Wu, T.-T., & Huang, Y.-M. (2017). A Mobile Game-Based English Vocabulary Practice System Based on Portfolio Analysis.
Educational Technology & Society, 20 (2), 265–277.
A Mobile Game-Based English Vocabulary Practice System Based on
Portfolio Analysis
Ting-Ting Wu1* and Yueh-Min Huang2
1
Graduate School of Technological and Vocational Education, National Yunlin University of Science and
Technology, Yunlin, Taiwan // 2Department of Engineering Science, National Cheng Kung University, Tainan,
Taiwan // [email protected] // [email protected]
*
Corresponding author
ABSTRACT
English learning has become a vital educational strategy in many non-English-speaking countries.
Vocabulary is a critical element for language learners. Therefore, developing sufficient vocabulary
knowledge enables effective communication. However, learning a foreign language is difficult and stressful.
In addition, memorizing English vocabulary is often considered boring, and learners may lack motivation for
learning activities. To increase English learning motivation and interest, this study constructed a mobile
game-based English vocabulary practice system that entails selecting words according to textbook passages,
a difficulty ratio, and learning portfolios. The learning activities involved in the system transform vocabulary
learning from tedious memorization to game-based learning, thereby enhancing learners’ vocabulary memory
and their familiarity with curriculum-related vocabulary through various multimedia. An experiment was
conducted by dividing students into three groups that involved different vocabulary review methods. All
students had similar English proficiency levels, and the course content and instructor were the same for all
groups. This study statistically analyzed whether learners become familiar with vocabulary after playing the
game. According to the analysis results, students who used the proposed system exhibited higher learning
interest, attention, and learning effectiveness, as well as a sense of accomplishment and triumph, compared
with other students.
Keywords
Game-based learning, English learning, Leaning portfolio, Lag Sequential Analyses
Introduction
In the era of globalization, English has become the common language of international communication (Spolsky &
Shohamy, 1999). The importance of English is evident in international trade as well as leisure and entertainment.
English learning has become a vital educational strategy and policy in numerous non-English-speaking countries.
Vocabulary is particularly critical for language learners, and developing a sufficient vocabulary is necessary for
achieving effective communication (Nation, 2001). Nation (2006) reported that in listening or speaking, a
vocabulary of 6000–7000 words is necessary to achieve more than 98% comprehension. In addition, Laufer (2001)
indicated that knowledge of vocabulary is highly correlated with writing and reading ability as well as academic
performance. Jordan (2007) also suggested that difficulties in writing are mostly due to insufficient knowledge of
vocabulary. Therefore, lack of sufficient knowledge of vocabulary hinders appropriate expression in writing. Oberg
(2011) proposed that sufficient vocabulary is critical for academic achievement and learning effectiveness.
Learners of English as a second language (ESL) or English as a foreign language (EFL) generally consider
language learning to be difficult and stressful (Turgut & İrgin, 2009). Moreover, learners typically consider that
memorizing English vocabulary is a boring learning activity (Chen & Chung, 2008). This perception affects the
learning interest and achievement of learners, which consequently diminishes their confidence in learning English.
Therefore, instructional methods and strategies should be adjusted to increase the motivation and interest of
learners to learn English (Chang, Liang, Yan, & Tseng, 2013; Jong, Lai, Hsia, Lin, & Lu, 2013).
Learning activities derived from instructional strategies influence the selection, acquisition, and construction of
information for learners, which in turn affect the behaviors and thoughts expressed in their learning portfolios
(Weinstein & Mayer, 1986). To achieve English vocabulary objectives, increase learning motivation and interest,
and facilitate active learning and flow experience, digital game-based learning approaches can be used in an EFL
learning environment (Ryu & Parsons, 2012).
The multimedia features of digital game-based learning are composed of text, voice, and images. Digital gamebased learning can effectively enhance the attention, interest, creativity, and community relationships of students.
Moreover, designing a series of rules and objectives in a digital game-based learning environment can enable
achieving mental and physical satisfaction and insight; such satisfaction and insight can thus facilitate the
realization of learning objectives (Burguillo, 2010). Games are typically characterized by curiosity, expectation,
control, and interactive features, which can increase learners’ learning interest and intrinsic motivation (Konradt
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& Sulz, 2001; Lim, Nonis, & Hedberg, 2006). Learners are willing to overcome difficult challenges to gain a sense
of achievement. Compared with conventional courses, digital game-based learning enables students to improve
their memory of course content and engage in more critical thinking (Ke, 2008; Ke, 2014; Papastergiou, 2008).
