Mobile-Enhanced Outdoor Education for Tang Sancai Heritage Tourism: An Interactive Experiential Learning Approach

Abstract

Outdoor experiences significantly enrich intangible cultural heritage tourism, yet limited interaction often restricts deep cultural learning. This research investigates how a mobile application, grounded in experiential learning theory, enhances tourists’ learning about Tang Sancai, a form of Chinese intangible cultural heritage, in the outdoor setting of Sancai Town, Luoyang. Employing a theory learning behavior design scenario framework, the application integrates activity-based exploration, reflective multimedia content, and immersive simulation scenarios to promote active participation, critical reflection, and context-rich outdoor learning experiences. Controlled experiments using pre- and post-tests and questionnaires revealed that participants using the application significantly outperformed those using conventional digital tools in knowledge retention, comprehension, and experiential learning outcomes. Technology acceptance analysis highlighted perceived usefulness as a critical driver of learning success. However, limited effects on behavioral progression suggest that short-term digital interactions may not sustain long-term behavioral change. This research offers a replicable mobile learning framework for outdoor cultural education, extends experiential learning theory to informal tourism contexts, and provides practical insights into using technology to enrich outdoor educational experiences, while supporting heritage preservation.

1. Introduction

Cultural heritage encompasses the legacy of physical artifacts, sites, and intangible attributes inherited from past generations. Cultural heritage is broadly categorized into tangible and intangible forms. Tangible cultural heritage includes physical artifacts such as buildings, monuments, landscapes, artworks, and archeological sites preserved for their historical, cultural, or artistic significance (UNESCO, 1972). In contrast, intangible cultural heritage (ICH) refers to the practices, representations, expressions, knowledge, and skills recognized by communities as part of their cultural heritage, such as oral traditions, performing arts, social practices, traditional craftsmanship, and knowledge concerning nature and the universe (UNESCO, 2003). However, ICH faces increasing challenges from globalization and modernization, including disrupted transmission and declining audiences. Traditional oral transmission and apprenticeship methods struggle to meet modern demands, necessitating innovative approaches to dissemination and education (Dagnino et al., 2018). UNESCO underscores that integrating ICH into formal and informal education enhances educational relevance and quality, ensuring its continuity among younger generations (Aziz et al., 2020; UNESCO, n.d.).

Outdoor experiences, a defining feature of cultural heritage tourism, provide learners with authentic and immersive learning contexts (tom Dieck et al., 2018a; Z. Chen et al., 2020). Cultural heritage tourism has thus become a significant platform for ICH education and transmission. Tourists increasingly prefer active participation over passive observation, seeking to understand local cultures through interactive experiences (Arcodia et al., 2021; Toker & Rezapouraghdam, 2021). Many prioritize cultural engagement as a primary travel motivation, pursuing authentic and in-depth experiences within limited timeframes (Sayeh, 2022). Unlike traditional sightseers, these “active learners” pursue meaningful knowledge acquisition. Meanwhile, digital technologies have transformed ICH preservation and tourism. Individuals and institutions increasingly use digital tools to document, preserve, and disseminate ICH, overcoming the limitations of traditional methods (Selmanovic et al., 2018; Q. Wang, 2022). The widespread use of mobile internet and smart devices has made mobile learning applications vital in cultural heritage tourism, offering real-time, personalized experiences that enhance both engagement and learning effectiveness (Koutsabasis et al., 2021; Li & Kang, 2023). In particular, mobile apps help address challenges such as disrupted transmission and declining participation by offering interactive alternatives to traditional skills training, fostering youth engagement through immersive outdoor learning experiences (Chung, 2024; Orphanidou et al., 2024).

ICH knowledge transmission is inherently contextual and experiential, relying on “living” methods like oral tradition and hands-on practice (UNESCO, n.d.; Yan & Chiou, 2021). This intergenerational process constitutes a dynamic, interactive form of informal education (Ferrer-Yulfo, 2022; Yan & Chiou, 2021). It aligns closely with Kolb’s experiential learning theory (ELT), which describes learning as a cycle of four stages: concrete experience (CE), reflective observation (RO), abstract conceptualization (AC), and active experimentation (AE) (Kolb, 2014). Widely applied in cultural education, ELT has proven effective in enhancing learner engagement and practical skills (Binbin et al., 2024; Ma’arif et al., 2023). The theory posits that deep interaction and personal experience are essential for internalizing and applying abstract knowledge (Kolb, 2014), making it highly relevant for rethinking ICH education models.

However, applying ELT to ICH tourism remains underexplored, particularly in outdoor heritage contexts. While Kolb’s model provides a strong theoretical foundation for ICH learning, how to translate it into systematic, context-appropriate design principles for tourism remains unclear (Binbin et al., 2024). A review of the recent literature identifies two key research gaps: first, the absence of defined design strategies for using mobile digital technologies to promote ICH learning (Koutsabasis et al., 2021; Li & Kang, 2023); and second, a lack of established methods for assessing ICH tourism learning outcomes (Qiu et al., 2022). These gaps are particularly pronounced in traditional handicraft-based ICH, where fragmented designs limit the educational and cultural potential of tourism experiences.

The Tang Sancai (tri-colored glazed pottery) firing technique, originating in the Tang Dynasty (618–907 AD), exemplifies traditional Chinese craftsmanship through its distinctive yellow, green, and white glazes and intricate multi-stage firing process (Jiang, 2009). Listed as a National Intangible Cultural Heritage of China in 2008, it draws tourists to Sancai Town in Luoyang, where ICH experience centers offer hands-on activities. As a form of intangible heritage, Tang Sancai represents a living repository of traditional craftsmanship and cultural identity. It reflects the artistic ideals, cosmopolitan spirit, and technological innovations of the Tang Dynasty, while symbolizing the cultural exchanges that flourished along the ancient Silk Road (Zhu, 2006). Its combination of esthetic appeal and hands-on learning potential makes it particularly valuable for heritage tourism. However, the current tourism model relies heavily on static displays and basic interpretations, lacking systematic instructional design or theoretical grounding. As a result, tourists often fail to gain a deep understanding of Tang Sancai’s historical context, technical processes, and cultural significance, undermining the potential of tourism as a vehicle for effective ICH transmission.

