Psychological Foundations for Effective Human–Computer Interaction in Education

Abstract

This paper investigates the integration of emotional, cognitive, and interactional processes in the design of educational technologies through the lens of Human–Computer Interaction (HCI). While previous studies have focused on cognitive and interactional engagement, emotional engagement remains underdeveloped in many tools, limiting learning effectiveness. To bridge this gap, this study proposes a theoretical holistic framework integrating usability, emotional intelligence, and adaptive interaction. Through a qualitative analysis, we examine educational platforms—including Duolingo, Khan Academy, and Google Classroom—alongside simulation-based systems such as EduTechRPGs. The study applies Cognitive Load Theory, Emotional Intelligence Theory, and Self-Determination Theory to assess their effectiveness. The findings highlight the importance of designing emotionally intelligent, scalable, and adaptive learning environments, and the proposed framework integrates psychological principles to boost engagement, motivation, and learning outcomes. This study contributes to a learner-centered HCI approach, ensuring that educational technologies support both cognitive and emotional development. Future research should validate the proposed framework empirically and explore interdisciplinary approaches to optimize educational technology. This study highlights the role of HCI in creating meaningful digital learning experiences by integrating psychology, cognitive science, and user experience design.

1. Introduction

Human-Computer Interaction (HCI) is an interdisciplinary field dedicated to designing intuitive, effective, and user-friendly computing systems [1,2]. In the educational domain, HCI ensures that learning technologies are accessible, adaptive, and engaging, drawing from design, computer science, and psychology [3]. As digital technologies continue to shape teaching and learning, it is crucial to develop interactive systems that not only support educational goals but also adapt to user behaviors and psychological needs.

This study highlights the importance of integrating emotional, cognitive, and interactional dimensions into HCI to create effective educational experiences. Previous research has examined usability and cognitive engagement in educational technologies [4,5], highlighting the fact that emotional engagement remains a significant challenge. Many current educational platforms do not fully meet learners’ affective and motivational needs, which can lead to disengagement, cognitive overload, and learning experiences that are not fully effective.

This study proposes a framework incorporating psychological principles into HCI design to bridge this gap, focusing on usability, motivation, and engagement [6,7,8,9,10] in educational technology. However, it is crucial to note that this study provides a theoretical proposal for a framework rather than a fully implemented model, serving as a conceptual guideline for future empirical research.

This paper has the following aims: (i) examine the limitations of existing educational technologies in addressing emotional engagement, (ii) investigate how psychological principles can be effectively integrated into HCI design for education, and (iii) propose the development of a framework to enhance user experience and learning outcomes within educational platforms.

Recent research underscores the transformative potential of AI-driven tools like ChatGPT [11], which enable adaptive and personalized learning experiences. However, challenges remain regarding the ability of these systems to effectively recognize and respond to learners’ emotional needs, a crucial aspect enabling long-term engagement [12].

HCI plays a crucial role in shaping learning technologies like Google Classroom, ensuring that they support meaningful interaction, engagement, and adaptability [13,14,15]. By incorporating insights from psychology, cognitive science, and user experience design, HCI plays a critical role in developing learner-centered, adaptive solutions that cater to diverse educational needs.

This study does not represent a systematic analysis or literature review. It instead introduces a theoretical framework to address existing gaps in educational HCI models that need future empirical validation to assess its effective practical implementation.

To achieve this, we analyze platforms developed and implemented within our research group, providing concrete examples of their application in the following sections. Additionally, among the wide range of available educational technologies, we have deliberately selected commercial platforms that emphasize framework-related aspects (e.g., Duolingo, Google Classroom, and Khan Academy), distinguishing them from MOOC-oriented platforms, which often do not address these aspects [16,17,18,19].

The platforms we developed were designed exclusively for educational purposes and based on psychological models to enhance users’ learning of specific competencies. A key example is EdutechRPGs (Educational Technology Enhanced Role-Playing Games), which integrate virtual agents to enable emotionally intelligent interactions that foster engagement, collaboration, and critical thinking [20].

This study employs a qualitative research approach to evaluate psychological factors influencing HCI in educational settings, including three interconnected components: (i) exploration of HCI, psychology, and educational technology literature to identify gaps in existing frameworks; (ii) analysis of widely used educational platforms (e.g., Khan Academy, Duolingo, and Google Classroom) and simulation-based systems (e.g., EdutechRPGs) to examine their cognitive, emotional, and interactional design elements; and (iii) application of psychological principles—including Cognitive Load Theory [6,7], Emotional Intelligence Theory [8], and Self-Determination Theory [9,10]—to propose a user-centered design model for educational technologies.

Despite their transformative potential, many HCI tools fail to address learners’ emotional and social needs, often resulting in disengagement, cognitive overload, and suboptimal learning outcomes. To address these challenges, this paper proposes a holistic framework that integrates HCI tools with psychological principles to enhance learning experiences and ensure that educational technologies effectively support both cognitive and emotional development.

The proposed framework aims to enhance educational technologies such as learning management systems (LMS), gamified platforms, and virtual learning environments (VLEs) by ensuring they are designed in alignment with key psychological principles: motivation, cognitive load management, and emotional engagement [20,21].

The psychological theories selected have been prioritized for their direct relevance to HCI in educational contexts and their strong empirical foundation in shaping user experience and learning effectiveness [22,23,24,25]. By contrast, behaviorist and social learning theories, while effective in some contexts, are not the most suitable for a user-centered model in educational technology [26,27,28].