Digital game-based learning, which combines entertainment and education activities, has been researched in
various academic fields (Liu, 2014; Liu, Cheng & Huang, 2011; Miller, Robertson, Hudson, & Shimi, 2012; Shih,
Shih, Shih, Su, & Chuang, 2010; Vos, Van der Meijden, Denessen, 2011). Digital game-based learning not only
reduces the English learning anxiety experienced by ESL students, but also facilitates such students in cultivating
interests toward learning; this thus increases the students’ motivation to learn English. For example, Uzun,
Cetinavci, Korkmaz, and Salihoglu (2013) constructed a game to help EFL university students who were enrolled
in basic English courses to practice English vocabulary. Their results showed that most students had positive
attitudes and satisfaction toward game-based learning in the classroom; this finding demonstrates that game-based
learning systems can support EFL instruction. Chou (2014) introduced game-based learning to students enrolled
in elementary school English courses and revealed that game-based learning could effectively help learners to
understand the meaning of English vocabulary and the content of instruction; this could increase the motivation to
learn English, enhance English learning performance, and make English learning easier and more interesting. In
addition, Chen and Yang (2013) used the video game BONE to teach EFL students, as well as to understand the
views of learners and benefits gained through the introduction of games. They found that the students generally
believed that game-based learning could effectively improve their English learning skills and motivation, and that
most of the students enjoyed learning English through games. Moreover, the introduction of the video game BONE
effectively improved the students’ English listening, reading, and vocabulary techniques and skills.
Because of the gradual development of wireless technology and mobile devices, topics related to mobile-assisted
language learning (MALL) have received considerable attention. Many studies have incorporated portability,
interactivity, connectivity, privacy, and real-time features into language-learning courses (Chen & Li, 2009; ElBishouty, Ogata & Yano, 2007; Petersen, Markiewicz, & Bjørnebekk, 2009; Wu, Sung, Huang, Yang & Yang,
2011). Chang, Tseng, Liang, and Yan (2013) constructed an English learning system for PDA devices used by 125
high school students; they explored the students’ continued use of the system and perspectives regarding the
benefits of the system. Their results revealed that most students had a positive view toward using mobile devices
for English learning and believed that the system was beneficial for English learning. Furthermore, Hsu (2013)
investigated the perceptions of EFL students in different countries toward MALL and reported that most learners
believed that mobile technology is a useful and practical tool for language learning. Combining MALL with gamebased learning also creates a revolutionary learning model and environment for language learning. Yu and Guan
(2013) constructed an English vocabulary passing game on smartphones; they demonstrated the convenience and
practicality of the devices, which enabled learning to become a part of life. Game-based learning can effectively
increase interest in and motivation for engaging in English learning, which consequently enhances English
vocabulary knowledge. Smith et al. (2013) constructed a game-based English vocabulary-learning system on ebooks and experimentally demonstrated that their interactive e-book game design increased the motivation for
engaging in English learning. Real-time learning tools and related assistant functions can effectively promote
students’ English-reading ability, thereby increasing the benefits of English learning.
According to the aforementioned advantages, this study constructed a mobile game-based English vocabulary
practice system on the basis of learning objectives, learning needs, and the learning scope. In the vocabulary
presentation game, words are selected according to textbook passages, a difficulty ratio, and learning portfolios.
This system could enable learners to achieve autonomous learning and self-planning according to the curricular
objectives and needs; moreover, the teacher used instructional objectives and the learning scope to set the game
content to meet curricular objectives. Regarding system development and construction, the game imitates a type
of block-clearing game that is popular among young students. The game converts the process of vocabulary
memorization, which is considered by students to be an uninteresting activity, into a game-based learning activity
so that learners can become proficient in English vocabulary. When learners finish reading an article, they can play
spelling games with diverse media effects. Learners can familiarize themselves with vocabulary by playing the
game, which can even serve as a formative assessment. The purpose of this study was to provide learners with a
relaxed and pleasant English vocabulary-learning environment that can reduce their learning anxiety and stress
and increase their learning interest and initiative. Learners can experience improving achievement in learning
English vocabulary, and this improvement is engendered by an inadvertent increase in the learning time and
concentration.
