Flow Learning Experience: Applying Marketing Theory to Serious Game Design

Abstract

The aim of this study was to design a digital game that imparts the concept of urban heat island effects to aid in environmental education. Within the play-time limits, gamers must be alert to signs of warning from the environment and keep the balance between economic growth and the temperature of the environment, so they can safely manage the development of a virtual city. We investigated gamers’ learning efficiency in terms of a city’s development scale, socioeconomics and the environment, environmental sustainability, increasing areas of green metropolitan space, and heat management of environmental knowledge and gaming experience through a survey of 209 sixth graders. Interestingly, results indicate that heavy gamers are less interested in serious games; they exhibit shorter periods of concentration and lower levels of immersion. If an individual exhibits a high level of fluency in the dimensions of challenge, player skills, control, and clear goals, then she or he is able to acquire knowledge through message involvement when gaming. This allows a serious game to appear less didactic and more fun. This study explored the means by which gamers acquire procedural and descriptive knowledge related to environmental protection through gameflow and immersion.

Keywords

hierarchy of effect digital-game-based learning serious game involvement gameflow

Introduction

The effect of urban heat islands (UHI) exerts an indirect impact on the ecological system, including events associated with climate change. To reduce the magnitude of such environmental crises, it is widely believed that metropolitan green space, green building materials, and the reduction of the artificial generation of waste heat are important endeavors. The meteorological research centers, meteorological societies, or college centers for atmospheric research in advanced countries have consistently put forth their best effort to deliver reports and research results. For example, modern cities’ UHI’s models, the low-cost application of weather forecasts in IoT, the newly established smart infrastructure in urban areas, and the estimate reports regarding extreme weather and climate events—all were satisfactory results of these endeavors (CMA News Press, 2016; Gardiner, 2011; Japan Meteorological Agency, 2017; Lee, 2017). Such strategies require public support, which highlights the significance of environmental education. In this regard, serious games, which integrate learning within the context of a digital game, have much to offer. Serious games can motivate young students to engage in autonomous learning in the pursuit of lifelong education. Advertising produces communication effects via mass media and the responses elicited in consumers. Such effects can be applied in the mechanism of a serious game aimed at increasing awareness of UHI: that is, deep immersion and a flow experience can enable the acquisition of knowledge and skills relevant to environmental education. Repetitive operation would increase these effects by allowing for the internalization of this awareness into long-term memory.

Literature Review

Communication Effects of Advertising and Digital-Game-Based Learning

Advertising imparts messages through a wide array of media channels. Its objectives are to establish and strengthen the audience’s recognition, attitude, or behavior; sometimes it even attempts to persuade consumers to develop new thoughts, attitudes, or behaviors. A series of communicative tasks and activities are executed to affect message recipients, with the ultimate goal of persuading consumers to buy the selected product (Hoffman & Novak, 1997). Engel, Blackwell, and Miniard (1995) define an advertisement as a piece of persuasive communication aired via mass media channels. Friestad and Wright (1999) put forward the persuasion knowledge model which analyzes how consumers apply their knowledge of persuasive tactics and motives to interpret and respond to advertising. Nelson (2016) stressed that instructional materials should be taught via advertisement forms in primary schools so that these young learners can be more readily persuaded and successfully acquire knowledge. This demonstrates how advertising literacy can be adroitly employed in an educational setting for the benefit of learners. Fishbein and Ajzen (1975) referred to the communication and persuasion theory developed by Hovland and Janis (1959), which describes the three stages of persuasion as follows: attention, comprehension, and acceptance. According to them, “…attitude is defined as a learned predisposition (of human beings in which an individual is presumed) to respond to an object (or an idea) or a number of things (or opinions).” They also emphasized that a person's attitude was determined by his salient beliefs about the object’s attributes and by his evaluations of those attributes. Researchers such as Lavidge and Steiner (1961) and Chow, Rose, and Clarke (1992) categorized the hierarchy of effects into communication effects and sales effects. Communication effects involve the internal phases experienced by a consumer: awareness → understanding → liking → preference → conviction → purchase. The earlier process can be categorized into three dimensions: cognitive or learning dimension (awareness and understanding), affective or attitude dimension (liking and preference), and conative or active dimension (conviction and purchase). Sales effects refer to the incremental sales brought by advertising; in other words, sales effects are measured by sales volumes. Hence, persuasive communication is a behavioral model incorporating learning and affective attitude. This theory can be usefully applied to the development of e-learning.

E-learning is a rapidly growing industry worldwide. Naidu (2006) described e-learning as a diverse array of channels—multimedia, audio-tools, websites, virtual environments, and games—designed to enable learning at the learner’s convenience. Lee, Hsiao, and Ho (2014) pointed out that multimedia instructional materials generate social clues that exert a significant impact on learners’ social perceptions, learning motivations, and learning performance. As a form of communication, games have existed in human societies since the dawn of civilization. Not only are they a form of cultural execution but they also provide a mechanism for humans to participate in society (Castronova, 2005; Murray, 2006). The advent of technology has brought forth an increasing variety of games. As traditional games have evolved into the virtual world (Wu & Tsuei, 2011), an increasing array of video games and online games have been absorbed into educational institutions and instructive settings (Liarokapis et al., 2010; Manlow, 2010). Hogle (1996) proffered that game-playing stimulates higher level conception in players since the design of computer games corresponds to human cognitive structure. Therefore, when instructional content is integrated into a game, and the learner or gamer is asked to create solutions for the problem at hand, learners are motivated to actively integrate what they have learned into the problem-solving process (Hamari et al., 2016). Prensky (2007) proposed a framework comprising the following 12 elements that explains the growing momentum of Digital-Game-Based Learning (DGBL): (a) games are a form of fun, (b) games are a form of play, (c) games have rules, (d) games have goals, (e) games are interactive, (f) games are adaptive, (g) games have outcomes and feedback, (h) games have win states, (i) games provide platforms for conflict or competition or challenge or opposition, (j) games involve problem-solving, (k) games provide a structure for social groups, and finally, (l) games involve representation and story.

