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CHAPTER 3: THEORY AND METHODOLGY
Introduction
Chapter 3 of this dissertation outlines the theoretical frameworks and research methods that underpin the study of gamification in education. It begins with an exploration of key theories that have shaped our understanding of digital gamification, connecting them to modern pedagogical approaches such as constructivism and behaviorism. The chapter then delves into the research design, including the data collection techniques and analytical methods used to assess the impact of gamification on language learning. By integrating semi-structured interviews and qualitative surveys, this chapter aims to establish a solid foundation for the study, ensuring that the findings contribute meaningfully to the field of educational gamification. It also explores the potential of digital gamification to improve learning outcomes and addresses the research questions in a structured manner.
This study aims to introduce the research methodology to offer a means of using qualitative data to construct a theory that clarifies the significance and impact of digital gamification in education. Chapter 3 provides a precise revision of Chapter 2 of the dissertation. It also offers a thorough discussion of the application of the New Learning theory, Constructivism theory, Transformation Learning theory, Imitation Learning theory, Social Learning theory, and Simulation Learning theory and how beneficial they are for this study. Chapter 3 of this study provides an overview of the present research, data sources, the researcher's role, qualitative methods, the study participants, data collection, data analysis procedures, and ethical concerns.
Because of the 21st-century learners’ learning preferences, traditional education systems are uninteresting and useless, and it is unable to meet the learners’ educational needs (Dicheva et al., 2015 & Kiryakova et al., 2014). Kiryakova et al. (2014) argue that to accommodate and cater to students with varying learning preferences, educators need to find solutions to important issues about learners’ demands. Surendeleg et al. (2014) study’s findings suggest that gamification is a concept that aims to improve users' experience and commitment to a system, and education is an area with great potential for implementing this concept. The concept of gamification in education was precisely defined by Ofosu-Ampong (2020) as "the application of game design elements in a non-game context purposely to promote desired behaviors or solve problems" (p.113).
There are two categories of game design elements in gamification, game mechanics, such as levels, badges, points, rewards, and progress bars, and game principles, which include freedom of choice, speedy feedback, and social interactions. Both elements must work together synergistically to convey learners' interests to meet the intended learning objectives (Aguilar et al., 2018; Surendeleg et al., 2014; Al-Saad & Gurugbo, 2021).
The "Level" element in gamification is closely related to Vygotsky's concept of the Zone of Proximal Development (ZPD), as it allows teachers to assist students based on their current knowledge levels and needs (Rohman & Fauzianti, 2022). McLeod et al. (2024) argue that digital tools and technology act as scaffolding artifacts, supporting students in reaching the next level of knowledge. As Cope & Kalantzis (n.d.) note in their article Skinner's Behaviorism, "learning is a process of 'conditioning' in an environment of stimulus, reward, and punishment" (para. 1).
Figure 3.1 illustrates the notion of ZPD, which helps to clarify learners' knowledge levels regarding what they can study on their own and with scaffolding.
Bíró (2014) disclosed that gamification and behaviorist learning theory share certain characteristics, including the dominance of positive reinforcements, small tasks, progressive challenges, and step-by-step instant feedback.
Numerous scholars have attested to the benefits of gamification in the classroom. For instance, Al-Azawi et al. (2016) suggest that, compared to traditional lectures, gamification is a more cost-effective approach in education, providing more engaging and appealing content. However, there are also significant drawbacks to gamification in education that must be addressed, such as the potential for addiction to game mechanics and ethical dilemmas (Hyrynsalmi et al., 2017). Laamarti et al. (2014) emphasize that serious games—one aspect of gamification—should be enjoyable but not at the expense of educational objectives, as the enjoyment of the game is the means by which learning goals can be achieved.
This study focuses on online simulation games, a key component of gamification in education, within the context of language education. Bostrom (2003) explored the idea that we may be living in an artificial simulation world in which actors and learners interact with existing knowledge and activities. In this world, learners engage in task-based activities that simulate real-life situations, where they assume roles, responsibilities, and possess sufficient knowledge of the real-life context to complete the activities (Peterson, 2010; Dhumal, 2015). Gilbert et al. (2001) note that “[t]he actors in the simulation activities can learn from their endeavors and from other actors with whom they collaborate” (p. 3). Similarly, the findings of Franciosi et al. (2016) suggest that online simulation games play a role in improving implicit language learning comprehension, motivation, and perception. Pivec et al. (2003) also examined the relationship between online games and collaborative social settings in education, finding that:
Using computer games and games in general for educational purposes offers a variety of knowledge presentations and it creates opportunities to apply the knowledge within a virtual world, thus supporting and facilitating the learning process. (p.1)
The following section outlines the objectives and research questions of this study.
Purpose and Research Questions
In response to criticisms of anachronistic education systems, especially, language acquisition in the United States, this study attempts to replace outmoded methods of language acquisition with more advanced techniques within the framework of gamification and its central idea, online simulation games in the light of certain learning theories.
This research seeks to address the following questions:
- What are the effects and consequences of using online gamification and its concepts in the classroom for language education in the United States?
- To what extent does using online gamification and its concepts transform anachronistic language education in the United States?
The following section examines the theories related to this study.
Theoretical Foundation
This study will employ a theoretical framework that integrates new learning theory, constructivist learning theory, and transformational learning theory. It will compare these theories with imitation learning, social learning, and simulation learning theories to enhance understanding of the role of gamification and digital simulation games in language education. This chapter will outline the key concepts, benefits, and limitations of these theories and present a logic model that links gamification in the classroom to the use of online simulation games for language learning.
New Learning Theory
Kalantzis and Cope (2012) describe New Learning Theory as a forward-thinking educational approach that focuses on preparing students for an open-ended future. This theory is based on four core principles that challenge conventional educational models and advocate for a more adaptable, inclusive, and technology-driven learning environment. These principles include embracing diversity, advancing a new epistemology of learning, prioritizing learning design, and adopting a global perspective on educational goals and content. The first principle is that diversity—when interpreted broadly and inclusively—is a fundamental component of modern societies. They argue that it is now generally accepted that traditional educational strategies are failing because they are not adequately adapted to the demands of diverse learners. The second principle states that education must promote its epistemology, or the philosophy regarding the sources, nature, and scope of human knowledge, which forms the foundation of New Learning. The third principle emphasizes the establishment and maintenance of a systematic focus on designing learning experiences and tracking learning processes. The fourth principle highlights international objectives and content based on a new educational framework that can be applied anytime and anywhere in the world. According to Kalantzis and Cope, these principles encompass the abilities, knowledge, and sensibilities required by contemporary culture, technology, and economy.