Crompton et al. [5] emphasize the importance of integrating HCI principles with pedagogy to ensure that educational technologies enhance usability and improve learner interactions, experiences, and outcomes. This study builds on this perspective by examining the interplay between emotional, cognitive, and interactional processes and HCI, ultimately proposing a framework that bridges technological design and learners’ psychological needs.

Through this approach, the study promotes the development of adaptive, learner-centered tools that balance cognitive demands, fostering emotional engagement. These insights align with established psychological principles [6,7,8,9,10] that are fundamental in shaping effective educational technologies [4]. By integrating cognitive, emotional, and social dimensions, this research aims to optimize how digital learning tools are harmonized with how individuals think, feel, and interact.

In conclusion, educational environments—physical or digital—are not just spaces, but dynamic contexts in which learning is actively constructed. From traditional classrooms to MOOCs and serious games, HCI plays a pivotal role in shaping learners’ engagement with content. By embedding adaptive and interactive technologies, HCI creates immersive educational experiences that cater to diverse learner needs [29]. This perspective underscores the transformative potential of technology when grounded in a deep understanding of human psychology and educational best practices [30,31].

We begin our work by describing the psychological models that, as introduced earlier, we have selected for their relevance in understanding engagement and learning in digital environments and their suitability for addressing the challenges of HCI in educational tools and systems.

More specifically, we identify key psychological aspects to consider when designing an effective HCI framework for education. We then outline a preliminary version of this framework and present case studies, based on a literature review and our research, to illustrate how the framework can be implemented in practice.

2. Psychological Models

2.1. Psychological Theories on Cognitive and Emotional Bases of Learning

Some well-established psychological models play substantial roles in shaping the design of educational technologies, as they provide a skeletal framework to understand the psychological mechanisms that underpin users’ learning and engagement. Among these, Goleman’s Emotional Intelligence framework [8], Cognitive Load Theory [6,7], and Self-Determination Theory [9] emerge as particularly powerful tools for designing engaging and effective educational technologies.

As Goleman proposed, emotional intelligence refers to the ability to recognize, understand, and manage emotions. This ability is crucial for the design of adaptive tools that can detect user frustration, apathy, and other emotional states.

Further psychological models such as Cognitive load theory [4,7] and Motivation theory [9,10,32,33] expand the understanding of psychological factors in educational technology. Cognitive load theory posits that as the cognitive capacity of learners is limited, thus they need instructional materials that can optimize cognitive processing. These theories distinguish between intrinsic load (complexity inherent in the material), extraneous load (unnecessary cognitive demands), and germane load (efforts contributing to meaningful learning). Moreover, effective educational technologies can be applied by the use of scaffolding techniques to minimize the extraneous load and maximise the germane load, ensuring that learners can focus on processing and acquiring new information. Motivation theory, particularly Deci and Ryan’s Self-Determination Theory [9], explores the psychological drivers of engagement, emphasizing intrinsic motivators such as relatedness and autonomy.

By integrating the Emotional Intelligence framework with the Cognitive Load and Motivation Theories, educational technologies can effectively address the emotional and cognitive dimensions of learning. Indeed, this approach enhances user engagement, satisfaction, and learning outcomes by ensuring that educational tools are both emotionally supportive and cognitively accessible. Moreover, these technologies foster intrinsic motivation by aligning with learners’ psychological needs, such as autonomy and competence, reducing frustration and cognitive overload through thoughtful design. As a result, such integrations pave the way for a more effective, meaningful, and sustainable integration and implementation of Human-Computer Interaction within educational contexts.

Learning theories provide foundational insights regarding how individuals acquire and process knowledge and provide the basis for effective educational technology design. The most influential include Constructivism, Behaviorism, and Situated Learning.

2.2. Learning Theories

Constructivism, supported by Vygotsky [34], posits that knowledge is actively constructed by the learner’s engagement with their environment and peers. This approach strongly accords with educational technologies that emphasize hands-on, experiential learning. Behaviorism [35] focuses on the roles of reinforcement and feedback in shaping behaviours and the learning processes. Many educational technologies embody behaviorist principles using immediate feedback and reward systems to favour desirable learning objectives. Situated Learning Theory [36] asserts that learning is most effective when occurring in authentic contexts of practice. This theory has inspired the design of educational technologies that embed learners in realistic scenarios, enabling them to acquire knowledge and skills within meaningful contexts. In summary, educational technologies can create enriched learning environments that address diverse psychological needs by integrating insights from Constructivism, Behaviourism, and Situated Learning. These theories offer a framework for designing tools that deliver knowledge and promote active engagement, critical thinking, and meaningful real-world applications.

3. Psychological Factors in HCI

Building on previous discussions of HCI, this section explores psychological factors influencing how learners interact with technology, emphasizing emotional, cognitive, and interactional engagement. We refer to these factors as ECI in HCI, and these are factors which form the foundation of our framework. These factors, along with considerations for designing effective educational technologies and the methods for doing so, are summarized in

Table 1. ECI in HCI: The first column presents the psychological factor, the second column (What) outlines the main elements associated with each factor, the third column (How) describes how these elements can be implemented in educational technologies, and the fourth (Educational Platforms) provides examples based on case studies.