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Mobile game-based English vocabulary practice system
System framework
For meeting the instructional objectives of English learning and the digital game-based instructional strategy, and
for promoting the introduction of mobile devices, this study provided a game-based learning environment to
immerse learners in game-based learning and improve their learning experience. This study used the input–
process–outcome game model implemented by Garris, Ahlers, and Driskell (2002) to design a mobile game-based
English vocabulary practice system on the basis of learning procedures and needs; students using this can be
immersed in the game and fully enjoy the learning process.
A three-tier model was used for constructing and developing the framework of the proposed system (Figure 1).
The three-tier framework comprises the presentation tier, application tier, and data tier. The presentation tier
primarily processes data presentation, the operational interface and functions, and necessary data exchange with
the application tier. The application tier is responsible for extensive data processing and computational procedures
for reducing the computational load imposed on mobile devices with limited resources; this tier serves as the
middle tier between the presentation tier and data tier. The data tier is the database server and functions as a
centralized data storage and management system to provide high-efficiency data access functions.
Figure 1. System framework of three-tier model
On the learner end, mobile phones, tablet computers, and other widely used smart mobile devices serve as gamebased learning devices. The application server of the game system can be connected to the web through Wi-Fi
wireless Internet or 3G (HSPA), 4G (LTE), or other mobile communication networks. Data transfer between the
two ends can be achieved using either a socket client/server or HTTP request/response model. The independent
database server can be placed on an intranet to increase data security, and the application server connects the
Internet and intranet.
System interface and functions
The proposed game-based assistive English vocabulary practice system was developed with the objective of
providing a software tool that can be used by students during class or after class for review, practice, and repeated
learning; its development was not aimed at replacing official classroom instruction. The game imitates a blockclearing game that is popular among students, and it supports English vocabulary, sentence, and listening practice.
The learner plays the game with selected sentences, and the goal is to clear continuous letters that constitute English
vocabulary words rather than blocks of the same color as in similar games. In addition, it provides a model that
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enables learners to practice listening to vocabulary words and sentences; specifically, learners clear English
vocabulary words or sentences after listening to them recited aloud. Words and sentences are selected according
to three factors:
 Textbook content: The system automatically selects vocabulary words or sentences from a textbook article
for gameplay; any word or sentence may be selected. Learners can use this method to review and familiarize
themselves with the vocabulary words and sentences in the textbook.

Difficulty ratio: The frequency ratio of the appearance of each vocabulary word or sentence is related to its
difficulty. The frequency ratio of sentence appearance is based on a positive or negative correlation with
difficulty. If positive, the appearance frequency is higher for more difficult sentences; if negative, the
appearance frequency is higher for easier sentences. The difficulty indices are based on the two definitions of
the Flesch reading ease readability formula and GEPT word lists, which have undergone adjustments and
revisions. The formula applied to the proposed system considers two parameters in the Flesch formula: the
number of syllables per vocabulary word and the length of the sentence, as well as more than 8000 vocabulary
words at the GEPT elementary, intermediate, and high-intermediate levels. In the formula, rDM(v) is the ratio
of vocabulary word occurrences, NoS(v) is the number of syllables in vocabulary word v, GEPT(v) is the level
of vocabulary word v (elementary = 1, intermediate = 2, and high intermediate = 3), and V is the set of
vocabulary words in the textbook.
The calculation of the sentence occurrence ratio rDM(s) entails considering the length of sentences, the syllables of
all vocabulary words constituting the sentence, and the GEPT level. In the following formula, LoS(s) represents
the length of an s sentence (number of vocabulary words in the sentence), 𝑆I represents a set of sentences in the
textbook, and Vs represents a vocabulary set constituting the s sentence.
