The Support Paradox in Japanese High Schools: Barriers to Credit Recognition for Third-party On-Demand Learning in Students with Chronic Illness

The Support Paradox in Japanese High Schools: Barriers to Credit Recognition for Third-party On-Demand Learning in Students with Chronic Illness | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article The Support Paradox in Japanese High Schools: Barriers to Credit Recognition for Third-party On-Demand Learning in Students with Chronic Illness Joe Hasei This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7736679/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Ensuring educational rights for students with chronic illnesses is a critical challenge globally. While technology-enhanced distance education, particularly on-demand learning, offers promising solutions, implementation faces numerous barriers. Despite Japan’s GIGA School Program establishing digital infrastructure, adoption remains limited, necessitating urgent investigation of current conditions and challenges. This study conducted the first prefecture-wide survey of 88 high schools in Okayama Prefecture from November 2024 to January 2025 using telephone, email, and online questionnaires to assess student enrollment in long-term medical treatment, online class implementation status, implementation challenges, and acceptability of third-party educational content for academic credit. The results showed that 12.5% of the schools enrolled students requiring long-term medical treatment, with 11.4% having a history of such treatment. While 50.0% implemented only synchronous online classes, 25.0% offered on-demand formats, and 25.0% did not. Among the 60 schools that reported barriers to on-demand provision, the most frequently cited were difficulty accommodating practical/skills-based subjects (61.7%), insufficient human resources (60.0%), inadequate equipment or cloud infrastructure (41.7%), and internal regulations (11.7%). Notably, schools reporting internal barriers were far less likely to accept third-party on-demand modules for credit than those reporting no barriers (20.0% vs. 50.0%; Fisher’s exact p=0.0059; OR=0.25). More than a year after national guidance enabled credit recognition for on-demand learning, implementation remains limited, largely due to staffing constraints and subject-specific hurdles. To secure learning opportunities for students with chronic illnesses, education boards should establish clear evaluation criteria, governance, and quality-assurance frameworks for external resources that move beyond school-by-school efforts. Social Policy On-demand learning Students with chronic illness Implementation barriers Credit recognition Upper secondary education Educational technology policy Figures Figure 1 Figure 2 Figure 3 Figure 4 1 Introduction For high school students receiving treatment for chronic conditions, including pediatric cancer, intractable neurological disorders, and psychiatric illnesses, educational continuity represents far more than academic credit accumulation (Thompson et al. 2015 ; Thongseiratch and Chandeying 2020 ). It constitutes a critical psychological scaffold for preserving self-esteem and maintaining hope for social reintegration during a medical journey. Ensuring educational access for these students directly affects their quality of life (QOL) and must be conceptualized as an integral component of therapeutic intervention that is inseparable from medical care itself (Wikel and Markelz 2023 ). Japan’s GIGA School Initiative, launched in 2019, has equipped all elementary and junior high schools nationwide with one-to-one computing devices, thereby establishing an unprecedented digital infrastructure for education (Oyanagi 2024 ). Building upon this foundation, the Ministry of Education, Culture, Sports, Science and Technology (MEXT) issued a pivotal notification in April 2023 authorizing credit recognition through asynchronous online instruction for students requiring long-term medical care. Theoretically, this policy enables students to engage in self-paced learning that is tailored to their physical abilities, facilitating educational continuity in both hospital settings and home environments. However, a substantial implementation gap persists between the policy framework and educational practices. Over half of Japanese teachers work more than 11 hours daily, and their mental health is becoming increasingly compromised (Matsushita and Yamamura 2021 ). Consequently, imposing additional responsibilities for developing, producing, and delivering online content on an overburdened workforce is untenable. While device deployment through the GIGA School Initiative has progressed, regional disparities in the human support infrastructure for effective utilization have emerged, creating a new “utilization divide” that perpetuates educational inequity (Isha and Wibawarta 2023 ; Oyanagi 2024 ). In this context, asynchronous learning support for students with chronic illness remains stagnant. Concerns are mounting that this promising policy may become merely aspirational, failing to reach the students who most urgently require support. Therefore, this study aims to empirically characterize post-notification educational implementation through a comprehensive census of all 88 high schools in Okayama Prefecture. The research pursued three primary objectives: (1) quantitative assessment of asynchronous instruction implementation for students requiring long-term medical care, (2) structural analysis of multifaceted adoption barriers, and (3) examination of public-private partnership potential, specifically third-party educational content utilization, as a solution to schools’ implementation challenges. Notably, this research identified a “support paradox”: schools experiencing greater challenges—including human resource constraints and practical curriculum accommodation difficulties—demonstrated increased reluctance to adopt external educational content that could potentially address these challenges. This paradoxical finding highlights a structural dilemma in Japan’s educational system, wherein institutions requiring maximum support exhibit the greatest caution regarding the adoption of novel support measures. Ensuring educational opportunities for students with chronic illnesses transcends technological implementation and individual institutional efforts (Baskaran et al. 2024 ; Pelizzari et al. 2025 ). This challenge is connected to the comprehensive educational digital transformation determinants, encompassing teacher workload reduction, the establishment of ICT support infrastructure, and educational quality assurance. This study provides foundational evidence for developing effective educational support models for students with chronic illnesses and advancing systemic reform toward equitable educational access for all students. 2 Materials and Methods 2.1 Study Design and Participants This cross-sectional descriptive study examined the provision of educational support and the associated challenges for students with chronic illnesses in Okayama Prefecture, Japan. The study population comprised 88 high schools operating within the prefecture during the 2023–2024 academic year, including prefectural (regionally administered public institutions), municipal, private, and part-time schools (flexible-schedule institutions serving diverse student populations, typically offering evening instruction). This census approach ensured comprehensive regional coverage. Online instruction modalities were classified as synchronous (real-time video conferencing) or asynchronous (prerecorded on-demand content). The primary outcome measure was institutional acceptance of academic credit recognition for third-party asynchronous educational modules. 2.2 Data Collection The survey was conducted between November 2024 and January 2025. A letter explaining the purpose of the study was sent to each school principal, requesting cooperation. To minimize the burden on respondents and accommodate each school’s situation, responses were collected through three methods: (1) telephone interviews by researchers (37 schools); (2) email responses to the questionnaire (13 schools); and (3) online survey form completion (38 schools) (Fig. 1a). The responses were primarily provided by vice-principals or teachers responsible for supporting students requiring long-term medical care. 2.3 Measurement Instruments The structured questionnaire comprised six domains: 1. Institutional characteristics : School type (prefectural, municipal, private, etc.) and academic department categories (general, industrial, commercial, comprehensive, etc.). 2. Enrollment status of students requiring long-term medical care : Selection from “Currently enrolled,” “Past experience with support,” or “No enrollment.” 3. Online class implementation status : For supporting students with chronic illnesses, selection from “Asynchronous delivery also implemented,” “Synchronous only,” or “No online classes implemented.” 4. Barriers to asynchronous class implementation : Multiple-response options including “Shortage of human resources,” “Hardware issues such as equipment and cloud environment,” “Difficulty providing content for subjects requiring practical training,” “School regulations prevent provision,” and “Other.” 5. Stance on third-party educational content utilization : Regarding recognition of attendance and credits for asynchronous educational content created by external organizations, responses on a four-point scale: “Possible,” “Not possible,” “Under consideration,” or “Unable to determine.” 6. Rationale for acceptance stance : Open-ended responses regarding specific reasons and concerns for the above response. 2.4 Statistical Analysis Quantitative analyses were performed using Python (version 3.11.8) with pandas, NumPy, SciPy, and statsmodels libraries. The primary research question examined the association between schools' barriers and their receptivity to using external on-demand educational content for credit. This association was tested using Fisher's exact test (scipy.stats.fisher_exact, two-sided). For associations among categorical variables, chi-square tests were conducted using scipy.stats.chi2_contingency (two-sided), and Cramér’s V was calculated as the effect size. Logistic regression (statsmodels.api.Logit) was used to estimate odds ratios with Wald 95% confidence intervals. Descriptive statistics and data aggregation were performed using pandas, and visualizations (including heatmaps) were created using matplotlib and seaborn. Statistical significance was set at α=0.05 (two-sided). Given the exploratory nature of the study, no adjustments for multiple comparisons were applied; individual test results are reported descriptively. For barrier breakdowns, percentages were calculated using as the denominator the number of schools that reported at least one barrier (n=60); group comparisons (barrier present vs no barrier) used complete-case coding. Open-ended responses regarding rationales for third-party content use were analyzed using content analysis and grouped into themes based on keywords. 