Games and advertising are both presented using mass media technologies. Games attract their target audience with fun, communicative, and educative powers, whereas advertising is used to communicate with and persuade target groups. Advertising typically has a shorter window for impact, while games are played over and over. In addition, digital games provide more opportunities for interaction and immersion and therefore can convey more complex messages (see Table 1). When consumers receive adverting stimuli, they are exposed to the hierarchy of effects produced by the advertisement. This behavioral pattern resembles children who are exposed to multitudes of messages when engaging in DGBL. Table 2 outlines the similarities between advertising and digital games.

Table 1.

Comparison of Advertisements and Digital Games.

Media	Spread time	Immersion	Interactive	Pass the message	Memory
Advertisements	Short	Low	Low	Relatively single	To be repeated accumulation
Digital games	Long	High	High	Relatively diversification	To be repeated accumulation

Table 2.

Twelve Characteristics of DGBL and Advertising’s Hierarchy of Effects.

Hierarchy of effect	Definitions	12 characteristics of DGBL
Cognitive or learning dimension (awareness and understanding)	A kind of knowledgeable and rational mentation	Rules, goals, adaptive, outcomes, and feedback
Affective or attitude dimension (liking and preference)	A kind of emotions and feelings mentation	Fun, play, win states, representation and story, conflict/competition/ challenge/opposition
Conative or active dimension (conviction and purchase)	A kind of urging force mentation which can make the individual produce the final behavior	Interactive, problem-solving, social groups

Note. DGBL = Digital-Game-Based Learning.

Environmental Education and Serious Games

The 1972 Stockholm Declaration and 1975 Belgrade Charter, both published by the United Nations conferences, were both efforts to address the importance of environmental education (Association of World Citizens, 2013). Cheng, Lou, Kuo, and Shih (2013) advised that digital games be incorporated into primary school curricula across Taiwan in order to increase young children’s access to environmental knowledge, thus developing healthy attitudes and behavior toward environmental sustainability. Greenfield (2009) developed a framework for nonformal learning settings where televisions, video games, and the Internet are employed to allow technological advantages to be leveraged to balance learners’ “digital media diet.”

Serious games are digital games designed to impart a target knowledge set. Learners need to carry out tasks and pay attention to a game’s functions, skills, and operating details to enact learning performance (Connolly, Boyle, MacArthur, Hainey, & Boyle, 2012). Klimmt (2009) discussed three aspects of serious games: motivation to understand relevant information, acquisition of knowledge, and a change of attitude. Ritterfeld, Cody, and Vorderer (2009) propositioned that serious games pave the way toward deeper exploration, and this deep-level learning can be transferred to the real world after the game ends. Yusoff, Crowder, and Gilbert (2010) stressed that a serious game is designed to help learners attain higher levels of learning achievement, which means that the virtual reward awarded to a player is aimed at motivating learners. In short, the main objective of a serious game is to help learners internalize the knowledge presented by the digital learning materials while engaging in playing the game.

Many researchers have explored the application of serious games to environmental education. Wang, Lien, and Lu (2009) investigated science-based digital games focused on environmental attributes to help students better absorb learning materials. Tests indicated that such games inspired young learners in their awareness, concern, and reflection of environmental affairs. Ghilardi-Lopes et al. (2013) designed a serious game which exhibits the impact of climate change on oceans and coastal areas. Players are enlightened in the game-playing process about the causes and subsequent influences of climate change and motivated to think of practical ways to strike a balance of socioeconomic development and environmental sustainability. Cheng et al. (2013) conducted a survey among school children to investigate their willingness to engage in environmental education through DGBL. Results indicated that leaners’ attitude of use and perceived use are entwined with their acceptance of DGBL. Wu and Huang (2015) explored children’s decision-making behavior and whether they could achieve reciprocal fairness using waste-resource digital games. Results revealed that the natural environment was the anonymous recipient of players’ pollution, while utility value, the recipient’s anonymity, and whether the recipient is able to voice dissent might affect reciprocal fairness and sharing. The combined evidence of these studies proves the advantages of serious games in terms of knowledge acquisition, skills development, and positive learning experiences. The current study asks how perceived ease-of-use can be applied to enhance players’ attitude of use under the topic of UHI effects.

Flow Theory and Involvement

Flow theory was advanced by psychologist Csikszentmihalyi (1975, 1996), who postulated that the flow experience of individuals when engrossed in an activity holds some common traits across humanity. This flow state can be defined as a harmonious state where an individual’s perceived environmental challenge and his perceived skills strike a balance. Smith and Sivakumar (2004) propositioned that a flow state can be used to explain a consumer’s behavior in computing environments, whereas a game can be used to gauge a person’s immersion behavior in a flow experience (Sherry, 2004). Jennett et al. (2008) presented the following five factors to describe a player’s levels of immersion in game-playing: (a) cognitive involvement, (b) real-world dissociation, (c) emotional involvement, (d) challenge, and (e) control. Sweetser and Wyeth (2005) proposed the following eight dimensions applicable to the flow state experienced by gamers, which they termed gameflow: (a) concentration, (b) challenge, (c) player skills, (d) control, (e) clear goals, (f) feedback, (g) immersion, and (h) social interaction. Sweetser and Wyeth (2005) postulated the game elements and criteria to measure a player’s engagement in game-playing, which inspired Jegers’ (2007) idea of “pervasive gameflow.” Then, Tsai (2014) drew inspiration from this concept to formulate a gameflow scale to evaluate a player’s experience of flow in the game-playing process. Kim and Han (2014) found evidence of a positive correlation among flow experience, reputation, entertainment, and reward. Chen and Sun (2016) stated that the flow state would be significantly affected by the player’s self-regulation over time.