𝑟DM (𝑠) = {

𝑟(𝑠),
1 − 𝑟(𝑠),
positive correlation
negative correlation
Learning portfolio: The system extracts and analyzes a student’s previous learning records from the learning
portfolio database. After analysis, sentences that should have been cleared but were not, or sentences that were
incorrectly or unsuccessfully cleared, are selected from the learner’s previous game. This method can prevent
the learner from always clearing shorter or easier sentences to accumulate points. The method can also prevent
the game from unintentionally omitting vocabulary words; thus, learners have more opportunities to improve
by reviewing and becoming more accustomed to unfamiliar vocabulary. Therefore, the system applies the
binary exponential back-off algorithm to calculate the occurrence ratio in the next game for sentences that
have not been successfully cleared. Words and sentences that have been missed more times exhibit a higher
occurrence ratio. The occurrence ratio is expressed as
where 𝑓(𝑣) = {
1, 𝑣𝑎? ? 𝑉𝑖 − 𝐹𝑖V
0, otherwise
In the formula, Vi is the set of selected words in the ith round of the game, FiV is the set of cleared words in the ith
̂ is the vocabulary words that the learner
round, n is the number of the games previously played by the learner, 𝑉
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could not successfully clear in the previous game, t(v) is the number of vocabulary words v that should have been
cleared in the previous game, and f(v) is a function representing whether a vocabulary word has been successfully
cleared in a single-round game. The sentence occurrence ratio is calculated in the same manner, as follows:
Figure 2 presents the operational interface. Most block-clearing games comprise connected square icons, and each
letter can be connected to only four adjacent letters. By contrast, the proposed game system contains contiguous
of hexagons, and this enables each letter to be connected to six adjacent letters. The learner forms a vocabulary
word by swiping his or her finger to connect letters. The corresponding letters disappear, causing the adjacent
letters to change position. Subsequently, the learner can find another vocabulary word by connecting the adjacent
letters. Moreover, the game system can produce questions by using four models. (1) English vocabulary model:
The system shows English vocabulary words, and the learner finds the words and clears them. (2) English sentence
model: The system shows English sentences, and the learner finds the vocabulary words constituting the sentence
and clears them. (3) Chinese word model: The system shows a Chinese word, and the learner finds the
corresponding English vocabulary word and clears it. (4) Chinese sentence model: The system shows a Chinese
sentence, and the learner finds the corresponding English sentence and clears it.
Assistance tools
Prompt question
Current level
Four model:
English vocabulary model
English sentence model
Chinese word model
Chinese sentence model
Learner
Timer
Figure 2. Interface of the mobile game-based English vocabulary practice system
Research design
Participants
The participants in this study were first-year students from three classes in the department of information
management at a private university in Taiwan; the students were enrolled in a basic English course. The participants
were divided into three groups on the basis of their class: Group T, comprising 30 (18 male and 12 female) students;
Group R, comprising 32 (20 male and 12 female) students; and Group G, comprising 32 (18 male and 14 female)
students. The students in Group T learned English in the classroom by engaging in only paper-based tasks
instructed through traditional lecture-style instructional methods. The students in Group E also learned English in
the classroom through traditional instructional methods, and half the class period each week was allocated to
vocabulary review. The students in Group G received the same instructional strategy as those in Group E did;
however, the students in Group G used the mobile game-based English vocabulary practice system for vocabulary
review, which was allocated half the class period. Because of the university admission mechanism (entrance exam)
in Taiwan, freshmen in the same department have relatively the same English proficiency level. Therefore, to
ensure that the students in the three groups received the same course content, the same instructor taught all three
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courses in this study; moreover, the students in the three groups used the same instructional material database for
the reading and learning processes.
Experimental procedures
The basic English course was conducted for two class periods per week in an 18-week semester. To meet the
instructional objectives stipulated by the school, all the students in the three groups first underwent lecture-style
instruction from Weeks 1 to 8. Midterm examinations were administered in Week 9; this study used this opportunity
to conduct a pretest of the experiment. The planned experimental activities began after the midterm examinations.
During Week 10, the English teacher used half the class period to explain the procedures and objectives of the
experimental activity to the students in Group G and allowed them to operate and practice using the system. Thus,
the students familiarized themselves with the system’s operational interface and environment. Between Weeks 11
and 17, the basic English course was conducted for two class periods per week. The students in Group T learned
English through traditional lecture-style instruction. The students in Group R also learned English in the classroom
through traditional lecture-style instruction, but the second half of the class period was allocated to English
vocabulary review. The students in Group G learned English in the classroom through traditional lecture-style
instruction; however, during English vocabulary review in the second half of the class period, they used the
proposed mobile game-based English vocabulary practice system for practice. All operating behaviors were
recorded in the back-end database. The introduction of the game improved the students’ learning motivation,
intent, and interest; thus, they achieved active and independent learning, which consequently promoted the
effectiveness of English learning. During the learning activity, the instructor and technicians helped the students
to troubleshoot any problems with the learning activity and system use. Figure 3 illustrates a flowchart of the
experimental procedure. Week 18 was the final examination week. In accordance with the school schedule, this
study used the final examination as the posttest for this experiment.
