Educational Games and the Potential of AI to Transform Writing Across the Curriculum

Abstract

Game-based learning has emerged as a promising tool in education, particularly for students with disabilities. Educational games can significantly enhance student engagement, motivation, and skill development across subjects by providing personalized learning experiences and immediate feedback. New developments in generative AI offer opportunities to embed advanced features into educational games. Drawing on focus group insights from educators and families (N = 21), we highlight the key features that teachers and parents want to see in educational games. We then discuss how generative AI can potentially supplement and ensure that those key features are included. A case study of applying these features to a game-based tool to support writing across curriculum is provided. This article offers a glimpse into the informal exploration phase of a larger design research project aimed to develop a proof-of-concept for an intervention that builds a bridge between AI, educational games, and scaffolding STEM content for students with all abilities.

1. Introduction

Children of all ages have a high interest in gaming. A recent report indicates that 79% of children under 18 play video games (Entertainment Software Association, 2024). Most users agree that video games can improve cognitive skills (73%) and provide accessible experiences for players with different abilities (74%). In recognition of youth’s interests in gaming (which typically refers to playing games for entertainment), a concept of game-based learning has been developed, which involves using games as an instructional tool to support specific knowledge and skills towards various educational goals (Plass et al., 2020; Prensky, 2001). One of the defining qualities is the use of game elements, competition, and immediate incentive systems to motivate and engage the player for extended periods, regardless of the game format (Plass et al., 2015). Plass et al. (2015) distinguish cognitive, affective, behavioral, and sociocultural engagement that support the effectiveness of educational games. Games can be powerful tools to engage students with and without disabilities and enhance student outcomes (Jabbar & Felicia, 2015; Tlili et al., 2022). Existing research supports increases in (a) engagement and motivation (e.g., Lamb et al., 2018), (b) personalization and differentiation (e.g., Antonova & Dankov, 2023), (c) immediate feedback (e.g., Rocha et al., 2019), and (d) practice and repetition (e.g., Ansari et al., 2020). This approach can engage students who struggle in traditional learning contexts, helping them to persist and complete a task in an environment where they believe they will be successful (Marino et al., 2014). Furthermore, games can “shorten feedback cycles to maintain engagement, give learners low-stakes ways to assess their own capabilities, and create an environment in which effort, not mastery is rewarded” (Su & Cheng, 2015, p. 270). Games can enhance access to content and further reinforce skills in need of remediation (Basham & Marino, 2013).

Educational games encompass various forms, including board games (online or off-line), card games and quizzes, digital and video games (using both computers and mobile devices), simulations, and virtual worlds, each serving distinct purposes. Serious educational games are specifically designed for K-12 educational content rather than pure entertainment. These games have learning goals targeting specific knowledge and skills, often simulating real-world scenarios, along with features that support engagement, feedback, problem solving, and collaboration (Vallett et al., 2014). Regardless of the format, game-based learning has shown to be effective in STEM areas. Recent meta-analyses found moderate effects on cognition, motivation, and behavior (Arztmann et al., 2022; Barz et al., 2023). Games have been used to present science concepts, visualize scientific phenomena, explore unreachable locations, and provide additional scaffolding (Klopfer & Thompson, 2020). With the rapid development and dissemination of technology, the use of digital games for STEM education has increased. A moderate significant positive effect size has been reported for digital games as compared to other instructional methods (both traditional and multimedia), suggesting the effectiveness of digital games in improving students’ academic performance in STEM education (Wang et al., 2022). Several other studies using game-based learning in STEM included students with disabilities, demonstrating that those students benefit from these interventions as much as typically developing learners (Arztmann et al., 2022). Reviewing the existing literature is an important first step in the preliminary informed exploration phase of a design research study focused on developing an AI-enhanced technology-based intervention incorporating educational games to support writing across the curriculum for students with various abilities and needs (Bannan-Ritland, 2003; Evmenova & Regan, 2023).

1.1. Including Students with Disabilities in Learning STEM Through Games

Game-based interventions have been found to be more effective than the traditional instruction for improving phonological awareness, word recognition, and vocabulary skills, as well as the writing skills of students with high-incidence disabilities, including learning disabilities (Ansari et al., 2020; Görgen et al., 2020; Al Otaiba et al., 2019; Rocha et al., 2019; Ronimus et al., 2019). They have been used to support social skills training for children with autism (Jiménez-Muñoz L. et al., 2022; Ke & Moon, 2018). Increased engagement and motivation, along with improvements in learner outcomes, were also reported for learners with intellectual and developmental disabilities (Koh, 2022). Serious games support students with attention, memory, executive functioning, and developmental disabilities by scaffolding their learning with increased motivation, independence, autonomy, and improved self-esteem (Papanastasiou et al., 2017). However, the research on using games designed specifically to support learners with disabilities in STEM areas is somewhat limited, with just a dozen of studies focusing on these areas (Tlili et al., 2022).

