (2014).

Gamiﬁcation for engaging computer science students

in learning activities: A case study. IEEE Transac-

tions on learning technologies, 7(3):291–301.

Khaleel, F. L., Ashaari, N., Meriam, T., Wook, T., and Is-

mail, A. (2016). The architecture of dynamic gam-

iﬁcation elements based learning content. Journal

of Convergence Information Technology, 11(3):164–

177.

Madni, A. M. (2008). Smart conﬁgurable wireless sensors

and actuators for industrial monitoring and control.

In 2008 3rd International Symposium on Communica-

tions, Control and Signal Processing, pages 447–448.

IEEE.

Mandryk, R. L., Isbister, K., and Schaffer, N. (2008). Game

usability: advice from the experts for advancing the

player experience.

Mathiyazhagan, T. and Nandan, D. (2010). Survey research

method. Media Mimansa, 4(1):34–45.

McIntyre, L. (2011). The practical skeptic: Core concepts

in sociology (p. 304).

Mellou, E. (1994). Play theories: A contemporary review.

Early child development and care, 102(1):91–100.

Mohamad, S. N. M., Salam, S., and Bakar, N. (2017).

An analysis of gamiﬁcation elements in online learn-

ing to enhance learning engagement. In Proceedings

Of The 6th International Conference On Computing

And Informatics, ICOCI 2017and Informatics, ICOCI

2017, volume 41, pages 452–460. Universiti Utara

Malaysia.

Moon, I., Lee, G. M., Park, J., Kiritsis, D., and

Von Cieminski, G. (2018). Advances in Produc-

tion Management Systems. Production Management

for Data-Driven, Intelligent, Collaborative, and Sus-

tainable Manufacturing: IFIP WG 5.7 International

Conference, APMS 2018, Seoul, Korea, August 26-30,

2018, Proceedings, volume 535. Springer.

Nicholson, S. (2012). Strategies for meaningful gamiﬁca-

tion: Concepts behind transformative play and partici-

patory museums. meaningful play 2012,(1999), 1–16.

Olds, B. M., Moskal, B. M., and Miller, R. L. (2005).

Assessment in engineering education: Evolution, ap-

proaches and future collaborations. Journal of Engi-

neering Education, 94(1):13–25.

Peterson, C. (2003). Bringing addie to life: Instructional

design at its best. Journal of Educational Multimedia

and Hypermedia, 12(3):227–241.

Rubin, K. H. (1982). Early play theories revisited: Contri-

butions to contemporary research and theory. In The

play of children: Current theory and research, vol-

ume 6, pages 4–14. Karger Publishers.

Ryan, R. M. and Deci, E. L. (2000). Intrinsic and extrinsic

motivations: Classic deﬁnitions and new directions.

Contemporary educational psychology, 25(1):54–67.

Salant, P., Dillman, I., and Don, A. (1994). How to conduct

your own survey. Number 300.723 S3.

Salen, K., Tekinbas¸, K. S., and Zimmerman, E. (2004).

Rules of play: Game design fundamentals. MIT press.

Simon, S. J., Grover, V., Teng, J. T., and Whitcomb, K.

(1996). The relationship of information system train-

ing methods and cognitive ability to end-user satisfac-

tion, comprehension, and skill transfer: A longitudinal

ﬁeld study. Information Systems Research, 7(4):466–

490.

Smith, C. A. and Ellsworth, P. C. (1985). Patterns of cogni-

tive appraisal in emotion. Journal of personality and

social psychology, 48(4):813.

Straus, A. and Corbin, J. (1998). Basics of qualitative

research: Techniques and procedures for developing

grounded theory.

Taylor, T. (2009). The assemblage of play. Games and

culture, 4(4):331–339.

Teddlie, C. and Tashakkori, A. (2003). Major issues and

controversies in the use of mixed methods in the social

and behavioral sciences. Handbook of mixed methods

in social and behavioral research, 1:13–50.

Tornatzky, L. and Fleischer, M. (1990). The process of tech-

nology innovation. Lexington, MA: Lexington Books,

165.

CONRIST 2019 - International Conferences on Information System and Technology

292

Vakkari, P. (2003). Task-based information searching. An-

nual review of information science and technology,

37(1):413–464.

Wimmer, R. D. and Dominick, J. R. (2013). Mass media

research. Cengage learning.

Yadav, A. (2017). Recent trends and challenges in develop-

ment of smart systems. International Journal of Engi-

neering and Computer Science, 6(4).

Zichermann, G. and Cunningham, C. (2011). Gamiﬁcation

by design: Implementing game mechanics in web and

mobile apps. ” O’Reilly Media, Inc.”.

Exploratory Study of a Smart System Framework for Educational Process with Gamiﬁcation: Case Study - Schools in Indonesia

293