2.5 Ethical Considerations Because this study surveyed school organizations without collecting personally identifiable information, it was deemed exempt from the ethical guidelines for medical research involving human subjects by the [Institution Name] Ethics Committee. Nevertheless, ethical considerations were maintained. All participating schools received a thorough explanation of the study’s purpose, content, data anonymization, strict data management, and methods for result dissemination. Voluntary participation was clearly communicated, and response submission was considered consent to participate. Data were statistically processed to prevent school identification, with utmost care taken to maintain anonymity in reporting the results. 3 Results 3.1 Response Rate and School Characteristics This survey achieved a 100% response rate, with valid responses obtained from all 88 high schools in Okayama Prefecture. The school type distribution comprised prefectural schools (n = 51, 58.0%), private schools (n = 23, 26.1%), part-time schools (n = 12, 13.6%), and municipal schools (n = 2, 2.3%) (Fig. 1 b). Academic department categorization revealed the predominance of general programs (n = 76, 86.4%), followed by industrial (n = 7, 8.0%), commercial (n = 4, 4.5%), and agricultural (n = 1, 1.1%) programs (Fig. 1 c). Regarding the enrollment of students requiring long-term medical care, 11 schools (12.5%) reported “currently enrolled,” 10 schools (11.4%) reported “past experience with support,” and 67 schools (76.1%) reported “no enrollment” (Fig. 1 d). 3.2 Online Instruction Implementation Status and Distribution Disparities Analysis of online instruction modalities revealed that “synchronous only” was implemented by 44 schools (50.0%), representing half of all institutions. Schools providing “asynchronous instruction also implemented,” which enables flexible learning aligned with students’ physical conditions, were limited to 22 schools (25.0%). The remaining 22 schools (25.0%) reported “no online instruction” (Fig. 2 a). Stratified analysis by school type demonstrated statistically significant differences in implementation patterns (χ²=29.71, df = 6, p = 4.5×10⁻⁵, Cramér’s V = 0.41). Municipal and part-time schools showed limited adoption of both synchronous and asynchronous modalities compared with prefectural and private schools (Fig. 2 b). Conversely, no significant differences were observed across academic department categories (χ²=3.24, df = 6, p = 0.78; Fig. 2 c). Furthermore, an analysis of the association between schools’ existing asynchronous instruction implementation and their acceptance of external asynchronous content (third-party creation) revealed no significant relationship (p = 0.97; Fig. 2 d). This finding provides important evidence that possessing internal asynchronous instruction technology and expertise does not necessarily facilitate active utilization of external resources. 3.3 Structural Barriers to Asynchronous Instruction Implementation Analysis of implementation barriers for asynchronous instruction (multiple responses allowed) across all schools (N = 88) identified “difficulty providing subjects requiring practical training online” (37 schools, 42.0%) and “shortage of human resources” (36 schools, 40.9%) as the two predominant obstacles. These were followed by “hardware (equipment/cloud) issues” (25 schools, 28.4%) and “internal regulatory constraints” (10 schools, 11.4%) (Fig. 3 a). This pattern became more pronounced when analyzing schools reporting barriers (N = 60): “practical training” (61.7%) and “human resources” (60.0%) exceeded 60%, indicating that these represent critical operational bottlenecks with extremely high priority (Fig. 3 a). Structural differences in barriers were evident across school characteristics. Heatmap analysis revealed that private schools reported “internal regulatory constraints” at a rate of 26.1%, which was higher than that of other school types. In comparison, prefectural schools showed a relatively high proportion (49.0%) citing “practical training” as challenging (Fig. 3 b). Academic department analysis demonstrated that specialized programs—industrial (57.1%) and commercial (50.0%)—more frequently identified “practical training” as a barrier compared with general programs (40.8%), confirming that curricula with high practical/hands-on training dependency face intrinsic hurdles to asynchronous adaptation (Fig. 3 c). 3.4 Third-Party Content Acceptance and Determining Factors Regarding academic credit recognition for external asynchronous educational content, “not possible” was most common (36 schools, 40.9%). However, combining “possible” (26 schools, 29.5%), “under consideration” (12 schools, 13.6%), and “unable to determine” (13 schools, 14.8%), nearly half indicated openness to or consideration of acceptance (Fig. 4 a). The most significant finding was a statistically significant difference in acceptance based on the presence of barriers. Among schools recognizing no barriers, 50.0% (14/28) responded “possible,” compared with only 20.0% (12/60) among schools with barriers. Fisher’s exact test confirmed the significance (p = 0.0059), demonstrating a strong negative association between barriers and the possibility of third-party content implementation (OR = 0.25, 95% CI = 0.094–0.662). Comparison across all response categories also showed significant differences (χ²=12.90, df = 4, p = 0.0118, Cramér’s V = 0.38), confirming that schools with unresolved barriers demonstrate greater caution toward adopting new options (Fig. 4 b). Keyword analysis of the open-ended responses corroborated these concerns. Frequently emerging themes included “lack of internal rules/regulations,” “undefined evaluation (grading) criteria,” and “ensuring learning/attendance/identity verification.” These represent fundamental questions regarding educational quality assurance and accountability, which are central to school administration (Fig. 4 c). Setting the dependent variable as whether credit recognition of third-party on-demand content was deemed possible (1 = possible, 0 = otherwise), we fit a multivariable logistic regression (n = 88), including the presence of any internal issues, online implementation status (reference: not implemented; synchronous only; on-demand), and school type (reference: prefectural, private, part-time, municipal). The presence of internal issues was significantly associated with lower acceptance (aOR = 0.22, 95% CI = 0.08–0.62, p = 0.004), while no other covariates were statistically significant (Fig. 4 d). 4 Discussion This comprehensive census of all high schools in Okayama Prefecture empirically demonstrates why the groundbreaking 2023 policy of the MEXT, which permits credit recognition through asynchronous instruction, remains underutilized in educational practice. The 25.0% adoption rate for asynchronous instruction clearly reveals that the digital infrastructure established through the GIGA School Program failed to adequately support students with chronic illnesses. We contextualized these findings within Japan’s broader educational system. 4.1 Structural Underpinnings of Human Resource Constraints: Fundamental Barriers to Educational Digital Transformation The “human resource shortage” reported by 40.9% of schools represents more than insufficient staffing. According to the 2024 Tokyo Metropolitan Board of Education survey, 60% of high school teachers exceed national overtime standards, with over 25% surpassing the karoshi threshold (80 hours of monthly overtime). Adding asynchronous content creation to this workload is infeasible. This resource deficit emerged from two intersecting structural problems within Japan’s educational system. First, teachers’ responsibilities exhibit an unbounded expansion, encompassing subject instruction, student guidance, extracurricular activities, parental communication, and administrative duties. Although the Digital Agency’s 2025 “Educational DX Roadmap” promotes operational digitalization, field-level implementation remains limited. Second, the ICT support infrastructure remains inadequate. Our survey’s qualitative responses frequently cited “insufficient technical support,” reflecting that approximately 30% of municipalities lacked dedicated ICT support personnel as of March 2024 (MEXT). Although some municipalities have implemented efficient remote-support models, the horizontal dissemination of these innovations remains slow. Without addressing these dual structural challenges, the fundamental barrier persists. Regardless of policy or technological excellence, schools often lack the necessary human capacity for implementation. 4.2 The Practical Subject Barrier: Revealing Educational DX’s Essential Challenge “Difficulty in providing practical subjects online” (42.0%) was particularly salient in specialized programs (Industrial: 57.1%, Commercial: 50.0%). This issue transcends technical limitations by questioning the fundamental nature of education. Practical training facilitates knowledge “embodiment.” Welding techniques and culinary skills require physical repetition and immediate feedback from the instructor. Current technologies cannot faithfully replicate this “corporeality” and “immediacy” digitally (Baurley et al. 2020 ; Lee et al. 2021 ). However, a deeper issue may involve conceptual rigidity in practical subjects. Industry 4.0 has shifted “manufacturing” from physical manipulation toward data management and systems thinking. Vocational education must adapt to these industrial transformations (Roll and Ifenthaler 2021 ). Asynchronous instruction for practical subjects requires not the digitization of conventional methods but paradigmatic reconceptualization of “practical training” for the digital era (Y. Wang 2024 ). 