Games such as Alien Rescue, You Make Me Sick!, and Prisoner of Echo were developed and tested to provide inquiry-based learning opportunities aligned with the National Science Education Standards and remove barriers for learners of different abilities and needs using Universal Design for Learning (UDL) guidelines (Marino, 2009; Marino et al., 2013; Marino et al., 2014). These games increase accessibility and the engagement of learners during the process of scientific discovery. Students prefer tracking clues, testing hypotheses, and participating in scientific exploration while relying on such features as text-to-speech, a virtual dictionary, and explicit instruction through animated tutorials (Marino et al., 2013). Thus, learners work towards a goal, choosing actions and experiencing the consequences of those actions along the way in a supportive environment. In fact, students with disabilities benefit from this technology more than their typically developing peers (Marino, 2009). This research highlights the increased engagement with video games as compared to alternative print-based materials (Marino et al., 2014). But creating effective interactive experiences that motivate and actively engage students in the learning process through immediate feedback and layers of support is not an easy task (Marino & Beecher, 2010).

The benefits of using engaging educational games in STEM learning, as compared to teacher-delivered lectures supported with paper-based laboratory exercises, are great especially for students with disabilities. For example, a study with 11th–12th grade students with severe emotional and behavioral disorders in a public day high school demonstrated improvements in students’ problem-solving skills, increased time-on-task, as well as a reduction in students’ negative emotional responses (Ritson, 2019). The increased interaction and immediate feedback were highlighted as most beneficial by teachers and students, which was corroborated by prior research (Jabbar & Felicia, 2015). Video games have also been found to encourage students’ participation in scientific discussions that led to higher-level content specific vocabulary used in everyday classroom discussions when the game was introduced as an intervention (Marino et al., 2013).

Digital-based interventions, including educational games, have shown to be effective for all students (Byun & Joung, 2018), including those with mathematical learning difficulties (Benavides-Varela et al., 2020). One specific study explored a virtual environment comprising 18 games that covered various mathematics topics in a playful setting for children between ages of 7–10 with dyscalculia. Web-based pre-algebra games were found to be effective for middle school students with learning disabilities (Ke & Abras, 2013). All three games prompted engaged learning and necessary scaffolds by externalizing mental visualizations or calculations via visual cuing and visual feedback. Game Building Workshop was also used to develop computational thinking skills in adolescents with autism spectrum disorders while playing five games with increasing complexity levels (Munoz et al., 2018).

Indeed, educational games can be a powerful tool for modern educators. These games are not only engaging, but also make learning feel less like work, providing a fun and interactive way for students to acquire new knowledge and skills (Young et al., 2012). Far from being a distraction, educational games offer a unique access to content, encouraging students to engage with learning activities in ways that traditional methods might not (Prensky, 2003; Sánchez-Mena et al., 2017). Moreover, these games can foster important social-emotional benefits by promoting social interaction, cooperation, and resilience, helping to build a sense of connectedness among students (Plass et al., 2020). For teachers, educational games offer the convenience of individualized instruction, allowing them to efficiently support students at varying skill levels, provide immediate performance feedback, and use data to inform instructional decisions. By incorporating games into tiered support systems and progress monitoring, educators can better track student progress and adapt their teaching strategies to meet the diverse needs of their students (Marino & Beecher, 2010; Regan et al., 2023). However, the success of these interventions depends on the game’s features (Tlili et al., 2022).

1.2. Important Features in Educational Games

Games are not engaging by default; they need to be thoughtfully designed to be effective and motivating. In a literature review, Tlili et al. (2022) identified several factors that can impact the effectiveness of game-based learning for students with disabilities, including the type of game, the level of customization, and the level of teacher (and/or parent) engagement. Based on the Activity Theory framework, existing studies on game-based interventions were reviewed according to the six components of an activity: subject (learners), object (targeted skills), tool (technology), rules (implementation procedures), community (learners, educators, and parents), division of labor, and learning outcomes. As a result, the analysis of the design and implementation of game-based learning for learners with disabilities revealed the importance of an accessible cross-platform design that promotes social interaction and collaboration among learners with disabilities. The need for educators (and parents) to use and analyze data regarding learners’ interactions with the game was also noted in order to support active engagement, enjoyment, and learning outcomes. Learners with disabilities, along with their community (e.g., educators, parents), should be involved in the design and implementation of game-based learning interventions. Games at different levels of difficulty aligned with learners’ characteristics can further increase attention and motivation.