Figure 3. Experimental procedure
Assessment tools
Learning achievement
Learning achievement can serve as a basis for performance evaluation to reflect the advantages and disadvantages
of an instructional design and instructional strategy. To understand whether the mobile game-based English
vocabulary practice system increases English proficiency and understanding and whether it benefits English
vocabulary learning, this study statistically analyzed the pretest and posttest results to evaluate learning
achievement. In addition to exploring differences in learning achievement associated with different learning
methods, this study explored whether the proposed system promotes students’ English vocabulary ability.
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Learning behaviors
Leaning behaviors are student reactions corresponding to learning contexts, particularly those caused by external
environmental stimuli. Learning situations can be understood through learning behaviors for providing appropriate
feedback to improve learning effectiveness (Politzer, 1983). To understand the learners’ operation and interaction,
determine the relationships and sequences of their learning behaviors, and identify the frequency of and procedure
for operating the system, this study encoded, defined, and classified the recorded learning portfolios. Subsequently,
lag sequential analysis (LSA), which enables exploring and summarizing the cross-dependencies occurring in
complex interactive sequences of behavior (Bakeman & Gottman, 1997; Hou, Chang & Sung, 2010), was adopted
for the modularized evaluation of the relationships among and sequences and frequency of learning behaviors. The
classification items were as follows: English vocabulary model (EV), English sentence model (ES), Chinese word
model (CW), Chinese sentence model (CS), use assistance tool (A), checking rank (R), and pronunciation (P).
Research results
Analysis of learning effectiveness
This study evaluated learning effectiveness by analyzing the pretest and posttest scores of the students in Groups
T, R, and G. Analysis of variance (ANOVA) and the general linear model were used for statistically analyzing the
data. Descriptive statistics were used to explore the effects of the introduction of the mobile game-based English
vocabulary practice system on the students’ performance in English vocabulary learning.
Table 1 presents the ANOVA results for the English performance of the three groups of students before the
experimental instruction process. The results revealed no significant difference in the English learning
performance of the three groups before the experimental instruction process (F = .418, p > .05, η2 = 0.79).
Group
Group T
Group R
Group G
Mean
69.03
69.28
68.25
Table 1. ANOVA results of pretests
N
Std. deviation
Levene
30
4.327
32
4.854
0.582
32
4.886
F
p
.418
.660
Table 2 lists the posttest results for Groups T, R, and G, obtained using ANOVA. The results revealed significant
differences in the posttest performance of the three groups (F = 5.38, p < .05, η2 = 0.863). Furthermore, the average
scores of the groups showed that the Group R students outperformed the Group T students in learning achievement,
because half the class period was allocated for English vocabulary review. Among the Group G students,
introducing the game increased learning motivation and learning interest. Therefore, the performance of Group G
was higher than that of Group R. Furthermore, according to the results of Scheffe post hoc comparisons, the
learning achievement of the three groups was ranked as follows: Group T < Group R < Group G. In addition, the
general linear model was used to evaluate the strength of correlations between different instructional strategies and
learning achievement. According to the criteria of Cohen (1988) for determining relevance, a moderate correlation
was observed between different instructional strategies and learning achievement (ω2 = .086).
Group
Group T
Group R
Group G
Note. *p < .05.
Mean
68.73
70.84
72.44
Table 2. ANOVA results of posttests
N
Std. deviation
Levene
30
3.413
32
5.030
3.944
32
4.690
F
p
5.380
.006*
This study also used a dependent sample t test to explore the differences between pretest and posttest values in the
three groups. As presented in Table 3, the results indicated no significant difference between the pretest and posttest
values in the students in Group T (t = .884, p > .05, d = 0.72). By contrast, a significant difference was observed
in the students in Group R (t = −3.892, p < .05, d = 0.69). Furthermore, the mean pretest and posttest values
indicated that the performance of the students in Group R improved slightly; this improvement was because they
engaged in English vocabulary review for the second half of the class period per week. In addition, a significant
difference was observed between the pretest and posttest values in the students in Group G (t = −7.081, p < .05, d
= 0.91). Thus, reviewing English vocabulary by using the proposed system reduced the students’ anxiety and
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obstructions regarding English learning. The game based-review system improved the students’ familiarity with
and understanding of vocabulary, and this thus enhanced their English-learning performance.