“Involvement” dates back to 1947, when American scholars, Sherif and Cantril, presented the concept of “ego involvement” as a predictor of attitude toward others’ opinions. Ego involvement is regarded as a psychological variable that indicates an individual’s drive or degree of concern toward the work at hand (Mitchell, 1981). According to Zaichkowsky (1985), involvement suggests how a person perceives a product will be associated with her or his inner need, interest, and values. According to Celsi and Olson (1988), “involvement” refers to the way an individual perceives something is related to oneself under certain spatial-temporal contexts Johnson and Eagly (1989) referred to involvement as a mental state, further specifying that when a person decides the value of something, she or he starts to exhibit a certain attitude and behavior as a response to that value judgment. Andrews et al. (1990) affirmed that an individual’s inner disturbance can be estimated in terms of intensity, direction, and continuity; thus determining how a person responds to external stimuli. A good number of researchers, including Gerend, Shepherd, and Monday (2008), Dholakia and Fortin (2002), Millar and Millar (2000), Martin and Marshall (1999), and Ganzach, Weber, and Ben-Or (1997), have attested that different involvement levels may interfere with the reception of message and thus generate varying communication effects. Chu (2008) evinced that an information-rich environment where web-based advertisements are created in accordance to “message framing” will enhance consumers’ online shopping behavior. Specifically speaking, product involvement exerts a positive effect on the advertisement, whereas product knowledge does not affect an advertisement’s communication effect, although such knowledge can be a significant factor influencing consumer attitude. In other words, the more powerful an advertisement’s communication effect is, the deeper the involvement of consumers that will be triggered, which in turn will lead to a more significant relationship between recipients and messages.

A large number of studies have pointed out that high-level involvement in a game or recreational activity may bring about an immersion effect and produce a flow experience. Brown and Cairns (2004) made a laudable effort to explore what players really mean when they refer to “immersion” in a game. They found that the self-perceived degree of involvement in a game denotes the level of immersion. Immersion can be categorized into three levels: involvement, preoccupation, and total immersion. These descriptions support the speculation that immersion is a cognitive phenomenon. Webster, Trevino, and Ryan (1993) asserted that immersion—known for its playful and exploratory elements—is basically a human–computer interaction. During the human–computer interactive process, an individual feels a subjective pleasure and involvement. As games have become more technically advanced, players feel more satisfaction and positive emotions, thus motivating them to explore deeper into the game or topic. Cheng and Lu (2015) cited surfing as an example to illustrate the positive relationship between high-level recreational involvement and high-level flow experience. This flow experience serves as an intermediary agent between recreational involvement and happiness. Lai and Yang (2015) defined “game immersion” as an emotional involvement or cognitive engagement that the totally concentrated player has in a game. Cheng and Hsu (2016) attested to a highly positive correlation between a player’s motivation and her or his involvement level, suggesting the more motivated a person is, the higher level of involvement she or he would exhibit. Hamari et al. (2016) posited that both challenge and familiarity with the game itself bring positive influence over game immersion.

While environmental sustainability has been promoted and executed in international communities, it is worth discussing how environmental awareness can be awakened through a variety of instructional materials (games included). The capacity to recognize and experience flow is highly positively correlated with people’s level of involvement. In other words, when children are immersed in a game and experience a flow state, they may well be involved in pursuit of knowledge and thus become more effective learners. Therefore, the aim of this study is to explore the correlation between children’s flow experience and involvement in the pursuit of environmental knowledge.

Experimental Design

The authors of this study performed a pilot study to test an original version of a digital game aimed at awareness of UHI. Based on the results of the pilot study, the authors revised the game and then invited 12 classes of sixth graders from three primary schools to operate the game. Following this, questionnaires consisting of self-edited UHI and gameflow scales were disseminated among these participants for sampling and experimental analysis.

Game Design

The central focus of the game lies in suppression of urban temperature rises by striking a balance between a city’s economic development and its surrounding natural environment. Since our aim was for primary school children to acquire environment-related information and cultivate a keen awareness of their surroundings, we based the game on a 3D presentation similar to that of “SimCity.” Reference values were created in accordance with the actual surroundings. Environmental parameters were set for game cycles, a four-season mechanism, a day-and-night mechanism, zoning restrictions, and architectural construction. The design of the game drew inspiration from suggestions provided by a panel put together for the pilot studies of 17 experts from diverse fields such as child education, interactive design, user experience, and programming design. As Lin and Yang (2010) recommended that metaphorical icons and photos of a product help to retain consumers’ memory of an advertisement, we incorporated environmental information into animated cards and tags, alongside multiple methods of operation, a status bar (showcasing environmental information), instant alerts, unexpected events and activities, mission critical systems, and game-level promotion, in the hope of increasing game stickiness and immersion. The login page and home screen are shown in Figures 1 and 2. The timing mechanisms are displayed in Tables 3 to 5: Table 3 reveals that an hour in the game was equivalent of 5 seconds in the real world. Two minutes meant a day in the game. Table 4 reveals the start and end of four seasons by syncing them up with actual months and dates. Tables 5 shows that 4 hours are set for a time zone, at which temperature-changing values were set in the game. Decision-making conditions are shown in Tables 6 to 8: Tables 6 illustrates the temperature-changing values of all the geographical conditions in the game. Table 7 reveals the two-level advancement process. The categories of architectures and architectural construction parameters were all shown. Table 8 reveals the two-level advancement process, in which “missions and achievement” and “triggering mechanisms” are presented for the gamers to know. Attention items and environmental messages can be found in Tables 9 to 11: Table 9 outlines a set of animated cards for instruction. Table 10 outlines a list of animated cards for “missions and achievement” in the process. Table 11 shows a series of animated cards for tags (signs of warning) and events.