Our own review of the literature has identified some specific design features that are important for increasing a user’s competency and skill acquisition. Firstly, the game narrative should be designed carefully in an attractive setting to keep learners immersed in the plot (e.g., Beserra et al., 2014). A motivating storyline may include real-life scenarios, dilemmas or massive problems, and hidden messages or elements of surprise (e.g., Tang, 2020). Secondly, choosing an avatar allows for players to identify themselves as part of the game (e.g., Annetta, 2010). Thirdly, immediate feedback (e.g., words of affirmation, balloons, smiley faces) along with incentives (e.g., increasing or decreasing objects, coins, stars, points, gaining access to magic powers and others), including for partial success, are important (e.g., Barz et al., 2023). Fourthly, reducing the complexity of instructions, using visually attractive animations and graphics, as well as graphic characters, increases learning motivation (e.g., Benavides-Varela et al., 2020). In fact, most students with disabilities will need to request adult mentors to orally read and explain game introductions if not supported with visuals and text-to-speech (e.g., Ke & Abras, 2013). Fifthly, it is also recommended to locate the mechanics in a playful environment, to avoid using too many potentially distracting graphics unrelated to the instructional purposes, and to present simple and consistent interfaces acting as a background for the game activities (Benavides-Varela et al., 2020). Sixthly, learning from repeated practice (e.g., Mohd Syah et al., 2016) as well as engaging with other players is reported as a preferred feature in several studies (e.g., Israel et al., 2016). Seventhly, regardless of the game type (e.g., role-playing, strategy games, simulations, adventures, action games, puzzles), it is important to build in adaptive leveling, where tasks have different levels of difficulty that automatically adapt to the player’s abilities based on his/her performance (e.g., Tang, 2020). Finally, it is crucial to not only design playful and engaging games for students to improve targeted skills, but also to design user-friendly mechanisms to involve teachers and caregivers to effectively evaluate student play and use data-driven decision making.

To promote scientific engagement and learning for students with disabilities that may not be possible otherwise, STEM-focused games should carefully consider content complexity and abstract representation throughout the game (Israel et al., 2016). Connecting content to everyday lives is another important consideration during game design. It is very time-consuming to develop educational games incorporating all the beneficial features (Ritson, 2019). Time constraints, cost, and the availability of appropriate games have been reported as some of the reasons for limited research in this area (Papanastasiou et al., 2017). Some of these barriers can be overcome with the development of generative artificial intelligence (AI) tools.

1.3. Generative AI to the Rescue: Potential Use

The emerging technology of generative artificial intelligence (AI) has taken the world by storm and has already shown promise to support learners with disabilities (Barua et al., 2022; Carg & Sharma, 2020; Zdravkova, 2022). It has been defined as a “disruptive technology with the potential to significantly change special education practices” (Marino et al., 2023, p. 404). Generative AI allows for the creation of new and original content based on large amounts of data and machine-learning algorithms. It has made its way into various technology-based interventions designed specifically as assistive solutions to increase, maintain, or improve the learning capabilities of students with disabilities. For example, text-to-speech programs, voice recognition systems, and AI-based tutoring systems provide necessary supports and personalized instruction resulting in new opportunities to learn and develop skills (Marino et al., 2023). Also, AI can help perceive, learn from, and interact with human emotions for individuals with autism (Thakkar et al., 2024). Conversational artificial intelligence (CAI)-enhanced speech-generating devices can improve communication for users that rely on augmentative and alternative communication (Higginbotham et al., 2025). In addition, different generative AI applications have been explored to support the implementation of UDL principles when designing inclusive educational practices for all learners (Evmenova et al., 2024a).

Specific to STEM learning, some initial explorations of how generative AI can support students with various abilities and needs have taken place. For example, the ChatGPT 3.5 application has been successfully used to generate differentiated worksheets to engage learners with disabilities in inclusive math instruction (Rizos et al., 2024). AI has been used to support individualized intelligent tutoring as well as customized learning supports in math and science (Kim & Kim, 2022). AI-powered platforms such as Minecraft Hour of Code use problem-solving and creativity to explore the basics of computer science and coding as well as to learn about the responsible use of AI (Alam, 2022). In addition, early adoption and STEM teachers’ perceptions towards this innovative technology have been explored. While the familiarity and attitudes are diverse, the majority of educators recognize the importance of equipping students with AI-related knowledge and skills (Cheah et al., 2025). AI-powered systems are proposed to make STEM educational materials accessible and engaging for learners with disabilities (Benetech, 2025).

In terms of game-based learning, the research on using generative AI is still in its infancy. Using generative AI to create personalized learning experiences, generate realistic visuals and immersive environments, and provide scaffolded and immediate feedback are the areas being explored. Existing AI components can support game functions such as player modeling, allowing for automated difficulty adaptation, natural language processing to support immediate and individualized feedback, and believable non-playable characters (with bodily motion and lip-synchronized speech; Westera et al., 2020). The ability to reuse these open-source components will result in the faster development of high-quality educational games at reduced cost. While educators still grapple with meaningful ways to use generative AI ethically and effectively (e.g., Reich, 2022; Tabassi, 2023), we initiated a design research study focusing on the development of educational games and AI-enhanced features to support writing across the curriculum for learners with and without disabilities. While our developments are still in its conceptualization stage, we hope that this example will encourage discussions about the future use of AI in K-12 education, specifically in STEM-related areas.

