=Paper=
{{Paper
|id=Vol-3902/10
|storemode=property
|title=Exploring AI-Driven RPGs for Managing Foreign Language Writing Anxiety (full paper)
|pdfUrl=https://ceur-ws.org/Vol-3902/10_paper.pdf
|volume=Vol-3902
|authors=Maria Goikhman
|dblpUrl=https://dblp.org/rec/conf/edu4ai/Goikhman24
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==Exploring AI-Driven RPGs for Managing Foreign Language Writing Anxiety (full paper)==
https://ceur-ws.org/Vol-3902/10_paper.pdf
Exploring AI-Driven RPGs for Managing Foreign
Language Writing Anxiety
An extended doctoral thesis abstract
Maria Goikhman1,2
1
University of Trento, Department of Psychology and Cognitive Sciences, Corso Bettini, 84 - 38068 Rovereto (TN), Italy
2
Fondazione Bruno Kessler, Via Sommarive, 18, - 38123 Povo (TN), Italy
Abstract
This paper is an extended abstract of an in-progress doctoral thesis. It explores how AI-driven text-based role-
playing games (RPGs) can alleviate Foreign Language Writing Anxiety (FLWA) in English and Italian L2 teenage
and young-adults learners. AI-powered RPGs offer a neutral, non-judgmental space for learners, potentially
reducing writing anxiety while enhancing Foreign Language Enjoyment through immersive role-playing. The
research also aims to develop methods for controlling AI language model output, such as enforcing CEFR level
constraints, to allow teachers to guide the learning process. In the upcoming research, mixed-methods approach
will be used, including pre- and post-tests with experimental and control groups to measure the impact of
AI-mediated RPGs on writing anxiety and performance. The findings will provide insights into how AI-mediated
tools can address emotional barriers to language learning.
Keywords
Foreign language learning, Foreign Language Anxiety, Foreign Language Enjoyment, Italian as foreign language,
English as foreign language, writing anxiety, educational technologies, AI for education, game-based learning,
writing skills development, text-based role-playing games, AI-mediated learning
1. Introduction
The process of foreign language acquisition involves both rational cognitive comprehension and affective
engagement. Emotions play a crucial role in language learning, influencing its outcomes. Positive
emotions, such as self-esteem and enjoyment, can enhance learning, while negative emotions, like
anxiety, can hinder it [1]. Foreign language learning can challenge an individual’s self-concept and
worldview, often inducing anxiety. To address this emotional challenge, Horwitz, Horwitz, and Cope
introduced the concept of Foreign Language Anxiety (FLA) in 1986, which they define as a combination
of self-perceptions, beliefs, emotions, and behaviors specific to language learning in a classroom
setting [2]. FLA often arises from students’ fear of communication due to anticipated difficulties in
understanding and being understood, as well as a lack of control over the communicative situation.
Cheng, Horwitz, and Schallert further differentiated between anxieties related to specific language
skills, identifying Foreign Language Writing Anxiety (FLWA) as a distinct issue [3]. [4] notes that
foreign language anxiety often has a greater impact on productive skills. Among the four aspects of
language learning, writing and speaking involve greater self-disclosure than reading and listening,
making them potentially more threatening to the student’s self-concept [5, 3].
With the growing integration of AI-assisted tools, virtual reality, mobile learning and other techno-
logical advancements into language learning, the traditional classroom environment is evolving. This
shift prompts researchers to investigate how technologies reshape the emotional dynamics of foreign
language learners.
Recent studies have explored the potential of AI tools to mitigate foreign language anxiety and
enhance language learning experience. AI-powered chatbots and speaking assistants have shown
1st Workshop on Education for Artificial Intelligence (edu4AI 2024, https:// edu4ai.di.unito.it/ ), co-located with the 23rd International
Conference of the Italian Association for Artificial Intelligence (AIxIA 2024). 26-28 November 2024, Bolzano, Italy
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promise in reducing FLA and improving willingness to communicate [6, 7]. These tools can provide non-
threatening practice environments, adapt to learners’ needs, and offer personalized immediate feedback,
suitable for self-regulated learning [8, 9]. However, a more immersive and interactive approach could
maximize the benefits of AI tools even further, not only adapting to learners’ linguistic needs but also
engaging them emotionally and creatively.
To bridge this gap, the current research relies on the experience of game-based learning and creative
storytelling. Game-based learning has shown positive effects on foreign language anxiety and enjoyment.