In response to these challenges, this study explores how experiential learning can enhance ICH tourism. Using the Tang Sancai heritage site in Luoyang as a case study, it integrates Kolb’s ELT with digital technology to design and evaluate a mobile application aimed at improving tourists’ ICH learning outcomes. Through this approach, this study seeks to deepen the understanding of tourists’ experiential learning processes and validate ELT’s relevance in heritage tourism settings. Accordingly, this study addresses the following research questions:

1. How can experiential learning theory inform the design of an effective mobile application for ICH tourism?

2. Can a mobile application based on ELT enhance tourists’ understanding of Tang Sancai?

To address these questions, this study develops a mobile application grounded in experiential learning theory, conducts a controlled experiment to validate its impact on tourist learning, and examines key technological acceptance factors influencing experiential learning outcomes. This research contributes to both ICH education and cultural tourism. Theoretically, it extends Kolb’s ELT application to short-term, informal tourism contexts; practically, it proposes a systematic mobile learning design model that integrates mobile digital technologies into outdoor cultural heritage contexts, providing learners with direct engagement, real-time interaction, and meaningful reflection opportunities.

2. Literature Review

2.1. Experiential Tourism in ICH Contexts

Tourism has increasingly shifted from traditional sightseeing to experiential tourism, which emphasizes active engagement in the cultural life of destinations to promote deeper cultural understanding and immersive emotional and sensory experiences (Arcodia et al., 2021; Toker & Rezapouraghdam, 2021). The experience economy theory conceptualizes experiences as unique economic offerings, defined through the 4E model—education, entertainment, escapism, and esthetics—where the degree of participation and environmental immersion shapes the depth of the experience (Pine & Gilmore, 1998). This framework highlights the importance of tourists’ emotional, physical, and intellectual involvement in creating meaningful and personalized encounters.

Authenticity theory supports experiential tourism by addressing tourists’ subjective perceptions and motivational needs (MacCannell, 2013). It posits authenticity as central to tourists’ pursuit of meaningful experiences, later distinguished into objective, constructive, and existential dimensions (Ning, 2017). Existential authenticity emphasizes introspective, personally meaningful experiences as central to tourism quality. Empirical studies confirm a strong positive correlation between perceived authenticity, tourist satisfaction, and cultural learning depth (Zuo et al., 2024).

Intangible cultural heritage (ICH) tourism is particularly well suited to experiential approaches in outdoor settings, where interactive, authentic, and context-rich environments facilitate immersive learning opportunities (tom Dieck et al., 2018a; Z. Chen et al., 2020). Many ICH practices, such as traditional crafts and performing arts, require hands-on participation and community interaction in real-world settings to effectively transmit cultural knowledge and values (Yan & Chiou, 2021). These contexts allow tourists to engage in “learning by doing,” fostering emotional connection and deeper cultural appreciation.

Nevertheless, current ICH tourism experiences in outdoor environments often remain fragmented, brief, and lacking in educational structure, limiting their potential for meaningful cultural understanding and knowledge internalization. Many products fail to incorporate clear learning objectives or systematic engagement strategies, resulting in superficial interactions. To address these gaps, it is essential to integrate educational theories and structured instructional models that enhance the cultural and pedagogical depth of outdoor ICH experiences, thereby promoting more effective cultural transmission and sustainable heritage preservation.

2.2. Experiential Learning Theory for ICH Tourism Education

Kolb’s experiential learning theory (ELT) frames learning as a cyclical process of concrete experience, reflective observation, abstract conceptualization, and active experimentation (Jiang, 2009), aligning closely with the transmission of intangible cultural heritage (ICH). Through hands-on practice, reflection on cultural meanings, the derivation of principles, and skill application, learners internalize ICH knowledge, particularly for craft-based skills. This iterative process mirrors traditional ICH education, where cultural practitioners develop expertise through direct engagement (Fang, 2024). However, ELT has limitations when applied to episodic, time-bound contexts (Egan et al., 2023), as the full learning cycle may be difficult to complete in short-term, informal tourism settings due to time constraints. To address these limitations, recent theoretical developments in situated learning and embodied cognition provide deeper insights, emphasizing the role of authentic contextual interactions and bodily engagement in achieving meaningful experiential learning outcomes (W. Chen et al., 2025; Faella et al., 2025).

Outdoor cultural experiences offer the ideal conditions for “concrete experience,” helping to address the constraints of short-term tourism in completing the experiential learning cycle and supporting cultural knowledge internalization. As a form of outdoor learning, educational tourism combines classroom knowledge with real-life experience, aligning with Kolb’s experiential learning theory (ELT) (Meng et al., 2024). In this setting, tourists develop intuitive understanding through hands-on ICH activities and become more motivated through interaction (tom Dieck et al., 2018a). For example, at Macau’s Drunken Dragon Festival, spontaneous participation creates a rich experiential landscape where ongoing interaction with performers and the community deepens cultural insight (Z. Chen et al., 2020). Tools like augmented reality (AR) further enrich these experiences by enabling immersion and enhancing learning outcomes (tom Dieck et al., 2018a). Educational tourism also promotes the development of knowledge, skills, and attitudes (McGladdery & Lubbe, 2017). However, without guided reflection, such experiences may remain superficial and fail to foster deeper understanding (Meng et al., 2024). Therefore, outdoor ICH tourism should incorporate educational design to ensure meaningful learning through immersion.

Recent studies validate ELT’s effectiveness in ICH education across diverse contexts. For instance, Ma’arif et al. found that an Indonesian batik workshop enhanced technical skills and cultural symbolism appreciation through ELT’s four stages (Ma’arif et al., 2023). Similarly, Yan and Chiou (2021) reported that a Chinese embroidery program deepened emotional connections to the craft, while Chai (2024) showed a lion dance workshop improved cultural awareness. In tourism, active participation through workshops or culinary experiences yields greater satisfaction and heritage understanding compared with passive observation (Toker & Rezapouraghdam, 2021). Such engagement fosters deeper cultural awareness and intercultural dialog (Orphanidou et al., 2024; Smith & Akagawa, 2009). However, these studies are often context-specific with small sample sizes, necessitating broader validation.