1.4. Writing Across the Curriculum

STEM education can be viewed as a cross-disciplinary combination of STEM disciplines, as well as the individual subjects of science, mathematics, technology, and engineering (Wang et al., 2022). In addition, science literacy for learners with disabilities involves other skills needed to navigate the complex issues around them, such as writing (Asghar et al., 2017). With the primary focus of educational games on traditional STEM content, it is important to expand the efforts to support writing across the curriculum. STEM learning involves learning facts, solving problems, and thinking critically, as well as sharing information through writing. Writing-to-learn has been identified as a promising strategy for developing all of these essential STEM skills (e.g., Graham et al., 2020). It can be used by learners as a means to apply, analyze, justify, communicate, and reflect on their thinking. Responding to STEM content in writing allows for students to organize their thinking, assess what they already know, and refine their understanding of complex topics (Bangert-Drowns et al., 2004). Scientific writing expresses scientific thinking that explores, verifies, reinforces, and improves existing knowledge, as well as allow for the construction of new knowledge (Kim & Kim, 2022). However, writing across the curriculum can be challenging, especially for students with disabilities (e.g., R. Mergen, 2024; Powell et al., 2017). Although quite limited, existing research supports the effectiveness of game-based learning for the development of writing skills, including both the mechanics of writing (e.g., handwriting, posture; Gargot et al., 2021) and higher-level writing tasks (e.g., organization and revision; Gayed et al., 2022). In this study, we aim to explore how digital educational games and AI support can further improve writing across the curriculum for learners with disabilities.

2. Materials and Methods

Before introducing the current study, it is important to provide the context in which we plan to incorporate the educational games and supports. WEGO is a technology-based writing intervention package with embedded self-regulated learning strategies, strategy instruction, and Universal Design for Learning (UDL) features. WEGO offers technological tools for students and technology-based instructional resources and professional development for teachers to support learners throughout the writing process across the curriculum. WEGO has been iteratively developed over the past decade with the support of the U.S. Department of Education, Office of Special Education Programs. WEGO tools have been used by students in grades 3–12 with and without disabilities and with those students identified as emerging multilingual learners. WEGO has been used by elementary school students in grades 3–12 struggling with writing, including those with high-incidence disabilities (learning disabilities, emotional disturbance, attention deficit disorders, and autism). Students use the WEGO tools for planning, writing, and reviewing their persuasive, expository, or personal narrative essays, and teachers use WEGO technology-based instructional resources and professional development for planning and implementing writing instruction. WEGO is a free, web-based, and evidence-based intervention that guides a student from selecting a prompt to evaluating their writing.

WEGO tools feature a technology-based graphic organizer. It is a free Chrome-based application (https://wegowriting.com; accessed on 1 May 2025). The graphic organizer includes five parts: (a) select a prompt and pick your goal, (b) fill in the table, (c) copy the text in the orange box, (d) read your essay and edit it, and (e) evaluate. First, students are guided through careful consideration of which writing prompt to choose. They then choose the goal for their essay using the drop-down menu, as well as a personal writing goal. After setting a goal, students are encouraged to brainstorm their ideas outside of the tool using one of the six brainstorming strategies. They then organize their ideas in the keywords column, aligning them with the IDEAS mnemonic in the graphic organizer which best supports the disciplinary writing genre (Regan et al., 2023). After writing complete sentences for each essay part, students check off what they have completed on the self-monitoring checklist. With one click, the sentences are copied into a complete essay. Self-regulated learning strategies embedded into the WEGO tool include goal setting, self-monitoring, self-evaluation, and self-efficacy. Several UDL features built into the WEGO tool include drop-down menus with transition words, text hints, audio comments, automatically combining sentences into a paragraph, and text-to-speech.

WEGO tools have been tested with more than 1500 students in grades 3–12, including more than 800 students with disabilities in inclusive, self-contained, and co-taught settings. The majority of struggling writers who received WEGO instruction improved the quantity of their essay writing (e.g., number of words and sentences), while all students, regardless of their abilities and needs, improved the quality and organization of their essay writing (e.g., the holistic writing quality score). Students who typically write a few sentences with little regard for organization are able to use the tool and its multiple features to plan and compose high-quality essays using transition words for cohesion. There was a functional relation between the number of words, sentences, transition words, essay parts, and holistic writing quality score and writing with the tool for 10 7th–8th graders with learning disabilities, emotional/behavioral disorders, and autism (e.g., Evmenova et al., 2016). Moreover, when given sufficient practice, students with and without learning disabilities were able to maintain their statistically significant improvements when the tool was removed (e.g., Regan et al., 2018; Evmenova et al., 2020). These results remain true when the WEGO tools were used to support writing in social studies (e.g., Boykin et al., 2019), science (e.g., Regan et al., 2024), and math (R. L. Mergen et al., 2024). However, over the past decade, the perpetual areas of the writing process that students continue to need support with are brainstorming and editing. Thus, it was important to further develop the WEGO tool by incorporating motivating educational games and AI supports to reinforce those specific skill areas.

