Mobile-assisted and gamification-based language learning: a systematic literature review

Automated search in web of science (WoS core collection)

A systematic investigation was made to filter irrelevant research and obtain adequate information. Our source was a curated database, Web of Science Core library that included over 21,100 peer-reviewed journals, top-class academic journals distributed worldwide (including Open Access journals), covering more than 250 disciplines (WoS, 2020). WoS is a tool that helps users collect, interpret, and share information from databases promptly (Princeton University, 2020). To conduct an SLR in an organized and timely manner, the researcher used this platform to retrieve the research articles by incorporating ‘AND’ and ‘OR’ Boolean operators with keywords to develop a search string. Figure 3 presented an overview of the search result obtained from the Web of Science.

Table 3 lists the final search string incorporated ‘AND’ and ‘OR’ Boolean operators with keywords, used to explore WoS Core Collection. Only titles were searched from the database, and a filter of indices and period were applied to restrict the search query for the study.

Selection based on inclusion/exclusion criteria

• 1. Inclusion criteria

The paper comprised in the review must be in MALL, mobile learning, and m-learning that must target the research questions. Paper published in the journals or conferences also from 2010 to 2020 was included in the review. Papers discussing MALL at school, college, and university level, focusing on learning, teaching, learning, and teaching (both), games (Example: Serious Game, Mobile games, learning application) were also included in the review.

• 2. Exclusion criteria

The articles were excluded not written in English and did not discuss or focused MALL, mobile learning or m-learning in schools, colleges, and universities to teach and learn English. A selection process of relevant articles for inclusion/exclusion criteria in detail was shown in Fig. 4.

Selection based on quality assessment

The collection of appropriate studies based on quality assessment (QA) was considered the critical step for carrying out any review. As the fundamental studies differed in nature, the essential assessment tool (Fernandez, Insfran & Abrahão, 2011) and (Ouhbi et al., 2015) used to conduct QA were also supplemented in our analysis by quantitative, qualitative, and mixed approaches. The accuracy of the selected records was determined using a QA questionnaire. The first author conducted the QA, using the following parameters for each study:

(a) If the analysis led to MALL, mobile language learning, m-learning, the result was indeed (1), otherwise (0).

(b) When there were simple answers for the MALL, mobile learning, m-learning of English, the analysis provided the following scores: ‘Yes (2),’ ‘Limited (1)’ and ‘No (0).’

(c) If the studies provided an empirical result, then award (1) else score (0).

(d) Studies analyzed concerning graded rankings of countries and journals (SCImago Journal & Country Rank (SJR), 2018) and conferences in computer science (CORE Conference Portal, 2018). Table 4 indicated potential findings for publications from known and reliable sources.

After combining the scores to the above questions, a final score (between 0 and 8) was determined for each study. Only papers included with four or more ratings in the final results.

Selection based on snowballing

Following the standard assessment, backward snowballing was performed, employing a reference list from any completed analysis to retrieve papers (Mehmood et al., 2020) and chose only those significant articles that met inclusion/exclusion requirements. After reading the introduction and then other portions of the document, the article's inclusion/exclusion was determined.

Overview of intermediate selection process outcome

MALL was a very active topic, and our analysis approach had to extract relevant research empirically and systematically from the Web of Science core collection. The next step of our systematic analysis was compiling records that form the foundation for this analysis. Approximately 57,000 papers were examined from the archive by providing the keywords for 2010– 2020. After creating a knowledge base from the digital library (Web of Science), the author reviewed the title, abstract, and accompanying complete document for each search result, as needed. During this process, irrelevant papers or papers of less than four pages were eliminated. During the inspection process, selected documents in the fields of MALL, mobile learning, and m-learning were read extensively to assess their significance & contribution and then created a comprehensive knowledge foundation of papers based on their findings to accomplish this research's core objective.

Overview of selected studies

Table 5 presented significant results of the primary search, filtering, and reviewed processes that included Web of Science indices. At the filtering/inspection stage, this amount decreased to 63 articles by the automatic search.

