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ILEIID 2025 | International Journal of Research and Innovation in Social Science (IJRISS)
ISSN: 2454-6186 | DOI: 10.47772/IJRISS
Special Issue | Volume IX Issue XXV October 2025
Combating Ebbinghaus’ Forgetting Curve with Lexigo: A
Multimodal and Gamified Mobile Application for Vocabulary
Enhancement
*
1
Lindey Easter Apolonius
2
Shirleen Octavia Austin,
3
Melissa Sen Mei Mei
1 2 3
Universiti Teknologi MARA, Kota Kinabalu, Sabah
*Corresponding Author
DOI:
https://dx.doi.org/10.47772/IJRISS.2025.925ILEIID000048
Received: 23 September 2025; Accepted: 30 September 2025; Published: 05 November 2025
ABSTRACT
LexiGo is a prototype mobile application designed for the improvement of English vocabulary grounded in
Ebbinghaus’ forgetting curve, which incorporates multimodal and gamified learning experiences. Through the
integration of spaced repetition, interactive challenges and multimedia input, form–meaning connections are
reinforced and cognitive processing is enhanced. Adopting the Technology Acceptance Model (TAM), this
study investigates learners' perception of usefulness, ease of use, attitude toward use and behavioural intention
toward LexiGo. Findings indicate high user acceptance (M > 4.0; α = .884–.981), and all constructs
significantly predicted behavioural intention (p <. 001). The regression model was significant, F(3, 56) =
48.72, p <. 001, which accounted for 72.8% of the variance in behavioural intention (R² =. 728). The results
affirm its value as an adaptable learner-centred tool for vocabulary retention in higher education environments.
These findings imply that LexiGo could be adopted as a tool for integrating AI-based adaptive learning in a
mobile-assisted language learning (MALL) environment with broad scalability.
Keywords: vocabulary, memory retention, gamification, multimodal learning, mobile-assisted language
learning (MALL)
INTRODUCTION
Vocabulary acquisition is a cornerstone of English language proficiency and plays a decisive role in mastering
the four core skills of speaking, listening, reading, and writing. Empirical studies consistently demonstrate that
vocabulary size strongly correlates with overall language competence and academic achievement (Brooks et
al., 2021; Alsahafi, 2023). Despite its importance, many Malaysian tertiary students continue to face
challenges in retaining newly learned vocabulary, primarily due to limited exposure and ineffective
memorisation techniques (Mohammadi et al., 2024). Traditional methods such as rote learning and word-list
drills often lead to rapid forgetting, aligning with Ebbinghaus’ (1913) forgetting curve, which posits that
memory decays sharply without timely review. As vocabulary knowledge fades quickly, repeated and
meaningful exposure is necessary to consolidate long-term retention (Teymouri & Teng, 2024).
Recent research has highlighted the role of mobile-assisted language learning (MALL) in promoting
contextualised and adaptive vocabulary reinforcement (Benlaghrissi and Ouahidi, 2023). Mobile applications
with gamified and multimodal features have been shown to enhance engagement and retention by integrating
auditory, visual, and interactive elements that stimulate deeper cognitive processing (Li & Hafner, 2022). In
Malaysia, gamified mobile-assisted tools showed positive effects on ESL learners’ lexical gains and
motivation (Al Shihri, 2025). Such tools align with the growing educational shift towards learner-centred,
technology-driven environments that address the limitations of conventional instruction.
In this context, LexiGo was conceptualised as a mobile-assisted vocabulary learning application grounded in
three pedagogical foundations: spaced repetition, multimodal input, and gamification. Drawing upon the
Technology Acceptance Model (TAM), the study evaluates learners’ perceived ease of use (PEOU), perceived
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Special Issue | Volume IX Issue XXV October 2025
usefulness (PU), attitude toward use (ATT), and behavioural intention to use (BI) LexiGo in vocabulary
learning. The research aims to bridge theory and practice by providing empirical insights into how mobile
technologies can counteract vocabulary attrition and support sustainable language learning among Malaysian
undergraduates.
Problem Statement
Vocabulary retention is an ongoing conundrum for second language acquisition (SLA) learners, especially
ESL learners who experience difficulty with retaining newly learned words. Based on Ebbinghaus’ (1913)
forgetting curve, some 75% of new information is forgotten within days without repetition. Despite progress in
the field of pedagogy, Rosetta's downfall is that many students still need to memorise and learn by rote
individual sounds, words, or sentences, which are not grounded in context or form (Teng 2023). It is reported
that deliberate vocabulary learning within context with interactive support results in fast attrition, while
incidental acquisition through real tasks, multimedia exposure, or game-based interaction increases motivation
and retention (Li & Hafner, 2022; Teymouri & Teng, 2024). Cognitive and experimental investigations also
support the effectiveness of spaced repetition systems (SRS) to boost memory retention via distributed and
adaptive practice (Chen & Chung, 2008; Liu & Hsiao, 2021). Despite MALL having been exploited
thoroughly as an area of ESL learning, there are few integrated solutions available which offer a combination
of spaced repetition, multimodal input and gamified reinforcement in a single learner-centred platform
(Mohammadi et al., 2024).