Despite its potential, applying ELT to ICH tourism faces challenges, including a lack of systematic design frameworks to operationalize the theory in time-constrained settings (Binbin et al., 2024). Brief tourist encounters hinder complete learning cycles, particularly reflection and conceptualization. Moreover, digital tools like virtual reality (VR) or augmented reality (AR), while engaging, often fail to support deep reflection without pedagogical grounding. For example, an AR app for the Drunken Dragon Festival provided initial engagement but lacked support for full ELT cycles (Luo & Hsiao, 2023), while a VR-based floral arrangement study required guided reflection for sustained learning (Y. Wang et al., 2025). These gaps highlight the need for adaptable ELT-based frameworks, the rigorous evaluation of digital tools, and longitudinal studies to assess sustained learning outcomes, advancing ICH tourism education and cultural preservation.

2.3. Mobile Learning Design for ICH Tourism Education

Mobile learning offers a scalable solution for intangible cultural heritage (ICH) education in tourism, enabling real-time, interactive experiences that address transmission challenges like declining participation (Boboc et al., 2022). By integrating Kolb’s experiential learning theory (ELT), mobile apps can guide tourists through hands-on engagement, reflection, and skill application, fostering deep cultural understanding (Koutsabasis et al., 2021). Unlike static displays, mobile platforms provide personalized, context-aware content, aligning with tourists’ preference for active participation over passive observation (Toker & Rezapouraghdam, 2021).

Despite these opportunities, designing effective mobile apps for ICH tourism faces significant challenges. Tourists’ mobility and time constraints demand lightweight, intuitive interfaces (Shukri et al., 2017), yet many apps prioritize technological novelty over pedagogical depth. For instance, augmented reality (AR) applications often deliver engaging visuals but lack pedagogical frameworks to support reflection and conceptualization, resulting in superficial learning (Yidan et al., 2025). Similarly, current apps rarely incorporate feedback mechanisms or interactive tasks, limiting their ability to facilitate complete ELT cycles (Barbara, 2022). Debates over interface complexity further complicate the design, with some advocating immersive multimedia (Anwar et al., 2025; Innocente et al., 2023; Marto et al., 2022), and others emphasizing simplicity to avoid cognitive overload (Barbara, 2022; Guo et al., 2024). These pedagogical and technical shortcomings hinder deep cultural learning in dynamic tourism settings. Recent advancements in situated learning and immersive technology emphasize the necessity of incorporating authentic contextual interactions into mobile educational designs to effectively facilitate learner reflection and deeper experiential engagement (Gumbheer et al., 2022; Yan et al., 2024).

These challenges reveal critical research gaps. Most mobile apps are designed for static contexts, neglecting tourists’ on-site needs for concise, ELT-grounded content, particularly in dynamic outdoor heritage tourism contexts. Furthermore, few apps enable sustained tourist–community interaction, such as co-created narratives or location-based storytelling, limiting cultural exchange and community empowerment (Abdo, 2019; Jing et al., 2021; Silva & Raposo, 2023). Current digital storytelling efforts remain fragmented, lacking cohesive frameworks (Cahyani et al., 2023). Future research should develop ELT-based mobile frameworks designed for outdoor tourism, evaluate their pedagogical efficacy, and investigate the long-term impacts on cultural learning and heritage engagement.

3. Application Design

3.1. Study Site Overview

Sancai Town, located in Luoyang, China, is the primary origin of Tang Sancai pottery and is recognized as the “First Village of Chinese Tang Sancai Culture”. It features a rich array of intangible cultural heritage sites, including ancient kiln sites, pottery workshops, museums, and cultural exhibitions. Tourists can observe ceramic works, interact with artisans, and participate in hands-on pottery-making activities. These experiential interactions showcase Tang Sancai’s heritage value while offering tourists authentic encounters with living traditions. The ceramics thus serve dual functions as cultural ambassadors and educational tourism resources. Such engaging activities effectively enhance visitors’ understanding of Chinese ceramic traditions, positioning Sancai Town as an ideal setting for experiential learning in cultural heritage contexts.

Sancai Town’s cultural tourism, however, encounters three key challenges. First, the current approach depends on static displays and brief explanations, lacking a cohesive cultural narrative, which impedes tourists’ comprehension of Tang Sancai pottery. Second, tourist experiences are often confined to surface-level visual appreciation, overlooking the historical context, evolution, and cultural value of Tang Sancai craftsmanship. Third, this approach restricts the opportunities for deep learning and engagement, obstructing the dissemination and preservation of Tang Sancai heritage.

Considering these limitations, this study introduces a mobile application grounded in Kolb’s experiential learning theory, integrating activity, information, and interaction-based scenarios to enhance cultural learning and support the sustainable transmission of Tang Sancai heritage.

3.2. Theoretical Framework for Design

This study employs Kolb’s experiential learning theory as its theoretical foundation, ensuring the alignment between conceptual grounding and practical application. Building on the literature review, this section explains how ELT informs the app’s design framework.

In response to the limitations of Kolb’s model in digital interactive environments, the study incorporates cultural tourism context features and introduces three key learning behaviors as mediators to guide tourists through Kolb’s complete learning cycle: (1) seeking challenging tasks, (2) critical reflection, (3) immersive engagement. These behaviors interact and form a system that enhances the depth of the learning cycle.

Seeking challenging tasks refers to learners engaging in moderately difficult activities with clear goals and feedback, increasing intrinsic motivation and involvement (Locke & Latham, 2019; Matsuo, 2019). Such tasks spark curiosity and foster deeper experiential learning (Davies & Easterby-Smith, 1984). In the Sancai Town tourism app, this is embodied through artifact exploration or themed interactive challenges, facilitating Kolb’s “concrete experience” and “active experimentation” stages and laying the foundation for the learning cycle.