The principles of New Learning Theory influence gamification in education in various ways. First, as noted by Surendeleg et al. (2014), gamification, as an innovative learning approach, aims to boost user engagement in learning activities within diverse environments. Second, one of the notable new tools is digital learning media, which essentially functions as a framework for learning and communication technologies grounded in New Learning Theory (Kalantzis & Cope, 2012). Finally, Zhang (2014) emphasized that New Learning provides essential concepts for gamification in education, suggesting that employing a variety of teaching techniques can significantly enhance the speed and effectiveness of student learning.
However, Gee (2007) asserted that today's teachers might not view gamification as a useful new learning paradigm and may overlook the opportunity to learn from both the successes and failures of gameplay. Gee further noted that teachers who are not gamers could find it frustrating to implement pedagogies and strategies with which they are not familiar.
The four fundamental principles of new learning theory are illustrated in Figure 3.2.
Kalantzis and Cope (2010) contend that new instructors are needed to approach the dynamic transformation in education, which includes technology. According to Kaimara and Deliyannis (2019), educators emphasize the importance of gamification in the learning process and the role of rewards in the new educational environments inundated with cutting-edge technology.
There are clear relationships between New Learning Theory and Multiliteracies Learning notions. Multiliteracies notion comprises two components to influence new learning environments, according to Kalantzis and Cope's (n.d.) blog, Works & Days. First, it offers flexibility in meaning-making across many social and cultural contexts, which is crucial in today's communication environments. The features of the new information and communications media give rise to the second element. Furthermore, Kalantzis and Cope state that oral, visual, auditory, gestural, tactile, and spatial modes of meaning interact with written-linguistic modes of meaning in the process of meaning-making, which is multimodal. Homes (2017) distinguishes between two core components of multi-pedagogies. First, knowledge can be imparted by a diverse range of teachers and tools, such as technological artifacts. Second, there are other settings outside of typical educational institutions where learning and teaching can occur, such as gamified learning environments.
However, Sang (2017) argues that the primary characteristic that sets new learning apart from the notion of multiliteracies is its emphasis on the significant shifts in common technologies and the corresponding cultural practices. Sang asserts that the multiliteracies learning notion goes beyond the traditional understanding of literacy as the ability to read and write texts. The multiliteracies learning notion also encompasses the use of digital technologies, such as video games, weblogs, and mobile texts, to create meaning and the ways in which these practices influence people's perceptions of new literacy. Four instructional traditions are indicated by the notion of multiliteracies, as shown in Figure 3.3 (Kalantzis & Cope, n.d.).
Behaviorism Learning Theory
Many researchers argue that gamification in education is fundamentally rooted in behaviorist learning theory. For instance, Egenfeldt-Nielsen (2006), in his examination of the educational use of video games, noted that behaviorism, which gained significant traction during the 1950s, continues to influence research on educational gamification,media, including video games that focus on overt and observable behaviors crucial for effective learning. According to behaviorism learning theory, learning is fundamentally about reinforcing relevant stimuli and responses (Egenfeldt-Nielsen, 2006).
Furthermore, Tuan et al. (2019) argued that behaviorism learning notion asserts that learning occurs when there is a noticeable and measurable change in behavior as a response to specific stimuli, such as the mechanics and principles of gamification. They identified two key principles of behaviorism: first, behaviors can be conditioned through repeated stimuli; and second, behaviors can be reinforced through rewarded responses. According to Cope’s and Kalantzis; (n.d.) Work & Days, website, the relationship between a response and its consequences is often straightforward, and changes in the likelihood of a response are not unexpected.
Bíró (2014) concluded that gamification aligns more closely with behaviorist learning theory—highlighting aspects like the effectiveness of positive reinforcement, the completion of small, incremental tasks, immediate feedback, and progressive challenges—than with other prominent concepts of gamification.
Constructivist Learning Theory
According to Lee (2012), constructivist learning is useful for gamification qualitative research in educational settings in several ways. First, constructivist learning theory is employed in gamification qualitative research because educational curricula, teaching methods, and policies are continually constructing new levels of knowledge. Second, Lee claimed that constructivism, as a theory of teaching and learning, considers important factors in education such as culture, context, literacy, language, learners' needs and interests, individual experiences, interpretation of reality, and application of knowledge. Lee suggests that qualitative studies can examine these components to see how they affect policies related to teaching and learning. Third, Mogashoa (2014) contends that by dissecting key elements of teaching and learning policies, transformative learning enables qualitative researchers to investigate how educational practices and procedures are constructed. Lastly, Mogashoa asserts that qualitative researchers may explore how educational policies reinforce constructivist claims about how constructivist instruction fosters critical thinking and produces engaged, active learners.
Bada & Olusegun (2015) defined constructivism as a psychological theory of learning that describes how individuals can pick up information and learn. They claimed constructivism's emphasis on student-centered learning remains perhaps its most significant contribution to the notion, and it affects how teachers instruct students and develop as educators. In the same vein, Priker & Gutl (2015) asserted the fundamental idea of contemporary education is constructivism.
However, according to Liu & Matthew (2005), the constructivist notion has recently come under fire. Liu & Matthew looked at the basic epistemological tenets of popular constructivist theories and their critiques, motivated by discrepancies in how constructivism is interpreted in recent work. They discovered that popular constructivist claims and criticisms are equally rooted in the dualist separation of the human mind and the outside world, rather than being based on divergent philosophical notions.
In conclusion, the constructivist theory is based on the idea that, if teachers uphold psychological, such as Cognitive & Social Constructivism learning theory, technological, such as gamification in education and pedagogical bases, students will actively engage in their learning endeavors and generate knowledge through experiences. The learning theories of Dewey, Piaget, and Vygotsky along with the technological base are firmly rooted in constructivism learning theory (Kurt, 2021).
The process of gamifying traditional education systems—particularly language learning—into progressive ones is demonstrated in Fig. 3.4 about the three main theoretical framework pillars of psychology, technology, and pedagogy bases.
Transformation Learning Theory
Transformative learning theory greatly amplifies the potential of gamification in education by promoting "...the process of effecting change in a frame of reference" (Mezirow, 1997, p. 5). According to this theory, genuine learning goes beyond merely acquiring knowledge; it involves a fundamental shift in how individuals perceive and understand the world. Imel (1998) further elaborates on this idea, suggesting that transformative learning fosters a deep change in a person's character, including resolving internal conflicts and broadening their awareness. This process leads to greater integration of the personality, making it particularly compatible with the immersive, perspective-altering nature of gamified learning environments. The ultimate goals of transformational learning are to increase one's autonomy through reasoned discourse, overcome systemically produced distortions of perception and communication, and attain self-emancipation through self-knowledge, according to Imel.