Studies have found that digital game-based learning can reduce FLA and increase motivation among
English as Foreign Language learners [10, 11], with high-anxiety learners particularly benefiting from
game-based learning [12]. Collaborative storytelling games with narrative grounding have been found
to enhance student engagement and creative language production [13]. Combining these ideas, the
current research proposes the concept of AI-Driven Role-Playing Games for language learning. These
games leverage AI to create dynamic, interactive storytelling experiences that offer learners a safe,
judgment-free space to practice language skills. In terms of Causality Orientation Theory from the
Self-Determination Theory framework [14], the final goal is to switch language learners’ attention
from the impersonal motivation characterized by anxiety concerning one’s competence and/or control
motivation pressure of mandatory education context to the the autonomy orientation, where individuals
act out of interest in and valuing of the activity process. By engaging learners in narrative-driven tasks,
this approach aims to reduce anxiety and enhance Foreign Language Enjoyment, providing a more
holistic solution to the emotional challenges of language learning. However, while this method can
offer students an enjoyable and engaging learning experience, the challenge remains in ensuring that
the AI-generated content can be effectively controlled to meet educational requirements. For teachers,
the ability to regulate the output, focusing on specific grammar and vocabulary and enforcing CEFR
levels, is crucial to guide the learning process, and future work will focus on achieving this level of
control.
2. Related Literature
2.1. Digital technologies and learners’ emotions in foreign language learning process
To understand the influence of recent advances in digital educational tools on Foreign Language Writing
and Speaking Anxieties, a thematic literature review is being conducted as part of this ongoing research.
It is focused on publications from 2021 to 2024 to capture the post-pandemic shift toward digital learning,
which significantly impacted the use of technology in education. The PRISMA framework was employed
to systematically identify 58 relevant articles and conference papers. The analysis revealed that the vast
majority of the studies reported positive or neutral effects of digital tools on language anxiety. Only
four papers highlighted negative perceptions or outcomes of technology use, while four others reported
moderate positive results. Young adults, particularly undergraduate students formed the majority of the
participants in these studies (n = 39). Fewer studies focused on school-aged learners (n = 8), middle-aged
learners (n = 2), and no studies included elderly learners. Interestingly, only nine articles considered
the perspective of teachers.
During the thematic analysis, the types of technologies used to address Foreign Language Anxiety
were classified into two broad categories: enhancing technologies and transformative technologies.
Enhancing technologies can be defined as those that complement and improve traditional methods
(e.g., online materials, learning platforms and videocalls instead of traditional textbooks and offline
classrooms), while transformative technologies fundamentally change the learning process, enabling
new forms of interaction and practice, such as AI assistants, avatars, and virtual reality.
In terms of psychological impact, although the search query focused on Foreign Language Anxiety,
many studies incorporated concepts from positive psychology, particularly Foreign Language Enjoyment.
Among the studies focused on enhancing technologies, a relatively balanced split was found between
those examining Foreign Language Anxiety alone (n = 11) and those also exploring motivation and
enjoyment (n = 17). In contrast, studies on transformative technologies were more likely to integrate
anxiety reduction with positive emotional outcomes, with 23 studies addressing both anxiety and
positive psychology concepts compared to 7 focused solely on anxiety. Technologies such as AI, VR, AR,
and avatars provide students with new ways to interact with the language and with each other, which
were not possible in traditional classrooms. The ”value added” of transformative technologies lies in
their novelty and their potential to fundamentally broaden the educational experience. Innovative
technologies are seen as a source of emotional uplift, pushing the researchers to consider not only their
effect on anxiety reduction, but also on increasing positive emotions.
2.2. Positive psychology in foreign language learning
Positive psychology (PP) has emerged as a significant influence in foreign language acquisition research
and teaching practices. This approach emphasizes the cultivation of positive emotions, traits, and
supportive institutional environments in language education [15]. Building upon earlier concepts like
the humanistic movement and affective filter, PP offers new perspectives on motivation and learner
experiences, positioning positive emotional states as crucial drivers of success in language learning
[16]. Since its introduction to foreign language acquisition in early 2010s, PP has gained substantial
recognition, leading to a growing body of research within applied linguistics [17].
Research has explored various positive factors such as engagement, enjoyment, resilience, and
well-being in language learning contexts [15]. A key focus of PP interventions is to foster states like
flow, hope, and optimism, which contribute to enhanced linguistic progress and reduce the impact
of negative emotions, including FLA [17]. Recent research has begun to integrate PP principles into
technology-enhanced learning environments, including game-based learning and AI-driven educational
tools, to create more immersive, enjoyable, and emotionally supportive learning experiences.
2.3. Game-based learning
Research indicates that game-based learning can effectively reduce FLA, increase enjoyment and
enhance language learning outcomes. Studies have shown that digital games can lower affective
barriers, increase willingness to communicate, and improve motivation in language learners [10, 18].