4.3 The Support Paradox: Illuminating Japan’s Educational Structural Dilemma Our study’s most significant finding—the “support paradox”—reveals that schools with barriers exhibit a greater reluctance toward external content utilization (schools with barriers: 20.0% vs. schools without barriers: 50.0%, p = 0.0059). This phenomenon transcends statistical correlations, exposing the severe structural dysfunction within Japan’s educational system. This paradox stems from “capacity saturation.” Schools confronting challenges exhaust their resources to manage daily crises and lack bandwidth for new initiative considerations or implementations (Creagh et al. 2025 ; H. Wang et al. 2025 ). While external content appears to reduce the workload, its implementation—developing regulations, establishing evaluation criteria, and parental communication—creates additional burdens. This phenomenon manifests universally across educational sectors, including part-time and special needs schools. Institutions requiring the greatest support lack the institutional, financial, and human resources to access new support mechanisms. This finding suggests that self-reinforcing mechanisms perpetuate educational disparities. 4.4 Public-Private Partnership Models: Quality Assurance Imperatives A majority (58.0%, 51/88) of schools demonstrated receptivity to recognizing third-party asynchronous educational content, using a broad definition (acceptable/under consideration/unable to determine); explicit acceptance alone was 29.5% (26/88). However, concerns regarding “undefined evaluation criteria” and “absent internal regulations” reveal profound anxieties about quality assurance. This ambivalence reflects the fundamental tension in public education: ensuring equal, high-quality education while leveraging the efficiency of the private sector within resource constraints. The challenge involves maintaining educational publicness while harnessing private-sector capabilities. Resolution requires governmental assumption of “quality guarantor” responsibilities. It is imperative to establish evaluation and certification frameworks analogous to the European Higher Education Area’s Standards and Guidelines for Quality Assurance (ESG) (Grek and Russell 2024 ; Janssens et al. 2022 ; Kohoutek et al. 2025 ). Systems must clearly define learning outcomes using measurable achievement metrics. Our findings identify critical considerations for the assurance frameworks. First, given the qualitative differences between general and specialized programs, a flexible institutional design that is responsive to school diversity is essential. Careful determination of content standards is required to ensure the educational quality of practical subjects that are resistant to online adaptation. Second, clarifying the evaluation criteria for external content equivalency in formal curricula is urgent. The response “lacking credit recognition judgment criteria” reflects resistance to equating viewing completion with attendance/credit. Objective learning outcome measurement standards are vital for system credibility. Finally, external content integration necessitates a redefinition of the teacher’s role. As the content creation burden decreases, teachers require enhanced professional competencies for individual progress monitoring and personalized support provision (Graham et al. 2023 ; Hou et al. 2024 ). Teacher training and support systems should be integrated into the quality assurance framework. 4.5 Study Implications and Future Directions This study demonstrates that ensuring educational opportunities for students with chronic illnesses presents a complex challenge that transcends isolated policies and technological solutions. This remains inextricably linked to comprehensive educational DX success, encompassing teacher workload reform, ICT support infrastructure, content digitalization, and quality assurance. Systemic redesign, not symptomatic interventions, is required: (1) fundamental restructuring enabling teachers to focus on core responsibilities; (2) nationwide deployment of efficient support models such as ICT support “hub-and-spoke” systems; (3) conceptual redefinition and strategic VR/AR implementation for practical subject digitalization (“Augmented Reality, Mixed Reality Experiential Learning: Transforming Educational Paradigms” n.d.; Thangavel et al. 2025); (4) public-private partnership quality assurance framework establishment; and (5) targeted support for schools facing barriers. Educational provisions for students with chronic illnesses test the educational system’s inclusivity and flexibility. Building on the identified challenges and opportunities, a sustained commitment to constructing truly equitable educational systems is essential. 4.6 International Contextualization of the Support Paradox The “support paradox” identified in Okayama Prefecture represents a universal phenomenon, not a Japan-specific one. This pattern is strongly correlated with global educational inequality structures that intensified during the COVID-19 pandemic. International meta-analyses demonstrated that pandemic-related learning losses disproportionately affected students from low-resource households, particularly in middle-income countries (Betthäuser et al. 2023 ). Even in the well-resourced Netherlands, brief closures produced significant learning deficits, especially among students from lower-education households (Engzell et al. 2021 ). These findings delineate international support needs. Critically, high-need populations coincide with those facing fundamental barriers to new interventional benefits. In regions with unstable connectivity and device shortages, remote or asynchronous education exacerbates learning inequalities. Brazilian evidence demonstrates that schools in low-income areas with connectivity and device limitations experienced greater academic decline under remote learning (Lichand et al. 2022 ). U.S. teacher interviews identified digital divides as direct impediments to remote education (Reynolds et al. 2022 ). Third-party asynchronous content implementation for credit involves curriculum alignment, assessment validation, identity verification, record integration, privacy, and data protection compliance (Wagman et al. 2023 ). Emergency remote teaching’s rapid expansion limited planning time, making teacher time/design burden primary barriers and demanding substantial school adaptive capacity (Beckmann et al. 2022 ; Tawfik et al. 2021 ). Consequently, “institutionally high-need schools/populations” face concurrent access constraints (inadequate learning infrastructure) and fixed implementation costs (governance, evaluation, and personnel workload), impeding short-term new measure adoption/operation. Therefore, our observed “support paradox” coherently aligns with international evidence. 4.7 Study Limitations Several methodological considerations should be acknowledged. Statistical analyses involving small subgroups (e.g., municipal schools, n = 2) limit generalizability. Non-significant logistic regression findings may reflect insufficient power, given the sample size (N = 88). Regarding the design limitations, the cross-sectional methodology precludes causal inferences. Second, the single-prefecture sampling requires additional research for national generalization. Third, perspectives limited to schools excluded student and parent viewpoints. Future studies should incorporate large-scale longitudinal designs with more comprehensive stakeholder perspectives. 5 Conclusion Through a comprehensive census of all high schools in Okayama Prefecture, this study systematically illuminated, for the first time, the actual conditions and underlying structural barriers to on-demand learning support for students requiring long-term medical care. This area has been conspicuously overlooked until now. The survey results highlighted a serious discrepancy between institutional requirements and educational practice, namely the “support paradox.” Despite MEXT’s notification clearly indicating the direction of utilizing technology to guarantee learning opportunities for all students, schools in the field are hindered by multiple compounding challenges—human resource shortages, the wall of practical subjects, and, most fundamentally, the absence of internal regulations—from adopting the rational and effective option of utilizing quality external educational content. This is not merely a delay in implementation but rather demonstrates a structural dilemma wherein schools with the highest need for support paradoxically have the least capacity to take new steps forward. The existence of this barrier, which is insurmountable through individual schools’ or teachers’ enthusiasm and efforts alone, strongly argues that a higher-level systematic intervention is essential to address this fundamental issue concerning the guarantee of students’ right to learn. The findings of this study represent a valuable first step in this problem domain; however, their academic contribution lies in illuminating multiple concrete pathways for future research. First, we must acknowledge the methodological limitations of this study, which is a cross-sectional study conducted in a single region (Okayama Prefecture) at a point in time (2025). Therefore, to verify the generalizability of the challenges identified in this study, strategic expansion of the survey scope to other prefectures with different compositions of urban and rural areas and varying ratios of public to private schools is required as the next step in multiregional comparative research. This will clarify whether the “support paradox” is a nationwide phenomenon or influenced by region-specific educational cultures and policy contexts. Moreover, longitudinal studies that track the same school cohort over several years are indispensable to obtaining essential insights. Elucidating the dynamic process by which factors (e.g., the formulation of new prefectural guidelines, sharing of successful cases, and implementation of teacher training) promote or stagnate the transition to on-demand support over time will provide a foundation for effective policy recommendations. In addition, the development of more practical and interventional research to overcome the barriers identified in this study is strongly anticipated. Beyond the current status of the analysis, developing concrete solutions and empirically evaluating their effectiveness is crucial. For example, constructing a “support model” that packages (1) alternative assessment rubrics for practical subjects, (2) templates for internal school regulations regarding third-party content use, and (3) detailed operational guidelines, including copyright processing and personal information protection, and planning intervention studies to introduce these in multiple cooperating schools could be considered. Evaluating changes in teachers’ sense of workload, students’ learning achievement and satisfaction, and schools’ decision-making processes before and after the introduction of mixed methods would have decisive significance in providing evidence-based solutions to the field. In the future, research exploring possibilities for combining advanced technologies, such as AI tutors and learning analytics, with third-party content to sophisticate and streamline teachers’ assessment work while providing adaptive learning support optimized for individual students will open new frontiers in this field. Finally, while this study was grounded in the perspective of the supply side (schools), education is an endeavor of diverse stakeholders. Therefore, expanding the research horizon to incorporate the perspectives of the recipients of support—students and their guardians—represents an extremely important future research challenge. What do students expect from on-demand learning formats? What difficulties and anxieties do they face in maintaining learning motivation, connecting with peers, and preserving their physical and mental health? Qualitative research is indispensable for preventing mismatches in support designed solely from a supply-side logic and for constructing a truly student-centered system. Through such multifaceted and developmental research, we are confident that we can overcome the structural challenge of the “support paradox” raised in this paper and contribute to realizing an inclusive educational environment where all students, regardless of their health status or geographical conditions, are guaranteed access to quality learning. References Augmented Reality, Mixed Reality Experiential Learning: Transforming Educational Paradigms. (n.d.). Virtual Reality . Baskaran, V., Chubb, L. A., & Fouché, C. B. (2024). Keeping students with Long-term Conditions connected with schools: Facilitators for sustainable virtual connections. Continuity in education , 5 (1), 111–127. Baurley, S., Petreca, B., Selinas, P., Selby, M., & Flintham, M. (2020). Modalities of expression. 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Academic continuity and school reentry support as a standard of care in pediatric oncology. Pediatric blood & cancer , 62 Suppl 5 , S805-17. Thongseiratch, T., & Chandeying, N. (2020). Chronic illnesses and student academic performance. Journal of Health Science and Medical Research . https://doi.org/10.31584/jhsmr.2020738 Wagman, K. B., Blinder, E. B., Song, K., Vignon, A., Dworkin, S., Clegg, T., et al. (2023). “We picked community over privacy”: Privacy and Security Concerns Emerging from Remote Learning Sociotechnical Infrastructure During COVID-19. Proceedings of the ACM on human-computer interaction , 7 (CSCW2), 1–29. Wang, H., Sun, Y., Wang, W., & Liang, H. (2025). Exploring the relationship between teachers’ perceived workload, challenge-hindrance stress, and work engagement: a person-centered approach. BMC psychology , 13 (1), 201. Wang, Y. (2024). Digital transformation of vocational education: Connotation, challenges and pathways. Region - Educational Research and Reviews , 6 (12), 43. Wikel, K. C., & Markelz, A. M. (2023). School reentry plans for students with chronic illness: Research, Advocacy, and Practice for Complex and Chronic Conditions , 41 (1), 22–44. Additional Declarations The authors declare no competing interests. Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-7736679","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":532247977,"identity":"f3e2d29c-dd7c-4f5b-94d2-57814f43f957","order_by":0,"name":"Joe Hasei","email":"data:image/png;base64,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","orcid":"https://orcid.org/0000-0002-4028-0786","institution":"Okayama Univerity","correspondingAuthor":true,"prefix":"","firstName":"Joe","middleName":"","lastName":"Hasei","suffix":""}],"badges":[],"createdAt":"2025-09-28 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07:09:09","extension":"html","order_by":12,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":88439,"visible":true,"origin":"","legend":"","description":"","filename":"earlyproof.html","url":"https://assets-eu.researchsquare.com/files/rs-7736679/v1/0d249a22cdd6b12a31a0991a.html"},{"id":93996682,"identity":"6a9c4d3f-54a2-4ff8-a5be-6c1bf47dc92a","added_by":"auto","created_at":"2025-10-21 07:09:08","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":72908,"visible":true,"origin":"","legend":"\u003cp\u003eStudy population and school characteristics. (a) Flow diagram of the prefecture-wide census, indicating a complete response from all targeted high schools (N=88). (b) Distribution of schools by institutional type. (c) Distribution by primary department category; “General” includes comprehensive/integrated programs. (d) Schools’ reported experience with students requiring long-term medical care.\u003c/p\u003e","description":"","filename":"Picture1.png","url":"https://assets-eu.researchsquare.com/files/rs-7736679/v1/876a45b72598035b62d6d29e.png"},{"id":93996683,"identity":"590e935a-3b52-4705-affc-9e1d1ac0deab","added_by":"auto","created_at":"2025-10-21 07:09:09","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":77341,"visible":true,"origin":"","legend":"\u003cp\u003eOnline instruction modes and their distributions. (a) Overall distribution of modes across schools (N=88): synchronous only (n=44), on-demand implemented (n=22), and no online classes (n=22). (b) Modes by school type shown as row-percent within each type. (c) Modes by department shown as row-percent within each category; “Other” aggregates industrial, commercial, and agricultural programs. (d) Acceptance categories for credit recognition of third-party asynchronous content, stratified by whether the school itself has on-demand instruction (“on-demand present” vs. “no on-demand”), displayed as row-percent within group; acceptance categories comprise acceptable, under review, undecidable, not acceptable, and declined.\u003c/p\u003e","description":"","filename":"Picture2.png","url":"https://assets-eu.researchsquare.com/files/rs-7736679/v1/887105fb2560882ce3902a89.png"},{"id":93996977,"identity":"c693d612-bbff-4c44-a621-d0dd434743e9","added_by":"auto","created_at":"2025-10-21 07:17:09","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":74425,"visible":true,"origin":"","legend":"\u003cp\u003eBarriers to implementing on-demand instruction. (a) Overall prevalence of reported barriers among all schools (N=88); multiple responses allowed. Counts with corresponding percentages (of N=88) are: “practicals difficult to deliver online” 37 (42.0%), “staff shortage” 36 (40.9%), “other” 34 (38.6%), “hardware/cloud constraints” 25 (28.4%), and “internal regulations” 10 (11.4%). (b) Heatmap of barrier prevalence by school type; cells indicate the percentage of schools within each type citing the barrier. (c) Heatmap by department; “Other” aggregates industrial (n=7), commercial (n=4), and agricultural (n=1). Values in (b) and (c) are row percentages within groups.\u003c/p\u003e","description":"","filename":"Picture3.png","url":"https://assets-eu.researchsquare.com/files/rs-7736679/v1/b691d6d2ca5ba37aff7195d7.png"},{"id":93996688,"identity":"7d6be81e-d200-4cad-a270-e75919468aea","added_by":"auto","created_at":"2025-10-21 07:09:09","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":82690,"visible":true,"origin":"","legend":"\u003cp\u003eInstitutional acceptance of third-party on-demand content for credit recognition. (a) Overall distribution of responses on whether third-party asynchronous content (e.g., external-provider videos) may count toward attendance/credit: acceptable, under review, undecidable, not acceptable, or declined to answer. (b) Association between the presence of any internal issue (≥1 barrier in Fig. 3) and acceptance; in this analysis, “Positive” denotes “Acceptable,” and all other categories are grouped as “Other.” Statistical significance was tested using Fisher’s exact test (two-sided); asterisks indicate significance (** p\u0026lt;0.01). (c) Thematic summary of free-text rationales provided by schools (multiple themes per school possible); themes include consensus building, external partnership, learning verification, staff shortage, practicals, internal regulations, and assessment criteria. (d) Multivariable logistic regression modeling the odds of a school responding “Acceptable.” Points show adjusted odds ratios (aOR) with 95% Wald confidence intervals on a log scale. Covariates include the presence of any internal issue (vs. none), online implementation status (reference: not implemented), and school type (reference: prefectural). In this model, the presence of internal issues was associated with lower odds of acceptance (aOR=0.22, 95% CI 0.08–0.62; p=0.004). Analyses were exploratory without adjustment for multiple comparisons; estimates for the municipal category are imprecise due to the small sample (n=2). Abbreviations: aOR, adjusted odds ratio; CI, confidence interval.