Psychological Factors	What	How	Examples of Educational Platforms
Emotions	- Positive emotions: curiosity, satisfaction, enjoyment - Negative emotions: frustration, anxiety, boredom	- Systems with emotional intelligence - Adaptive tools that detect and respond to users’ emotional states	- EduTechRPG (ENACT, ACCORD, S-Cube, CODINC): Emotionally intelligent virtual agents provide tailored guidance and feedback to regulate emotions and sustain motivation, as well as manage conflict resolution. - Hyper-Activity Books: Blend digital and physical elements to foster curiosity and reduce anxiety.
Cognition	- Retention of information in memory - Attention management - Maintaining an adequate cognitive load	- Tools that prevent cognitive overload by managing information density - Scaffolding: breaking down complex tasks into manageable steps - Chunking: grouping information into meaningful units	- Khan Academy: Step-by-step instructional design with personalized learning paths. - Duolingo: Uses adaptive learning and spaced repetition to enhance memory retention. - Hyper-Activity Books: Integrate digital and physical interactions to reinforce learning.
Interaction	- User–system interactions - Peer interaction: collaboration, dialogue, mutual feedback	- Real-time feedback mechanisms - Gamified collaboration features - Social learning components	- Google Classroom: Facilitates peer interaction, discussions, and collaborative learning. - S-Cube (EduTechRPG): Multiplayer role-playing games for training soft skills in collaborative settings. - ENACT; ACCORD: Provide real-time personalized feedback through emotionally intelligent virtual agents, supporting users in negotiation and conflict resolution scenarios. - CODINC: Coding and robotics tools promoting problem-solving and collaborative learning.

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Emotions significantly shape learners’ engagement with educational technologies. Positive emotions such as curiosity, satisfaction, and enjoyment foster intrinsic motivation, sustain engagement and improve learning outcomes. Conversely, negative emotions like frustration, anxiety, or boredom can create barriers to effective learning.

Systems designed with emotional intelligence, capable of detecting and adapting to users’ emotional states, have demonstrated effectiveness in maintaining learners’ motivations and reducing frustration; evoking positive emotions and mitigating negative ones creates enriching and supportive learning environments. Furthermore, adaptive interfaces that track emotional metrics are crucial to adjusting content delivery in real time and to sustaining emotional engagement [37,38,39].

Cognitive Processes encompass how learners process information, retain it in memory, and sustain attention while they interact with educational technologies. These processes are fundamental in supporting cognitive engagement, and their optimization is essential for effective learning outcomes. As reported above, Cognitive Load Theory [6,7] highlights the need to balance information complexity so that learners do not feel overwhelmed or bored. Tools designed with this principle aim to manage information density, reduce cognitive overload, and maintain adequate cognitive stimulation. Effective educational technologies leverage mechanisms such as scaffolding (breaking down complex tasks into manageable steps) and chunking (which enhances memory retention by grouping information into meaningful units).

Interactional processes focus on the role of interactions both between users and systems or among peers in the promotion of learning. Effective HCI facilitates collaboration, dialogue, and mutual feedback, which is crucial for learning which is deeper and more meaningful, as well as for skill development.

Features like real-time feedback, gamified collaboration, and social learning components foster engagement by promoting active participation and a sense of community.

ECI in HCI and User Engagement

Integrating psychological principles into Human-Computer Interaction (HCI) allows the design of educational technologies that create meaningful learning experiences and favour user engagement. Emotional, cognitive, and interactional engagements represent key factors defining how learners interact with digital tools, and thus influencing their motivation and collaboration.

Emotional engagement plays a vital role in how learners connect with educational tools. As highlighted earlier, positive emotions, such as curiosity, joy, and satisfaction, enhance motivation and persistence, while negative emotions, like frustration and anxiety, can disrupt learning.

As Goleman’s Emotional Intelligence framework [8] underscored, recognizing and managing emotions in educational settings is pivotal in fostering meaningful and effective learning experiences. Indeed, tools that dynamically respond to users’ emotional states can help reduce frustration, sustain motivation, and foster resilience.

Cognitive engagement refers to the alignment between educational technologies and learners’ mental processes, including attention, memory, and cognitive load. Sweller’s Cognitive Load Theory [6,7] argues that learning tools should balance the complexity of information to avoid overwhelming learners while providing enough challenges and stimulating growth.

Memory and attention are also critical components of cognitive engagement. Effective tools use chunking, scaffolding, and repetition to improve memory retention. Situated learning environments, such as those described by Dell’Aquila et al. [20], immerse learners in realistic contexts that encourage critical thinking and problem-solving. Gamification elements, such as leaderboards and progress tracking, support cognitive engagement by providing rewards and challenges that maintain focus and effort.

Interactional engagement emphasizes collaboration and active participation. Features like real-time feedback, peer collaboration tools, and gamification encourage meaningful interactions, fostering dialogue, teamwork, and social learning.

As explored by Ponticorvo et al. [40], situated learning environments immerse learners in realistic scenarios in which they collaborate with peers and systems to solve practical problems, enhancing both interactional and cognitive engagement.

In the next section, we will explore how to integrate and align psychological factors with technological design to create a more effective and engaging user experience.

4. Bridging Psychological Factors and Technological Design

Integrating psychological factors into the design of educational technologies remains a critical challenge. Indeed, many existing systems cannot adequately address the cognitive, emotional, and interactional dimensions of learning that we have discussed earlier. In this section we explore these challenges, propose key design principles informed by psychological theories and models, and examine how usability and learning effectiveness can be enhanced through user-centered approaches in which the interplays among users, tasks, and environment shape the design process.