Data Collection

An initial proof-of-concept step in the informed exploration phase of a design research study (Bannan-Ritland, 2003) was to understand practitioner or parent/caregiver perspectives on the use (if any) of educational games in their classroom(s) and/or homes, as well as to identify the features that educators and families prefer to see in engaging educational games that lead to positive outcomes for students with disabilities, specifically those with high-incidence disabilities. The purpose of this step was to use this information to systematically and thoughtfully develop motivating digital games that scaffold writing across the curriculum. We recruited participants from many long-standing research partner schools (public and private) to be representative of (a) general education teachers, (b) special education teachers, (c) instructors of students with disabilities in alternative settings, and (d) parents or caregivers of children with or without disabilities. Thus, as part of the iterative development, we completed a series of focus groups. Five separate focus groups were conducted over Zoom with 21 educators and/or parents/caregivers. The group sizes ranged from 3 to 5 participants in each session. The 21 participants included 19 females and 2 males ranging in age between 28 and 65 (M = 45.05; SD = 12.36). While such prevalence of females is typical for special education (more than 85% of special education teachers are women; DataUSA, 2022), these demographics are a limitation of the study that limits the generalizability of our findings. Recruiting more fathers of students with disabilities would have provided additional insights. While we trust that our participants represented information-rich cases for brainstorming the features of educational games, additional male participants could have proposed more ideas, especially around the entertainment value of games. Most of the participants were teachers (n = 17), with six parents/caregivers represented among the groups (note: some teachers were also parents of learners with disabilities). Teachers were from elementary, middle, and high schools, inclusive of public and private settings, across four states representing urban, suburban, and rural settings. They had, on average, 15.5 years of teaching experience (SD = 9.01). The study was approved by the Institutional Review Board, and each participant provided informed consent to participate in the focus groups.

The same semi-structured interview protocol was followed by a member of the research team for each of the focus group sessions. At the beginning of each session, WEGO context was briefly re-introduced, as most of the participants had previous experience with the WEGO tools. Permission for audio and video recording was obtained from all the participants so that the research team knew which participants were speaking during the focus group. Data, including individual responses as well as interactions between group members, were then elicited. The protocol consisted of questions across the following seven areas: (a) experiences with digital educational games (across content areas), (b) general perceptions/opinions of educational games for learning, (c) preferred features found in good games, (d) characteristics of bad games, (e) concerns about the use of games in the classroom or at home, (g) use of data provided by the game, and (g) the perceptions of using generative AI to support learners’ writing across the curriculum. The protocol was piloted by experts in the area of writing across the curriculum. In order to ensure equal participation, the focus group moderator used additional probes and prompts to engage all of the participants to respond to each question. Focus group interviews lasted an average of 70 min in length and were recorded for data analysis. One member of the research team was the primary facilitator of the questions, and another team member took notes on a shared document during each session. After the recorded sessions were transcribed verbatim, all transcripts and supplemental field notes were reviewed and coded using a constant-comparative method of qualitative analysis (Glaser, 1965). Specifically, researchers coded data from each of the focus groups, looking for patterns, similarities, and differences. Frequent debriefing sessions throughout the data analysis allowed for the research team to collaboratively refine categories and themes and to check assumptions. Data triangulation across the focus groups, investigator triangulation, as well as these peer reviews among the authors, were used to ensure credibility and trustworthiness of the data analysis (Brantlinger et al., 2005). Additionally, the research team maintained an audit trail of all events from recruitment to the distribution of a gift card for each participant. Analysis of focus group data revealed a consensus of the key characteristics desired in educational games.

3. Results and Discussion

Overall, the participants had positive attitudes towards using educational games to enhance teaching and learning by students with disabilities. Five key features emerged as critical for the effective and efficient implementation of educational games to support student learning. We also discuss the potential ways that existing generative AI tools can facilitate the future development of these key features.

3.1. Content-Driven and Relevant

Our teacher participants valued their instructional time and wanted the games to teach and reinforce the content of the curriculum. The educational value of the games was highlighted over the entertainment value of games that could be used as a reward. As one participant summarized, “You can almost trick students into just thinking it’s a game while they are actually learning”. This comment aligns with the core definition of game-based learning targeting specific knowledge and skills within an educational goal (Plass et al., 2020). Games addressing the specific and relevant goals are more likely to be implemented than those that “waste the time”. As was shared by our participants, some games “spend too much time getting into the content … there is too much time on the fluff and not enough time on the content”. Furthermore, one participant remarked, “I feel like you want to capitalize on the minutes that you have them in there. So, you want to spend that time… doing something fun that’s content-based versus just using [games] as a reward”. Many educational games lack learning objectives and outcomes, resulting in reduced learning outcomes (Marino et al., 2013). Thus, it is important to design any digital game with specific content learning and objectives in mind (Marino & Beecher, 2010).