\u003c/p\u003e","description":"","filename":"Picture4.png","url":"https://assets-eu.researchsquare.com/files/rs-7736679/v1/754a129b24ec87ee8039405c.png"},{"id":93998379,"identity":"412c6cae-0e8d-478e-8e78-115691011f7c","added_by":"auto","created_at":"2025-10-21 07:33:09","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1218023,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7736679/v1/b7de58a3-879b-476f-b36a-b1fb23af50eb.pdf"}],"financialInterests":"The authors declare no competing interests.","formattedTitle":"\u003cp\u003e\u003cstrong\u003eThe Support Paradox in Japanese High Schools: Barriers to Credit Recognition for Third-party On-Demand Learning in Students with Chronic Illness\u003c/strong\u003e\u003c/p\u003e","fulltext":[{"header":"1 Introduction","content":"\u003cp\u003eFor high school students receiving treatment for chronic conditions, including pediatric cancer, intractable neurological disorders, and psychiatric illnesses, educational continuity represents far more than academic credit accumulation (Thompson et al. \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2015\u003c/span\u003e; Thongseiratch and Chandeying \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). It constitutes a critical psychological scaffold for preserving self-esteem and maintaining hope for social reintegration during a medical journey. Ensuring educational access for these students directly affects their quality of life (QOL) and must be conceptualized as an integral component of therapeutic intervention that is inseparable from medical care itself (Wikel and Markelz \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2023\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eJapan\u0026rsquo;s GIGA School Initiative, launched in 2019, has equipped all elementary and junior high schools nationwide with one-to-one computing devices, thereby establishing an unprecedented digital infrastructure for education (Oyanagi \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). Building upon this foundation, the Ministry of Education, Culture, Sports, Science and Technology (MEXT) issued a pivotal notification in April 2023 authorizing credit recognition through asynchronous online instruction for students requiring long-term medical care. Theoretically, this policy enables students to engage in self-paced learning that is tailored to their physical abilities, facilitating educational continuity in both hospital settings and home environments.\u003c/p\u003e\u003cp\u003eHowever, a substantial implementation gap persists between the policy framework and educational practices. Over half of Japanese teachers work more than 11 hours daily, and their mental health is becoming increasingly compromised (Matsushita and Yamamura \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). Consequently, imposing additional responsibilities for developing, producing, and delivering online content on an overburdened workforce is untenable. While device deployment through the GIGA School Initiative has progressed, regional disparities in the human support infrastructure for effective utilization have emerged, creating a new \u0026ldquo;utilization divide\u0026rdquo; that perpetuates educational inequity (Isha and Wibawarta \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2023\u003c/span\u003e; Oyanagi \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). In this context, asynchronous learning support for students with chronic illness remains stagnant. Concerns are mounting that this promising policy may become merely aspirational, failing to reach the students who most urgently require support.\u003c/p\u003e\u003cp\u003eTherefore, this study aims to empirically characterize post-notification educational implementation through a comprehensive census of all 88 high schools in Okayama Prefecture. The research pursued three primary objectives: (1) quantitative assessment of asynchronous instruction implementation for students requiring long-term medical care, (2) structural analysis of multifaceted adoption barriers, and (3) examination of public-private partnership potential, specifically third-party educational content utilization, as a solution to schools\u0026rsquo; implementation challenges. Notably, this research identified a \u0026ldquo;support paradox\u0026rdquo;: schools experiencing greater challenges\u0026mdash;including human resource constraints and practical curriculum accommodation difficulties\u0026mdash;demonstrated increased reluctance to adopt external educational content that could potentially address these challenges. This paradoxical finding highlights a structural dilemma in Japan\u0026rsquo;s educational system, wherein institutions requiring maximum support exhibit the greatest caution regarding the adoption of novel support measures.\u003c/p\u003e\u003cp\u003eEnsuring educational opportunities for students with chronic illnesses transcends technological implementation and individual institutional efforts (Baskaran et al. \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2024\u003c/span\u003e; Pelizzari et al. \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2025\u003c/span\u003e). This challenge is connected to the comprehensive educational digital transformation determinants, encompassing teacher workload reduction, the establishment of ICT support infrastructure, and educational quality assurance. This study provides foundational evidence for developing effective educational support models for students with chronic illnesses and advancing systemic reform toward equitable educational access for all students.\u003c/p\u003e"},{"header":"2 Materials and Methods","content":"\u003cp\u003e\u003cstrong\u003e2.1 Study Design and Participants\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis cross-sectional descriptive study examined the provision of educational support and the associated challenges for students with chronic illnesses in Okayama Prefecture, Japan. The study population comprised 88 high schools operating within the prefecture during the 2023–2024 academic year, including prefectural (regionally administered public institutions), municipal, private, and part-time schools (flexible-schedule institutions serving diverse student populations, typically offering evening instruction). This census approach ensured comprehensive regional coverage. Online instruction modalities were classified as synchronous (real-time video conferencing) or asynchronous (prerecorded on-demand content). The primary outcome measure was institutional acceptance of academic credit recognition for third-party asynchronous educational modules.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e2.2 Data Collection\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe survey was conducted between November 2024 and January 2025. A letter explaining the purpose of the study was sent to each school principal, requesting cooperation. To minimize the burden on respondents and accommodate each school’s situation, responses were collected through three methods: (1) telephone interviews by researchers (37 schools); (2) email responses to the questionnaire (13 schools); and (3) online survey form completion (38 schools) (Fig. 1a). The responses were primarily provided by vice-principals or teachers responsible for supporting students requiring long-term medical care.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e2.3 Measurement Instruments\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe structured questionnaire comprised six domains:\u003c/p\u003e\n\u003cp\u003e1. \u003cstrong\u003eInstitutional characteristics\u003c/strong\u003e: School type (prefectural, municipal, private, etc.) and academic department categories (general, industrial, commercial, comprehensive, etc.).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e2. \u003cstrong\u003eEnrollment status of students requiring long-term medical care\u003c/strong\u003e: Selection from “Currently enrolled,” “Past experience with support,” or “No enrollment.”\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e3. \u003cstrong\u003eOnline class implementation status\u003c/strong\u003e: For supporting students with chronic illnesses, selection from “Asynchronous delivery also implemented,” “Synchronous only,” or “No online classes implemented.”\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e4. \u003cstrong\u003eBarriers to asynchronous class implementation\u003c/strong\u003e: Multiple-response options including “Shortage of human resources,” “Hardware issues such as equipment and cloud environment,” “Difficulty providing content for subjects requiring practical training,” “School regulations prevent provision,” and “Other.”\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e5. \u003cstrong\u003eStance on third-party educational content utilization\u003c/strong\u003e: Regarding recognition of attendance and credits for asynchronous educational content created by external organizations, responses on a four-point scale: “Possible,” “Not possible,” “Under consideration,” or “Unable to determine.”\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e6. \u003cstrong\u003eRationale for acceptance stance\u003c/strong\u003e: Open-ended responses regarding specific reasons and concerns for the above response.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e2.4 Statistical Analysis\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eQuantitative analyses were performed using Python (version 3.11.8) with pandas, NumPy, SciPy, and statsmodels libraries. The primary research question examined the association between schools' barriers and their receptivity to using external on-demand educational content for credit. This association was tested using Fisher's exact test (scipy.stats.fisher_exact, two-sided). For associations among categorical variables, chi-square tests were conducted using scipy.stats.chi2_contingency (two-sided), and Cramér’s V was calculated as the effect size. Logistic regression (statsmodels.api.Logit) was used to estimate odds ratios with Wald 95% confidence intervals. Descriptive statistics and data aggregation were performed using pandas, and visualizations (including heatmaps) were created using matplotlib and seaborn. Statistical significance was set at α=0.05 (two-sided). Given the exploratory nature of the study, no adjustments for multiple comparisons were applied; individual test results are reported descriptively. For barrier breakdowns, percentages were calculated using as the denominator the number of schools that reported at least one barrier (n=60); group comparisons (barrier present vs no barrier) used complete-case coding. Open-ended responses regarding rationales for third-party content use were analyzed using content analysis and grouped into themes based on keywords.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e2.5 Ethical Considerations\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eBecause this study surveyed school organizations without collecting personally identifiable information, it was deemed exempt from the ethical guidelines for medical research involving human subjects by the [Institution Name] Ethics Committee. Nevertheless, ethical considerations were maintained. All participating schools received a thorough explanation of the study’s purpose, content, data anonymization, strict data management, and methods for result dissemination. Voluntary participation was clearly communicated, and response submission was considered consent to participate. Data were statistically processed to prevent school identification, with utmost care taken to maintain anonymity in reporting the results.