One key challenge lies in addressing the emotional dimension of learning. Indeed, many systems are not designed to detect or adapt to learners’ emotional states, such as frustration, boredom, or anxiety, which are typical in environments characterised by excessive learning pressure. Another major challenge is cognitive overload, when complex systems present excessive amounts of information, leading to mental fatigue and disengagement [37]. For instance, unintuitive navigation or poor instructional design often overwhelm users, reducing their ability to retain information effectively. On the other hand, technologies that are simplistic or lack adaptive features may fail to stimulate curiosity and critical thinking, resulting in under-stimulation and diminished engagement [41].

The interaction level can also present challenges, as educational tools—such as digital platforms—often have complex interfaces that make navigation and usability difficult for learners. These challenges fall within the User Experience (UX) domain, one which plays a crucial role in the design and development of educational tools. Poor UX can lead to frustration and negatively impact learning outcomes.

Moreover, effective learning often relies on interaction with peers and instructors. However, some platforms lack robust collaborative tools, making group work and discussions less effective.

It is essential to incorporate psychological-theory-based concepts into the design process to address these challenges. In the following subsections, we will explore these aspects in detail.

4.1. Design Concepts Based on Psychological Theories

Adopting design principles grounded in well-established psychological models, such as Vygotsky’s Zone of Proximal Development (ZPD) and scaffolding techniques [34], Norman’s Emotional Design Theory [42], and Self-Determination Theory [9], can serve as a guide in overcoming learning challenges and align educational technologies with learners’ psychological needs. As emphasized throughout the discussion, these principles must address ECI—emotional, cognitive, and interactional—dimensions to ensure a holistic approach that fosters users’ engagement and learning effectiveness.

Vygotsky’s ZPD provides a foundational framework for scaffolding learners’ experiences. It represents the distance between what a learner can accomplish unsupported and what they can achieve with the assistance of adult guidance or more knowledgeable people. Thus, it highlights the potential for growth through guided learning and collaboration, in which assistance helps the learner progress to a higher order of understanding or skill, and educational technologies can enhance cognitive engagement by adapting tasks to learners’ skill levels by gradually increasing complexity without overwhelming them.

Norman’s Emotional Design Theory emphasizes the importance of aesthetically attractive and emotionally resonant interfaces. The theory defines three different levels of analysis comprising interconnected levels of emotional interaction with the design: visceral (involving biologically based reactions involving initial sensory impressions and the aesthetic appeal of objects, and resulting in negative or positive feedback); behavioural (focusing on functionality and the satisfaction derived from ease of use—the feeling of control); and reflective (relating to deeper personal meaning, self-awareness, and identity, as influenced by experience and culture). These levels influence how users emotionally connect with objects and value a product.

According to Mayer’s multimedia design principles (e.g., the segmentation and coherence principles), educational technologies can enhance learners’ ability to engage with complex material effectively, fostering deeper comprehension and retention [21].

Self-Determination Theory (SDT) examines the impacts of social environments on natural motivation and the integration of external incentives into personal values. As previously described in this work, this framework helps researchers to understand human motivations differentiated among three basic psychological needs, namely, autonomy (acting with a full sense of volition), competence (experience of mastery and efficacy), and relatedness (connection to other people in a meaningful way), highlighted as essential motivators in sustaining engagement [9,10]. Educational technologies incorporating gamification elements, such as leaderboards, badges, and progress tracking, align with these principles to boost motivation and user satisfaction. The findings of this study demonstrate that educational technologies can be enhanced by the alignment of design principles with psychological processes.

4.2. Usability and Learning Effectiveness

As we have hinted, usability principles, such as clear and intuitive interfaces, are critical in reducing cognitive load and enabling learners to focus on educational content rather than be distracted by technical navigation. Building on this foundation, adaptive systems that respond dynamically to real-time user feedback further enhance usability.

Usability must be seen as a multi-dimensional concept that integrates cognitive simplicity, emotional engagement, accessibility, and collaborative functionality. By applying these principles holistically, educational technologies can bridge the gap between usability and learning effectiveness, delivering learning experiences that are more inclusive, engaging, and impactful.

In the Case Studies section, we will examine how these principles can be applied in practice within the framework and provide examples of their implementation.

5. A Framework for Enhancing Educational Technologies

The design and implementation of educational technologies must be guided by a robust, comprehensive framework that integrates key psychological factors—emotional, cognitive, and interactional processes—as components essential to creating an engaging and meaningful user experience.

In this section, we outline the core elements of a framework, summarized in

Table 2. Framework for effective interaction in educational technology. The first column presents core components of the proposed framework; the second, the key theories supporting each dimension; the third details their key elements; and the fourth provides examples of educational platforms that apply these principles.