Critical reflection involves participants actively reconsidering and analyzing their experiences to transform knowledge (Mezirow, 1991). Kolb stresses that without reflection, experiences rarely become lasting knowledge. The design integrates reflection mechanisms, such as multimedia content or prompts, encouraging tourists to think deeply post experience. This strengthens Kolb’s “reflective observation” and “abstract conceptualization” stages, enabling further learning (Kirillova et al., 2017; Pipitone, 2018).

Immersive engagement entails full sensory, emotional, and cognitive engagement, often resulting in a flow state (Csikszentmihalyi & Csikzentmihaly, 1990). Studies show that immersive interactions significantly boost engagement and learning quality (D.-I. D. Han et al., 2019; tom Dieck et al., 2018b). This enhances tourists’ overall experience of Kolb’s learning cycle, supporting sustained, in-depth learning (Shin, 2018).

To operationalize these behaviors, three corresponding interactive scenarios are designed: (1) activity scenes (e.g., task-based challenges) guide tourists in completing challenging tasks; (2) information scenes (e.g., post-experience feedback and intangible heritage storytelling) reinforce critical reflection; (3) interaction scenes (e.g., simulated Sancai pottery-making games) create immersive engagement. These distinct yet interconnected scenes collectively drive the experiential learning cycle. This “theory → learning behavior → design scene” mapping (Figure 1) converts theory into a clear design strategy, supporting the dissemination of intangible cultural heritage knowledge.

3.3. Design Implementation

To integrate interactive scenarios and learning behaviors into the design, this study developed an interactive map customized to reflect Sancai Town’s spatial layout and cultural resources (Figure 2). The design incorporates three core modules: (1) task-based exploration routes for historical and craft experiences (activity scenario), (2) multi-sensory information delivery with interactive feedback (information scenario), (3) a simulation game replicating the Tang Sancai pottery-making process (interactive scenario). The following section describes the implementation of these scenarios within the application.

3.3.1. Activity Scenario: Seeking Challenging Tasks

This scenario uses interactive features to encourage tourists to undertake moderately difficult, goal-oriented tasks, fostering intrinsic motivation and active participation. Three themed routes were created: “historical exploration”, “craft exploration”, and “integrated exploration”, each consisting of five to six connected attractions. Tourists choose a route based on their interests and complete interactive tasks at each stop. A step-by-step unlocking system grants access to the Sancai pottery simulation game upon completing a route (Figure 3), promoting deeper engagement and linking the exploration to hands-on learning.

3.3.2. Information Scenario: Critical Reflection

This scenario fosters critical reflection on Tang Sancai culture through layered multimedia content and interactive feedback. A structured progression system ensures that tourists complete hands-on tasks before accessing deeper reflective content, preventing superficial engagement. After finishing tasks at each attraction, tourists access multimedia materials (images, videos, and audio) that explore the site’s significance and the cultural depth of Tang Sancai, accompanied by guided reflection prompts that encourage tourists to connect their hands-on experience with cultural meanings, prompting reflection immediately after the experience. An interactive commenting feature also allows tourists to share their thoughts, creating opportunities for dialog and a deeper exploration of Tang Sancai’s cultural value (Figure 4). This structured approach addresses ELT’s limitations in short-term contexts by ensuring that tourists have adequate time and structured guidance to achieve deeper reflective understanding.

3.3.3. Interactive Scenario: Immersive Engagement

To support immersive engagement, this scenario features a touch-based simulation game that reconstructs the full Tang Sancai pottery-making process. Tourists follow guided steps—shaping, glazing, high-temperature bisque firing, and low-temperature re-firing—experiencing the craftsmanship virtually. Upon completion, users can share their pottery on a community platform, encouraging peer interaction and reinforcing cultural identity. This activity aligns with the “concrete experience” and “active experimentation” stages of Kolb’s experiential learning cycle (Figure 5).

The interface adopts Tang Sancai’s distinctive color palette—yellow, green, and white (Jiang, 2009)—to establish a unified and recognizable visual identity. This cultural reference creates an immediate emotional link with the heritage theme, enhancing immersion and enriching the overall user experience.

Through these interactive scenarios, the application translates experiential learning theory into a concrete design model for ICH tourism in Sancai Town. This directly addresses the study’s first research question: “How can experiential learning theory be used to design a mobile tourism learning application for intangible cultural heritage?” For a comprehensive summary of the learning behaviors, task types, scenario implementation, and expected outcomes, refer to

Table 1. Experiential learning scenarios: tasks, behaviors, implementations, and outcomes.

Scenario Type	Learning Task	Learning Behavior	Design Implementation	Learning Outcome
Activity Scenario	Historical route exploration task	Challenge seeking	Themed route selection, point-based progression, task unlocking mechanism.	Motivation for exploration, acquisition of basic cultural knowledge.
Information Scenario	Cultural interpretation and feedback module	Critical reflection	Multimedia content (text, image, video), tourist comment interaction.	Deeper cultural understanding, attitudinal engagement.
Interaction Scenario	Simulation of Tang Sancai making	Immersive engagement	Step-based simulation of the Tang Sancai making process, glazing interaction, post-task sharing.	Procedural understanding and emotional engagement with Tang Sancai craftsmanship.

.

4. Experiment Methods

Based on Kolb’s experiential learning theory, this study developed a mobile application to support intangible cultural heritage tourism knowledge learning, addressing the first research question: how to effectively design an experiential learning application to facilitate ICH knowledge acquisition. To address the second research question regarding the application’s effectiveness in enhancing tourists’ understanding and experience of Tang Sancai culture, a quasi-experimental design was employed, assigning tourists to experimental and control groups with pre- and post-tests to measure the differences in Tang Sancai knowledge retention, depth of understanding, and tourism experience. This chapter details the participant selection criteria, the development and validation of instruments, experimental procedures, and data analysis methods.