\u003c/p\u003e"},{"header":"3 Results","content":"\u003cdiv id=\"Sec9\" class=\"Section2\"\u003e\u003ch2\u003e3.1 Response Rate and School Characteristics\u003c/h2\u003e\u003cp\u003eThis survey achieved a 100% response rate, with valid responses obtained from all 88 high schools in Okayama Prefecture. The school type distribution comprised prefectural schools (n\u0026thinsp;=\u0026thinsp;51, 58.0%), private schools (n\u0026thinsp;=\u0026thinsp;23, 26.1%), part-time schools (n\u0026thinsp;=\u0026thinsp;12, 13.6%), and municipal schools (n\u0026thinsp;=\u0026thinsp;2, 2.3%) (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eb). Academic department categorization revealed the predominance of general programs (n\u0026thinsp;=\u0026thinsp;76, 86.4%), followed by industrial (n\u0026thinsp;=\u0026thinsp;7, 8.0%), commercial (n\u0026thinsp;=\u0026thinsp;4, 4.5%), and agricultural (n\u0026thinsp;=\u0026thinsp;1, 1.1%) programs (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003ec). Regarding the enrollment of students requiring long-term medical care, 11 schools (12.5%) reported \u0026ldquo;currently enrolled,\u0026rdquo; 10 schools (11.4%) reported \u0026ldquo;past experience with support,\u0026rdquo; and 67 schools (76.1%) reported \u0026ldquo;no enrollment\u0026rdquo; (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003ed).\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec10\" class=\"Section2\"\u003e\u003ch2\u003e3.2 Online Instruction Implementation Status and Distribution Disparities\u003c/h2\u003e\u003cp\u003eAnalysis of online instruction modalities revealed that \u0026ldquo;synchronous only\u0026rdquo; was implemented by 44 schools (50.0%), representing half of all institutions. Schools providing \u0026ldquo;asynchronous instruction also implemented,\u0026rdquo; which enables flexible learning aligned with students\u0026rsquo; physical conditions, were limited to 22 schools (25.0%). The remaining 22 schools (25.0%) reported \u0026ldquo;no online instruction\u0026rdquo; (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003ea).\u003c/p\u003e\u003cp\u003eStratified analysis by school type demonstrated statistically significant differences in implementation patterns (χ\u0026sup2;=29.71, df\u0026thinsp;=\u0026thinsp;6, p\u0026thinsp;=\u0026thinsp;4.5\u0026times;10⁻⁵, Cram\u0026eacute;r\u0026rsquo;s V\u0026thinsp;=\u0026thinsp;0.41). Municipal and part-time schools showed limited adoption of both synchronous and asynchronous modalities compared with prefectural and private schools (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eb). Conversely, no significant differences were observed across academic department categories (χ\u0026sup2;=3.24, df\u0026thinsp;=\u0026thinsp;6, p\u0026thinsp;=\u0026thinsp;0.78; Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003ec).\u003c/p\u003e\u003cp\u003eFurthermore, an analysis of the association between schools\u0026rsquo; existing asynchronous instruction implementation and their acceptance of external asynchronous content (third-party creation) revealed no significant relationship (p\u0026thinsp;=\u0026thinsp;0.97; Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003ed). This finding provides important evidence that possessing internal asynchronous instruction technology and expertise does not necessarily facilitate active utilization of external resources.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec11\" class=\"Section2\"\u003e\u003ch2\u003e3.3 Structural Barriers to Asynchronous Instruction Implementation\u003c/h2\u003e\u003cp\u003eAnalysis of implementation barriers for asynchronous instruction (multiple responses allowed) across all schools (N\u0026thinsp;=\u0026thinsp;88) identified \u0026ldquo;difficulty providing subjects requiring practical training online\u0026rdquo; (37 schools, 42.0%) and \u0026ldquo;shortage of human resources\u0026rdquo; (36 schools, 40.9%) as the two predominant obstacles. These were followed by \u0026ldquo;hardware (equipment/cloud) issues\u0026rdquo; (25 schools, 28.4%) and \u0026ldquo;internal regulatory constraints\u0026rdquo; (10 schools, 11.4%) (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003ea). This pattern became more pronounced when analyzing schools reporting barriers (N\u0026thinsp;=\u0026thinsp;60): \u0026ldquo;practical training\u0026rdquo; (61.7%) and \u0026ldquo;human resources\u0026rdquo; (60.0%) exceeded 60%, indicating that these represent critical operational bottlenecks with extremely high priority (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003ea). Structural differences in barriers were evident across school characteristics. Heatmap analysis revealed that private schools reported \u0026ldquo;internal regulatory constraints\u0026rdquo; at a rate of 26.1%, which was higher than that of other school types. In comparison, prefectural schools showed a relatively high proportion (49.0%) citing \u0026ldquo;practical training\u0026rdquo; as challenging (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eb). Academic department analysis demonstrated that specialized programs\u0026mdash;industrial (57.1%) and commercial (50.0%)\u0026mdash;more frequently identified \u0026ldquo;practical training\u0026rdquo; as a barrier compared with general programs (40.8%), confirming that curricula with high practical/hands-on training dependency face intrinsic hurdles to asynchronous adaptation (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003ec).\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec12\" class=\"Section2\"\u003e\u003ch2\u003e3.4 Third-Party Content Acceptance and Determining Factors\u003c/h2\u003e\u003cp\u003eRegarding academic credit recognition for external asynchronous educational content, \u0026ldquo;not possible\u0026rdquo; was most common (36 schools, 40.9%). However, combining \u0026ldquo;possible\u0026rdquo; (26 schools, 29.5%), \u0026ldquo;under consideration\u0026rdquo; (12 schools, 13.6%), and \u0026ldquo;unable to determine\u0026rdquo; (13 schools, 14.8%), nearly half indicated openness to or consideration of acceptance (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003ea).\u003c/p\u003e\u003cp\u003eThe most significant finding was a statistically significant difference in acceptance based on the presence of barriers. Among schools recognizing no barriers, 50.0% (14/28) responded \u0026ldquo;possible,\u0026rdquo; compared with only 20.0% (12/60) among schools with barriers. Fisher\u0026rsquo;s exact test confirmed the significance (p\u0026thinsp;=\u0026thinsp;0.0059), demonstrating a strong negative association between barriers and the possibility of third-party content implementation (OR\u0026thinsp;=\u0026thinsp;0.25, 95% CI\u0026thinsp;=\u0026thinsp;0.094\u0026ndash;0.662). Comparison across all response categories also showed significant differences (χ\u0026sup2;=12.90, df\u0026thinsp;=\u0026thinsp;4, p\u0026thinsp;=\u0026thinsp;0.0118, Cram\u0026eacute;r\u0026rsquo;s V\u0026thinsp;=\u0026thinsp;0.38), confirming that schools with unresolved barriers demonstrate greater caution toward adopting new options (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eb). Keyword analysis of the open-ended responses corroborated these concerns. Frequently emerging themes included \u0026ldquo;lack of internal rules/regulations,\u0026rdquo; \u0026ldquo;undefined evaluation (grading) criteria,\u0026rdquo; and \u0026ldquo;ensuring learning/attendance/identity verification.\u0026rdquo; These represent fundamental questions regarding educational quality assurance and accountability, which are central to school administration (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003ec). Setting the dependent variable as whether credit recognition of third-party on-demand content was deemed possible (1\u0026thinsp;=\u0026thinsp;possible, 0\u0026thinsp;=\u0026thinsp;otherwise), we fit a multivariable logistic regression (n\u0026thinsp;=\u0026thinsp;88), including the presence of any internal issues, online implementation status (reference: not implemented; synchronous only; on-demand), and school type (reference: prefectural, private, part-time, municipal). The presence of internal issues was significantly associated with lower acceptance (aOR\u0026thinsp;=\u0026thinsp;0.22, 95% CI\u0026thinsp;=\u0026thinsp;0.08\u0026ndash;0.62, p\u0026thinsp;=\u0026thinsp;0.004), while no other covariates were statistically significant (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003ed).\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003c/div\u003e"},{"header":"4 Discussion","content":"\u003cp\u003eThis comprehensive census of all high schools in Okayama Prefecture empirically demonstrates why the groundbreaking 2023 policy of the MEXT, which permits credit recognition through asynchronous instruction, remains underutilized in educational practice. The 25.0% adoption rate for asynchronous instruction clearly reveals that the digital infrastructure established through the GIGA School Program failed to adequately support students with chronic illnesses. We contextualized these findings within Japan\u0026rsquo;s broader educational system.\u003c/p\u003e\u003cdiv id=\"Sec14\" class=\"Section2\"\u003e\u003ch2\u003e4.1 Structural Underpinnings of Human Resource Constraints: Fundamental Barriers to Educational Digital Transformation\u003c/h2\u003e\u003cp\u003eThe \u0026ldquo;human resource shortage\u0026rdquo; reported by 40.9% of schools represents more than insufficient staffing. According to the 2024 Tokyo Metropolitan Board of Education survey, 60% of high school teachers exceed national overtime standards, with over 25% surpassing the \u003cem\u003ekaroshi\u003c/em\u003e threshold (80 hours of monthly overtime). Adding asynchronous content creation to this workload is infeasible. This resource deficit emerged from two intersecting structural problems within Japan\u0026rsquo;s educational system. First, teachers\u0026rsquo; responsibilities exhibit an unbounded expansion, encompassing subject instruction, student guidance, extracurricular activities, parental communication, and administrative duties. Although the Digital Agency\u0026rsquo;s 2025 \u0026ldquo;Educational DX Roadmap\u0026rdquo; promotes operational digitalization, field-level implementation remains limited. Second, the ICT support infrastructure remains inadequate. Our survey\u0026rsquo;s qualitative responses frequently cited \u0026ldquo;insufficient technical support,\u0026rdquo; reflecting that approximately 30% of municipalities lacked dedicated ICT support personnel as of March 2024 (MEXT). Although some municipalities have implemented efficient remote-support models, the horizontal dissemination of these innovations remains slow. Without addressing these dual structural challenges, the fundamental barrier persists. Regardless of policy or technological excellence, schools often lack the necessary human capacity for implementation.