Core Components	Key Theories	Key Elements	Examples of Educational Platforms
Integration of Emotional Processes	- Norman’s Emotional Design Theory (2004) [42] - Self-Determination Theory [9,10,43]	- Evoking positive emotions (curiosity, satisfaction, confidence). - Supporting intrinsic motivation (autonomy, competence, relatedness). - Creating a supportive environment to reduce anxiety and build resilience.	- EduTechRPG (ENACT, ACCORD, S-Cube, CODINC): Uses emotionally intelligent virtual agents to adapt to users’ emotional states, providing tailored guidance, fostering motivation, and reducing frustration. - Hyper-Activity Books: Combine physical and digital interactions to stimulate curiosity and alleviate anxiety, reinforcing emotional engagement.
Alignment of Cognitive Processes	- Cognitive Load Theory [7] - Mayer’s Multimedia Learning Theory [4]	- Managing cognitive load. - Breaking down tasks into manageable steps. - Adapting content to learner’s pace and capabilities. - Ensuring focus on essential and generative processing.	- Khan Academy: Implements personalized learning pathways with structured scaffolding to manage cognitive load. - Duolingo: Uses adaptive learning and spaced repetition to enhance memory retention and sustain attention. - Hyper-Activity Books: Enhance memory retention through experiential learning, supporting cognitive engagement.
Enhancement of Interactional Processes	- Social Learning Theory [44] - Situated Learning Principles [36] - Dual-Channel Theory [21]	- Encouraging collaboration, dialogue, and active participation. - Implementing real-time feedback, gamification, and collaborative tools. - Supporting multimedia design to prevent cognitive overload. - Developing problem-solving and teamwork skills.	- Google Classroom: Facilitates peer collaboration, discussions, and project-based learning. - S-Cube (EduTechRPG): Multiplayer simulation games designed for training soft skills, negotiation, and teamwork. - ENACT; ACCORD (EduTechRPG): Single-player simulation games designed for training soft skills, negotiation, and teamwork. - CODINC: Uses coding and robotics to promote collaborative learning and problem-solving skills.

and pictured in Figure 1, that emphasizes the alignment of technological design with the specific psychological needs of learners. The framework aims to foster deeper engagement and improve learning outcomes by addressing these factors.

5.1. Integration of Emotional Processes

At the framework’s core lies the integration of emotional design principles inspired by Norman’s Emotional Design Theory. Interfaces must evoke positive emotions such as curiosity, satisfaction, and confidence to motivate and engage learners. Self-Determination Theory [10,43] highlights the determination that fostering intrinsic motivation requires meeting the three key psychological needs of autonomy, competence, and relatedness, which are essential for enduring engagement, enhanced motivation, and ultimately improved educational outcomes (Figure 1). Indeed, educational tools can help learners overcome anxiety and build resilience by creating a supportive emotional environment, as evidenced by games and simulation platforms.

5.2. Alignment of Cognitive Processes

The cognitive dimension of the framework draws on Cognitive Load Theory, promoting a balance between intrinsic, extraneous, and germane cognitive loads. Educational technologies should scaffold learning by breaking down complex tasks into manageable steps and adapting content delivery to the learner’s pace and capabilities. According to Sweller [7] and Mayer [4], balancing cognitive load is crucial in educational technology design, as it ensures that learners can focus their limited cognitive resources on essential and generative processing, thus enhancing comprehension and retention (Figure 1).

5.3. Enhancement of Interactional Processes

Interactional processes emphasizing collaboration, dialogue, and active participation are central to this framework (Figure 1). The framework draws on Social Learning Theory and Situated Learning Principles [36,44], thus incorporating interactive features like real-time feedback, gamification, and collaborative tools. The proposed framework also aligns with Mayer’s Dual-Channel Theory, which explains that people process verbal and visual information separately, have a limited capacity to process information, and actively process material for meaningful learning. These principles highlight the need for a multimedia design that supports rather than overwhelms learners [21]. These interactive features enhance user engagement and help learners develop critical skills such as problem-solving and teamwork [45].

6. Implementation of the Framework and Case Studies

This integrated framework applies psychological principles to the design of engaging, user-friendly educational technologies. By holistically addressing emotional, cognitive, and interactional dimensions, educational technologies can effectively bridge the gap between theoretical learning models and practical applications, fostering meaningful and impactful learning experiences. Table 1 and Table 2 reference the framework to the case studies to connect the proposed framework with its potential implementations.

The framework represents a guideline for designing and improving educational technologies, ensuring that they align with learners’ psychological and cognitive needs. It emphasizes the importance of adaptive learning, emotional intelligence, and social interaction, all of which contribute to sustained engagement and optimal learning outcomes. To demonstrate its applicability, this section examines selected platforms developed within our research group, alongside commercial educational platforms that align with the psychological principles outlined in our model, incorporating the above-mentioned psychological theories.

Two main categories of educational technologies are explored: platforms developed within our EU research projects (i.e., Enact, Accord, S-cube, HAB, and Codinc) and commercial platforms widely used in educational contexts (i.e., Google Classroom, Khan, and Duolingo).

6.1. EU-Project Educational Platforms

EduTechRPGs (ENACT, ACCORD, and S-Cube) are interactive role-playing games designed to enhance soft-skills training through simulation-based learning [41,46,47,48].

Several EU-funded projects have leveraged this framework to enhance education through simulation-based learning. Examples include the following:

• ENACT: Focuses on training negotiation and communication skills through AI-driven role-playing games that simulate real-life conflict resolution scenarios.
• SG-ACCORD: Specializes in intercultural conflict resolution; players engage in interactive simulations to develop their ability to manage diverse social interactions effectively.
• S-Cube: A multiplayer role-playing game that promotes collaboration, teamwork, and strategic decision-making in professional and educational contexts.
• CODINC: A role-playing platform that promotes digital inclusivity, catering to learners from diverse cultural and linguistic backgrounds.
• Hyper-Activity Books (HABs): Multisensory educational tools that integrate tactile and visual elements, improving accessibility for learners of varying abilities.