4.1. Participants

The target participants of this study were tourists visiting Sancai Town in Luoyang, China. Inclusion criteria were as follows: (1) first-time visitors to Sancai Town, to eliminate bias from prior experience (Pasaco-González et al., 2023); (2) aged between 18 and 70, ensuring independent decision-making ability; (3) willingness to use digital tourism tools (S. Han et al., 2021).

Considering the feasibility of on-site experiments, this study employs purposive sampling (Etikan et al., 2016), recruiting eligible participants by posting notices in advance on the “Destination Forum—Luoyang Section” of Ctrip, one of China’s largest online travel communities. Based on statistical power analysis and recommendations from related tourism field experiments (Chin et al., 2019; Hincapié et al., 2021; VanVoorhis & Morgan, 2007), this study initially targeted 45 participants per group to meet the requirements for statistical analysis. During implementation, a total of 84 tourists participated, with valid data obtained from 41 control group and 43 experimental group participants.

4.2. Instruments

Learning in heritage tourism is highly contextual and informal, requiring careful attention to measurement design (Falk & Dierking, 2016). To assess tourists’ learning outcomes regarding Tang Sancai, two types of instruments were developed: a knowledge test and a tourist experience questionnaire.

The knowledge test was constructed based on Chinese Tang Sancai (Zhu, 2006) and structured according to Bloom’s revised taxonomy (Anderson & Krathwohl, 2001), which distinguishes clearly between retention (remembering) and comprehension (understanding) as fundamental cognitive processes. This approach enables the precise evaluation of both factual recall and deeper understanding, aligning with the study’s goal of assessing tourists’ meaningful comprehension rather than superficial memorization of intangible cultural heritage content. Following two dimensions commonly used in museum and heritage learning (Chin et al., 2024), the test comprised retention and comprehension sections. The retention section used multiple-choice items assessing factual knowledge, including glaze characteristics, firing techniques, functional use, and stylistic influences. The comprehension section employed open-ended questions to evaluate understanding of production principles and historical–cultural context. To minimize memory effects, the pre-test and post-test used the same items in a randomized order.

To ensure content validity, the test was reviewed by two complementary domain experts who confirmed its accuracy in representing core Tang Sancai knowledge. One expert from the Luoyang Sancai Art Museum provided practical expertise in Chinese ceramic archeology and Tang Sancai preservation, while an academic expert from Luoyang Normal University contributed scholarly insights into Tang Sancai craftsmanship and intangible cultural heritage knowledge transmission. Their feedback informed revisions that enhanced both item clarity and cultural accuracy.

The tourist experience questionnaire combined the Generic Learning Outcomes (GLOs) framework and the Technology Acceptance Model (TAM). The GLOs framework, developed by Hooper-Greenhill et al. (Hooper-Greenhill, 2004), has been widely validated in heritage tourism contexts (tom Dieck et al., 2018c). Given the digital nature of the application, two TAM dimensions were incorporated: perceived ease of use and perceived usefulness, both key predictors of user adoption in mobile tourism research (Jung et al., 2015).

The questionnaire contained two sections. The first section, based on the GLOs framework, included 19 items covering 5 learning dimensions: Knowledge and Understanding (KU), Skills (S), Attitudes and Values (AV), Enjoyment, Inspiration, and Creativity (EIC), and Action, Behavior, and Progression (ABP). The second section consisted of 9 items measuring PEOU and PU. A 7-point Likert scale (1 = strongly disagree, 7 = strongly agree) was used to capture nuanced differences in tourist perceptions and experiences (

Table 2. Questionnaire design.

Constructs	Dimensions	Number of Items	Source
Generic Learning Outcomes	Knowledge and Understanding (KU)	4	(Hooper-Greenhill, 2004); (tom Dieck et al., 2018c); (Li et al., 2022)
	Enjoyment, Inspiration, and Creativity (EIC)	4
	Skills (S)	5
	Attitudes and Values (AV)	3
	Action, Behavior, and Progression (ABP)	3
Technology Acceptance	Perceived Usefulness (PU)	5	(Davis, 1989); (de Oliveira Nunes & Mayer, 2014); (Hamouda, 2022)
	Perceived Ease of Use (PEOU)	4

).

The reliability and validity of both instruments were verified through expert review. For the knowledge test, feedback from two experts in archeology and art history ensured alignment with learning objectives and cultural authenticity. For the tourist experience questionnaire, three experts in educational technology and cultural tourism assessed content relevance, item clarity, and logical structure, affirming its content validity.

In addition, construct validity and reliability testing were conducted for the tourist experience questionnaire. Factor analysis showed that the data were suitable for analysis, with a KMO value of 0.779 and a significant Bartlett’s test of sphericity (χ2 = 1199.763, df = 378, p < 0.001). Reliability analysis indicated high internal consistency, with an overall Cronbach’s α of 0.916. Subscale α coefficients ranged from 0.761 to 0.910, all exceeding the acceptable threshold (>0.7). These statistical results confirm that the tourist experience questionnaire is both valid and reliable, supporting its use in this study.

4.3. Procedures

The experimental procedure is illustrated in Figure 6. Upon arrival at the visitor center, participants signed an informed consent form and completed a pre-test assessing their knowledge of Tang Sancai. They were then randomly assigned to one of two groups: the experimental group used the newly developed tourism map application, while the control group received a conventional digital map. Both groups followed the same guided route, and the only difference was the type of map provided.

To ensure consistency, all participants were given standardized instructions on how to use their assigned systems prior to starting the tour. The route included six designated sites that represented key aspects of Tang Sancai’s history and craftsmanship. Participants explored these sites within a 90 min time frame. Research assistants were stationed along the route to offer technical support and observe tourist behavior. After completing the route, participants returned to the visitor center to complete a post-test and the tourist experience questionnaire. The research team supervised the entire process to ensure standardization and data quality.

4.4. Data Analysis

Data were analyzed using SPSS 26.0 to evaluate the application’s effectiveness in enhancing the learning of Tang Sancai’s intangible cultural heritage. First, an independent samples t-test was conducted to verify baseline equivalence between groups by comparing pre-test knowledge scores. Next, paired samples t-tests were used within each group to assess knowledge gains from pre- to post-test (Chin et al., 2024).