Transformation learning theory has a few key elements. The element of experience is the foundation of the theory and serves as the basis for its reflectional content. Transformation requires critical engagement with life experience in a reflective manner, and the whole process revolves around change, specifically developmental and growth to enhance changes. Human development is both a precondition and a result of the process of transformation. Critical thinking is an individual's own development and is required to bring change. Transformation learning involves three phases, such as critical reflection on one’s assumption which leads to discourse of validation the critically reflective insight, as phase two, and action which makes dynamic changes as the last phase of the transformation learning notion (Segers, & De Greef, 2021).
Transformation via Educational Gamification
Transformative learning theory is well suited for the qualitative study of gamification in education in numerous ways. Firs, it is based on the principle that adult learners experience a transformation in the way they view their experiences. Secondly, Transformational learning paves the way for the learner to formulate perspectives, which it is the core aspect of a qualitative study through critical reflection and the assumptions upon their interpretations, and beliefs (Mezirow, 1997).
Tan et al. (2023) claimed that by introducing game design elements into educational environments, gamification has been used to increase student engagement and spark interest in learning.The feasibility and effectiveness of gamification in reforming underachievers were investigated in Tan et al.'s study. They found that gamification may effectively increase underachievers' interest in learning; they contended that to transform underachievers into achievers, a gamified learning platform needs to have game elements like meaning, teams, social pressure, and an onboarding tutorial. In the same vein, Al-Saad & Durugbo (2021) found that when gamification is used strategically, it transforms the co-creation process to help people become more capable of making decisions, which can change educational institutions and interventionists' mindsets.
However, Segers & De Greef (2021) contend that several objections to the transformation learning theory have evolved. First, although transformation learning theory places an excessive amount of emphasis on rationality, the process is intuitive. The second criticism of transformation learning theory is that it does not provide a cogent, all-encompassing theory of social change because it places too much emphasis on the transformation of the individual perspective and ignores the social context in which structural inequalities are deeply ingrained. Next, transformation learning theory is acontextual and does not take into consideration the cultural context of learning. Family, Al-Saad & Durugabl (2021) argued that although gamification as a paradigm of transformation learning theory adds value through process, learning, and transformation, there are important boundaries in gamification design methods that could easily overlook the benefits of gamification.
Imitation Learning Theory
Numerous scholars have investigated imitation learning theory in the context of gamified learning. For instance, Gorman (2009) claimed that imitation learning theory, as defined by Michael (1950) in the American Psychological Association Dictionary of Psychology, represents the initial phase of cultural learning, during which the learner internalizes certain behavioral strategies and intentions of the model for carrying out the behavior. Imitation learning theory aims to accelerate learning by utilizing data gathered from examples of specific activities (Gorman, 2009). Hussein et al. (2017) argued that imitation learning facilitates the teaching and learning of complicated tasks with little to no expert knowledge of the task, leading to the increasing popularity of the learning-by-imitation paradigm.
The theory of imitation learning in language acquisition hypothesizes that people pick up linguistic patterns and structures by mimicking the speech of others. This suggests that children learn language primarily by watching and imitating their peers and caregivers, rather than through natural mechanisms or explicit instructions (McLeod, 2024). According to Bullard and Anderson (2014), people can observe behaviors directly through social interactions with others or indirectly through media. Hussein et al. (2017) also argued that imitation learning methods aim to replicate human behaviors in each task. In the context of gamification and online simulation games, imitation learning theory suggests that students emulate behaviors, strategies, and problem-solving approaches exhibited by characters or peers within gamified learning environments (McLeod, 2024).
In many respects, the idea of imitation learning is useful for qualitative research on gamification and online simulation games. First, the notion of imitation learning facilitates researchers' observation of participant behaviors during qualitative surveys and interviews. Second, it is a well-developed social skill in qualitative studies, as such methods rely on participants' perspectives. Third, imitation learning is the ability to mimic the behavior of others as a skill that living beings either naturally acquire or develop over time. Lastly, imitation plays a critical role in skill development during the early stages of human growth, particularly in language learning (Bandura & Walters, n.d.; Davis, 1973).
Bandura's social learning theory, which underpins imitation learning theory, includes three significant concepts: observation, imitation, and modeling (McLeod, 2024). Bandura’s social learning theory emphasizes that when learners are engaged in simulated activities, they can observe and copy effective practices, thereby reinforcing their learning outcomes (How Social Learning Theory Works, 2024). Social Learning Theory stresses that imitative learning is part of many teaching and learning strategies, and most language laboratory resources—including films, slides, audio materials, videotape recordings, and even the lecture format itself—are imitative (Ahn et al., 2020). Ahn et al. further asserted that, in the context of gamification and its critical component, online simulation games, role modeling has garnered significant attention because it can reveal the mechanisms through which imitation occurs. Like Social Learning Theory, imitation learning theory assumes that the observer copies the model. However, as a critique of imitation learning, it is suggested that individuals also intentionally learn from others, rather than merely imitating their reinforcing behaviors (Social Learning Theory, 2022).
Imitation learning theory is comparable to simulation learning theory in several ways. First, both learning by imitation and simulation often present a reduced version of real-world circumstances, which may limit the applicability of learned skills and knowledge. Second, as paradigms of imitation and simulation learning, online simulation games frequently prioritize cognitive involvement over emotional engagement while also providing opportunities for problem-solving and intellectual challenges. Third, both learning by simulation and imitation can diminish the potential for social learning and collaboration. Lastly, contentious or sensitive subjects may be covered by both simulation and imitation learning, raising ethical questions (Gilbert et al., 2001; de Castell et al., 2014; Bandura et al., 1963; Davis, 1973).
However, simulated learning theory and imitation learning theory differ in certain ways. For example, digital gameplay experiences an epistemological change when player and game interactions are reinforced by bodily imitation as a central element of gaming, rather than being restricted to simulations of movements on a screen (Higgs, 2000).
Logic Model
The shift from traditional language learning and teaching to modern educational approaches has been supported by gamification and virtual simulation games, which harness the combined influence of various theoretical frameworks. These include New Learning Theory, Constructivism, Transformative Learning Theory, Imitation Learning Theory, Bandura's Social Learning Theory, and Simulation Learning Theory (Bandura et al., 1963; Davis, 1973). Each of these theories offers distinct perspectives on the learning process, together forming a strong theoretical foundation for understanding the effectiveness of gamification in language education. The degree to which learners intend to acquire new information determines the efficacy of imitation learning theory in the context of gamification and its central idea, online simulation games (Peterson, 2010 & Dhumal, 2015). The New Learning, Constructivism Learning, and Transformation Learning theories were selected as the basis for this qualitative study because they emerged from the literature review that offers a crucial understanding of Bandura's Social Learning, Simulation Learning, and Multiliteracies Learning theories.