Group
Group T
N
30
Group R
32
Group G
32
Table 3. Statistical results of pretests and posttests
Test
Mean
SD
t
Pre-test
69.03
4.33
.884
Post-test
68.73
3.41
Pre-test
69.28
4.85
-3.892
Post-test
70.84
5.03
Pre-test
68.25
4.89
-7.081
Post-test
72.44
4.69
p
.192
.000*
.000*
Note. *p < .05.
Analysis of learning behavior
The behaviors of the students in Group G associated with the use of the mobile game-based English vocabulary
practice system were recorded in the back-end database. Portfolio data were analyzed to explore the sequence and
frequency of the students’ operation and interaction. First, the learning portfolios in the database were arranged
according to the classification items. Subsequently, LSA was applied to evaluate the sequence and frequency of
all learning behaviors. The assessment results for Group G are listed in Table 4.
EV
ES
CW
CS
A
R
P
EV
1573
1482
1490
736
579
1097
231
Table 4. LSA assessment results for Group G
ES
CW
CS
A
1362
1423
876
583
1067
1395
681
768
983
1408
517
308
495
632
487
397
757
298
370
19
848
907
430
0
138
49
27
0
R
792
502
638
248
0
59
0
P
249
192
57
33
0
0
17
In Table 4, the value in each cell with row items x∊{ EV, ES, CW, CS, A, R, P} and column item y∊{ EV, ES, CW,
CS, A, R, P } represents behavior y occurring immediately after behavior x. Finally, the z score was adopted for
the analysis and computation according to the LSA results (Allison & Liker, 1982). The analytic results are
presented in Table 5.
EV
ES
CW
CS
A
R
P
EV
10.83
9.57
9.74
3.63
2.01
6.92
-3.04
ES
7.38
6.46
6.03
1.17
3.89
4.98
-4.68
Table 5. Group G z score results
CW
CS
A
8.85
5.23
2.16
7.93
3.02
4.07
8.28
1.76
-1.48
2.38
0.83
-0.13
-2.09
-0.57
-8.03
5.92
0.31
-8.84
-6.21
-7.17
-10.02
R
4.52
1.42
2.85
-2.96
-8.79
-5.37
-10.32
P
-2.75
-3.89
-5.85
-6.98
-9.21
-9.38
-8.58
The analysis value was greater than 1.96, indicating a significant relevance and correlation between learning
behaviors. To facilitate the research analysis, the information in Table 5 was converted into diagrams of behavioral
relationships, as shown in Figure 4.
The line thickness represents the strength of the relationship between two behaviors. When the students used the
proposed system, they could switch the t model to experience a different practice method. According to Figure 4,
the English vocabulary model was the most frequently used model, followed by the Chinese word model and the
English sentence model; the least frequently used model was the Chinese sentence model. In addition, the students
exhibited more active behaviors toward the English vocabulary and Chinese word models than the other models
during the practice process. The results indicated that the students frequently switched between the English
vocabulary and Chinese word models of the system. Moreover, the students frequently reviewed the ranking when
they used the English vocabulary model and Chinese word model, because they needed to determine only one
English vocabulary word and clear it. These two models were simpler than the other models. Therefore, the
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students could quickly achieve the game levels, which promoted a mentality of competitiveness. Furthermore,
because the English vocabulary model and English sentence model prompted English questions, the students
naturally wanted to determine the words quickly and clear them. Therefore, the assistance tools were often used,
especially for English sentences. Moreover, each game level has a time limit that students must complete before
time-out. Although the system provides a pronunciation function, it was rarely used because of the pressure of the
time-out.
Figure 4. Behavior pattern of Group G
Discussion
This study constructed a type of block-clearing game on the basis of learning objectives, learning needs, and the
learning scope; this game is currently popular among students. This English vocabulary practice system entails the
use of the game-based learning method and textbook content, difficulty ratios, and learning portfolios; thus, it
enables students to practice and review vocabulary in a relaxed and enjoyable learning environment. The statistical
analysis results regarding the three teaching strategies show that the students who received traditional lecture-style
instruction passively accepted knowledge. Thus, no significant difference was observed in their learning
effectiveness. By contrast, the learning effectiveness of the students in Groups R and G improved significantly.
Our results are consistent with those of previous studies that have demonstrated that the percentage of forgotten
words was highest 20 minutes after the students acquired knowledge. However, the proposed system facilitates
remembering forgotten words, and it can effectively strengthen memory and learning ability and reduce learning
stress after adequate memorization, review, and practice (Runquist, 1983; Miao, 2008; Wang, Liu, & Li, 2014).