Potential of AI. Generative AI provides unique opportunities for educators to develop educational games that are unique to their specific learning environments. Many AI tools and models allow for building custom chatbots to help learners master very specific knowledge and skills. These custom chatbots rely on the specific content provided by the teacher supporting their unique goals. “When chatbots have the same teacher as the students they are assisting, it’s more likely they will contribute something valuable to the classroom” (Lindgren, 2024). Custom chatbots can be designed using such platforms as ChatGPT, as well as other tools that support K-12 learners across subject areas including STEM. For example, Mizou (https://mizou.com; accessed on 1 May 2025) allows for teachers to create AI chatbots or agents by uploading specific instructions and instructional materials. Students can then interact with text, audio, and images, as well as receive instant feedback towards a specific learning goal. From exploring facts and videos about the weather and climate in elementary school to learning about real-life scenarios related to heredity, custom chatbots can support any STEM topic.

3.2. Accessibility and Navigation

It was not surprising to see an overarching theme among the participants’ comments related to the accessibility of the games. This theme consisted of both providing accessible features (e.g., text-to-speech, speech-to-text, captions, descriptions of visuals) and ensuring accessibility of content. For example, if a game is not intuitive, a recommendation was to include a how-to video model for the user. One of the groups discussed the barriers of complex directions in games. As one participant noted, “If I have to sit with them and walk them through [the directions] more than once or twice, that would be really frustrating”. The need for designing multiple means of engagement, representation, and action/expression, also known as UDL principles, was also discussed. It included suggestions for intuitive navigation, alternative input, and need for reminders to keep students “productive”. This theme is widely supported by existing research in which the inclusive nature and accessibility of the games that address the diverse needs of learners is often taken into consideration when selecting the intervention (Ke & Abras, 2013).

Potential of AI. Generative AI tools can be used to support various UDL principles while reducing the overwhelming amount of work traditionally associated with creating UDL materials (Evmenova et al., 2024a). Tools like ChatGPT can be used to efficiently generate content with varying demands, summarize large amounts of text, and allow for learners to demonstrate their knowledge and skills by evaluating AI-generated content. It can improve the efficiency of the teaching–learning processes, as well as make learning more accessible by supporting various accommodations commonly listed in individualized education plans (Ciampa et al., 2025). Many existing programs that can be used to create STEM games and videos incorporate built-in accessibility checkers and generate accessible content. For example, Powtoon, a popular program to create animated presentations and videos (https://powtoon.com; accessed on 1 May 2025), now incorporates Imagine Voice AI. This feature allows for adding high-quality realistic voiceovers available in many languages based on the text provided. The voices can be filtered according to the age, gender, tone, and purpose. In turn, tools like Accessibility CoPilot (https://chatgpt.com/g/g-79A7V2SzZ-accessibility-copilot; accessed on 1 May 2025) have been developed in ChatGPT to help analyze the accessibility of web content and provide suggestions for improving it.

3.3. Personalization

The personalization theme included several sub-themes. Character customization was discussed as a way to engage and motivate the learners. “Decorating your avatar or your background” were mentioned by the participants as strategies to add learner buy-in. Personalization would immerse the players into the environment, increasing their engagement and motivation. The participants also noted the sense of ownership that personalized games could offer their students. Along the same lines, teacher participants also noted a preference for the adaptability of the game to different difficulty levels based on the user input. Adapting to each student’s skill level provides experiences that are neither too easy nor too difficult, but which provide optimal learning and prevent frustration or boredom. Finally, the need for immediate and effective feedback was voiced, especially by the parents. As one parent stated, “I don’t know what this product should look like … so, I need something more concrete as a parent”. Immediate and tailored feedback improves learning outcomes by helping students understand their mistakes and make changes immediately. All of these elements support the affective and motivational foundations of game-based learning (Barz et al., 2023; Plass et al., 2015). Choosing a character or avatar allows for players to identify themselves as part of the game (Annetta, 2010; Beserra et al., 2014).

Potential of AI. A myriad of generative AI tools allow for the design of creative and fun avatars and visuals. For example, Canva for Education (https://www.canva.com/education/; accessed 1 May 2025) offers great AI-supported tools for creating presentation, posters, characters, environments. In fact, platforms already exist for exchanging advanced game components and media assets (e.g., 3D-objects, textures, sounds) for serious games supported by technical documents and training materials (Westera et al., 2020). Numerous generative AI programs can also be used to produce the same content on different levels of difficulty. Most chatbots, such as Diffit or Magic School AI, offer text leveler features ensuring students have access to grade-level content adjusted for their ability levels. Thus, Diffit (https://app.diffit.me/; accessed on 1 May 2025) can re-level or translate any complex text PDF, book article, or video, as well as create content, activities, assessments, and summaries aligned with standards. As a result, the quality of student engagement in differentiated STEM content improves, and collaboration among diverse learners can take place in the classroom.