The design of these EU-funded educational platforms is deeply rooted in established psychological frameworks, particularly Cognitive Load Theory, Emotional Intelligence Theory, and Self-Determination Theory. These theories collectively shape the pedagogical strategies implemented within these platforms, ensuring an effective and immersive learning experience. More specifically, the methodology for creating valid and effective learning experiences in Educational Technology-Enhanced Role-Playing Games (EduTechRPGs) is structured within three interconnected layers: Visible, Hidden, and Evaluation [20,39,40,46]. This multi-layered architecture makes EduTechRPGs immersive, adaptive, and effective, bridging theory and practice in aid of real-world skill development.

• Visible layer—the gameplay and narrative that the player directly interacts with, including dialogue choices, character interactions, and immersive visual elements. This layer ensures engagement and provides realistic, scenario-based learning experiences.
• Hidden layer—the underlying pedagogical and psychological models that shape in-game decision-making and character behaviors. It embeds theories such as negotiation, assertive communication models, and emotional intelligence principles, ensuring that every interaction aligns with learning objectives. The identified psychological theory (i) defines AI-driven avatars’ responses, (ii) shapes dialogue and non-verbal cues, and (iii) ensures that AI avatars display realistic facial expressions and body language and use an appropriate tone of voice.
  This layer operates in the background, but directly influences the player’s experience. Though not explicitly visible, the Hidden layer affects game dynamics, guiding the player toward real-world applicable skills through contextualized decision-making.
• Evaluation layer—the assessment and feedback system, which tracks the player’s actions, evaluates their soft skills, and provides personalized feedback based on their choices. This layer actively monitors, assesses, and provides feedback to reinforce learning through the following means:
  • Real-time AI-driven reactions help players understand the immediate impacts of their choices.
  • Post-scenario reports break down strengths, areas for improvement, and alternative strategies.
  • Learning analytics track behavioral trends, enabling AI tutors to adjust difficulty levels and suggest improvements.

This layer ensures that players receive structured insights on communication effectiveness, progressively refining their skills.

In summary, while the Visible layer presents engaging gameplay through dialogue-based scenarios, the Hidden layer ensures that the role-playing interactions reflect real-world communication and negotiation models. Meanwhile, the Evaluation layer provides structured feedback that helps players refine their skills through iterative learning. The integration of these layers bridges theoretical knowledge and practical and transferable applications, enhancing engagement, learning outcomes, and long-term skill retention.

Although the Codinc [37] and HAB [39] platforms are distinct from EdutechRPGs, they adopt the same layered approach to enhance the educational process dynamically.

While distinct from role-playing games, these platforms integrate the layered approach to optimize cognitive, emotional, and interactional engagement. CODINC utilizes structured challenges and collaborative problem-solving to reinforce learning, while HABs enhance accessibility through multisensory interaction. Each platform employs the three layers uniquely to tailor learning pathways, optimize feedback, and engage users dynamically.

6.1.1. Cognitive Engagement in EU Educational Platforms

The EU-funded projects apply cognitive engagement strategies by balancing cognitive load and knowledge retention through the following means:

• ENACT and SG-ACCORD dynamically adjust difficulty levels based on learners’ progress, preventing cognitive overload. This process is mediated by the Hidden and Evaluation layers, which personalise interactions by dynamically modifying game scenarios, character responses, and challenges based on player decisions.
• CODINC incrementally structures problem-solving activities to enhance logical reasoning and computational thinking. The Evaluation layer provides continuous assessment, analyzing user progress and adjusting task complexity in real time.
• HABs integrate multisensory learning techniques to strengthen memory retention and conceptual understanding. The Visible layer facilitates engagement through interactive, real-world-inspired learning environments that optimize cognitive load.

6.1.2. Emotional Engagement in EU Educational Platforms

Emotional intelligence is central to EduTechRPGs, as seen in the following applications:

• In ENACT and SG-ACCORD, virtual agents detect users’ emotions through the Hidden layer and provide adaptive feedback via the Evaluation layer to maintain motivation. Based on detected engagement levels, the system can modify dialogue tone, narrative complexity, and encouragement strategies.
• S-Cube fosters emotional resilience through challenging yet rewarding collaboration tasks. The Hidden layer ensures that task difficulty and interpersonal interactions remain emotionally engaging without causing frustration.
• HABs provide an engaging, anxiety-free environment that enhances curiosity and positive learning experiences. The Visible layer incorporates interactive visuals, physical activities, and audio feedback to foster positive emotional states during learning.

Embedding emotional intelligence principles across the three layers enables personalized engagement, allowing users to feel supported while tackling complex challenges.

6.1.3. Interactional Engagement in EU Educational Platforms

Interactional engagement is a crucial component of these EU projects:

• S-Cube uses multiplayer role-playing mechanics to foster teamwork and negotiation skills. The Hidden layer governs the behavior of AI-driven non-player characters and real-time interactions between human players, ensuring realistic social engagement.
• CODINC promotes collaborative coding, encouraging peer learning and knowledge exchange. The Visible layer ensures that interaction tools are engaging, intuitive, and adaptable within different group dynamics.
• ENACT and ACCORD integrate realistic social scenarios in which players engage in negotiation-based interactions, mirroring real-world conflict resolution. The Hidden layer dynamically models interpersonal behaviors, adapting responses based on user interaction styles, while the Evaluation layer tracks communication strategies and provides structured feedback for improvement.