THEORIES

Theory of planned behavior: The Theory of planned behavior (TPB) noted that behavioral intentions motivated human behavior. Behavioral intentions rely on three determinants; an individual's mood, cultural norms, and perceived influence (Cheon et al., 2012).

Sociocultural theory: Sociocultural theory recognized human evolution as socially influenced by cooperation with more professional members of society, through which children learned their cultural norms, ideologies, and problem-solving techniques (Kearney et al., 2012) (Mcleod, 2020).

Experiential Learning Theory: The concept of experiential learning was implemented in a learning game. Players performed exercises to seek information within a gameplay environment that made the learning process enjoyable, engaging, and interesting (Tsai et al., 2016).

Dual-Coding theory: The dual-coding theory suggested that the verbal and imagery systems (mental images and representations) could be co-activated as rich and substantive referential relations connected dual-coded objects (Teng, 2018).

Theory of cognitive style: Two types of learning, field independence and field dependence, were based on critical and interpersonal personality characteristics. Field-independent students were independent-minded, and the social environment could not readily affect their learning style. Field-dependent students tended to learn in visual settings or scenarios (Ou-Yang & Wu, 2016).

Attribution theory: Bouchaib (Bouchaib, Ahmadou & Abdelkader, 2018) used Weiner attribution theory (1992) as a framework that provided failure or success reasons or explanations for people in education. Moreover, it was also a social cognitive theory of motivation.

Instructional theory: The instructional theory sought to explain how people can learn, evolve, and established environments that promote learning opportunities and strengthen teaching (Fisser, Voogt & Bom, 2012) (Top Hat, 2019).

Learning aspect

A mobile adaptive language learning system in which recommended material for reading and reading annotation facilities was provided to pupils to improve learning outcomes (Hsu, Hwang & Chang, 2013). A Mobile learning tool and five-step vocabulary learning (FSVL) strategy were developed in a situational learning environment to assess their effects on English as a foreign language (EFL) performance and learning motivation. According to the mobile learning tool, a global positioning system (GPS) was used to develop and provide learning material (Huang et al., 2016). Similarly, a mobile learning application ‘Raz-Kids’ for an extensive reading program was designed by ‘Learning A to Z.’ The tool aimed to create the concentration of the students to enhance their essential reading ability. Furthermore, it provides e-books of alphabets for students and teachers’ class management tools (Lin, 2014).

The study conducted experimental research using ASR, Non-ASR and Control Group. The ASR group Nuance Dragon Dictation application was designed and installed on their mobile phone to finish weekly pronunciation activities with immediately written visuals (Pictures) feedback provided by the application without any human interaction. Five native French speakers pronounced all words and phrases to test the application (Liakin, Cardoso & Liakina, 2014). In a study by Chang et al. (2013), ‘Mebook,’ a multimedia eBook system that can be played in the format of MP3 was developed. It integrated text, images, voice, and pictures that provided directions for listening, speaking, writing, and reading.

Furthermore, it also included speed adjustment of audio and switching of language from English to Chinese and Chinese to English. Duolingo, a free mobile assisted language learning tool (for vocabulary acquisition) is available in the web and mobile (Android and iOS) versions to examine out of class engagement informally. Translation exercises of sentences and words are the delivery method of this application. Moreover, instructors can see logs and progress to keep an eye on the students (Gafni, Achituv & Rahmani, 2017). A mobile-based gaming approach for English grammar and vocabulary learning ‘Save the princess with Teddy’ was developed and students’ learning achievement with gameplay at different levels was analyzed. It was hoped to enhance students’ learning motivation with the game and assistance to learn the English grammar concept (Chu, Wang & Wang, 2019). In the context of academic English, a mobile data-driven learning (DDL) experiment was discussed by designing and developing an application’ AKWIC (academic key words in context)’ for voluntary. This application provided support for academic writing (vocabulary learning), and data were obtained from logs generated by the application (Quan, 2016).