Figure 1.

Figure 2.

Home screen.

Table 3.

Conversion of Real Time to Game Cycles.

Real time	Game cycles
5 seconds	1 hour
1 minutes	12 hours
2 minutes	24 hours

Table 4.

Four-Season Mechanism.

Season	Period	Month
Spring	(Mar 21 to Jun 21)	Mar, Apr, May, Jun
Summer	( Jun 22 to Sep 22)	Jun, Jul, Aug, Sep
Autumn	(Sep 23 to Dec 21)	Sep, Oct, Nov, Dec
Winter	(Dec 22 to Mar 20)	Dec, Jan, Feb, Mar

Table 5.

Day-and-Night Mechanism.

Day or Night	Time	Urban heat island	Temperature changes	Recommended temperature
Day 1	6 to 10 o'clock (4 h)	N	N	+0
Day 2	10 to 14 o'clock (4 h)	N	Rise up	+1
Day 3	14 to 18 o'clock (4 h)	Y	Rise up	+2
Night 1	18 to 22 o'clock (4 h)	Y	Rise up	+0
Night 2	22 to 2 o'clock (4 h)	Y	Rise up	−1
Night 3	2 to 6 o'clock (4 h)	N	N	−1.5

Table 6.

Zoning Restrictions.

Type	Can architecture?	Warming (h)
Hillside	N	−1
Near hillside	Y	−0.5
Plain	Y	0
Near river level	Y	0
River	N	0
Road	N	0.5

Table 7.

Architectural Construction Parameters.

Object	Type	Population supply and demand	Electricity supply and demand	Construction costs	Income and Expenses (h)	Temperature (h)
Level 1
House	Residential	4/0	0/1	80	−4	0.1
Apartment	Residential	10/0	0/2.5	400	−12	0.12
Building	Residential	32/0	0/4	1,600	−36	0.2
Large community	Residential	52/0	0/8	4,000	−102	0.2
Shop	Business	0/3	0/2	400	50	1
Office building	Business	0/12	0/5	1,600	300	2
Hotel	Business	0/12	0/16	1,600	130	1.5
Department store	Business	0/24	0/36	4,000	620	4.5
Part	Public	0/7	0/1	320	−125	−1.8
Power plant	Public	0/14	155/20	800	40	1.2
Universities	Public	0/7	0/7	240	−5	−0.5
Road	Public	N/A	N/A	N/A	N/A	N/A
Level 2
House	Residential	2/0	0/1	100	−4	0.1
Apartment	Residential	8/0	0/3	500	−16	0.12
Building	Residential	28/0	0/5	2,000	−48	0.25
Large community	Residential	50/0	0/10	5,000	−144	0.2
Shop	Business	0/2	0/2	500	52	1
Office building	Business	0/12	0/6	2,000	320	3
Hotel	Business	0/12	0/18	1,600	140	2
Department store	Business	0/24	0/42	5,000	650	5
Part	Public	0/8	0/1	400	−150	−1.4
Power plant	Public	0/16	150/20	1,000	40	1.2
Universities	Public	0/8	0/8	300	−6	−0.4
Road	Public	N/A	N/A	N/A	N/A	N/A

Table 8.

Achievement Parameters.

Achievement type	Achievements	Achieve parameters
Level 1
Population	Miniature population city	160 (P)
Population	Medium population city	220 (P)
Population	Large population city	275 (P)
Business	Well-off city	48,000 (M)
Business	Middle class city	51,000 (M)
Business	Plutocracy city	54,000 (M)
Environment	Reduce carbon city	390 (S) +More than 1 building
Environment	Excellent environment city	600 (S) +More than 2 building
Environment	Demonstration environment city	810 (S) +More than 3 building
Level 2
Population	Miniature population city	156 (P)
Population	Medium population city	185 (P)
Population	Large population city	215 (P)
Business	Well-off city	43,000 (M)
Business	Middle class city	46,000 (M)
Business	Plutocracy city	50,000 (M)
Environment	Reduce carbon city	360 (S) +More than 1 building
Environment	Excellent environment city	570 (S) +More than 2 building
Environment	Demonstration environment city	720 (S) +More than 3 building

Note. P = population; M = money; S = real-time seconds.

Table 9.

Animated Cards: For Instruction.

1. Explore issues	2. UHI Encyclopedia	3. Role play as mayor
4. Function button introduction (Left side)	5. Real-time information area (Top)	6. Achievement System Introduction (Right side)
7. Operation Introduction	8. Game promotion (1)	9. Game promotion (2)
10.Game over introduction	11. Reminders

Table 10.