The process of transformation of traditional education systems, especially, language learning into progressive ones by gamification is illustrated in the light of four primary pillars of the theoretical framework, such as psychological-based, technological-based, transformational-based, and pedagogical-based in Fig. 3.5.
The next section analyzes the methodology and design used in this study.
Methodology Design
This study investigates gamification's effectiveness in education in general and online simulation games on language learning in particular in undergraduate learners in the United States.
In the Chapter 3 Part 1, qualitative methods have been identified, chosen, and discussed thoroughly which led to propose two key research questions:
RQ1: What are the effects and consequences of using online gamification and its concepts in the classroom for language education in the United States?
RQ2: To what extent does using online gamification and its concepts transform anachronistic language learning in the United States?
The research will deploy qualitative methods using surveys, and semi-structured interviews to determine perceptions and reflections of language instructors, education technology integration experts, curriculum designers, and developers’ specialists about the effect of gamification in education.
In Part 2 of Chapter 3, the study will provide a deep description of qualitative methods including its epistemological assumptions, limitations, and its rationale of why this design is appropriate for the selected research questions. Qualitative methods description will also include the methods historical development, practical stance, philosophical assertions, strengths and weaknesses, and its challenges for researchers, as well as some of its related key concepts.
Qualitative Methods Approach: Overview
This research will employ a qualitative methods approach. According to Fidel (1993) qualitative methods approach has no precise, elegant, and universal agreed-upon definition. Similarly, Tylor and Trujullo (2001) contend many scholars has defined qualitative methods approach in different ways, such as: A qualitative methods approach is:
- “A field of inquiry in its own right” that “privileges no single methodology over any other” (Denzin & Lincoln, 1994, pp. 1, 3).
- “Drawn to a broad, interpretive, postmodern, feminist and critical sensibility” as well as to “more narrowly defined positivist, post positivistic, humanistic, and naturalistic conceptions of human experience” (Nelson, Treichler, & Grossberg, 1992, p. 4).
- “Emphasizing inductive, interpretive methods applied to the everyday world which is seen as subjective and socially created” (Anderson, 1987, p. 384).
Stake (2010) asserted that:
Many people who do qualitative research want to improve how things work. And empathy and advocacy are and should be part of the lifestyle of each researcher. However, focusing on doing good can interfere with understanding how things work and ultimately may weaken improvements by “blueprinting” the works too simply. Advocacy may endanger research by getting in the way of skepticism. (p.16)
According to Taherdoost (2022), the goal of qualitative research is to gather primary, first-hand textual materials and apply certain interpretative techniques to its analysis. Because of its exploratory nature, it is a helpful strategy for examining phenomena about which there is little readily available information. As a result, the qualitative method can produce fresh concepts, theories, and insights.
Fidel (1993) explained characteristics of the qualitative methods as “…noncontrolling, holistic and case oriented, about processes, open and flexible, diverse in methods, humanistic, inductive, and scientific” (p. 219). He claimed that because qualitative research explains human behavior and explains why it occurs, it is noncontrolling and nonmanipulative; it does not establish causation or effect or test theories that researchers may hold about human behavior; qualitative research is holistic and case-oriented because it provides academics with a detailed, descriptive, and comprehensive explanation of social activities occurring at a certain location and time; its approach is process-focused since it examines the dynamics of a process instead of its static features; qualitative research is flexible and open-ended since it does not rely on an apriorist conceptual framework that observable facts are supposed to fit into; Fidel further states that a project in qualitative research uses a range of methodologies because it uses several data-gathering techniques—a procedure called methodological triangulation. Bekhet and Zauszniewski (2012) argues that methodological triangulation has been shown to be helpful in confirming results, offering more thorough data, boosting validity, and improving comprehension of the phenomena under study.
The upcoming section reviews types of qualitative research.
Types of Qualitative Research Design Approaches
According to Hoover (2021), qualitative approaches come in several varieties. First off, the historical qualitative research technique is the most suitable choice for qualitative studies. It necessitates a close examination of historical individuals, occasions, and documents. The goal of historical research is to draw conclusions from past findings about the present and the future. Hoover states the second is phenomenology, a broad field of study. According to this research paradigm, the investigator seeks data that clarifies people's experiences wand perceptions of a phenomena. This paradigm acknowledges that everyone has a unique perspective on the world and that there is no one objective reality. The next is grounded theory; according to Tarozzi (2020, p. 3), grounded theory was defined as "...a general method of comparative analysis and a set of procedures able to generate a theory grounded in the data" by Barney Glaser and Anselm Strauss in 1967. Grounded theory is a way to collect fact-based evidence rather than trying to build a theory only from data (Khan 2014). Furthermore, Hoover claimed ethnography is a different kind of qualitative research which is the study of a particular group within a civilization. He states this study method requires researchers to fully immerse themselves in the culture they are studying. Finally, Hoover contends that another qualitative method is case study, which is used to investigate an individual, a community, an organization, or a group. Hoover further argues this kind of researcher may use a variety of data sources, including observation, interviews, and documents, to carry out the case study.
The following section provides a comparison and contrast of quantitative methods.
Comparisons and contrasts qualitative with quantitative methods
This study uncovered numerous similarities and differences between qualitative and quantitative methods. The origins of qualitative research design traced back to the modifications made in sociology and anthropology, however the qualitative line of inquiry has been referred to a few events, including postmodernism, post-positivism, natural inquiry, cultural investigations, constructivist paradigm, phenomenological investigation, and post-structuralism (Schwandt, 2001). Like quantitative research, qualitative research is rigorous, methodical, disciplined, and often provides a useful substitute for quantitative research methods (Randy & McKenzie, 2011). Both methodologies have these two characteristics. First, there is a focus on events that occur in real-world environments, or natural settings. Second, they entail investigating such occurrences in all their complexity (Leedy & Ormrod, 2010); however, a quantitative research design is to control the relationship that exists in a population between an independent variable and a dependent or consequence variable (Hopkins, 2008). Comparatively, qualitative approaches assume that there are several ways to construct and interpret only partially objective descriptions of the world. But deductive reasoning, which follows a logical progression from general to specific, is a foundational idea in quantitative research. To sum up, measuring tools and statistically represented data analysis are required for quantitative research. However, qualitative research permits a more flexible and open-ended method of evaluation (Randall et al., 2011).