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec15\" class=\"Section2\"\u003e\u003ch2\u003e4.2 The Practical Subject Barrier: Revealing Educational DX\u0026rsquo;s Essential Challenge\u003c/h2\u003e\u003cp\u003e\u0026ldquo;Difficulty in providing practical subjects online\u0026rdquo; (42.0%) was particularly salient in specialized programs (Industrial: 57.1%, Commercial: 50.0%). This issue transcends technical limitations by questioning the fundamental nature of education.\u003c/p\u003e\u003cp\u003ePractical training facilitates knowledge \u0026ldquo;embodiment.\u0026rdquo; Welding techniques and culinary skills require physical repetition and immediate feedback from the instructor. Current technologies cannot faithfully replicate this \u0026ldquo;corporeality\u0026rdquo; and \u0026ldquo;immediacy\u0026rdquo; digitally (Baurley et al. \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Lee et al. \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2021\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eHowever, a deeper issue may involve conceptual rigidity in practical subjects. Industry 4.0 has shifted \u0026ldquo;manufacturing\u0026rdquo; from physical manipulation toward data management and systems thinking. Vocational education must adapt to these industrial transformations (Roll and Ifenthaler \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). Asynchronous instruction for practical subjects requires not the digitization of conventional methods but paradigmatic reconceptualization of \u0026ldquo;practical training\u0026rdquo; for the digital era (Y. Wang \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e2024\u003c/span\u003e).\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec16\" class=\"Section2\"\u003e\u003ch2\u003e4.3 The Support Paradox: Illuminating Japan\u0026rsquo;s Educational Structural Dilemma\u003c/h2\u003e\u003cp\u003eOur study\u0026rsquo;s most significant finding\u0026mdash;the \u0026ldquo;support paradox\u0026rdquo;\u0026mdash;reveals that schools with barriers exhibit a greater reluctance toward external content utilization (schools with barriers: 20.0% vs. schools without barriers: 50.0%, p\u0026thinsp;=\u0026thinsp;0.0059). This phenomenon transcends statistical correlations, exposing the severe structural dysfunction within Japan\u0026rsquo;s educational system. This paradox stems from \u0026ldquo;capacity saturation.\u0026rdquo; Schools confronting challenges exhaust their resources to manage daily crises and lack bandwidth for new initiative considerations or implementations (Creagh et al. \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2025\u003c/span\u003e; H. Wang et al. \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2025\u003c/span\u003e). While external content appears to reduce the workload, its implementation\u0026mdash;developing regulations, establishing evaluation criteria, and parental communication\u0026mdash;creates additional burdens.\u003c/p\u003e\u003cp\u003eThis phenomenon manifests universally across educational sectors, including part-time and special needs schools. Institutions requiring the greatest support lack the institutional, financial, and human resources to access new support mechanisms. This finding suggests that self-reinforcing mechanisms perpetuate educational disparities.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec17\" class=\"Section2\"\u003e\u003ch2\u003e4.4 Public-Private Partnership Models: Quality Assurance Imperatives\u003c/h2\u003e\u003cp\u003eA majority (58.0%, 51/88) of schools demonstrated receptivity to recognizing third-party asynchronous educational content, using a broad definition (acceptable/under consideration/unable to determine); explicit acceptance alone was 29.5% (26/88). However, concerns regarding \u0026ldquo;undefined evaluation criteria\u0026rdquo; and \u0026ldquo;absent internal regulations\u0026rdquo; reveal profound anxieties about quality assurance. This ambivalence reflects the fundamental tension in public education: ensuring equal, high-quality education while leveraging the efficiency of the private sector within resource constraints. The challenge involves maintaining educational publicness while harnessing private-sector capabilities. Resolution requires governmental assumption of \u0026ldquo;quality guarantor\u0026rdquo; responsibilities. It is imperative to establish evaluation and certification frameworks analogous to the European Higher Education Area\u0026rsquo;s Standards and Guidelines for Quality Assurance (ESG) (Grek and Russell \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2024\u003c/span\u003e; Janssens et al. \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Kohoutek et al. \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2025\u003c/span\u003e). Systems must clearly define learning outcomes using measurable achievement metrics.\u003c/p\u003e\u003cp\u003eOur findings identify critical considerations for the assurance frameworks. First, given the qualitative differences between general and specialized programs, a flexible institutional design that is responsive to school diversity is essential. Careful determination of content standards is required to ensure the educational quality of practical subjects that are resistant to online adaptation. Second, clarifying the evaluation criteria for external content equivalency in formal curricula is urgent. The response \u0026ldquo;lacking credit recognition judgment criteria\u0026rdquo; reflects resistance to equating viewing completion with attendance/credit. Objective learning outcome measurement standards are vital for system credibility. Finally, external content integration necessitates a redefinition of the teacher\u0026rsquo;s role. As the content creation burden decreases, teachers require enhanced professional competencies for individual progress monitoring and personalized support provision (Graham et al. \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2023\u003c/span\u003e; Hou et al. \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). Teacher training and support systems should be integrated into the quality assurance framework.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec18\" class=\"Section2\"\u003e\u003ch2\u003e4.5 Study Implications and Future Directions\u003c/h2\u003e\u003cp\u003eThis study demonstrates that ensuring educational opportunities for students with chronic illnesses presents a complex challenge that transcends isolated policies and technological solutions. This remains inextricably linked to comprehensive educational DX success, encompassing teacher workload reform, ICT support infrastructure, content digitalization, and quality assurance.\u003c/p\u003e\u003cp\u003eSystemic redesign, not symptomatic interventions, is required: (1) fundamental restructuring enabling teachers to focus on core responsibilities; (2) nationwide deployment of efficient support models such as ICT support \u0026ldquo;hub-and-spoke\u0026rdquo; systems; (3) conceptual redefinition and strategic VR/AR implementation for practical subject digitalization (\u0026ldquo;Augmented Reality, Mixed Reality Experiential Learning: Transforming Educational Paradigms\u0026rdquo; n.d.; Thangavel et al. 2025); (4) public-private partnership quality assurance framework establishment; and (5) targeted support for schools facing barriers. Educational provisions for students with chronic illnesses test the educational system\u0026rsquo;s inclusivity and flexibility. Building on the identified challenges and opportunities, a sustained commitment to constructing truly equitable educational systems is essential.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec19\" class=\"Section2\"\u003e\u003ch2\u003e4.6 International Contextualization of the Support Paradox\u003c/h2\u003e\u003cp\u003eThe \u0026ldquo;support paradox\u0026rdquo; identified in Okayama Prefecture represents a universal phenomenon, not a Japan-specific one. This pattern is strongly correlated with global educational inequality structures that intensified during the COVID-19 pandemic. International meta-analyses demonstrated that pandemic-related learning losses disproportionately affected students from low-resource households, particularly in middle-income countries (Betth\u0026auml;user et al. \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). Even in the well-resourced Netherlands, brief closures produced significant learning deficits, especially among students from lower-education households (Engzell et al. \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). These findings delineate international support needs. Critically, high-need populations coincide with those facing fundamental barriers to new interventional benefits. In regions with unstable connectivity and device shortages, remote or asynchronous education exacerbates learning inequalities. Brazilian evidence demonstrates that schools in low-income areas with connectivity and device limitations experienced greater academic decline under remote learning (Lichand et al. \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). U.S. teacher interviews identified digital divides as direct impediments to remote education (Reynolds et al. \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e2022\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eThird-party asynchronous content implementation for credit involves curriculum alignment, assessment validation, identity verification, record integration, privacy, and data protection compliance (Wagman et al. \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). Emergency remote teaching\u0026rsquo;s rapid expansion limited planning time, making teacher time/design burden primary barriers and demanding substantial school adaptive capacity (Beckmann et al. \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Tawfik et al. \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). Consequently, \u0026ldquo;institutionally high-need schools/populations\u0026rdquo; face concurrent access constraints (inadequate learning infrastructure) and fixed implementation costs (governance, evaluation, and personnel workload), impeding short-term new measure adoption/operation. Therefore, our observed \u0026ldquo;support paradox\u0026rdquo; coherently aligns with international evidence.