By addressing cognitive, emotional, and interactional engagement through the Visible, Hidden, and Evaluation layers, these platforms provide holistic learning experiences, making educational technologies more effective, personalized, and engaging for diverse learners.

6.2. Commercial Platforms in Educational Contexts

The methodology for enhancing learning experiences in commercial educational platforms relies on integrating different engagement strategies. However, unlike EU-funded platforms that systematically address cognitive, emotional, and interactional engagement, commercial platforms primarily integrate key psychological principles to improve learning effectiveness. Their approach to engagement, however, is often fragmented, comprising a primary focus on cognitive engagement, some incorporation of interactional engagement, and limited emphasis on emotional engagement. While gamification and adaptive learning methods help sustain motivation, emotional engagement remains less explicitly developed. Thus, they apply Cognitive Load Theory, Emotional Intelligence Theory, and Self-Determination Theory to varying extents. Some notable examples include [49,50,51]:

• Khan Academy: A free online platform offering structured lessons and adaptive learning pathways to support personalized education.
• Google Classroom: A learning management system that facilitates communication, collaboration, and assignment management in digital classrooms.
• Duolingo: A gamified language-learning platform that employs spaced repetition, adaptive feedback, and motivational elements to enhance engagement and retention.

Cognitive, Emotional, and Interactional Engagement in Commercial Platforms

Categorizing commercial platforms based on their support for cognitive, emotional, and interactional engagement helps clarify their strengths and limitations. While some platforms, such as Google Classroom and Duolingo, incorporate cognitive and interactional engagement through structured learning environments and gamified collaboration, emotional engagement remains largely unaddressed. Others, like Khan Academy, primarily focus on cognitive engagement, with minimal opportunities for interaction or emotional support.

• Duolingo: Designed primarily for language learning, Duolingo integrates cognitive engagement through adaptive learning pathways and spaced repetition algorithms. Motivational features like streaks, rewards, and gamified challenges help sustain user engagement. However, while these features support motivation, they are not explicitly structured for the true emotional engagement seen in EU-funded platforms. Additionally, its interactional engagement is limited to leaderboard-based competition rather than meaningful peer collaboration.
• Google Classroom: Enhances cognitive engagement by organizing lessons and assignments systematically. It supports interactional engagement through discussion boards, collaborative documents, and peer feedback. While it does not explicitly target emotional engagement, it fosters a supportive learning environment through teacher–student interactions and structured collaboration.
• Khan Academy: Focuses heavily on cognitive engagement through mastery-based progression and structured scaffolding. Its self-paced learning approach reduces stress and frustration, indirectly supporting emotional engagement. However, its interactional engagement remains minimal, as it lacks extensive peer collaboration tools beyond teacher-assigned tasks.

While effective in structured content delivery, many commercial learning tools do not incorporate the same depth of psychological modelling seen in EU-funded projects. They often lack adaptive emotional responses or interactive social mechanisms that actively shape learning experiences based on user behavior and engagement patterns.

This distinction underscores the differences between commercial and EU-funded platforms. The latter are specifically designed to integrate all three engagement dimensions more comprehensively, creating a strong synergy between theoretical learning and practical, real-world applications [52].

6.3. Considerations for Adoption and Scalability

Cost considerations are critical to the successful adoption of advanced educational technologies and demonstrate how collaborative interdisciplinary partnerships between educational institutions, small enterprises, game designers, and technology developers can achieve cost-efficient solutions without compromising psychological design principles. Indeed, the social impact of our work lies in making education inclusive and accessible to everyone, breaking down barriers of all kinds, including geographical, economic, and social, and thus creating learning opportunities that are equitable and universally available.

Ensuring accessibility is a fundamental step toward equitable education for all learners. Educational technologies should be designed to accommodate diverse needs, including those of individuals with disabilities, limited digital literacy, or geographical barriers that restrict access to traditional educational resources. Designing inclusive learning environments means integrating features such as multilingual interfaces, assistive technologies, and intuitive navigation, ensuring that learners of all backgrounds and abilities can fully engage with digital learning platforms.

Scalability is another crucial factor in ensuring widespread adoption of the framework. Adaptive systems like those used by Khan Academy and Duolingo exemplify scalable solutions, employing algorithms that personalize content for all users. Simulation games developed under the S-Cube project offer similar scalability for soft-skill training using virtual agents and a cloud-based delivery system. Integrating such scalable technologies into formal education systems could help to enable their wide reach.

Scalability is another key consideration in determining the widespread adoption of these frameworks. Adaptive learning systems, such as those used by Khan Academy and Duolingo, are prime examples of scalable solutions that leverage algorithms to personalize content for individual learners, making high-quality education accessible on a large scale. Similarly, simulation-based training games developed under the S-Cube project offer scalability in soft-skills training by using virtual agents and cloud-based delivery systems, allowing a wide reach across different educational contexts. The integration of these scalable solutions into formal education systems has the potential to enhance learning accessibility and produce global impacts.