According to constructivist perspectives, researchers often establish information rights in a qualitative study design (Creswell, 2003). Creswell further contends that plans for inquiry such as narratives, phenomenologist, ethnographies, grounded theory studies, or case studies were employed in qualitative design. He differentiated qualitative method from quantitative design by stating that quantitative study design, on the other hand, is defined and conceived differently; he states that in quantitative study, the researcher primarily applies post-positivist assertions about how knowledge evolves. Creswell goes on to say that examples of above claims include cause and effect reasoning, narrowing the focus to certain variables, hypotheses, and questions, using measurements and observations, and testing ideas. Experiments, surveys, and pre-made tools for data collecting that yield statistical data are common strategies in quantitative study methodology. Despite this, Bryman (2004) notes that quantification is often emphasized in the data collecting and analysis process in quantitative research. Thus, the topic of size or depth vs breath is the primary contrast between qualitative and quantitative research approaches (Sayer, 1992). There are more distinctions between qualitative and quantitative research than only what happens when statistical analysis is used instead of in-depth interviews, surveys, case studies, or tests of replication. In addition to the question of technique, the research also involves the choice of a research strategy that considers the politics or opinions that underpin the scenario under study (Randall, Gravier, & Prybutok, 2011). Unlike qualitative research methods approach, the quantitative research methods approach generally involves the systematic gathering of data about a situation, using stereotype quantifiers and statistical analysis (Hammarberg et al., 2016 & Andre et al., 1917).
Bryman (2004) distinguished between qualitative and quantitative research methodologies by focusing on three key elements: ontology, epistemology, and the relationship between theory and research. Figure 3. 4 depicts these three crucial elements in detail (Bryman, 2004).
Mehrad & Zangeneh (2019) contended that even though there is a lot of overlap between the methodologies and data types used in qualitative and quantitative research in social investigations, there is also a significant deal of hostility between the proponents of each research style. According to Mehrad & Zangeneh, the two approaches differ noticeably from one another, and these are shown as being inversely composed in Table 3.1.
The selection between qualitative and quantitative methods was a challenging task for the researcher of this study, however, the worthiness of qualitative research in the context of gamification in education over quantitative research had the researcher to choose the qualitative method for this research (Judith, 2023). The qualitative method’s suitability over the quantitative research is outlined in Table 3. 2.
Strengths and Limitation of Qualitative Methods Approach
According to Andre et al. (1917), a qualitative study methods approach has many strengths. First, it provides in-depth insights into the subjective experiences, perceptions, and behaviors of individuals involved in research. Second, a qualitative methods approach usually involves a multiplex theoretical structure and the systematic collection, administration, description, and interpretation of textual, verbal, or visual data. Third, Creswell (2003) claimed that a qualitative design conducts meticulous analysis without the help of routine numerical rules. Next, Fidel (1993) stated that the qualitative methods approach provides the most effective means of investigating human behavior; and researchers must exemplify the validity and reliability of their qualitative analysis and conclusions. Furthermore, Creswell states that qualitative methods approach is appropriate when the research goal is to explain a situation by relying on the perception of a person’s experience in each circumstance; he asserted it is considered exploratory because it is the most effective way to investigate complex phenomena when there is little information available about them. Finally, Fidel contends that the qualitative methods approach is not typically used to examine retrieval systems from a purely computational standpoint.
Although qualitative methods approach provides significance benefits to this research, the approach has several significant drawbacks. According to Justus (2006), one is that it is unable to ascertain if a system demonstrates a certain quality, such local stability. It is an inevitable drawback of the qualitative approach, and it is somewhat true of any modeling technique that doesn't make use of quantitative data on the system. Justus states that the extremely limited circumstances are another unique drawbacks of the qualitative methods approach. Through his research about the qualitative methods approach, Rahman (2016) found a few drawbacks with the qualitative technique as well; he stated that contextual sensitivity is occasionally overlooked in favor of stressing meanings and experiences in qualitative research methodologies. In Table 3.3, Andre et al. (1917) summarized the main benefits and limitations associated with qualitative research types.
Even though surveys and interviews have their limitations, their benefits are more suitable for qualitative studies than any other research approaches (Andre et al., 1917). The researcher tried to collect qualitative data through surveys and semi-structured interviews.
Qualitative Study limitations and Threats to Validity
Many researchers contend that qualitative methods face various limitations and challenges to their validity. Morse et al. (2002), for instance, argue that a fascinating shift has emerged from the rejection of validity and reliability in qualitative inquiry in the 1980s, moving the focus for ensuring rigor from the researcher's activities throughout the study process to the reader of qualitative examinations. Techniques for assessing validity and usefulness that are implemented after a study is completed have replaced those that are prioritized during the research process. Morse et al. argue that validity is still a useful concept for achieving rigor in qualitative research. They found that by including integral and self-correcting verification procedures throughout the course of the investigation, qualitative researchers can take back accountability for validity. Morse et al. claimed that qualitative research loses its usefulness and turns into fiction when it is conducted without rigor. As a result, validity and reliability are given careful consideration in qualitative research methods. Similarly, Maxwell (1992) found that to describe, analyze, and explain phenomena of interest, qualitative researchers depend, either explicitly or implicitly, on a range of understandings and associated forms of validity.
Qualitative Research Method Techniques
Hoover (2021) notes that a variety of techniques can be used to collect qualitative data. According to Hoover, in a single qualitative study, the following methods may be utilized:
- Interview: Researchers can interview individuals face-to-face and in-depth; by doing this, they are able to learn from the participants and better comprehend their experiences.
- Focus groups: Though they engage several people at once, focus groups are comparable to interviews. They offer an additional means of gathering feedback and conducting observational interviews.
- Observation: As a less direct approach to data collection than focus groups or interviews, observation calls for close observation of participants' actions and demeanor.
- Analysis of documents: In addition to electronic records, print documents can yield valuable information for researchers. To extract conclusions from the collection of connected documents, careful analysis is required (Hoover, 2021).
The next section justifies the use of qualitative methods in this study.
Justification for Using of Qualitative Methods in This Study
There are multiple justifications for employing qualitative methods in this research. Tylor and Trujullo (2001) stated that throughout the past 20 years, a growing number of academics have used qualitative approaches to examine various aspects of communication. They found that researchers have turned to qualitative methods for a variety of reasons. First, the acceptance of alternative approaches to the study of organizations; second, the limitations of positivist epistemology in quantitative procedures; and third, the expanding use of qualitative approaches in corporate communication.
To address the research questions, the study proposed method will be qualitative for many reasons. First, as the research seeks to develop a theory from the data related to gamification in education in general and online simulation games in language acquisition in particular, the researcher chose the qualitative method for the current study because it is based on the observations and evaluations of participants' sense of different events through qualitative surveys and interviews. Second, it takes a snap of the people’s perception in a natural setting (Suzuki& Kopala,1999; Khan, 2014). Third, it is interpretive and focuses on the meanings of human affairs as seen from different views, so their researchers are comfortable with its providing multiple meanings of the research. Next, it is personalistic and empathic which leads to understanding individual perceptions. Furthermore, the qualitative methods seek uniqueness more than commonality; and it honors diversity and seeks participants’ points of view, frames of reference, and values commitments (Stake, 2010). Stake also claimed that a qualitative study is suitable when research aims to explain a situation by relying on perceptions of people’s experiences in each phenomenon. Last, but not least, Creswell (2003) outlined his research findings on qualitative research methods that a qualitative method is a proper approach when a researcher attempts to comprehend correlations between study participants’ perspectives about a certain topic.
