This paper aims to provide a critical analysis of the Criollo-C et al. (2021) mixed-methods study, “Exploring the technological acceptance of a mobile learning tool used in the teaching of an Indigenous language.” This analysis will include the study’s purpose, connections with existing research, sampling, study design, significant findings, future research, study strengths, and summary.
       This article was selected for analysis due to an interest in the preservation and revitalization of Indigenous languages using mobile educational technologies.
       The context for the Criollo-C. et al. (2021) study is Ecuador in 2019, where 18 Indigenous communities speak 14 ancestral languages. The authors argue that these Indigenous languages are the primary means of transferring culture and history to the next generations and are at risk of being lost. Kichwa, Spanish, and Shuar are the three constitutionally recognized official languages for intercultural communications in Ecuador (Cobo, 2015). The authors point to “racial discrimination, underestimation of [the importance of Indigenous] language[s], and the lack of interest and motivation of the new generation to learn” as underlying causes (p. 1).
       This study illustrates a pragmatic knowledge claim. Creswell, J. W. ( 2003, p 11) explains that pragmatic research “always occurs in social, historical, political, and other contexts.” This study also reflects an advocacy and participatory knowledge claim. Creswell, J. W. (2003, p. 9) argues that these researchers believe that the study “should contain an action agenda for reform that may change the lives of the participants” and “speak to important issues of the day.” The actions of the Criollo-C et al. team underpin the greater goal of decolonization.

Study Purpose
       The purpose of the study was clearly stated. Criollo-C et al. (2021) illustrated the primary objective of their research in the question: “Can the use of mobile learning applications in the learning of [the] Kichwa language be well-perceived by students?” (p. 2). The researchers stated their hypothesis: "The technology, through the mobile application Otavalo Rimay, can be well perceived by students for learning the Kichwa language.” Otavalo Rimay is the Mobile Learning (M.L.) application the researchers (with the assistance of the research participants) created. Unintended bias, which was not controlled for in the study, is apparent in the wording of the research question.
       The authors sought to mitigate the risk of Indigenous language loss with the opportunities afforded by the upward trends of mobile device ownership and M.L. technologies. The most significant phenomenon related to this research is that M.L. creates opportunities to learn from any location and that M.L. technologies may democratize the preservation of Indigenous languages.

Connections with Existing Research
       Criollo-C et al. (2021) identified a research gap in existing knowledge regarding M.L. application acceptance and its use in the learning of the Kichwa language (p. 1). The researchers cited that almost 77% of Ecuadorians owned a minimum of one smartphone (Alban & Sanchez, 2020), and student perceptions are vital to accepting ML technology in the educational arena (Almaiah & Jalil, 2014; Almaiah, Jalil & Man, 2016).
       The studies that were the most central to the Criollo-C et al. research were those that provided information guiding the development of the prototype of the ML application, including Grasso & Roselli (2005), Ahmad et al. (2018), and Dekhane & Johnson (2014). Also central to their research were the “Unified Theory of Acceptance and Use of Technology (UTUAT)“ (Nitsche, K., 2013) and the “Technology Acceptance Model” (Davis, F. D., 1985), both studies that informed the survey questions in parts two “ Perception of the use of mobile learning by users” and three “Questions related to UTUAT” of the study.

Sampling
The sampling process was not purposeful. The researchers sent an anonymous survey to students of one Kichwa language learning centre cluster in Otavalo, Ecuador, and 68 students responded. The percentage response rate was not identified. The researchers advised that they did not perform a “covert question and answer method” in their study, resulting in a potential for bias. The students who responded may have wanted to be included in the study. Controls for this type of bias would be the random assignment to a control or intervention group with students unaware of the purpose of the study.
 

