AI Action Research practice

Literature Review

Question 1

What is the impact of using the Mizou AI voice-activated tool on reducing students' anxiety and improving their WTC in the target language?

Question 2

What is the impact of using the Mizou AI voice-activated tool on the quantity of students’ target language production as measured by word count?

Question 3

What is the impact of using the Mizou AI voice-activated tool on the complexity of a student's target language production as measured by the use of varied sentence structures? 

What does CALL stand for?

Computer Assisted Language Learning

Computer Assisted Language Learning does…

the use of computers and digital technologies to support and enhance the learning and teaching of languages while maintaining the safety

What does (FERPA) stand for?

Family Educational Rights and Privacy Act which is a aw the protects the privacy of students records

Willingness to Communicate (WTC)

defined as a learner’s readiness to initiate communication in a second language at a particular moment with specific people and is influenced by factors such as their confidence, anxiety and motivation to use the second language also known as L2 which in this study the L2 is Spanish

MacIntyre et al., 1998

describes WTC as a complex interplay of cognitive, affective, and social variables that affect language learning and communication initiation.

MacIntyre 2007

expanded the concept of WTC, emphasizing the role of individual differences in shaping communication readiness and engagement in second language acquisition. WTC fluctuates with situational and psychological factors; learners are more likely to engage in communication when they feel psychologically prepared and experience low stress and anxiety, which makes the learning environment critical to promoting successful language use.

Stephen Krashen’s 1982 Affective Filter Hypothesis

suggests that emotional factors such as anxiety, motivation, and self-confidence can influence language acquisition by creating a mental barrier that affects the learning process. A low affective filter allows for better language input and acquisition.

Dulay & Burt, 1977 affective filter (need better definition

is a concept that extends Krashen's Affective Filter Hypothesis, highlighting how emotional and social factors can obstruct or facilitate language acquisition. It emphasizes the impact of learners' attitudes and feelings on their ability to process and acquire a new language.

Han 2020

found that students who engaged in additional, low-pressure speaking practice demonstrated improved self-confidence and reduced anxiety, which in turn encouraged more frequent use of the L2. These studies highlight the importance of creating conditions that reduce anxiety to optimize WTC. This work underscores the significance of conducive learning environments in fostering language acquisition and willingness to communicate (WTC) in second language learners.

Krashen, 1982, p.31

literature suggests that a supportive, low-anxiety learning environment allows students to learn from their mistakes without judgment, thereby reducing anxiety and increasing motivation, thereby assisting students with L2 learning

Henry and Thorsen 2018

examined the importance of a positive teacher student relationship in promoting language development, emphasizing its influence on learners' motivation and confidence in using the target language. These studies suggest that when students feel supported, respected, and free of judgment, they are more willing to take risks in communication.

Han, 2020; Kim and Su, 2024; Peng and Liang, 2025; Zang et al, 2024

Although the studies examined different student populations and AI platforms, a common pattern emerged: students reported lower anxiety, greater confidence, and increased participation in communication activities

Peng and Liang 2025

investigated the effects of AI on language acquisition, highlighting how technology facilitates interactive learning environments and enhances student engagement in language tasks.

Kim and Su 2024

explored the role of AI in personalized learning, showing that tailored feedback through AI tools can improve students' language skills and foster adaptive learning strategies. found that students who interacted with AI chatbots experienced lower levels of anxiety and higher perceived communication competence

 Han 2020

examined the integration of AI in educational settings, focusing on its impact on student performance and attitudes toward learning, and found significant improvements in engagement and feedback responsiveness. AI chatbot interactions improved students’ confidence and emotional responses toward language learning, thereby reducing anxiety.

Zang et al. 2024

highlighted the influences of AI in enhancing collaborative learning experiences, demonstrating that AI-supported group activities can lead to improved communication and teamwork skills among students.

Kukulska-Hulme & Lee, 2020

focused on mobile-assisted language learning, revealing how AI can facilitate language acquisition through flexible and accessible learning environments. They demonstrated that mobile technologies integrated with AI can enhance learner engagement and provide immediate feedback, fostering a more personalized learning experience.

Xiudi Zhang 2025

found that university students who used AI speaking tools demonstrated measurable improvements in pronunciation, grammatical accuracy, and overall fluency.

Gass & Selinker, 2008; Joker, 2021

The use of AI is still developing, and inaccuracies in feedback can occur.  According to contemporary applied linguistics, frequent errors in EFL production are often the result of Negative Language Transfer, where the learner's native language interferes with the target language.

The city population

 113,458

Student population at the school

2,923

White Population at the school

36,000

Latino population at the school

33,000

Asian population at the school

14%

African American population at the school

4%

Native American population at the school

2%