The Researcher Role
The researcher of this study has worked as a Doctor of Medicine for more than 8 years in Indira Gandhi Children Hospital, Kabul, Afghanistan, and he served as an assistant professor at a foreign languages institute in California, the United States for more than ten years. Currently, he works as an Education Services Specialist in California, the United States.
He holds a first professional degree of Doctor of Medicine from Nangarhar Medical School, Nangarhar, Afghanistan, and a Master of Art in Instruction Technology from the University of Massachusetts Global, formerly Brandman University, California, the United States.
Qualitative methods were selected over the quantitative methods by the researcher for pragmatic reasons. First, according to Fındıklı & Saygın (2023) & Daniel (1999), qualitative methods will generate the kind of data the researcher is looking for, a method commonly known as situational. Second, unlike a quantitative study, in the qualitative research, the researcher does not only collect data, but the researcher also analyzes and reports with different approaches, engages in the construction of the study, empathizes, sometimes experiences events with the participants, and interprets the results from the view he has obtained in this way. Third, the involvement of the researcher as an advocate, evaluator, and interpreter in the research may influence the study itself, so, the researcher is avoiding intrusion and risk to human subjects ethically. The researcher is often the main research instrument in the research.
Logic Model
The link between the theoretical framework, methodology, and data-collecting sources, as well as the data analysis approach, which includes triangulation components selected for the study's execution, is graphically illustrated in the logic model that follows.
This logic model aids in the organization and justification of the research. It will also make easier and faster for others to comprehend how this research study will be used.
To consider the conceptual frameworks that inform the transformative learning practice based on the transformation learning, constructivism learning, and new learning theories as discussed in the previous sections, the following are the overarching questions that guide this study:
- What are the effects and consequences of gamification in language learning environments?
- To what extent do gamification and its concepts transform anachronistic language learning environments into modern language learning environments?
The four main pillars of the theoretical framework—psychological, technological, transformational, and pedagogical—showcase the process of gamifying traditional education systems, particularly language learning, to create progressive ones. A constructivist gamification environment theoretical framework that seeks to revolutionize traditional educational institutions is shown in Figure 3.6, Logic Model, (Machmud et al., 2003).
Implementatoin Plan
Section 2 of Chapter 3 of this study provided a comprehensive overview of the qualitative methods approach, including its limitations and epistemological suppositions as well as why this design is relevant for the selected research topic. The practical position, philosophical claims, strengths and shortcomings, obstacles for the researcher, and some associated essential ideas were all covered in the presentation of qualitative methodologies.
In Chapter 3 Part 3, the study implementation plan, the study participants and sites, the data sources, data collection instruments, data collection procedures, chosen data analysis method, validation plan, methodologies triangulation, ethical concerns and implementation timetable are discussed.
The Study Participants and Sites
The study sample will be drawn from a population of participants, such as language instructors and educators from the Defense Language Institute Foreign Language Center, a large research-based institute in California, the United States and educators from Californian Army Nation Guard Civilian Education Department. Participants have worked full time. There will be a participants’ age limitation. Every participant must be older than eighteen (18) and shows no signs of mental impairment based on their ability to fulfill the duties associated with their jobs.
To reduce any further dangers pertaining to confidentiality, all recorded materials will be deleted after five years, upon final approval by the study committee.
All participants will have to be fluent in the English language, but English will not have to be their native language. Educators and language instructors will be the target population to participate in this research.
Participants will be recruited via a professional network, such as work emails, phone calls and Microsoft Team communication software. The researcher will make contacts with potential participants to respond to the survey questionnaires and semi-structured interviews’ questions. The researcher expected approximately 10-20 participants for the research. The final number of participants will be 15.
Data Collection Sources and Instruments
In this study, the data collection sources consist of:
- Surveys
- Interviews
The study uses surveys and semi-structured interviews as its methods, which are outlined as follows.
Surveys
This study uses surveys to gather data because, according to Marsland et al. (2001), the 1980s marked a shift toward qualitative survey methods in development projects, largely in response to the limitations of traditional quantitative questionnaires. Andre et al. (1917) defined surveys as a qualitative method that allows for data collection directly from individuals involved in the research through a set of open-ended questions presented in an organized manner. They argued that surveys are the most used qualitative technique because they enable the collection of information about a given situation through the formulation of open-ended questions that reflect the opinions, perceptions, and behaviors of participants in a qualitative study (Andre et al., 1917).
According to Andre et al. (1917) and Braun et al. (2021), surveys offer many benefits for qualitative research on gamification in education. First, surveys are highly representative of the entire population and are less expensive than other alternatives. Second, their findings prioritize qualitative research values and enhance the rich potential of qualitative data. Additionally, surveys provide significant advantages for qualitative researchers, especially with the availability of online delivery options. Finally, surveys are a dynamic and flexible method with profound applications, benefiting both researchers and participants alike (Andre et al., 2017 & Braun et al., 2021).
However, Fricker and Schonlau (2002) found that surveys also have several downsides. First, the reliability of survey data depends on the design of the survey and the accuracy of the responses provided by the participants. Furthermore, survey methods remain underutilized, and there is little methodological discussion available. Braun et al. (2020) also asserted that misplaced assumptions about survey data often lack in-depth narratives in the research.
In addition to surveys, the research also aimed to collect qualitative data through interviews.
Interviews
Interviews were also used in this study to gather data. The data collection and analysis for this study will be guided by semi-structured interviews, which will provide detailed insights into the respondents' perspectives and experiences with gamification in education, as described in Appendix C. Using this concept as a foundation, Cheron et al. pointed out forth three qualities in Figure 3.7 that encourage the use of the qualitative approach interview as a qualitative research method.
Cheron et al. (2022) claimed that the interview establishes a direct relationship between the interviewer and the interviewee, both subjects of the study; however, this association differs from an open conversation between comparable partners. They asserted that the interview is an objective, hierarchical conversation that is instrumental to a greater or lesser extent, in which the interviewer defines the framework according to their interests within the scope of the research.
The video below briefly reviews some core concepts and perspectives on the qualitative research interview process. It also serves as a useful prompt for significant considerations when conducting qualitative interviews, highlighting the need for preparation before the actual interview (Sonia, 2020).
Types of Qualitative Interviews
There are various types of interviews, including structured, semi-structured, unstructured, and focus group interviews, and they differ in how their questions are formulated (George, 2023). Table 3.4 outlines the key distinctions among the different types of interview questions (George, 2023).