An SMS text message application, ‘Fetion’ explores the effectiveness of vocabulary learning using mobile technology. Specifically, SMS from mobile phones enhanced English vocabulary than outdated printed material (Zhang, Song & Burston, 2011). In contrast, a location-based vocabulary learning activities application for Thai and German users was proposed in a study with personalized learning motivation. Moreover, the aim was to enhance user acceptance by providing relevant learning content to evaluate an online questionnaire (Bohm & Constantine, 2016). A free mobile assisted language learning tool (vocabulary acquisition) ‘Duolingo,’ available for web and mobile (Android and iOS) versions examined out of class engagement informally. Translation exercises of sentences and words are the content of this application, and instructors can see logs and progress to track students’ progress (Botero, Questier & Zhu, 2018). ‘Mobile assisted listening application’ was developed to examine L2 multimedia glosses’ effects in a mobile learning environment, for vocabulary and listening comprehension, validated through a pilot study (Çakmak & Erçetin, 2017).

An offline mobile assisted language learning application system, ‘My English Vocabulary Assistant mobile edition’ (MYEVA Mobile) was developed to engage students in mixed-modality vocabulary learning to improve their vocabulary. The users learned targeted words via four vocabulary learning strategies: flashcard, imagery, word card, and Chinese assonance. A log analyzer server was installed, and log files were used to analyze the results (Ou-Yang & Wu, 2016). Furthermore, a mobile application like WhatsApp and Internet search engine (Google) were used by students to access materials for reading and interaction with peers and instructors outside the class. This application was used to improve learning skills in EFL reading (Hazaea & Alzubi, 2018).

A crowdsourced mobile-based ‘LingoBee,’ an open-source and freely available application, explored creativity and mobility in language learning. It was the part of the European countries’ project “SIMOLA”, designed to help collaborative language learning using the idea from social networks and crowdsourcing. Users created content for language learning, stored it on their device, and shared it with other users via a cloud-based repository. The application was evaluated through user studies in European countries (Petersen, Procter-Legg & Cacchione, 2013). In contrast, an application ‘English Practice’ was used to analyze the usage behavior of 53,825 users from 12 countries, and the evaluation was conducted through log files generated by the Google Firebase analytics tool (Pham, Nguyen & Chen, 2017).

Teaching and learning

An online assessment tool, ‘Grammar Grabber,’ was discussed in this study to evaluate grammar at the school level. Using this tool, users do practice online and get constant feedback to know their performance. The authors investigated this online assessment tool to perceive pedagogical, technological, and social affordances using multiple-choice questions and allowing re-attempt for wrongly answered questions. The log files of the application were used as the dataset (Ramadoss & Wang, 2012). An application, ‘Literacy and Numeracy Drive’ to teach and learn languages, was discussed at the school level. This application provided some practice and then some assessment exercises for the English language. This application aimed to teach singular/plural, use of has/have/had/is/am/are/ was/were, and reading comprehension (Ishaq et al., 2020b). A serious online game that was designed to extend the students’ vocabulary in primary school was discussed in this study. This game was part of the national project ‘Educational Time Extension (ETE).’ The students spend more time than expected class timing to learn and improve their vocabulary. Applications for teaching and learning at the college level was not adopted/developed for English language learning in the selected studies.

LINE App, an application that was used to investigate the teaching of English for specific purpose (ESP) effects on Business Language Testing Service (BULATS) (Shih, 2017). Whereas ‘Mobagogy’ a professional learning community of academicians to investigate the use of mobile technologies in learning and teaching while ‘The bird in the Hand’ initiative by the UK to examine the experience of trainee and newly qualified teachers by providing them smartphones to use in their offices and teaching schools to enhance professional practices of pedagogy. Australian University developed the application Mobagogy’, and The Bird in the Hand was sponsored by the UK (Kearney et al., 2012) to evaluate the benefits of mobile applications and an application 'English Fun Dubbing' designed for English’s oral practice its users. Learning material in this application was: animations, songs, movies, short videos, and textbooks developed by the Chinese Sci-Tech Company (Zhang, 2016). To enhance teaching and learning of English vocabulary, a mobile-based application ‘VocUp’ was designed and implemented to evaluate external parties (Makoe & Shandu, 2018). A mobile application, ‘WhatsApp’ was used in this study to examine the efficiency of teaching 40 phrases.