Accordingly, this study aims to:
1. Provide language learners with a highly effective and engaging platform for vocabulary acquisition.
2. Ensure long-term retention through spaced repetition, interactive multimedia, and data-driven
personalised practice.
Product Description
With the app’s simple, user-friendly and intuitive interface, learners can easily search unfamiliar words and get
prompt feedback that includes definitions, example sentences, and pronunciation. Below is the list of the app’s
features:
1. Search Feature: Users can search for unknown words and receive definitions, example sentences, and
pronunciation.
2. Progress Tracking: The app records every word the learner searches and provides personalised revision
schedules based on spaced repetition theory.
3. Interactive Practice: Vocabulary quizzes and exercises are generated based on the user's word history.
4. Gamification: Quizzes, rewards, and badges are incorporated to maintain motivation.
5. Multimedia Learning: The app uses text, audio, and visuals to reinforce word meanings.
Figure 1: Interface and search features
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METHODOLOGY
Design: The study used a quantitative survey design to test the acceptance of the LexiGo concept with target
users. The questionnaire was developed from the Technology Acceptance Model (TAM), and it is a well-
established framework widely applied in technology adoption and educational research (Davis, 1989;
Venkatesh & Davis, 2000). TAM focuses on four main constructs: Perceived Ease of Use (PEOU), Perceived
Usefulness (PU), Attitude toward Use (ATT), and Behavioural Intention to Use (BI).
Participants: A total of 60 participants (N = 60) were included in the study. The respondents were second-
language students in higher education with various linguistic backgrounds. Convenience sampling was used
for recruitment, and voluntary participation was sought. Though the sample has offered an initial glimpse, the
small size precludes generalisability.
Instruments: The questionnaire was based on the TAM (Davis, 1989; Venkatesh & Bala, 2008) and it
measured PEOU, PU, ATT, and BI by using a five-point Likert type scale (1 = strongly disagree to 5 =
strongly agree). Items reflected participants’ perceptions of LexiGo features such as AI-driven personalisation,
adaptive spaced repetition, interactive quizzes, and multimedia vocabulary learning tools. Internal consistency
for each dimension was measured with Cronbach’s alpha.
Procedure: The online survey was administered via institutional communication channels. Participants were
introduced to LexiGo’s conceptual features before completing the questionnaire. They rated their perceptions
of usefulness, ease of use, and behavioural intention. Informed consent and anonymity were ensured
throughout the process.
Data Analysis: Data were analysed using SPSS (Version 29). Descriptive, reliability, and inferential statistics
were computed for all TAM constructs.
RESULTS AND DISCUSSION
The LexiGo app was assessed for acceptance by the learners following the Technology Acceptance Model
(TAM). As indicated in Table 1, all factors were rated highly (M = 4.11 - 4.39) with excellent internal
reliability (α =. 884–. 981), indicating positive perceptions. All variables were positively related to BI (p <.
001). The regression model was statistically significant, F(3, 56) = 48.72, p <. 72, which accounted for 72.8%
of variance in BI (R² =. 728). The variables with major influence being Perceived Ease of Use (PEOU) and
Attitude Toward Use (ATT) that reinforce learners' intention to use LexiGo are most affected by the ease of
use and positive attitude. These results are congruent with the Technology Acceptance model (Venkatesh &
Davis, 2000) and MALL literature where easy-to- use user-friendly appealing mobile tools can increase learner
motivation and continued usage (Teng, 2023; Zou & Xie, 2023).
Next Phase: Pilot Study
A pilot study will assess the pedagogical value and usability of LexiGo in actual classroom environments
based on an agile, feedback-oriented design process. The research goals are to evaluate the effectiveness of
LexiGO to increase ELLS’s retention rate, monitor levels of participation through mechanisms for data
collection in-app, determine satisfaction levels via indicators from TAM, and provide qualitative feedback on
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app interface and usability. A quasi-experimental pre-test–post-test design will be employed with three groups
of participants in terms of the learners' proficiency level, that's based on collecting data using vocabulary tests,
user log files and post-use questionnaires. In particular, it’s hypothesised that participants will produce large
vocabulary gains (p <. 05), greater motivation, and positive acceptance, indicating that LexiGo has potential
for wider MALL adoption.