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec20\" class=\"Section2\"\u003e\u003ch2\u003e4.7 Study Limitations\u003c/h2\u003e\u003cp\u003eSeveral methodological considerations should be acknowledged. Statistical analyses involving small subgroups (e.g., municipal schools, n\u0026thinsp;=\u0026thinsp;2) limit generalizability. Non-significant logistic regression findings may reflect insufficient power, given the sample size (N\u0026thinsp;=\u0026thinsp;88). Regarding the design limitations, the cross-sectional methodology precludes causal inferences. Second, the single-prefecture sampling requires additional research for national generalization. Third, perspectives limited to schools excluded student and parent viewpoints. Future studies should incorporate large-scale longitudinal designs with more comprehensive stakeholder perspectives.\u003c/p\u003e\u003c/div\u003e"},{"header":"5 Conclusion","content":"\u003cp\u003eThrough a comprehensive census of all high schools in Okayama Prefecture, this study systematically illuminated, for the first time, the actual conditions and underlying structural barriers to on-demand learning support for students requiring long-term medical care. This area has been conspicuously overlooked until now. The survey results highlighted a serious discrepancy between institutional requirements and educational practice, namely the \u0026ldquo;support paradox.\u0026rdquo; Despite MEXT\u0026rsquo;s notification clearly indicating the direction of utilizing technology to guarantee learning opportunities for all students, schools in the field are hindered by multiple compounding challenges\u0026mdash;human resource shortages, the wall of practical subjects, and, most fundamentally, the absence of internal regulations\u0026mdash;from adopting the rational and effective option of utilizing quality external educational content. This is not merely a delay in implementation but rather demonstrates a structural dilemma wherein schools with the highest need for support paradoxically have the least capacity to take new steps forward. The existence of this barrier, which is insurmountable through individual schools\u0026rsquo; or teachers\u0026rsquo; enthusiasm and efforts alone, strongly argues that a higher-level systematic intervention is essential to address this fundamental issue concerning the guarantee of students\u0026rsquo; right to learn.\u003c/p\u003e\u003cp\u003eThe findings of this study represent a valuable first step in this problem domain; however, their academic contribution lies in illuminating multiple concrete pathways for future research. First, we must acknowledge the methodological limitations of this study, which is a cross-sectional study conducted in a single region (Okayama Prefecture) at a point in time (2025). Therefore, to verify the generalizability of the challenges identified in this study, strategic expansion of the survey scope to other prefectures with different compositions of urban and rural areas and varying ratios of public to private schools is required as the next step in multiregional comparative research. This will clarify whether the \u0026ldquo;support paradox\u0026rdquo; is a nationwide phenomenon or influenced by region-specific educational cultures and policy contexts. Moreover, longitudinal studies that track the same school cohort over several years are indispensable to obtaining essential insights. Elucidating the dynamic process by which factors (e.g., the formulation of new prefectural guidelines, sharing of successful cases, and implementation of teacher training) promote or stagnate the transition to on-demand support over time will provide a foundation for effective policy recommendations.\u003c/p\u003e\u003cp\u003eIn addition, the development of more practical and interventional research to overcome the barriers identified in this study is strongly anticipated. Beyond the current status of the analysis, developing concrete solutions and empirically evaluating their effectiveness is crucial. For example, constructing a \u0026ldquo;support model\u0026rdquo; that packages (1) alternative assessment rubrics for practical subjects, (2) templates for internal school regulations regarding third-party content use, and (3) detailed operational guidelines, including copyright processing and personal information protection, and planning intervention studies to introduce these in multiple cooperating schools could be considered. Evaluating changes in teachers\u0026rsquo; sense of workload, students\u0026rsquo; learning achievement and satisfaction, and schools\u0026rsquo; decision-making processes before and after the introduction of mixed methods would have decisive significance in providing evidence-based solutions to the field. In the future, research exploring possibilities for combining advanced technologies, such as AI tutors and learning analytics, with third-party content to sophisticate and streamline teachers\u0026rsquo; assessment work while providing adaptive learning support optimized for individual students will open new frontiers in this field.\u003c/p\u003e\u003cp\u003eFinally, while this study was grounded in the perspective of the supply side (schools), education is an endeavor of diverse stakeholders. Therefore, expanding the research horizon to incorporate the perspectives of the recipients of support\u0026mdash;students and their guardians\u0026mdash;represents an extremely important future research challenge. What do students expect from on-demand learning formats? What difficulties and anxieties do they face in maintaining learning motivation, connecting with peers, and preserving their physical and mental health? Qualitative research is indispensable for preventing mismatches in support designed solely from a supply-side logic and for constructing a truly student-centered system.\u003c/p\u003e\u003cp\u003eThrough such multifaceted and developmental research, we are confident that we can overcome the structural challenge of the \u0026ldquo;support paradox\u0026rdquo; raised in this paper and contribute to realizing an inclusive educational environment where all students, regardless of their health status or geographical conditions, are guaranteed access to quality learning.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eAugmented Reality, Mixed Reality Experiential Learning: Transforming Educational Paradigms. (n.d.). \u003cem\u003eVirtual Reality\u003c/em\u003e.\u003c/li\u003e\n\u003cli\u003eBaskaran, V., Chubb, L. A., \u0026amp; Fouch\u0026eacute;, C. B. (2024). 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School reentry plans for students with chronic illness: \u003cem\u003eResearch, Advocacy, and Practice for Complex and Chronic Conditions\u003c/em\u003e, \u003cem\u003e41\u003c/em\u003e(1), 22\u0026ndash;44.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":true,"highlight":"","institution":"Okayama University","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":true,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"On-demand learning, Students with chronic illness, Implementation barriers, Credit recognition, Upper secondary education, Educational technology policy","lastPublishedDoi":"10.21203/rs.3.rs-7736679/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7736679/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eEnsuring educational rights for students with chronic illnesses is a critical challenge globally. While technology-enhanced distance education, particularly on-demand learning, offers promising solutions, implementation faces numerous barriers. Despite Japan’s GIGA School Program establishing digital infrastructure, adoption remains limited, necessitating urgent investigation of current conditions and challenges. This study conducted the first prefecture-wide survey of 88 high schools in Okayama Prefecture from November 2024 to January 2025 using telephone, email, and online questionnaires to assess student enrollment in long-term medical treatment, online class implementation status, implementation challenges, and acceptability of third-party educational content for academic credit. The results showed that 12.5% of the schools enrolled students requiring long-term medical treatment, with 11.4% having a history of such treatment. While 50.0% implemented only synchronous online classes, 25.0% offered on-demand formats, and 25.0% did not. Among the 60 schools that reported barriers to on-demand provision, the most frequently cited were difficulty accommodating practical/skills-based subjects (61.7%), insufficient human resources (60.0%), inadequate equipment or cloud infrastructure (41.7%), and internal regulations (11.7%). Notably, schools reporting internal barriers were far less likely to accept third-party on-demand modules for credit than those reporting no barriers (20.0% vs. 50.0%; Fisher’s exact p=0.0059; OR=0.25). More than a year after national guidance enabled credit recognition for on-demand learning, implementation remains limited, largely due to staffing constraints and subject-specific hurdles. To secure learning opportunities for students with chronic illnesses, education boards should establish clear evaluation criteria, governance, and quality-assurance frameworks for external resources that move beyond school-by-school efforts.\u003c/p\u003e","manuscriptTitle":"The Support Paradox in Japanese High Schools: Barriers to Credit Recognition for Third-party On-Demand Learning in Students with Chronic Illness","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-10-21 07:09:01","doi":"10.21203/rs.3.rs-7736679/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"9f842e3c-266c-42b4-bd79-77f2fc440682","owner":[],"postedDate":"October 21st, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[{"id":56575437,"name":"Social Policy"}],"tags":[],"updatedAt":"2025-10-21T07:09:01+00:00","versionOfRecord":[],"versionCreatedAt":"2025-10-21 07:09:01","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-7736679","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7736679","identity":"rs-7736679","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}