Based on the characteristics of semi-structured interviews and the qualitative nature of this study, the researcher has also selected the semi-structured interview as the qualitative data collection approach.
Semi-Structed Interview
The researcher of this study will use semi-structured interviews, detailed in Appendix C, to collect qualitative data through open-ended questions because “…a pre-set and completely structured interview would not produce the most complete desired outcome” (Sonia, 2020, p. 52). A semi-structured interview is a qualitative approach that combines a specific set of open-ended questions designed to prompt discussion with the opportunity for the interviewer to explore specific themes further (Coryn, 2018). Similarly, Ayres (2008) defined the semi-structured interview as “…a qualitative data collection strategy in which the researcher asks informants a series of predetermined but open-ended questions” (p. 810). The semi-structured interview involves verbal communication with participants in a self-conscious manner and is based on a partially structured approach. Semi-structured interviews provide a blend of structured and unstructured interview types (Longhurst, 2012; George, 2023). The advantages and disadvantages of the semi-structured interview are discussed below.
Benefits and Limitations of the Semi-Structed Interview
In separate studies on qualitative semi-structured interviews, George (2023) and Sonia (2020) identified several advantages of this approach. First, it is considered one of the best qualitative methods because it combines elements of both structured and unstructured interviews, harnessing the strengths of each. Second, semi-structured interviews provide comparable, reliable data while allowing flexibility for follow-up questions. Third, they minimize distractions by enabling the design of a thematic framework that keeps both the interviewer and interviewee focused. Additionally, semi-structured interviews often yield more detailed insights from the interviewer than other interview types due to their open-ended nature. They typically offer a high response rate, as the interviewer can clarify questions to prevent misinterpretation by the interviewees. Moreover, according to George (2023), this method is particularly effective for studying gamification in education. George further noted that the interviews began with open-ended questions about the interviewees' initial interests in gamification and their broader career aspirations. He stated that the interviews concluded with additional open-ended questions to encourage deeper exploration of the research topic.
On the other hand, George (2023) and Andre et al. (1917) also highlighted several disadvantages of the semi-structured interview. First, its flexibility can lead to low validity, as it may be difficult to compare responses between interviewees depending on how much the interviewer deviates from the predetermined list of open-ended questions. Second, there is a high risk of research bias; the open-ended nature of the questions may prompt leading questions, introducing bias. Additionally, the semi-structured format allows interviewees to provide answers based on the interviewer's preferences, which can further skew results. Third, crafting effective open-ended questions for semi-structured interviews can be challenging due to the need to balance pre-planned questions with the spontaneity of interviewee responses. Arranging a semi-structured interview can also be time-consuming, and the predetermined answer options may lack the flexibility needed for some discussions.
The interviews will be conducted using Microsoft Teams, and recordings will only take place with the interviewees' permission. No interviews will be conducted without written and verbal informed consent from the participants. The semi-structured interviews will contribute to the specifications of gamification in education. Each interview will be transcribed by the researcher, who has signed a non-disclosure agreement found in Appendix C, prior to transcription. These interviews will serve as a significant means of engaging with participants from the study area. All collected data—encompassing the interviewees' experiences, thoughts, and emotions—will support the development of new insights into gamification in education (Ayres, 2008).
Procedures Followed
The detailed procedures carried out during the research process aim to maintain a systematic and thorough approach to data collection and analysis. The Institutional Review Board (IRB) approval form will be sought from the University of Illinois at Urbana-Champaign. Once approval is granted, the researcher will email participants within his professional contacts. Participants will receive a link to the survey via email, and their anonymity will be assured regarding both the surveys and the survey data. The confidentiality of the survey will also be confirmed. To improve objectivity and reduce potential bias, the researcher will employ several strategies: 1. The researcher will refrain from participating in the surveys, ensuring a clear distinction between data collection and analysis. 2. An external reviewer will be consulted to evaluate the survey questions and interview guide for any potential bias or leading questions. 3. Multiple coders will be involved in the data analysis to ensure inter-rater reliability and minimize individual bias in interpretation. 4. Throughout the study, the researcher will keep a reflexive journal to identify and address any personal biases or preconceptions that might influence the research process.
The qualitative interviews will be conducted using Microsoft Teams. Both the interviewer and the interviewee will be in separate rooms. As an introduction to the interview, the researcher will ensure that the interviewee is in a room with a closed door. The Microsoft Teams software will be used to record the interview with the participant's permission. Furthermore, after receiving final approval from the study committee, all recorded materials will be deleted after five years to mitigate any potential risks to confidentiality in the future. The timeline for data collection is outlined below.
Data Collection Timeline
The data collection for the study will be conducted in two phases. In the first phase, surveys will be utilized to gather data. In the second phase, semi-structured interviews will be conducted to collect more in-depth qualitative data.
In the first week of November 2024, the researcher will organize an informational session via Microsoft Teams with potential participants from the Defense Language Institute and the California Army National Guard Civilian Education Department, followed by the distribution of consent forms. During the second week of November 2024, participants will return their consent forms. Volunteers wishing to participate in the research must submit their completed and signed consent forms. Only those who return their consent forms will be allowed to take part in the study voluntarily. Once the consent forms are collected from the volunteers, the researcher will distribute the survey questionnaires in English through professional networks, such as email, to potential participants at the beginning of the third week of November 2024. The completed questionnaires must be returned within seven days.
In the fourth week of November 2024, the researcher will conduct semi-structured interviews with participants who have completed and returned the survey questionnaires. These interviews will be conducted in English via Microsoft Teams, and each session will be recorded with the participants' permission using Microsoft Teams software. Each semi-structured interview will last approximately 30 minutes. In terms of the data collection sequence, the survey data will be collected first, followed by the qualitative semi-structured data.
Validation and reliability of Finding
The data collection and analysis strategies in this study aim to address the key research questions, which include: What are the advantages and disadvantages of incorporating gamification, particularly online simulation games, into language instruction classrooms? To what extent does using online gamification and its concepts transform anachronistic language learning in the United States? Surveys, along with open-ended semi-structured responses, will be used to validate the qualitative data. To enhance the validity and reliability of the data, surveys and semi-structured interview responses from educators and language instructors, as well as methodological triangulation techniques, will be utilized as part of the study’s final output.
Methodological Triangulation
In this study, the researcher will use triangulation methods to ensure the validity and reliability of the findings. This study will triangulate data findings from qualitative surveys and qualitative semi-structured interviews related to gamification in language education. According to Bekhet and Zauszniewski (2012), methodological triangulation is the process of investigating a topic using multiple techniques. Likewise, Morse (1991) contended that “[m]ethodological triangulation is the use of at least two methods to address the same research problem. When a single research method is inadequate, triangulation is used to ensure that the most comprehensive approach is taken to solve a research problem” (p. 120). Bekhet and Zauszniewski claimed that methodological triangulation has been beneficial in strengthening validity, providing more comprehensive data, validating findings, and enhancing understanding of the phenomenon being studied. They further stated that methodological triangulation can be employed to improve the analysis and interpretation of findings. Bekhet and Zauszniewski also argued that when data are gathered from multiple sources, the researcher’s understanding of the various issues underlying the phenomenon under study is enhanced.