Animated Cards: For Missions and Achievement.

Population (1)	Population (2)	Population (3)
Business (1)	Business (2)	Business (3)
Environment (1)	Environment (2)	Environment (3)

Table 11.

Animated Cards: Tags and Events.

Raining	The breaker has tripped!	Warning! Temperature is too high
Prohibit building
Excessive consumption
	Run out of money! Game over!	Temperature over! Game over!
Inadequate population
Electricity consumption exceeds

Sampling

Subjects for this experiment were sixth graders with basic knowledge regarding temperature and climate conditions. A total of 238 children from 12 classes at three primary schools were invited to play the designed game in a computer room for 50 minutes to heighten immersion. Within the 50-minute period, brief explanations of operation guidelines and UHI effects were given, followed by game-playing, distribution and completion of the questionnaire, and a short prize-giving. The questionnaire was divided into three parts: basic information (7 questions: A01 to A07), UHI scale (15 questions: B01 to B15), and gameflow scale (28 questions: C01 to C28); 209 valid questionnaires were obtained. The results of basic demographic data collection are shown in Table 12. The other two scales are discussed later.

Table 12.

Basic Information (A01 to A07).

Title	Item	Statistics (person)	Percentage (%)
A01. Gender	Boy	107	51.2
	Girl	102	48.8
	Total	209	100
A02. Age	11 to 12 years old	209
A02. Age	Total	209
A03. Class and seat number	Omit
A04. Have you ever understand or listen to urban heat island?	Y	83	40
	N	126	60
	Total	209	100
A05. Have you ever played a PC game?	Y	138	66
	N	71	34
	Total	209	100
A06. What is the number of hours of PC games per week?	Not at all	82	39.2
	1 to 7 hours	77	36.8
	8 to 15 hours	27	13.1
	16 to 24 hours	9	4.3
	Over 25 hours	14	6.6
	Total	209	100
A07. What is the final level of the UHI game?	Level 1	109	52
	Level 2	100	48
	Total	209	100

UHI Scale

A widely applied scale, the New Ecological Paradigm (NEP) scale, measures individuals’ perception and attitude toward the environment. Fifteen questions encompass the following five dimensions: (a) limits to growth, (b) balance of nature, (c) anti-anthropocentrism, (d) eco-crises, and (e) anti-exemptionalism (Dunlap, Van Liere, Mertig, & Jones, 2000). Responses are selected from a 5-point Likert-type scale (1 = strongly disagree, 5 = strongly agree). We referred to several sources (Landsberg, 1981; Basiago, 1998; Gardiner, 2011; Chang, 2016) to formulate a UHI scale based on the NEP model. This resulted in 15 questions covering the following five dimensions: (a) a city’s development scale, (b) socioeconomics and the environment, (c) environmental sustainability, (d) increasing areas of green metropolitan space, and (e) heat management (shown in Table 13).

Table 13.

Urban Heat Island (UHI) Scale (B01 ∼ B15).

B01. Urban development has reached crisis proportions and its limit in many cities.

B02. Humans have the right to change the natural environment for the sake of economic activities.

B03. When a city develops beyond a certain point, environmental crises will inevitably ensue.

B04. Green metropolitan space can ensure urban habitableness.

B05. Artificial heat damages the environment on a daily basis.

B06. A well-thought-out urban plan offsets UHI effects.

B07. Humans should try to maintain balance within the natural environment so all organisms can live in harmony.

B08. Environmental sustainability may assuage the impact of UHI effects.

B09. Even though green metropolitan space helps to assuage the impact of UHI effects, we still want to see urban development.

B10. “Urban desert” is an exaggerated term for artificial heat.

B11. Today’s cities are like a micro-greenhouse, where green spaces are small and cooling effect dwindles.

B12. Humans can effectively manage a city’s natural resources.

B13. The balance of the nature is fragile and vulnerable to harm.

B14. The increase of green metropolitan space may one day take control of UHI effects.

B15. We will be faced with a serious global warming crisis if we don’t put a stop to waste heat emissions.

Gameflow Scale

This study formulated a gameflow scale to evaluate the level of immersive behavior exhibited by game players. The resulting 28 questions are categorized into eight dimensions. These reflect the concept of pervasive gameflow proffered by Jegers (2007) and later revised by Tsai (2014). A few semantic adjustments were made in the questions to accommodate the game topic, namely UHI effects (see Table 14).

Table 14.

Gameflow Scale (C01 ∼ C28).

Item	Question
C1	Game graphics attract my attention and enhance my willingness to play.
C2	I can generally stay focused on the game.
C3	This game is not too difficult for me.
C4	I respond intuitively during the course of the game.
C5	I think the degree of difficulty of the game is appropriate.
C6	As my skills develop, the game will become increasingly difficult to challenge me.
C7	I think this game is challenging.
C8	The “practice mode” helps me understand the game.
C9	I have a feeling of deep involvement in the game.
C10	I gradually mastered the ability to attain new levels.
C11	The interface is easy to use.
C12	I have no difficulty managing the process of the game (e.g., select, start, stop game).
C13	I can control complex movements of the virtual spinning top, such as moving forward, and coordinating collisions.
C14	I feel that I am in complete control during the game.
C15	The overall objective of the game is clear.
C16	I am fully aware of the sequence of the game.
C17	After playing this virtual game, I would love to use a real spinning top.
C18	I received sufficient visual feedback throughout the game (e.g., when the spinning top struck something).
C19	My actions were met with immediate reactions in the game.
C20	I am able to immediately comprehend the situations I encounter.
C21	I can earn rewards through my successes in the game.
C22	While playing, I am unaware of what is going on around me.
C23	While playing, time seems to pass quickly.
C24	While playing, I feel emotionally invested in the game.
C25	The game tips prompt me to accept further challenges.
C26	Competition among players makes me more committed to continue the game.
C27	Competition among players makes me want to beat the other players.
C28	I would enjoy discussing this game with other players.