Online simulation games and problem-based gaming approaches have been found to reduce FLA levels
across different anxiety level groups and improve vocabulary learning, particularly for moderate and
high-anxiety students [19, 20]. Interestingly, high-anxiety learners’ gaming performance positively
correlated with their learning performance, suggesting that game-based learning may be especially
beneficial for these students [12]. In addition to these benefits, gaming technologies have shown promise
in preventing and correcting language anxiety among teenage learners, a group particularly prone to
affective barriers in language learning [21]. Game-based learning can engage students by blending
entertainment and education, offering dynamic learning experiences that capture attention and enhance
emotional involvement.
2.4. AI for role-playing and storytelling
While current studies focus on role-playing games conducted in the players’ native languages, where
the challenges of language acquisition and foreign language anxiety are certainly not a factor, research
has already begun to explore the potential of AI in enhancing role-playing games, particularly in
well-established frameworks like Dungeons & Dragons (D&D) [22, 23, 24]. Studies have focused on AI
dungeon masters, where language models are used to generate story prompts, manage game mechanics,
and facilitate gameplay interactions [22, 23]. AI game masters are found capable of producing engaging
and believable fantasy narratives, even if they still fall short in terms of consistency, adaptability, and
the nuanced decision-making skills of human dungeon masters [22]. Other areas of research focus on
the creative applications of AI for storytelling and role-playing. [25] examine how AI-based characters
can be used to inspire creative writing, providing dynamic prompts and character arcs that assist players
or writers in co-creating narratives. In addition, research into interactive narrative environments
demonstrates how AI can create immersive story worlds, offering players personalized quests and
interactive dialogue through a combination of knowledge graphs and language models [26].
3. Research Objectives
This research aims to investigate the effectiveness of AI-mediated text-based role-playing games in
reducing Foreign Language Writing Anxiety among English and Italian L2 learners, considering its
effect both on learners of global and a locally significant language. The study will focus on teenage
and young-adults students. While young adults would normally have coping strategies to deal with
possible FLA, teenagers are more likely to experience emotional obstacles [21], being more vulnerable
to self-concept threats that can occur during writing and speaking in foreign language. By offering a
judgment-free, narrative-driven environment, AI RPGs are expected to not only reduce anxiety but
also enhance Foreign Language Enjoyment (FLE) through collaborative creative storytelling. The study
will also explore how teachers can interact with AI tools to guide the learning process, particularly by
controlling the AI’s output to adhere to linguistic constraints such as CEFR levels requirements and
more specific grammar and vocabulary themes.
The study addresses two main research questions:
3.1. RQ1: Controlling the output to meet educational requirements
How can the output of AI language models be controlled to meet educational requirements, such as
enforcing both CEFR-based and chosen specifically by teacher grammar and vocabulary constraints?
This exploratory research question focuses on understanding how AI language models can be adapted
to align with pedagogical goals. It includes following sub-questions:
• What is the current accuracy of AI models in generating grammatically correct Italian text?
• To what extent can AI models follow linguistic constraints provided in prompts, such as grammar
and vocabulary?
• How can prompt engineering or fine-tuning techniques improve the enforcement of these con-
straints?
• What strategies can ensure that AI outputs meet specific educational goals, allowing teachers to
effectively guide the learning process?
3.2. RQ2: AI RPG influence on Foreign Language Writing Anxiety
How do AI-mediated text-based RPGs influence foreign language writing anxiety in English and Italian
L2 learners compared to traditional writing exercises?
This research question seeks to explore how AI-driven RPGs can create a more supportive environment
for reducing writing anxiety, fostering enjoyment, and improving language proficiency. Specific sub-
questions include:
• What features of AI-mediated text-based RPGs contribute most to anxiety reduction?
• How do students’ engagement and motivation differ between AI-mediated RPGs and traditional
exercises?
• How does AI feedback in RPGs compare to teacher feedback in terms of its impact on writing
anxiety?
4. Methodology and Future Work
This study adopts a mixed-methods approach and is structured into two lines of development that align
with the two research questions.
4.1. Track 1: AI Model Output Control
The first line of development, addressing RQ1, focuses on exploring how the AI-generated content can
be controlled to meet specific linguistic constraints relevant to language learning, such as CEFR levels
and grammatical accuracy.
4.1.1. Pilot Study: A1-Level Constraints
As part of this track, a pilot study is currently being conducted to evaluate how well various language
models can adhere to A1-level constraints in English, Italian, and Russian as formulated by [27], [28]
and [29]. The models are tested on their ability to generate content that aligns with specific grammar
and syntax requirements, at this point excluding vocabulary constraints. The three languages have
been chosen to compare the language models performance on the languages that are, firstly, differently
represented in training corpora, and, secondly, have different levels of constraints specificity. The pilot
study involves feeding the models prompts designed to elicit A1-level responses in Italian, English, and
Russian. These prompts include both specific communicative tasks based on CEFR A1 requirements and
instructions constraining grammar and syntax usage to the A1 proficiency level in all three languages.