3.4. Collaborative, Engaging, and Interactive

Our participants also reportedly desired games which were collaborative, engaging, and interactive. One participant remarked on the use of a timer within a game to encourage student focus, and others discussed how student interest can be encouraged by earning “points”. The ability to play with (or against) peers was noted as an important feature. Interestingly, there was no consensus around the competition component. While some participants highlighted the importance of competition (e.g., “Competition is the way we roll!”), others were concerned about the possible frustration associated with competition. Such inconsistency exists in previous research. For example, one of the findings by Clark et al. (2016) included that single-player games without completion and collaborative team games outperformed single-player games with competition. At the same time, while not robust, there was a moderating effect of peer competition in another meta-analysis, suggesting that competitive games were better than non-competitive games for promoting learning (Ho et al., 2022). More research is needed to understand the possible importance of competition and collaboration within game-based learning environments specifically for students with disabilities.

Potential of AI. While many might question the use of AI for collaboration, underlying the importance of human interactions, some generative AI tools can still be used to support both teachers and students. From a teacher usage perspective, chatbots can be used to design activities and scenarios for collaboration. Designing the directions for an activity to replicate collaboration in a real-life science lab can be much faster with AI. From a student perspective, AI tools can provide help in brainstorming, synthesizing, and evaluating group work. The back-and-forth interactive nature of most generative AI programs allows for a constant dialog, engaging students in learning the content. Thus, Microsoft Copilot AI creates opportunities for a scaffolded dialog between a student and a chatbot. Learners can engage in a personalized two-way communication, practice typing in text, or using voice chat features. Microsoft Copilot can also provide response options for students who struggle to generate original responses around various STEM topics.

3.5. Meaningful and Usable Data

Another prevalent theme gleaned from the focus groups was for a game to provide meaningful and usable data. For example, participants shared that it was important to have some sort of pre-assessment “to inform [appropriate] placement in the game”. Connecting with the first theme, the participants desired data from the game that was connected to the curriculum standards (e.g., summary of what students have completed, mastery towards standards/goals) in addition to overall usability data (e.g., clicks, duration, idle time). Teachers were planning to use these data to know “what specifically the students struggled with … to be able to go back to [that topic]” for additional remediation. These data could also be used for instruction “to group students based on their strengths and weaknesses”. In comparison, parent participants suggested that not only the child’s performance data from the game be accessible, but also that the explicit interpretation of the data from the game be provided.

Potential of AI. AI functionalities can support game components such as player analytics. Also, when it comes to writing across the curriculum, natural language processing can provide immediate and helpful essay feedback. In fact, we have explored and compared feedback and data-based instructional suggestions generated using different AI tools (Evmenova et al., 2024b). While the feedback varied greatly based on the tool and the type of the prompt, generative AI was able to interpret and score students’ writing products using a criterion-based rubric when provided or creating its own criteria for evaluating writing outcomes. The immediacy of the sufficient formative feedback about student writing was truly impressive (Steiss et al., 2024; Wilson, 2023).

4. Application

Informed by former research and the data shared by our participants, we were able to develop prototypes for six games, supporting the different aspects of writing across the curriculum. Our games are content-specific and relevant, with clear goals that address the brainstorming, drafting, and editing phases of the writing process. The games are accessible with text-to-speech, screen reader compatibility, and alternative text and image descriptions, with easy navigation and abilities to interact with the interface using keyboard navigation. The game concept focuses on players helping a team of Writing Warriors (animal superheroes: Waverley Whale or ‘’Wave” for short, Wilder Wolf, and Wynne Woodpecker) combat the tiny but villainous Scrawler, who’s causing havoc in the city with writing-themed sabotage. Tasked by the cyber-assistant Boris AI with recovering stolen magical writing objects and superpowers, players obtain points through episodic minigames, each representing a mission integrated into the game’s environment and adventurous story (see Figure 1).

Games support aspects of the writing process (i.e., brainstorming, writing process, and editing/revising). Students are able to personalize their experience and choose one of the writing warriors they want to power up within their game. Based on how successful students are in the game, their chosen writing warrior appearance will reflect Fully Powered Up, Almost There, or Not Quite. The difference is in the pose and brightness of their unique digital writing device (see Figure 2).

In addition, students’ actions will increase or decrease the “watts” as a unique and engaging reward system. Each time a player answers a question correctly or makes a mistake, they will earn or lose “watts”. Visually represented as an electrified W icon, they keep characters’ writing devices powered up. This adds a narrative element that enhances the player’s connection to the game. Also consistent with what we learned from the focus group data, students will receive immediate feedback throughout the games based on their actions, including reassuring phrases (e.g., Great work! Try again!), visual feedback (e.g., laser beams around a writing artifact increasing or disappearing based on the response), and audio and sound effects (e.g., Scrawler laugh, wrong answer buzzer, a positive chime), all contributing to create immersive experiences.