Subsequently, independent samples t-tests were performed to compare the experimental and control groups in terms of knowledge improvement, the five dimensions of the Generic Learning Outcomes (GLOs)—Knowledge and Understanding (KU), Enjoyment, Inspiration, and Creativity (EIC), Skills (S), Attitudes and Values (AV), and Action, Behavior, and Progression (ABP)—as well as technology acceptance measures: perceived usefulness (PU) and perceived ease of use (PEOU). Cohen’s d was calculated to determine the effect size of between-group differences (Cohen, 2013).

Finally, to explore the predictive role of technology acceptance in learning outcomes, a multiple linear regression analysis was conducted with PU and PEOU as independent variables (Aloqaily et al., 2019). The significance level for all statistical tests was set at α = 0.05.

5. Results

This chapter first presents participants’ demographic characteristics to confirm sample representativeness and group comparability. The results are then organized into four sections: tourists’ knowledge performance (retention and comprehension), experiential learning outcomes based on the GLOs framework, the perceptions of technology acceptance, and a regression analysis of key learning predictors.

Table 3. Sample demographics.

Item	Subtype	Experimental Group (n = 43)	Control Group (n = 41)
Age	18–30	17 (39.5%)	16 (39%)
	31–45	14 (32.6%)	14 (34.1%)
	46–60	9 (20.9%)	9 (22%)
	61–70	3 (7.0%)	2 (4.9%)
Ethnicity	Han	36 (83.7%)	37 (90.2%)
	Ethnic minorities	7 (16.3%)	4 (10%)
Gender	Female	21 (48.8%)	19 (46.3%)
	Male	22 (51.2%)	22 (53.7%)
Highest Qualification	High School or below	5 (11.6%)	4 (9.8%)
	Associate’s degree	15 (34.9%)	12 (29.3%)
	Bachelor’s degree	20 (46.5%)	22 (53.7%)
	Master’s degree or higher	3 (7.0%)	3(7.3%)
Frequency of Tourism Application Use	Never	7 (16.3%)	5 (12.2%)
	Rarely	17 (39.5%)	19 (46.3%)
	Sometimes	14 (32.6%)	13 (31.7%)
	Often	5 (11.6%)	4 (9.8%)

summarizes the participants’ demographic characteristics. The sample consisted primarily of young to middle-aged adults (18–45 years), predominantly Han Chinese, with most participants holding an associate’s degree or higher education. Additionally, the majority reported relatively limited prior experience with tourism applications. This demographic composition aligns well with the typical profile of domestic tourists engaging in cultural heritage tourism in China, supporting the broader generalizability of this study’s findings.

5.1. ICH Knowledge Learning Outcomes

An independent samples t-test was conducted to compare pre-test knowledge scores between the experimental and control groups. The results showed no significant difference between the control group (n = 41, M = 37.10, SD = 8.69) and the experimental group (n = 43, M = 35.88, SD = 8.23) prior to the intervention (t = −0.66, p > 0.05), indicating comparable baseline knowledge levels.

Next, paired samples t-tests were conducted within each group to assess pre- and post-test changes. Both groups demonstrated a significant improvement in knowledge scores after the intervention (p < 0.05); however, the experimental group exhibited a substantially greater gain (Cohen’s d = 1.90) compared with the control group (Cohen’s d = 0.79). These results suggest that the application significantly enhanced tourists’ acquisition of Tang Sancai knowledge, supporting its effectiveness in promoting ICH learning.

Further independent samples t-tests were performed to compare post-test results between the two groups.

Table 4. The t-test results of knowledge retention and comprehension.

Question Type	Experimental Group (n = 43)			Control Group (n = 41)			t	Cohen’s d
	M	SD	Std. Error	M	SD	Std. Error
Retention	32.65	6.32	0.96	28.54	8.03	1.25	2.6 *	0.57
Comprehension	21.72	6.34	0.97	16.34	6.77	1.06	3.76 ***	0.82
Average score	54.37	9.89	1.51	44.88	11.77	1.84	3.99 ***	0.87

* p < 0.05, *** p < 0.001.

shows that the experimental group scored significantly higher on multiple-choice questions measuring retention (M = 32.65, SD = 6.32) than the control group (M = 28.54, SD = 8.03), with the difference reaching statistical significance (t = 2.60, p < 0.05). The effect size (Cohen’s d = 0.57) indicates a moderate effect. These findings demonstrate that the application designed based on experiential learning theory effectively supported participants’ memory and recall of Tang Sancai knowledge.

For open-ended comprehension questions, the difference was even more pronounced. The experimental group scored significantly higher (M = 21.72, SD = 6.34) than the control group (M = 16.34, SD = 6.77), with stronger statistical significance (t = 3.76, p < 0.01) and a large effect size (Cohen’s d = 0.82). This indicates that the application not only supported factual retention but also improved participants’ deeper understanding and analytical interpretation of Tang Sancai ICH.

Regarding overall knowledge scores, the experimental group (M = 54.37, SD = 9.89) also significantly outperformed the control group (M = 44.88, SD = 11.77), with a large effect size (t = 3.99, p < 0.01, Cohen’s d = 0.87). In addition, the lower standard deviations in the experimental group suggest more consistent learning.

Figure 7 illustrates that both groups began at similar levels in the pre-test. However, following the interventions, the experimental group showed an average increase of 18.5 points, significantly exceeding the 7.8-point gain in the control group. This pattern aligns with the statistical results above and further supports the application’s effectiveness in promoting learning within intangible cultural heritage contexts.

5.2. Experiential Learning Outcomes

Table 5. The t-test results of the GLOs scale.