The generated outputs are being evaluated both by language models and by human experts using
CEFR-based rubrics to assess how accurately the models maintain A1-level constraints. Preliminary
findings suggest that while the models are capable of generating grammatically correct sentences,
in Italian and in Russian they struggle with consistently staying within specific A1-level grammar
constraints. Moreover, when models are asked to self-evaluate their outputs by assigning true/false
labels to determine whether they meet the given constraints, their performance is notably poor. Even
advanced models like ChatGPT 4o struggle with this task, particularly when asked to give direct answers
without offering a “chain of thought” explanation.
4.1.2. Enhancing Linguistic Control in AI-Generated Text
Building on the results of the pilot study, the language models will be prompted to follow linguistic
constraints of different CEFR levels and its performance will be evaluated. At the same time, feedback
from teachers’ will be collected to define more neccessary constraints and instruments to meet their
needs. Based on the teachers’ input, the prompts and models will be adapted to ensure better adherence
to the constraints, refining the AI’s performance before proceeding to the second phase.
4.2. Track 2: Experimental Study of AI RPG effect on FLA
This line of research aims to investigate AI-mediated test-based role-playing games in reducing writing
anxiety among English and Italian L2 learners, addressing RQ2.
4.2.1. Pilot Study: Comparing Storyteller and Educator Avatars’ Effect on FLA and FLE
Before the main experimental phase, a pilot study will be conducted, leveraging an existing tool for
creating AI conversational agents. The within-subject study will involve University of Trento students
who study English as foreign language and are currently at a B1 level. Using ConvAI, a tool for creating
AI conversational agents, the experiment will compare the effects of two approaches: one avatar will be
acting as a traditional language tutor assigning writing tasks, and the other as an impersonal narrator
engaging in role-playing based on students’ interests. Pre- and post- tests will be administered to
measure the levels of Foreign Language Anxiety and Foreign Language Enjoyment. It is hypothesized
that interactions with the narrating agent will provoke less anxiety and more enjoyment than those with
the educator. One of the expected challenges is how to urge students to produce more written output
in the storytelling mode, as since players can limit themselves to very short phrases with minimal
interaction, they may stay in a more passive, reading-focused mode while the AI game master continues
advancing the story.
4.2.2. Pre- and Post-test study on English FLWA
The study will involve English L2 learners, focusing on middle and high school students. Experiments
is planned for two months, with one 45-minutes session per week. Participants will be divided into
experimental group, engaging on a weekly basis in AI-mediated text-based RPGs and control group,
completing traditional writing exercises without AI support. Both groups will complete pre- and
post-tests to assess changes in writing anxiety and language proficiency. The Foreign Language Writing
Anxiety Scale (FLWAS) [30] will be used to measure participants’ anxiety levels before and after the
interventions. Participants’ written output will be assessed using a CEFR-based rubric to measure
proficiency gains. Additionally, semi-structured interviews and surveys will explore participants’
experiences with AI-mediated RPGs and their perceptions of how the game format affected their anxiety
and enjoyment. Teachers will provide qualitative feedback on how well the AI tools support language
learning and meet educational goals.
4.2.3. Comparative study of AI RPG effects on English and Italian FLWA
In order to broaden the results and explore potential differences across age groups and language contexts,
a follow-up mixed-methods comparative study with university students learning both English and
Italian will be conducted. During a 4-weeks intervention with one 45 minutes session per week, an AI
game-master will use the same narrative plots both in Italian and in English, with only difference being
the language. FLWA questionnaires and CEFR-based writing tasks will be provided as pre- and post-test
assessments. As the number of international students studying Italian in the University of Trento is
not enough to achieve a sample size sufficient for statistically significant conclusions, the study will
supplement the pre- and post-test assessment results with the thematic analysis of in-depth interviews
after the intervention. This approach allows for a qualitative exploration of students’ experiences
and perceptions, aiming to identify potential differences in Foreign Language Writing Anxiety across
languages.
5. Conclusion
This research contributes to the emerging field of AI-mediated language learning tools, offering a novel
approach to reducing Foreign Language Writing Anxiety through interactive, narrative-driven tasks.
By integrating AI and role-playing games, this study aims to create a more supportive and enjoyable
language learning environment that fosters Foreign Language Enjoyment and motivation. The use
of AI in this context offers unique opportunities for providing students with judgment-free practice
environments that can significantly enhance their learning experiences.
The development of methods to control AI-generated content according to specific linguistic con-
straints, such as CEFR levels will provide educators with tools to tailor instruction to learners’ proficiency
levels, with this approach not only supporting language development but also enhancing the role of AI
as an adaptable teaching assistant.
Finally, applying AI to create combination of emotional and linguistic support has the potential
to transform language learning by bridging the gap between personalized instruction and scalable
technology.
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