Study Design
       Ethics approval for the anonymous survey was provided by the Dean of the School of Engineering and Applied Sciences at the University of the Americas in Quito, Ecuador.
       The Criollo-C et al. (2021) research used a mixed-methods approach and was primarily quantitative with a small, qualitative component. Suter, W. N. (2006, p. 41) describes quantitative studies as including testing a specific hypothesis stated in advance and providing measures that could be statistically analyzed. Creswell, W. J. (2003, p. 13) referred to strategies aligned with the quantitative approach to research as including “quasi-experiments and correlational studies.” both of which were present in the Criollo-C et al. (2021) study. Quasi-experiments lack the random assignment of true experimental designs (Suter, 2014, Ch. 10). Correlations were drawn between questions (Example: if student A answered positively on question 14, they would answer positively on question 15). At one point, the students were able to ask the researchers questions and provide feedback on improving the Otavalo Rimay application (a qualitative process).
       The procedure in the study was clear and complete. The quantitative survey began with socio-demographics and students’ current perceptions of using a mobile device to learn a language. Answers to these questions were in the form of a Likert scale of 1 – 5, with “1 = I strongly disagree, 2= I disagree, 3= I am so so, 4= I agree, and 5= I strongly agree”. At this point in the study, the participants were taught how to use the prototype of the ML application and then provided qualitative feedback to the researchers that informed the beta version of the ML application. The students used Otavalo Rimay again and then answered the final ten survey questions related to user perceptions. The final questions were also answered using the Likert scale. The researchers reported that they did not include an open question and recognized this as a limitation of their study.
       Suter, W. N. (2006, p 166) describes experimenter expectancy bias as creating “conditions favouring expected findings.” According to student feedback, the prototype was improved, which caused confounding of the independent variable. It would be difficult for the researchers to be impartial regarding the study’s outcome, given that they developed the mobile application included in the hypothesis. By asking the students to be involved in improving Otavalo Rimay, it would also be difficult for them to be impartial in their perceptions of the application, thus decreasing the study's internal validity. Criollo-C et al. reported that they did not ask questions that could provide information on negative perceptions or impacts of the use of their M.L. application. Suter, W. N. (2006, p. 166) describes unintended bias as the result of the wording of research questions.
       According to the raw data, 91% of the students surveyed had previous experience using a mobile application to learn a language. This information presents the potential for an alternate hypothesis, ‘the mobile application, Otavalo Rimay, can be well perceived for learning the Kichwa language by students who have previously used a mobile language learning application.’ 

       The most significant constructs studied were importance, improved performance, learning tools, ease, and fun in relation to the use of the ML application.
       The raw quantitative data is illustrated in Figure 5, p. 10. A scatter plot diagram and table (see Figure 6 and Table 2) illustrated the mean, median, and standard deviation of responses related to student perceptions of using ML (before their training on the prototype). Another scatter plot diagram and table (see Figure 7 and Table 3) illustrated the mean, median and standard deviation of responses to questions related to “perceived utility, [ease] of use, social influence, facilitating conditions, and perceived entertainment” after the students used the improved version of Otavalo Rimay.
       Criollo-C et al. (2021) quantitatively created two clusters, with Cluster 1 consisting of participants that responded the most favourably to the surveys on the use and acceptance of mobile learning (answering 3, 4, and 5 on the Likert Scale. Cluster 2 participants supported the use and acceptance of mobile learning but responded lower on the Likert scale regarding the impact of “social influence, facilitating conditions, and perceived entertainment.” The researchers used the two clusters to create a circular fan dendrogram to illustrate hierarchical ties (see Figure 12, p 19).
 

Significant Findings and Future Research
       The findings effectively answer the research question. For the most part, Criollo-C et al. (2021, p. 12) found positive responses to the use of M.L. and technologies in the educational context (p. 13, p. 15). The team reported that 78% of the students owned their mobile phones, 19% owned two devices, 34% had access to a data plan, and 97% had internet access at home. Thirty-one percent of students strongly disagreed that ML devices should be used during class hours.
       The researchers identified that communities also speak the Kichwa language in “Bolivia, Peru, Colombia, Chile, and northern Argentina,” and future studies could include those countries. This study could inform future research on ML and Indigenous language education.
       The authors suggest potential future research may include integrating accessibility features into the application, improving the design, and improving the study methods and procedures.
 

Study Strengths
       The Criollo-C et al. team conducted an intensive literature review. The researchers were generous and created Otavalo Rimay to test students’ receptiveness to using a mobile application to learn the Kichwa language. In the spirit of pragmatism, the researchers were focused “with - ‘what works’- and solutions to problems” (Creswell, W. J., 2003, p. 13).
 

Summary
       The Criollo-C et al. (2021) team was concerned with the loss of Indigenous languages, which are the means of ensuring that Indigenous cultures and history are preserved. The authors developed a mobile application for learning Kichwa and studied its acceptance by a small group of students from one language school in Ecuador. The study adds to the body of research on ML use in teaching languages as part of the broader dialogue of educational technologies and the intersection of Indigeneity with racism and colonization.
       The authors argue that “today’s education cannot and should not be limited to the traditional classroom; both students and teachers should have the opportunity to move, therefore fostering a collaborative education outside of the physical classroom (Criollo-C & Lujan-Mora, 2018a; Criollo-C & Lujan-Mora, 2018b).
 

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