The successful implementation of these technologies depends not only on their design but also on teacher training and institutional support. Educators must be provided with the skills and resources necessary for seamlessly integrating these tools into their teaching practices, ensuring alignment with broader educational objectives. Initiatives like the Accord MOOC, designed for intercultural conflict management, provide scalable training units for teachers, enabling them to use emotionally and cognitively intelligent tools to enhance their classroom practices. Furthermore, testing these frameworks in diverse educational settings—particularly in underserved communities—is essential for evaluating their real-world applicability and refining their adaptability to different learning environments. Piloting these technologies in schools with limited digital resources would provide valuable insights into their scalability and demonstrate their potential to reduce educational inequality.

However, achieving widespread adoption and impact requires collaborative efforts among governments, NGOs, and private stakeholders. These partnerships are essential for identifying the specific needs of different communities and developing tailored, accessible, and impactful solutions. By working together, stakeholders can ensure that innovative educational technologies reach a wider audience, making high-quality learning experiences available to those who need them most.

Case studies of platforms like Khan Academy, Duolingo, and Google Classroom, along with insights from the key European projects discussed in this work, highlight the importance of addressing psychological factors in the design of educational technologies. While many of these platforms effectively support cognitive and interactional engagement, there is still room for improvement in fostering emotional engagement. The proposed framework aims to bridge this gap by developing cost-effective, accessible, and scalable educational technologies that integrate psychological insights into their design. By doing so, it is possible to create more inclusive, engaging, and equitable learning environments that meet the diverse needs of learners worldwide.

7. Conclusions and Further Results

The exploration of psychological processes within the field of Human–Computer Interaction (HCI) highlights their critical role in developing and designing effective and impactful educational technologies. This paper introduces a theoretical framework that integrates emotional, cognitive, and interactional dimensions to enhance both the usability of these systems and learning effectiveness. Additionally, we have incorporated case studies to demonstrate the practical applications of this model.

Our analysis highlights the importance of these components in fostering effective learning experiences. However, we recognize the need for further empirical validation of the proposed framework. Future research should explore systematic comparisons between existing educational platforms, such as Khan Academy and Duolingo, as well as other emerging HCI solutions, assessing their alignment with our model.

Additionally, a deeper investigation into AI-driven tools and their role in emotional engagement within learning environments could provide further insights. For instance, it would be highly relevant to investigate the evolution of adaptive learning systems, particularly their ability to recognize and respond to learners’ emotional and cognitive needs. A dedicated study on these aspects could strengthen the empirical foundation of our framework and contribute to the broader discourse on HCI in education.

Furthermore, we acknowledge the limitations of our study, particularly the absence of an empirical validation of the proposed framework. Given the theoretical nature of this work, future research should aim to implement and test the model in real-world educational settings to assess its effectiveness. Methodologies such as experimental studies, user testing, and longitudinal analyses could provide valuable data on its applicability and impact. Another promising avenue for future research is the integration of artificial intelligence and augmented reality with HCI and educational psychology. Examining how these technologies enhance emotional engagement, personalization, and adaptability in learning environments could further refine the theoretical framework proposed in this paper.

It has been highlighted that emotional factors—such as motivation and satisfaction—are essential for sustaining learner engagement. At the same time, cognitive processes, including memory retention and cognitive load management, are crucial for delivering educational content effectively. Similarly, interactional engagement enriches learning by fostering collaboration and meaningful connections, aligning with the principles of social constructivism.

By proposing a holistic framework informed by psychological theories, this paper aims to highlight the potential to develop and implement educational tools that are adaptive, inclusive, scalable and effective across diverse contexts. Future research will focus on expanding the scope of the proposed framework by incorporating emerging technologies, such as artificial intelligence and augmented reality, that will enhance learning environments further. These advancements highlight the call for interdisciplinary collaboration in developing innovative, evidence-based solutions that address the evolving needs of learners and educators and embrace the innovative features offered by modern technology.

The alignment of technology with well-established learning theories is paramount to ensure the robustness of product design from the perspective of learning [5,20]. Additionally, metacognition and reflective learning practices should be supported through interactive elements, such as self-assessment questions, reflection prompts, and adaptive learning pathways, fostering deeper engagement and flexible thinking. The ongoing digital transformation of education emphasises the crucial need for collaboration among psychologists, educators, and technology designers to create tools that move beyond functionality and consider the psychological principles of learning in meaningful ways. Future research should extend our understanding of learner engagement across diverse educational contexts, focusing on inclusivity and adaptability. Investigating the long-term effects of emotionally intelligent systems and adaptive interfaces on learning outcomes can offer valuable insights relevant to the refinement of design principles. Additionally, integrating emerging technologies, such as artificial intelligence and augmented reality [5], can open new opportunities for the creation of more immersive educational environments.

Practical implementation of those strategies must ensure scalability and accessibility, making these technologies effective and equitable across varied socio-economic and socio-cultural backgrounds. For example, this could be addressed by incorporating natural language processing to support multiple languages, thus enhancing inclusivity and engagement in diverse settings for context-based learning.

Therefore, educational technology design must prioritise learners’ psychological well-being and engagement. Through interdisciplinary collaboration, we can develop innovative educational experiences that empower learners with knowledge, emotional intelligence, and the socio-relational skills necessary to thrive in a rapidly evolving world. This interdisciplinary approach has the potential to fill in the gaps between technology, psychology, and pedagogy, ushering in a new era of innovative, impactful, learner-centered educational tools.