POTENTIAL FINDINGS
It is anticipated that there will be positive results with LexiGo in MALL, especially in terms of enhanced
learner motivation, recall of vocabulary and use of technology. With the inclusion of spaced repetition,
multimodal glossing, and gamification to help with vocabulary acquisition at a research-based MALL
application's best practices. Research has demonstrated that mobile-based spaced repetition is beneficial for
recall and long-term retention (Teymouri & Teng, 2024; Mihaylova et al., 2022; Lin & Lin, 2019). LexiGo’s
reinforced algorithm operationalises these principles for distributed learning and memory consolidation.
Likewise, evidence on multimodal glossing proves that text with the aid of pictures and audio increases depth
of processing and vocabulary retrieval (Ramezanali et al., 2021; Teng, 2023; Bukhari & Dewey, 2023).
With respect to gamification, studies have proved that reward-based tasks and feedback result in increasing
motivation and perseverance (López-Cirugeda & López-Cirugeda, 2021; Zou & Xie, 2023). LexiGo’s rewards
and corrective feedback systems are intended to maintain engagement and improve retention. Furthermore,
prior research underscores that a learner’s outcome can be attributed to factors such as autonomy, self-
regulation and user interface design (Guo et al., 2022), implying the effectiveness of LexiGo with respect to
being adaptive to various kinds of users’ needs and proficiency levels.
Market Opportunity & Scalability
The demand for digital language education rising throughout Malaysia and Southeast Asia. In 2024,
Malaysia’s EdTech market valued at USD 270 million, anticipated to surpass USD 500 million by 2030, while
the Southeast Asian online language education market may attain USD 1.3 billion by 2032 (IMARC Group,
2024; Meticulous Research, 2024). This increase indicates a significant regional interest in English language
skills and mobile learning, which aligns with LexiGo’s emphasis on accessible, AI-driven vocabulary
acquisition. By integrating a freemium model and cloud-based design, LexiGo allows expansion to diverse
markets. Collaborations with academic partners and education authorities will expand its reach. The initiative
aligns with Malaysia’s Digital Education Blueprint and UNESCO SDG 4, promoting affordable, inclusive, and
continuous language learning.
Novelty
The majority of vocabulary applications focus on a single method. For instance, Duolingo highlights
gamification, whereas Memrise uses spaced repetition or mnemonic devices (Hasif & Darmi, 2024). LexiGo
combines three research-supported techniques: spaced repetition, gamification, and multimodal learning,
within a single mobile platform. Previous research has analysed these characteristics individually. For
example, Chen et al. (2019) found that learning vocabulary through mobile games boosted motivation and
performance, whereas Teng (2023) reported that multimodal input improved vocabulary retention. A
systematic review conducted by Lin and Lin (2019) similarly demonstrated that mobile-assisted vocabulary
learning (MALL) notably enhances language results in comparison to conventional methods.
This research is unique as it investigates the interaction among these three methods, rather than solely their
individual impacts. By emphasizing both educational results and user experience in independent mobile
learning, LexiGo offers a thorough and inspiring framework for vocabulary development.
CHALLENGES, LIMITATIONS AND RECOMMENDATIONS
Although it possesses strong pedagogical strength, the Lexi Go framework encounters various practical
challenges during implementation. The digital divide continues to be a significant obstacle, as unequal access
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to technology and internet connectivity threatens to increase educational inequalities (Tang et al., 2025).
Moreover, mobile distractions can impair attention, as students might multitask or interact superficially instead
of maintaining deep focus (Yu & Lee, 2022). Additionally, the possible excessive dependence on technology
might diminish chances for cultivating critical thinking and innovative problem-solving (Poom-Valickis &
Matre, 2023).
To address these problems, a number of suggestions are put forward:
1. Educators ought to incorporate LexiGo as an additional resource in blended or flipped learning
environments, guaranteeing guided use and pedagogical balance (Andujar, et al., 2020).
2. Developers should enhance AI-powered personalisation for adaptive learning pathways (Chen, et al.,
2023) and integrate social gamification elements to maintain motivation (Zou & Xie, 2023).
3. Researchers are urged to undertake longitudinal and mixed-method studies examining long-term
vocabulary retention (Tseng, 2020), as well as to pinpoint specific gamification elements (e.g., feedback,
rewards, leaderboards) to discern their distinct motivational impacts.
CONCLUSION
With the integration of spaced repetition, gamification, and multimodal learning, LexiGo contributes to
Malaysia’s education aspirations and UNESCO‘s SDG 4 by enabling inclusive and quality learning as a result
of AI guided design. Future studies should investigate its longer-term effects and ways it could be
personalised.
ACKNOWLEDGEMENTS
The authors would like to express their sincere gratitude to all respondents who participated in the survey. This
project would not have been possible without their contribution.
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