Category	Experimental Group (n = 43)		Control Group (n = 41)		t	Cohen’s d
	M	SD	M	SD
KU	5.27	0.41	4.23	0.51	10.27 ***	2.25
EIC	5.01	0.6	4.15	0.47	7.3 ***	1.59
S	5.22	0.61	3.91	0.58	10.09 ***	2.2
AV	4.63	0.6	4.17	0.67	3.28 **	0.72
ABP	4.41	0.61	4.31	0.67	0.73	0.16

** p < 0.01, *** p < 0.001.

shows that the experimental group outperformed the control group in four of the five dimensions of the Generic Learning Outcomes (GLOs). Specifically, significant differences were observed in Knowledge and Understanding (KU) (t = 10.27, p < 0.001, Cohen’s d = 2.25), Enjoyment, Inspiration, and Creativity (EIC) (t = 7.30, p < 0.001, Cohen’s d = 1.59), Skills (S) (t = 10.09, p < 0.001, Cohen’s d = 2.20), and Attitudes and Values (AV) (t = 3.28, p < 0.01, Cohen’s d = 0.72). These findings suggest that the experimental group experienced substantial benefits in multiple experiential learning dimensions, with generally large effect sizes.

Notably, the KU and S dimensions exhibited the largest effects, with Cohen’s d values of 2.25 and 2.20, respectively. This indicates that the application, grounded in experiential learning theory, was especially effective in supporting tourists’ acquisition of heritage knowledge and the development of practical skills.

However, in the dimension of Action, Behavior, and Progression (ABP), no significant difference was found between the experimental group (M = 4.41, SD = 0.61) and the control group (M = 4.31, SD = 0.67), with t = 0.73, p > 0.05 and Cohen’s d = 0.16. This suggests that both learning approaches resulted in comparable behavioral outcomes.

5.3. Technology Acceptance: Perceived Usefulness and Ease of Use

Table 6. The t-test results of the TAM scale.

Category	Experimental Group (n = 43)		Control Group (n = 41)		t	Cohen’s d
	M	SD	M	SD
PU	5.9	0.66	4.81	0.84	6.55 ***	1.44
PEOU	5.66	0.79	5.32	0.67	2.12 *	0.46

* p < 0.05, *** p < 0.001.

presents the group differences in the two core dimensions of the Technology Acceptance Model (TAM). The experimental group reported significantly higher scores in perceived usefulness (PU) (M = 5.90, SD = 0.66) compared with the control group (M = 4.81, SD = 0.84), with t = 6.55, p < 0.001 and a large effect size (Cohen’s d = 1.44). In perceived ease of use (PEOU), the experimental group also scored higher (M = 5.66, SD = 0.79) than the control group (M = 5.32, SD = 0.67), with t = 2.12, p < 0.05 and a moderate effect size (Cohen’s d = 0.46). These results indicate that the application received more favorable evaluations across both TAM dimensions, particularly in perceived usefulness.

5.4. Predictive Effects of Technology Acceptance on Experiential Learning Outcomes

To investigate the extent to which perceived usefulness (PU) and perceived ease of use (PEOU) predict tourists’ experiential learning outcomes, a multiple linear regression analysis was conducted. The results revealed significant positive effects for both predictors, with PU demonstrating a stronger influence.

Table 7. Regression analysis of technology acceptance on learning outcomes.

	β	t	95% CI
PU	0.677	9.10 ***	[0.529, 0.826]
PEOU	0.225	3.02 **	[0.077, 0.373]
R2	0.567

** p < 0.01, *** p < 0.001.

shows that the standardized regression coefficient for PU was β = 0.677 (t = 9.10, p < 0.001), while for PEOU it was β = 0.225 (t = 3.02, p = 0.003). The model’s coefficient of determination was R² = 0.567, indicating that PU and PEOU together explained 56.7% of the variance in learning outcomes, suggesting a good overall model fit.

Figure 8 illustrates the regression relationship between PU and learning outcomes, with data points showing a strong positive trend, indicating that tourists who perceived the application as more useful tended to achieve higher learning outcomes. Figure 9 presents a similar but weaker trend for PEOU, with more dispersed data points suggesting a less consistent association.

6. Discussion and Conclusions

6.1. Key Findings

This study explores the application of Kolb’s experiential learning theory in the context of intangible cultural heritage tourism. It proposes a “theory learning behavior design scenario” structural mapping framework to address the applicability of Kolb’s model in short-term, mobile tourism experiences. The empirical results show that the application significantly improves tourists’ memory and comprehension, particularly in conceptual understanding and skill development. These improvements align with the core arguments of authenticity theory (MacCannell, 2013; Zuo et al., 2024), indicating that digitally enhanced experiential interactions can effectively deepen tourists’ personal and cultural engagement. These findings also resonate with the educational and esthetic dimensions of the 4E model (Pine & Gilmore, 1998), underscoring that immersive and reflective interactions significantly enhance the quality of experiential learning.

In response to the first research question, this study develops a design framework integrating Kolb’s experiential learning theory with three key behaviors: seeking challenging tasks, critical reflection, and immersive engagement. This framework bridges the theory–practice gap in ICH education (Binbin et al., 2024). The application uses three interactive scenarios, activity, information, and interaction-based, aligned with Kolb’s learning cycle. Exploration tasks in activity scenarios foster intrinsic motivation (Matsuo, 2019); reflection mechanisms in information scenarios aid knowledge transformation; and immersive engagement in interaction scenarios supports “flow” experiences (Csikszentmihalyi & Csikzentmihaly, 1990). This design advances beyond the fragmented, tech-centric approaches in existing apps and addresses the key challenges in presenting ICH digitally (Koutsabasis et al., 2021; Yidan et al., 2025). Guided reflection prompts effectively mitigate ELT’s short-term reflection limitations (Egan et al., 2023).