In addition to personalization, the games will use adaptive leveling following the three up, two down algorithm. The player can choose the difficulty of the game: Novice Warrior, Warrior-in-Training, or Expert Warrior. However, after two incorrect responses, the next level will automatically be easier. Subsequently, after three correct responses, the next level will be harder. While WEGO games are designed to be single-player games, teachers can support competition among the students by reporting the highest number of watts for students to see somewhere in the classroom. Overall, the games will be highly engaging and interactive (e.g., players throw rings on a pole in a ring toss game). Finally, numerous data will be collected from the games and saved in the WEGO teacher dashboard. The data include the chosen difficulty level, duration, and correct/incorrect answers, etc. These data will be included in existing data-driven decision making maps for teachers to use when determining the next consequential instructional decision (see Regan et al., 2024). While we are still in the process of conceptualizing our games, we look forward to the possibilities of AI integration and expansion of AI models for neurodiverse learners and those with learning disabilities (U.S. Department of Education, Office of Educational Technology, 2023). At this time, we are planning to incorporate AI in the final prototypes during gameplay for real-time scaffolding (e.g., personalized pace, features), automated feedback (e.g., hints, prompts), and/or adaptive leveling (e.g., data-driven decisions within the game). We do, however, already use AI to support writing across the curriculum for students with disabilities.

AI to Support Writing Across the Curriculum

In addition to using findings to develop educational games to be integrated in the WEGO tools, we have explored how AI can specifically support the brainstorming phase prior to writing across the curriculum. Although the WEGO tool teaches students about six specific strategies for brainstorming their ideas, we have consistently observed that students continue to struggle with the higher-order cognitive skill of idea generation or brainstorming. While most of our focus group participants were nervous about using AI in the classroom, several saw a benefit. Thus, in collaboration with our participants, we developed an AI-supported feature for the brainstorming component of WEGO’s graphic organizer. This AI feature will activate students’ prior knowledge on a topic and, in turn, facilitate their ability to generate ideas. It will provide personalized and student-centered supports during the writing process. According to our participants, it is important to have “guardrails,” to avoid any issues with the content and bias common for open AI tools. Thus, we designed our own large language model to generate ideas based on the thousands of essays we already have in the WEGO database. The AI feature will include ideas to support or counter an opinion or argument when writing. In addition, teachers will be able to customize any of the AI suggestions. Another feature requested by our participants was the ability to “enable or disable [the AI support], so that we could give it to those who would benefit and hide it from those who might abuse it”. The premise that teachers would greatly benefit from AI but should still be at the center of instructional delivery is recommended by the U.S. Department of Education, Office of Educational Technology (2023) and echoed by the Center for Innovation, Design, and Digital Learning (CIDDL, 2024). Thus, the WEGO teacher dashboard will include the ability to turn the AI support feature on and off for each individual student and/or for a group of students. With this flexibility, the AI-supported brainstorming feature can support learners when a teacher is not available to conduct individual check-in with students and help them get started on their essays. Thus, AI can support students’ STEM-related writing. Existing research supports our development endeavors, reporting teachers’ positive perceptions of an AI-enhanced scaffolding program that was designed to support students’ scientific writing (Kim & Kim, 2022).

5. Conclusions

WEGO is an example of a bridge between AI, educational games, and writing across the curriculum, including responding to STEM related prompts. While this work is still in its preliminary phases, we hope that this case study demonstrates how numerous technology-based tools and features can be integrated to provide access and equity to inclusive education for all learners regardless of the subject area. We also believe that this case study shows how effective technology integration (Evmenova et al., 2024c) and AI implementation “requires collaboration, planning, and open dialog among stakeholders to address challenges and maximize benefits” (CIDDL, 2024). User feedback, including teacher and parent perspectives, are critical steps for informing the iterative developments of technologies.

While we continue to explore the use of AI in K-12 teaching and learning, we cannot forget the current issues associated with generative AI tools. In addition to access, AI tools are known to produce hallucinations and errors in STEM content (Montenegro-Rueda et al., 2023). While using AI in all education contexts comes with risks and limitations (e.g., Evmenova et al., 2024a), these are exacerbated for students with disabilities. Concerns for the use of AI in special education focus on the following: bias in algorithms that are not always trained by users with disabilities; privacy and data security, including sensitive information about students’ diagnosis; and accessibility, as many innovative AI tools lack accessibility features (Klein, 2024). It is important to remind our teachers to always review content generated by AI for any explicit or implicit bias, to never share any personally identifiable information about students with disabilities, and refrain from putting students on an AI tool without careful consideration of how accessible it is.

Specific STEM context, information generated by AI sometimes includes contradictions (e.g., in response to basic physics questions, Gregorcic & Pendrill, 2023), false facts (e.g., incorrect Webb Telescope facts; Leffer, 2023), or responses lacking nuance (e.g., oversimplifying math problems; Jennings, 2023). Thus, it is imperative to introduce AI literacy to our learners, especially to those with disabilities. Interestingly, several researchers have already attempted to tackle prompting K-12 students’ awareness of AI using game-based learning. Thus, Lee et al. (2021) described the design of a game-based learning environment that provides opportunities for inquiry-based learning centered on AI applied toward solving life-science problems. As you can see, the topics of these special issues are closely intertwined, resulting in exciting new learning prospects.