Results

We performed statistical tests on questionnaire responses using analysis of variance (ANOVA) and Scheffe tests, independent sample t-test, and linear analysis.

ANOVA and Scheffe Tests

Participants were asked to self-report their digital game use by responding to the question “A06: How many hours do you spend on playing computer games a week?” Responses were divided into the following five temporal variables: (a) “not at all,” (b) “1 to 7 hours,” (c) “8 to 15 hours,” (d) “16 to 24 hours,” and (e) “over 25 hours.” We then performed ANOVA analysis to seek correlations between game use and UHI learning and gameflow. Significant differences were not found in the UHI scale (p > .05). However, a significant difference existed between the temporal variable “over 25 hours” and the following three questions of the gameflow scale: “C07: I think this game is challenging,” “C11: The interface is easy to use,” and “C28: I would enjoy discussing this game with other players” (p < .05; see Table 15). Interestingly, a Scheffe test of responses to these three questions revealed that those who on average play over 25 hours a week were outperformed in terms of interface navigation, taking on challenges, and social interaction by their counterparts who spend far less time on computer games, in particular those who reported not playing computer games at all.

Table 15.

ANOVA and Scheffe Test: Weekly Gaming Hours Versus Gameflow Scale.

	ANOVA	Scheffe
	Significant	(I) A06 What is the number of hours of PC games per week?	(J) A06 What is the number of hours of PC games per week?	Significant
C07 I think this game is challenging.	.007*	4.0	.0	.015*
			1.0	.010*
			2.0	.031*
			3.0	.191
C11 The interface is easy to navigate and use.	.007*	4.0	.0	.021*
			1.0	.066
			2.0	.593
			3.0	.300
C28 I would enjoy discussing this game with other players.	.032*	4.0	.0	.037*
			1.0	.071
			2.0	.258
			3.0	.549

*Mean value: > 0.05 = significant.

Independent Sample t-Test

To address the seeming contradiction indicated earlier, we conducted an independent sample t-test on Question A06 by dividing the participants into two groups: “over 25 hours” (12 samples, ≥ 4.0) and “less than 24 hours (including not playing at all)” (184 samples, < 4.0) for comparison and analysis. Analytical results revealed significant levels in the following questions relevant to the gameflow scale: “C03: This game is not too difficult for me,” “C04: I respond intuitively during the course of the game,” “C07: I think this game is challenging,” “C10: I gradually mastered the ability to attain new levels,” “C11: The interface is easy to use,” “C20: I am able to immediately comprehend the situations I encounter,” and “C28: I would enjoy discussing this game with other players” (p < .05; Table 16). Results revealed that those who spend less time gaming surpassed heavy gamers in terms of the following five dimensions of gameflow: (a) concentration, (b) challenge, (c) player skills, (d) feedback, and (e) social interaction.

Table 16.

T-Test.

		p value
C1	Game graphics attract my attention and enhance my willingness to play.	.090
C2	I can generally stay focused on the game.	.478
C3	This game is not too difficult for me.	.006*
C4	I respond intuitively during the course of the game.	.018*
C5	I think the degree of difficulty of the game is appropriate.	.387
C6	As my skills develop, the game will become increasingly difficult to challenge me.	.489
C7	I think this game is challenging.	.037*
C8	The “practice mode” helps me understand the game.	.589
C9	I have a feeling of deep involvement in the game.	.192
C10	I gradually mastered the ability to attain new levels.	.019*
C11	The interface is easy to use.	.002*
C12	I have no difficulty managing the process of the game (e.g., select, start, stop game).	.283
C13	I can control complex movements of the virtual spinning top, such as moving forward, and coordinating collisions.	.423
C14	I feel that I am in complete control during the game.	.583
C15	The overall objective of the game is clear.	.567
C16	I am fully aware of the sequence of the game.	.777
C17	After playing this virtual game, I would love to use a real spinning top.	.217
C18	I received sufficient visual feedback throughout the game (e.g., when the spinning top struck something).	.217
C19	My actions were met with immediate reactions in the game.	.466
C20	I am able to immediately comprehend the situations I encounter.	.013*
C21	I can earn rewards through my successes in the game.	.326
C22	While playing, I am unaware of what is going on around me.	.444
C23	While playing, time seems to pass quickly.	.131
C24	While playing, I feel emotionally invested in the game.	.113
C25	The game tips prompt me to accept further challenges.	.139
C26	Competition among players makes me more committed to continue the game.	.218
C27	Competition among players makes me want to beat the other players.	.174
C28	I would enjoy discussing this game with other players.	.002*

*Mean value: >0.05 = significant.

Linear Correlation

We conducted linear analysis on the second and third sections of the questionnaire to understand participant’s knowledge acquisition with regard to UHI effects. Analysis indicated that 368 out of the 420 pieces of data showed significant linear correlation (p < .01 and p < .05; 87.6%). These 368 cases were mostly low-to-moderately positively correlated (Table 17). We then identified all relevant pieces of data contained in the five dimensions of the UHI scale and eight dimensions of the gameflow scale and calculated the value of relevance of each of the aforementioned dimensions for the purpose of data interpretation and analysis (Table 18).