However, Denzin (1978) referred to methods triangulation as between-methods triangulation, explaining its justification as follows: "Observers can achieve the best of both while overcoming their unique deficiencies by combining methods," noting that the shortcomings of one method are often the strengths of another. Table 3.6 presents the main research questions along with the data collection instruments utilized for each.
Data Analysis
The data analysis will be based on critical theories, which Mellor (2013, p. 1) defines as "philosophical, political, and pedagogical responses to real-world circumstances aimed at reshaping the purposes, scope, aims, and delivery of education to foster cultural and social transformation through the progressive development of individuals." This theoretical framework will guide a multi-step analysis process: 1. Initial coding: Identifying key themes and concepts in the raw data. 2. Focused coding: Refining and categorizing themes to form a coherent analytical framework. 3. Theoretical coding: Investigating the relationships between categories to construct a theoretical model of gamification in language education. 4. Constant comparative analysis: Continuously comparing new data with existing codes and categories to ensure that the emerging theory remains grounded in empirical evidence. This comprehensive, theory-driven approach will ensure that the study's findings not only describe but also provide a deeper insight into the transformative potential of gamification in education. The goal of the data analysis will be to provide a valid means of reporting the evidence obtained and to present it in a way that is meaningful for the readers of this study. The analysis will include a combination of qualitative surveys and semi-structured interviews. Comprehensive participation will reflect the dependent variables of this study, including the number of participants who respond to the surveys and attend the semi-structured interviews. In this context, this dissertation's objective—transforming education in general and language acquisition in particular from traditional methods to progressive approaches by incorporating gamification mechanisms and principles into learning environments—will be achieved. Table 3.7 outlines the implementation timeline for the study.
Ethical Concerns
Participants’ confidentiality will be assured throughout this research, and participants will regularly be advised that all personal identification surveys and interviews responses would be anonymized or synthesized. The letter of Informed Consent will obey the US Department of Health and Human Services (HHS) federal guidelines which state that:
Information about a research project must be presented in such a way that enables each person to voluntarily decide whether to participate as a research subject. Thus, the information must be conveyed in language understandable to those being asked to participate as subjects in the research (HHS.gov., n.d., p. 1).
The researcher will ensure that ethics remained a top priority throughout the study, however Stake (2010) argued that most researchers view themselves as objectively seeking explanations and understanding. Stake points out that researchers often recoil at the suggestion that they might be biased or overly subjective. Stake argues that "research should be value-free." However, few people today believe that social researchers can work without reflecting their personal values (Stake, 2010).
However, according to Cheron et al. (2022), no participant has a direct relationship with the researcher that will represent a conflict of interest, such as a reporting relationship, contract, or any relationship with the researcher that may have imparted bias on the study. However, the biases arise from the different ways of seeing, being, feeling, understanding, and representing the scenario, both from the interviewer and from the interviewee. The bias starts when the researcher chooses the interview questions to be proposed to the interviewee (Cheron et al., 2022).
The study researcher will not intend to be a part of conflicts of interest or bias in the research, and he will not intend to configure the result of the study. That is why the researcher will not be involved in the surveys, however, he will use the surveys and semi-structured interviews data in the study analysis. In addition, the consent letter and all communications with participants will be braced the ethical elements of the study.
Logic Model
Gamification and its concepts have facilitated the transformation of traditional language learning and teaching into modern language education through the synergistic interaction of new learning theory, multiliteracies theory, constructivism theory, transformation theory, imitation learning theory, social learning theory, simulation learning theory, and qualitative grounded theory (Bandura et al., 1963; Davis, 1973; Tarozzi, 2020). Grounded theory and the reviewed literature served as the foundation for the development of imitation learning theory. The extent to which learners are motivated to acquire new information determines the efficacy of both new learning theory and imitation learning theory in the context of gamification and its central concept, online simulation games (Peterson, 2010; Dhumal, 2015). new learning, constructivism learning, and transformation learning theories were chosen as the basis for this qualitative study because the literature provides critical insights into social learning, simulation learning, and multiliteracies learning theories.
To gather information on gamification in education, the study's researcher will utilize qualitative methods and tools, including questionnaires for surveys and semi-structured open-ended inquiries. Thematic analysis will be employed to examine both qualitative surveys and semi-structured data. The study's outcomes will be determined by interpreting the data, and the results will be established through triangulating the data, as illustrated in the following logic model. Figure 3.8 presents a revised logic model for the qualitative study of gamification in education, along with qualitative data collection instruments, thematic analysis, interpretation, and the use of methodological triangulation to validate the qualitative survey and semi-structured interview data (Bekhet & Zauszniewski, 2012).
Conclusion
Chapter 3 of this study discusses the research methodology and design, the data collection instruments, the analysis of each data set, and the ethical considerations involved. To effectively address the research questions, the study will utilize qualitative methods, including qualitative surveys and semi-structured interviews, along with methodological triangulation. Adhering to the methods outlined in Chapter 3 is essential for ensuring the validity and reliability of the study. Each potential participant will be presented with the informed consent form before participating in the qualitative survey and semi-structured interview. The informed consent letter will comply with U.S. federal guidelines to minimize risks to human subjects involved in the study.
After selecting, analyzing, and establishing a theoretical framework for qualitative techniques, Part 1 of Chapter 3 presents two primary research questions:
- What are the impacts and outcomes of implementing online gamification and its concepts in language education classrooms in the United States?
- How significantly does the use of online gamification and its concepts change outdated language learning practices in the United States?
The research will employ qualitative methods, including qualitative surveys and semi-structured interviews, to gather insights and reflections from language instructors and educators regarding the impact of gamification in language education.
Section 2 of Chapter 3 offers a detailed overview of qualitative techniques, discussing their limitations and epistemological assumptions, and explaining why this design is appropriate for the chosen research questions. This discussion includes the historical context, practical perspectives, philosophical assertions, strengths and weaknesses, challenges faced by researchers, Institutional Review Board (IRB) considerations, and related key concepts.
Part 3 of Chapter 3 outlines the study's implementation plan, including information on participants, sites, data sources, tools, and procedures. It also addresses the methodology, validation strategy, chosen data analysis approach, triangulation techniques, ethical considerations, and the implementation timeline. The qualitative survey questionnaire and semi-structured interview questions are detailed in Appendices A, B, and C.
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