For the second research question, the experimental results reveal that the experimental group outperformed the control group in memory-based and comprehension-based knowledge. Improved retention may result from the application’s multisensory design (Selmanovic et al., 2018), while its reflective and immersive features boost comprehension, challenging the notion that digital tools only support superficial learning (Burlingame, 2022). In General Learning Outcomes, the experimental group excelled in Knowledge and Understanding; Enjoyment, Inspiration, and Creativity; Skills; and Attitudes and Values, with large effect sizes in the first two dimensions. However, no significant difference was observed in the Action, Behavior, and Progression (ABP) dimension, suggesting that while short-term digital tools improve cognition and attitudes, their impact on behavior is limited. This aligns with the gradual nature of behavior change theory and highlights the time limitations of Kolb’s model (Prochaska & DiClemente, 1983). A single digital experience is unlikely to foster lasting change, as behavioral transformation typically requires prolonged iteration. Future research should explore sustained interaction mechanisms to extend single experiences into ongoing engagement.

The technology acceptance analysis shows that perceived usefulness (PU) and perceived ease of use (PEOU) together explain 56.7% of the variance in learning outcomes, with PU showing a stronger effect. The experimental group demonstrated a clear advantage in PU over PEOU. This contrasts with earlier mobile learning models that typically emphasize ease of use as the primary factor influencing initial adoption (Almaiah et al., 2019; Davis, 1989). A plausible explanation is that today’s tourists are already highly familiar with mobile apps, which makes perceived usefulness a more decisive predictor of learning outcomes. This shift suggests a change in digital ICH tourism: as smart device use becomes widespread, tourists increasingly prioritize educational value over operational simplicity. Future tourism app designs should thus move beyond simply “simplifying operations” toward “delivering valuable experiences” that emphasize content richness and meaningful functionality.

6.2. Theoretical and Practical Implications for Learning in ICH Tourism

Kolb’s experiential learning theory, traditionally applied to formal education and long-term learning processes (Binbin et al., 2024; Kolb, 2014), has seen limited use in short-term tourism settings. This research extends the theory to informal learning environments, demonstrating its applicability in time-constrained tourism experiences. The findings show that systematic interaction design effectively supports all four stages of Kolb’s model, even in time-constrained tourism settings. Specifically, activity scenarios enable concrete experience and active experimentation, while information scenarios foster reflective observation and abstract conceptualization. This application of theory to practice challenges the belief that digital tools deliver only superficial content (Burlingame, 2022) and highlights the central role of perceived usefulness in learning outcomes.

Building on these insights, the digital interactive map enhances tourists’ cultural identity and knowledge acquisition while reducing the physical impact on heritage sites (Ariza-Colpas et al., 2023). Unlike static displays or basic tours, the tool enhances the tourist experience through interaction, real-time feedback, and multisensory engagement, fostering deep cultural understanding and effectively bridging education with heritage conservation. For Sancai Town and similar ICH destinations, the “theory learning behavior design scenario” framework offers a practical model for tourism planning, providing local stakeholders with an actionable guide. This strengthens the educational dimension of tourism while promoting mutual gains for communities and heritage conservation.

As demonstrated by this case study, ICH tourism’s educational role faces evolving demands amid global digitization. By leveraging digital media design, this study supports deeper cultural understanding and identity development, aligning with UNESCO’s emphasis on ICH education (Aziz et al., 2020). It also provides innovative responses to long-standing challenges, such as heritage transmission gaps and declining audience engagement (Chung, 2024; Orphanidou et al., 2024). The experimental results reveal significant improvements in tourists’ comprehension and skills, offering robust empirical support for cultural tourism design and highlighting the potential of experiential learning in short-term ICH contexts.

6.3. Limitations and Future Research

This study has several limitations. First, the limited sample size and single cultural context constrain the generalizability of the findings. Cultural differences may influence tourists’ ICH perceptions, interaction preferences, and technology acceptance, warranting further cross-cultural validation. Second, the experiment focused only on short-term experiences, making it difficult to evaluate the long-term durability of the learning outcomes, particularly regarding behavior and skill changes. For instance, it remains unclear whether the participants developed intentions to disseminate cultural knowledge or engage in culturally relevant behaviors after their experiences. Third, the application lacks features enabling direct interaction with local artisans, limiting community involvement—a key component of sustainable tourism. This highlights a broader challenge in digital ICH preservation: balancing technological convenience with cultural authenticity (Y. Chen et al., 2024; Zuo et al., 2024). While craft-based ICH is relatively easier to digitize due to its visual and procedural clarity, performing arts and oral traditions may require distinct interactive strategies (Kettula & Hyvönen, 2012).

Future research can expand in several directions: First, exploring culturally adaptive designs that tailor interaction mechanisms to tourists from diverse backgrounds. Second, developing long-term engagement pathways, such as pre-tour content, on-site activities, and post-tour learning tools, to support Kolb’s complete learning cycle. Third, employing longitudinal study designs (e.g., follow-up surveys or analysis of digital platform interaction data) to better capture sustained knowledge retention and behavioral changes. Fourth, supplementing quantitative findings with qualitative analyses (e.g., user logs and in-depth interviews) to provide deeper insights into participants’ dynamic learning processes. Combining these approaches can comprehensively capture tourists’ long-term learning outcomes and behavior dynamics.

In addition, future research could expand the theoretical and technological dimensions of digital cultural heritage experiences. Specifically, researchers could incorporate constructs from the Unified Theory of Acceptance and Use of Technology (UTAUT), such as performance expectation and community influence, to comprehensively analyze mobile learning acceptance in cultural heritage contexts. Furthermore, future studies could explore advanced sensory technologies, particularly for craft-based ICH like pottery, by incorporating realistic glaze color transitions and authentic kiln firing sounds to vividly reproduce kiln variation processes and significantly enhance immersive experiences. Additionally, future research should investigate interaction models that integrate tourists, communities, and cultural heritage (Geçikli et al., 2024), incorporating local communities as co-creators in digital platform design to achieve community-centered sustainable cultural tourism.

In conclusion, this research demonstrates the effectiveness of applying Kolb’s experiential learning theory to ICH tourism, addressing short-term learning challenges and enhancing heritage education practices. The tourism map application enhances cultural understanding and practical skills, effectively supporting cultural engagement in heritage tourism contexts. Integrating experiential learning with digital tools, this study offers practical strategies for improving ICH dissemination and education, underscoring digital media’s potential to balance cultural authenticity with accessible educational experiences.