Table 17.

Linear Correlation: UHI Scale Versus Gameflow Scale.

UHI Gameflow	B01	B02	B03	B04	B05	B06	B07	B08	B09	B10	B11	B12	B13	B14	B15
C01	R:.084 P:.258	R:.129 P:.081	R:.185* P:.013	R:.058 P:.434	R:.114 P:.126	R:.254** P:.001	R:.223** P:.002	R:.155 * P:.036	R:.113 P:.129	R:.145 P:.051	R:.240 ** P:.001	R:.101 P:.177	R:.150 * P:.044	R:.109 P:.145	R:.222 ** P:.003
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*Correlation is significant at the .05 level (two tailed); Gray blocks are no correlation.

**Correlation is significant at the .01 level (two tailed).

Table 18.

Percentage of Significance of Positive Correlation (UHI Scale Versus Gameflow Scale).

UHI Gameflow	Environmental sustainability B (3,8,13)	A city’s development scale B (1,6,11)	Socioeconomics and the environment B (2,7,12)	Heat management B (5,10,15)	Increasing areas of green metropolitan space B (4,9,14)	Average value
Control C (12 to 14)	9/9 = 1 100%	9/9 = 1 100%	9/9 = 1 100%	9/9 = 1 100%	9/9 = 1 100%	100%
Clear goals C (15 to 17)	9/9 = 1 100%	9/9 = 1 100%	8/9 = 0.89 89%	9/9 = 1 100%	9/9 = 1 100%	97.8%
Challenge C (5 to 8)	9/9 = 1 100%	9/9 = 1 100%	11/12 = 0.92 92%	9/9 = 1 100%	11/12 = 0.92 92%	96.8%
Player skills C (9 to 11)	12/12 = 1 100%	12/12 = 1 100%	12/12 = 1 100%	12/12 = 1 100%	6/9 = 0.67 67%	93.4%
Feedback C (18 to 21)	12/12 = 1 100%	12/12 = 1 100%	9/12 = 0.75 75%	8/12 = 0.67 67%	10/12 = 0.83 83%	85%
Social interaction C (26 to 28)	9/9 = 1 100%	9/9 = 1 100%	7/9 = 0.78 78%	6/9 = 0.67 67%	6/9 = 0.67 67%	82.4%
Concentration C (1 to 4)	12/12 = 1 100%	11/12 = 0.92 92%	10/12 = 0.83 83%	7/12 = 0.58 58%	7/12 = 0.58 58%	78.2%
Immersion C (22 to 25)	10/12 = 0.83 83%	10/12 = 0.83 83%	9/12 = 0.75 75%	8/12 = 0.67 67%	7/12 = 0.58 58%	73.2%
Average value	97.9%	96.9%	86.5%	82.3%	78.1%

As shown in Table 18, it seemed that the participants paid particular attention to the dimensions “a city’s development scale” and “environmental sustainability” (respective mean values of 96.9% and 97.9%). This was highly positively correlated with the eight dimensions of the gameflow scale. In terms of gameflow, participants attained the highest fluency and knowledge involvement in “control,” “clear goals,” “challenge,” and “player skills.” The highest mean value reached 100%. This was highly positively correlated with the UHI scale. Conversely, the values of “concentration” and “immersion” were relatively lower (78.2% and 73.2%, respectively).

General Discussion

Linear analysis revealed low to moderately positive correlation (see Table 17). From this, it can be inferred that when participants were immersed in the game, they had higher knowledge involvement and learned the target content more effectively as a result. Reference to relevant literature indicates that the five factors of game immersion suggested by Jennett et al. (2008) may well correspond to the characteristics of pervasive gameflow presented by Jegers (2007; see Table 19).

Table 19.

Five Factors of Game Immersion Versus Eight Elements of Pervasive Gameflow.

Five factors of game immersion (Jennett et al., 2008)	Eight elements of pervasive gameflow (Jegers, 2007)
Cognitive involvement	Clear goals, feedback
Emotional involvement	Player skills, social interaction
Real-world dissociation	Concentration, immersion
Challenge	Challenge
Control	Control

According to Gutierrez et al. (2007), learners who are immersed in a virtual environment tend to have more satisfactory learning performance than those engaged with traditional instructional materials. When Lai and Yang (2015) and Yang and Quadir (2016) explored the relationship between DGBL immersion and command of the English language, they identified varying levels of positive change associated with differing levels of immersion; specifically, the dimensions of “real-world dissociation,” “challenge,” and “control” increase learning performance. Hamari et al. (2016) attested that “challenge” serves as a powerful predictor for learning performance. They emphasized that the design of an educational game and the challenges contained therein should satisfy learners’ evolving needs and increasing capacities.

Our results indicated a significance in the dimensions of “challenge” and “control,” which supports the findings of Lai and Yang (2015). Yet, “concentration” and “immersion,” both of which were categorized into “real-world dissociation,” albeit showed significance, were relatively lower than the aforementioned two factors. Thus, it seems that for the majority of the participants who were not heavy gamers, the designed game provided an easy-to-use interface, allowing them to easily carry out the proposed missions and respond appropriately in the process. For these less-seasoned players, the game was challenging and they enjoyed discussing its challenges with peers. Heavy gamers, however, indicated low levels of interest in the game, which led in turn to lower levels of concentration and immersion. Hsu and Cheng (2017) stated that the use of a serious game may significantly increase young learners’ learning efficacy in natural science. In terms of problem-solving behaviors, results indicated that participants who were totally immersed in the game tended to use inspirational or analogical methods to resolve problems, which bears resemblance to the strategies adopted by experts. Conversely, participants who did not experience immersion were inclined to resort to “trial-and-error” strategies to solve problems.