Furthermore, the posttest scores of Groups R and G reveal that Group G exhibited improved learning effectiveness;
this finding indicates that the game-based learning method increased the students’ attention and interest. An
interactive and diverse virtual environment as well as appropriate instructional material design and construction
can provide students with an environment conducive to continual practice and review; this can effectively improve
the students’ ability to face failure and setbacks as well as, in addition to enhancing their confidence and judgment
(Ke, 2008, 2014; Papastergiou, 2008; Burguillo, 2010). The system’s question mechanisms repetitively receive
information to facilitate students in increasing their familiarity with the system and enhancing their memory. Thus,
the students in Group G exhibited the highest improvement in posttest performance (Ebbinghaus, 1964; Mayer,
1983; Mayer, 2001; Mayer, 2003; Churchill & Hedberg, 2008; Diependaele, Lemhöfer & Brysbaert, 2013).
Regarding learning behaviors, this study analyzed the learners’ operation of and interaction with the proposed
system to understand the relationships and sequence of their learning behaviors. The statistical results show that
the English vocabulary model and Chinese word model were frequently used during English vocabulary review,
and the students demonstrated a more competitive and comparative mentality when they used these two models.
According to the teacher’s observation, the students exhibited high learning interest and attention when they used
the English vocabulary model and Chinese word model; this can be attributed to the models’ ease of operation.
Consequently, it provided the students with a sense of accomplishment and triumph. As reported in previous
studies, digital game-based learning is characterized by numerous features such as triumph, conflict, competition,
and challenge; all of these features can immerse students in the learning process and thus prompt them to take the
initiative to acquire knowledge and resolve problems, which can consequently engender active learning and self273
learning (Burguillo, 2010; Hainey, Connolly, Stansfield & Boyle, 2011; Jong, Lai, Hsia, Lin, & Lu, 2013; Prensky,
2001). Therefore, to immerse students in the learning process, instructors can incorporate some of the mentioned
features in designing a game-based learning system. In addition, the students in the present study frequently
utilized the assistance tools to accomplish the levels in the English vocabulary model and English sentence model.
According to the students’ feedback after the experiment, the game system prompted English questions, which
enabled them to find the answers and clear the words without translation. However, the time constraint made them
feel anxious. Therefore, the assistance tools were used frequently to release anxiety under time pressure. Previous
studies have reported that moderate anxiety can enhance student motivation and stress resistance (Chapell et al.,
2005; Young, 1991). Consequently, in the learning process, students can be given appropriate pressure for
enhancing their learning momentum.
Conclusion and future works
This study constructed a mobile game-based English vocabulary practice system on the basis of digital game-based
learning. The textbook content, difficulty ratio, and learning portfolio were considered in selecting vocabulary.
The learners enjoyed the game, and their motivation for and interest in English learning as well as their learning
achievement also increased significantly. The behavior analysis results show that the introduction of the proposed
system to students enhanced their competitive and comparative mentality, as well as their satisfaction and positive
attitudes. Personal satisfaction is a crucial factor for the continuation of motivation (Keller, 1999; Small & Gluck,
1994; Lee, 2000), which is the guiding force behind behaviors and strength (Gagné, Yekovich & Yekovich, 1993).
Therefore, higher learning motivation instills a sense of competence, self-efficacy, positive emotions, and
expectations, which improve learning achievement (Cameron & Pierce, 1994; Elliott, & Dweck, 1988; Moos,
2014; Duffy & Azevedo, 2015). This study suggests that future studies establish an instructional design for English
review that involves characteristics such as triumph, conflict, competition, and challenge, as well as similar
question-writing strategies, to help students practice and review English vocabulary.
To meet the course schedule of the students in this study, the proposed system was introduced only after the
midterm examinations. To achieve more in-depth analysis and exploration in the future, the proposed system can
be introduced for the whole semester after sufficient analysis and discussion with instructors. Moreover, this study
analyzed learning achievement and learning behavior. Future studies may analyze and explore cognitive and
learning styles to understand students’ learning processes in detail when they use the system.
Acknowledgements
The research reported in this paper has been supported in part by the Ministry of Science and Technology (MOST)
in Taiwan under the research project number MOST 103-2511-S-224 -004 -MY3, MOST 104-2511-S-224-003MY3, and MOST 105-2628-S-224 -001 -MY3.
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