According to Simanullang and colleagues (2021, pp. 1–2), a Learning Management System (LMS) is a type of software commonly used to support digital learning. In simple terms, an LMS helps move many educational processes from manual to digital. According to Alshammari and colleagues (2018, pp. 455–456), an LMS serves as the core platform that organizes and manages educational content while also tracking and overseeing both academic and administrative learning activities.

Pimenko (2025) notes that Moodle continues to refine its features and improve overall stability, especially in versions 4.1 and 4.5. The platform also has several upcoming enhancements in the pipeline, such as deeper AI integration and a more streamlined, modern interface. Together, these developments highlight Moodle’s ongoing commitment to evolving its platform to meet the expectations of today’s digital learning environment.

This study provides essential guidance for HEIs on how to systematically understand stakeholder needs, categorize system features as core, advanced, and functional, and implement these features within a practical LMS model, specifically for this study the SCROLLE model.

The SCROLLE LMS offers 28 AI-assisted innovative features categorized as core, advanced, and functional. The KAT-Soft model facilitates the systematic categorization and phased modular implementation of these features, ensuring that stakeholders initially receive essential functionalities and progressively gain access to additional modules in alignment with implementation phases and their growing familiarity with the LMS.

The aim of this research is to develop and validate the KAT-Soft framework—an integration of the Kano model, TAM, and AI-enhanced TPACK—to systematically categorize and prioritize the functional requirements of the SCROLLE (Scalable Collaborative Role-based Outcome-focused Localized Learning Ecosystem) LMS for HEIs in Latvia, ensuring the platform meets specific stakeholder needs and localized digital requirements.

This article reports the findings and analysis of the author’s final doctoral research, conducted using the Kano method.

Gorbāns and Bierne (2013, p. 57) highlight a clear disconnect between what Moodle could offer as a modern learning tool and how it’s actually used in Latvian higher education. They call for broader, system‑level changes to unlock its full potential. Dzelme (2024, pp. 555–556) highlights a gap in Latvia’s education system and recommends making “Modern Educational Technologies” a mandatory subject that blends STEM with humanities, including AI ethics. It also calls for national AI guidelines to ensure fairness, reduce bias, and maintain human oversight, while using Latvia’s strong IT sector to test and refine AI tools for real classroom needs.

Tuchler (2021, pp. 323–325) highlights the importance of using technology in ways that genuinely improve interaction, clarity, and support for students. Purina‑Bieza and Sarva (2022, pp. 213–215) add that many educators in Latvia still prefer digital tools available in Latvian, even though Russian and English platforms are common. While foreign‑language tools may spark initial curiosity, they are often used less over time, suggesting that the shortage of Latvian‑language options limits the adoption of more advanced or interactive learning technologies.

Ansone (2024, pp. 179–180) points out that Latvian HEIs still face several overlooked barriers when adopting digital technologies, including skill gaps, limited IT training for faculty, and students arriving with very different levels of digital literacy. Purina‑Bieza and Sarva (2022, pp. 222–223) add that these challenges make localized solutions essential, emphasizing the need for a high‑quality LMS in Latvian to better support digital learning across institutions.

Considering the significant investments from both the EU and Latvia’s national budget in digital education and skills development, the environment is highly supportive for start‑ups looking to develop LMS solutions designed specifically for the needs of Latvian higher education.  

The survey, based on the Kano Model, comprised 28 paired question sets (S1–S28) to evaluate Latvian HEI stakeholders’ perceptions of proposed LMS features, measuring perceived functionality, potential dissatisfaction if absent, and overall importance for teaching and learning and policy. The analysis used responses from 105 participants to classify LMS features. Descriptive statistics were calculated for all functional, dysfunctional, and importance items across stakeholder groups. Skewness and kurtosis were assessed to check distribution patterns, and Pareto charts and interval plots highlighted feature priorities. Regression analysis and SEM modeling were applied to examine relationships within the LMS framework. Summary tables of mean scores provided a clear overview of the final Kano results. Model Evaluation Summary the SEM model demonstrates a strong balance between statistical fit, theoretical clarity, and overall stability, making it the most suitable model for this study. Model Fit: The structural model demonstrates a strong overall fit. The significant Chi Square result (χ² = 417.208, df = 283, p < .001) is expected in complex, unpaired datasets drawn from multiple professional groups, where higher model complexity is normal. Research Question: How does the Kano based KAT Soft framework, supported by the TAM model and the TPACK framework, help shape the design of the new LMS SCROLLE and influence how it is expected to be accepted within Latvia’s higher education institutions? Research Methods: literature on digital learning, LMS use, alongside an analysis of the Latvian HEI context and their use of platforms like Moodle. It also applied the TAM and TPACK frameworks to examine how technology is adopted and integrated in these institutions. Primary Data Collection: Interviews were held with key stakeholders—teachers, students, course designers, planners, and administrators—from Latvian HEIs. Questionnaires were also distributed to gather quantitative insights on LMS limitations and support the Kano analysis. Primary Data Analysis: The study used descriptive and inferential statistics to interpret survey results and compare stakeholder groups, along with content analysis of interview responses. Data validation was performed using JASP 0.19.3, while diagrams and graphs were created with Canva, Python prompts, Excel, and JASP. Research Process: Phase 1 gathers insights through qualitative work—literature review, context analysis, interviews, and workshops—to create and test pilot tools. Phase 2 uses these refined tools in a large‑scale survey to validate the findings and develop the KAT‑Soft framework, which then helps the final design of the SCROLLE LMS. Research period: November 2021 – December 2025.

Current LMS limitations show the need for SCROLLE and KAT Soft, which offer adaptive, user centred, and pedagogically aligned solutions. Latvian HEIs require a context sensitive, scalable LMS, and stakeholder demand confirms the need for a locally tailored platform like SCROLLE. KAT Soft directly shapes SCROLLE’s design. Educators, Teachers, Trainers, and Education Professionals 1. Advocate for a single, unified LMS to reduce training time and administrative workload. 2. Participate in SCROLLE development consultations to ensure the platform aligns with real teaching practices. Students and Learners 1. Provide structured feedback on LMS usability, including navigation issues and language barriers. 2. Advocate for one seamless digital platform where all course materials and communication are accessible in a single place. Management in Higher Education Institutions of Latvia 1. Conduct a full Total Cost of Ownership (TCO) audit to identify hidden costs in current digital systems. 2. Pilot SCROLLE in partnership with local EdTech developers to co-create a platform tailored to institutional needs. Policy Recommendations for the Ministry of Education and Science of Latvia 1. Allocate EUR 500,000 from the Digital Transformation Budget to support domestic EdTech development. 2. Create a national licensing framework for SCROLLE, enabling all HEIs to adopt it under one agreement and reduce costs by up to 75%. Business Prospect: The long term goal for SCROLLE is to grow from a research project into a sustainable, commercially viable EdTech solution. By 2030, it aims to become a global example of localized, AI driven, inclusive digital learning—competing with major platforms while showcasing Latvian innovation. It supports national digital transformation efforts and turns academic research into a scalable, high impact business.

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