Furthermore, the study also aimed to enhance vocabulary acquisition (Shahbaz & Khan, 2017). An application ‘Anglictina (English) TODAY’ was developed by a Ph.D. student of Computer Science with a language teacher’s help. This application helped pupils for the preparation of final exams by learning from anywhere at any time. To discuss students’ perception of using a mobile application, this was developed based on their needs to make EFL vocabulary teaching and learning useful (Klimova & Polakova, 2020).

Gamification based learning and teaching

A serious game ‘MEL application’ developed in which 25 animals from five continents (Asia, South-America, Africa, Oceania, and North-America) were involved developed. The game was played during the visit to the zoo and at home in which two modes were available in which one was totally related to the zoo situation. One was independent of GPS that allowed children to access animals in different continents (Sandberg, Maris & Geus, 2011). To investigate a mobile English learning application that would be supplement and support for learning English at school was adopted for the study by enhancing game features. The application’s learning material on animals from the zoo resulted in the students’ outperformance using the mobile application for a fortnight than users for a fixed period (Sandberg, Maris & Hoogendoorn, 2014). A game-based system, ‘Happy English Learning System,’ in which learning material was integrated to experiment, was installed on mobile devices to see the learner's motivation for achievement. The activities were divided into levels of difficulties: Easy, Medium, and Advanced, according to the ability of users (Tsai et al., 2016).

Game-based applications Excel@ EnglishPolyU, Alphabet vs. Aliens, and Books vs. Brains@PolyU, business vocabulary after completing level challenges may acquire by the learners (Kohnke, Zhang & Zou, 2019). Similarly, an application, ‘PHONE Words,’ was developed by Alice English Education Studio for vocabulary learning, designed with game functions (MEVLA-GF) and without game functions (MEVLA-NGF) to investigate the perceptions and measure the learning performance of learners. This application also provides an assessment with a gamified competition mechanism (Chen, Liu & Huang, 2019). To give the students’ opportunity, ‘SOS Table,’ a mobile-based game application, was designed and developed to repeat tenses, high-frequency words, and sentence string. Time challenge was provided to create negative, positive, or correct sentences with words and pronunciation after completing the task (Önal, Çevik & Şenol, 2019). The serious game was not adopted/developed at the college level for English language learning in the selected studies.

In the study (Holden & Sykes, 2011), an augmented reality-based language learning game developed for Spanish in Southwestern US to explore foreign and second language learning’s benefits and complexities. Similarly, a mobile-based English Vocabulary system for practice was designed and developed not to replace traditional classroom teaching methods. The aim was to provide students with assistance to review, proficiency, and practice in and after the class. The game system was designed based on the ARCS model, which provided assistance in vocabulary learning and listening and worked as a testing tool (Wu, 2018). ‘Idiomobile’ a mobile-based game that was made available for specific handsets based on the knowledge of using idiomatic expressions in a critical situation (Amer, 2014).

Measures for teaching and learning

In the teaching and learning section, terminologies were described from the selected studies also presented the instruments used in these studies were shown in Table 15.

Pedagogy: a study of educational techniques, including the purposes of instruction and the approaches to accomplish them (Peel, 2017).

Motivation: originates from the term ‘motive’ that means needs, wants, wishes, or drives in people. It is the method of inspiring individuals to take steps to meet the targets (MSG Management Study Guide, 2020).

Perception: To organize, define, and interpret sensory input to reflect and recognize the input or situation presented (Perception, 2020).

Curiosity: originated from the flow concept, which means people prefer to communicate in the state of flow with their surroundings. Curiosity is preserved when people consider the world as fun or fascinating (Chang et al., 2013).

Continuance Intention: The level to which people intend to keep using smartphone English learning (Chang et al., 2013).