The results of this study contradicted those of Lai and Yang (2015) in terms of “clear goals” and “feedback” (cognitive involvement) and “player skills” and “social interaction” (emotional engagement). This might be explained by the differing natures of the two games: The game devised by Lai and Yang (2015) was aimed at helping English learners (descriptive knowledge), whereas the educational game devised by this study was oriented toward environmental education (part descriptive knowledge and part procedural knowledge). According to Wu, Su, and Lin (2013), design knowledge can be divided into descriptive knowledge, which is applied to practical scenarios, and procedural knowledge, which is full of abstractions. When Anderson (1976, 1983, 1993) illustrated these two types of knowledge, he stressed that all knowledge starts in a declarative form, where consciousness and control begin. This control paves the way toward procedural process. Meanwhile, descriptive knowledge has become the basis of knowledge transfer. Lee and Chao (2009) stated that when mission design requires players to explore new game space and exploit game resources, they can easily acquire procedural knowledge related to solving problems arising from the context. At the same time, their descriptive knowledge (related to the role, location, or object they are finding) is strengthened in the process.

Nowadays, some firms or organizations entrust video game agents to promote their products or services. These games are called “advergames” and are designed along a diverse range of themes—business, politics, or educational. Most have a commercial focus. An, Jin, and Park (2014) estimated that 75% of children have little skepticism when it comes to advergames and advised that programs should be created to promote advertising literacy so as to help build young audiences’ knowledge of persuasive strategies. While the game devised by this study relies on advertising effects for message communication, they are different in their nature, purpose, and operating procedures. First, an advergame is a commercial game, which is designed to attract consumers to buy a particular product. Even though we cannot deny the educational value of many advergames, their design is based on a fundamentally different purpose to serious games.

The game designed in this study was aimed at conveying environment-related knowledge through a digital interface, drawing on rich communication effects. A minority of the participants (those who are heavy gamers) failed to become immersed in the game; however, most participants did experience flow and immersion. Later we address some limitations of this study and recommendations for future research:

A more diverse collection of knowledge dimensions related to environmental education would be of benefit. This study devised a game to address UHI issues and developed a scale for measurement by relying on literature regarding UHI effects and the NEP scale. A more comprehensive integration of disciplines would allow for extension into more dimensions. UHI effects are but one of the many eco issues facing today’s rapidly changing world. Furthermore, this study puts emphasis on pupils’ acquisition of environmental knowledge through playing serious games. We have used a scale of measurement to measure their learning performance. Yet, this UHI scale failed to communicate the initial situation or the diagnostic of needs. Therefore, we have suggested that future researchers provide relevant qualitative measurement so as to supplement this research study.

A more nuanced design of a serious game would accommodate players’ differing needs. Read (2005) classified the functions of children’s software into three types: fun, usability, and learning. A serious game can combine these three functions. McFarlane, Sparrowhawk, and Heald (2002) posited that most educational software can be used to evaluate children’s special skills; yet, school children take a fancy to such software for recreational rather than educational purposes. In other words, the older a child, the more interested she or he will become in seeking fun and stimuli. If an educational game aims to disseminate descriptive knowledge, addition of recreational scenarios, missions, resource exploration, and interaction can help formulate the goals of the game as acquisition of procedural knowledge. On the other hand, educational games primarily processing procedural knowledge can also contain descriptive knowledge, such as game guides or tips, background knowledge, or historical details.

We employed a number of methods to gauge a wide variety of learning behaviors. In this complicated learning process, multiple variables interplay to determine the outcomes. How is learning measured? When is there evidence of learning? What kind of learning? All the questions are worth exploring. This study adopted quantitative methods to examine how gamers tried to obtain procedural-and-descriptive knowledge regarding environmental protection through game-playing and immersion. The currently available data proves to be unable to disclose the actual points at which children absorbed knowledge and exhibited specific learning behaviors. We are convinced of the insufficiency of quantitative data and would advise future researchers take advantage of log files, audiovisual records, and qualitative methods to investigate the participants’ learning behavior, in order to garner more evidence to illustrate learners’ behaviors.

Future designs could incorporate a more diverse range of gaming platforms. This study chose the desktop computer as the apparatus for this experiment because we needed to be descriptive in large amounts of data in a controlled environment. It is recommended that smart phones, tablets, AR/VR devices, or other newly invented gadgets be used for future experiments of this nature to allow for generalizability.

Footnotes

Declaration of Conflicting Interests

The authors declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The authors received no financial support for the research, authorship, and/or publication of this article.

Author Biographies

Chung-Hsiang Wang is currently an UX/SA designer at OLE Group, a game development platform company known for integrating technology and software. He graduated from the National Taipei University of Technology, with master degrees in Interactive Design in 2016. He is interested in interactive design and environmental protection.

Ko-Chiu Wu is a professor in the Department of Interaction Design, National Taipei University of Technology, Taiwan, ROC. He has professional practices of spatial design and media communication. His research focuses on Human–computer interface design, information seeking behavior and cognition differentiation of media.

Saiau-Yue Tsau is an associate professor in the Department of Interaction Design, National Taipei University of Technology, Taiwan, ROC. Now she holds a concurrent post as director in IFoundry & Maker space of NTUT. She has professional practices of exhibition design and interactive arts. Her research focuses on interactive arts, gender studies, and interactive technology.

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