Attitude: An optimistic, pessimistic, or mixed assessment of an entity communicated at a certain level of anxiety. This represents an advantageous or disadvantageous assessment of a person, position, object, or event (iEduNote.com, 2020).

Achievement: Somebody succeeded in achieving something, particularly after much effort (Collins English Dictionary, 2020).

Self-Directed Learning: A learning approach that encourages learners to take control of their learning method (diagnosis requirements for learning, assessment of learning priorities, choice of learning methods, and the measurement of academic achievement and outcomes) (IGI Global, 2020).

Behavior Pattern: A repeated way for a person or group to behave against a particular object or condition (Dictionary.com, 2020).

Learning Behavior: Learning Behavior stresses the crucial relationship between child and youth learning and their social experience and behavior (Northampton Centre for Learning Behaviour, 2020).

Learner Autonomy: The autonomy of learning is when pupils take care of their learning, both in respect of what they learn and, in the direction, they study it (Oxford University Press ELT, 2013).

Affordance: An affordance is an object quality or a condition that makes it possible for the person to take action (Definitions for Affordance, 2020).

Technical evaluation measures

It is the Human-Computer Interaction (HCI) category to measure the applications' UI/UX (Ishaq et al., 2019). The following were the terminologies discussed in selected studies also, approaches used in these studies were shown in Tables 14 and 15.

Usefulness: The perceived usefulness (PU) is also one of the separate structures in the TAM. It is the extent to which a person believes that a specific process may improve the efficiency of his/her job (World Leaders in Research-Based User Experience, 2020) (Ishaq et al., 2020c).

Ease of Use: The primary use of computer programs in the TAM is a significant determinant of the target. A discreet individual describes a simple usage as evident in implementing a procedure and directly impacts the perceived usefulness (Ishaq et al., 2020b).

Effectiveness: Effectiveness is a participant's ability to execute a task in a given context. In general, efficacy is assessed by determining whether participants can carry out such tasks (Harrison, Flood & Duce, 2013).

Perceived convenience: The extent to which users perceive mobile English learning to be comfortable in terms of time, location, and the method to complete a task (Chang et al., 2013).

Usability: Usability is a common factor that determines how convenient it is to use interface design. The term "usability" also applies to the approaches used during the design process to increase ease of use (World Leaders in Research-Based User Experience, 2020).

Efficiency: Efficiency is the user's ability to deliver their role quickly and productively, representing the user's value during its use. Quality can be calculated in various ways, for example, the time taken to complete or the number of keystrokes necessary to finish a task (Collins English Dictionary, 2020).

Scalability: Scalability is characteristic of an entity, structure, model, or process, defining its ability, under increased or expanding workload or scope to handle and compete well (Hayes, 2020).

Reliability: Reliability means the possibility that a product, device, or service can perform its intended function properly for a given period or work without interruption within a fixed environment (ASQ, 2020).

Flexibility: Flexibility is a characteristic that explains how a person can tolerate changes in situations and think in novel, imaginative ways about issues and tasks (Flexibility, 2020).

Evaluation methodologies

The methodology is the basic techniques or methods used to identify, collect, retrieve, and interpret information on the topic (Paul, 2000). A quantitative study using a quasi-experiment (Pre-test and Post-test) was conducted by (Hsu, Hwang & Chang, 2013) (Wu, 2018) (Chang et al., 2013) (Kalogirou, Beauchamp & Whyte, 2017) (Fisser, Voogt & Bom, 2012) to collect data through questionnaires whereas, a quantitative study using questionnaire only was conducted by (Zhang, 2016) (Kohnke, Zhang & Zou, 2019) (Bourekkache & Kazar, 2020). A mixed-method approach was used (Amer, 2014) (Botero, Questier & Zhu, 2018) (Ou-Yang & Wu, 2016; Quan, 2016) (Önal, Çevik & Şenol, 2019; Zhang & Pérez-Paredes, 2019) (Ishaq et al., 2020b) to conduct interviews and questionnaire for the collection of information, whereas a qualitative approach in which interviews were conducted by (Hazaea & Alzubi, 2018) (Makoe & Shandu, 2018).