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An Integrative Framework for Action Research, Experiential Learning, and AI Advancements

 

 

Abstract

The paper explores the synergistic integration of action research methodology and experiential learning in undergraduate logistics and supply chain management (LSCM) programs. We examine how this novel approach addresses the demands of the dynamic LSCM industry by combining theoretical knowledge with practical skills, enhancing critical thinking abilities, and real-world engagement. By examining case studies and extant literature, we illustrate how action research and experiential learning synergise to create a holistic educational experience. We present a comprehensive framework for integrating action research and experiential learning pedagogies that aims to empower students with the essential skills and adaptability to excel in the evolving world of LSCM. The study highlighted several critical elements for educators to implement this integrated approach successfully. Additionally, we explore the impacts of artificial intelligence (AI) on teaching and learning within this integrated framework. The potential benefits and concerns when adapting AI within this integrated framework include enabling personalised learning, data-driven insights, collaborative engagement, and ethical considerations.

 

Keywords

action research, experiential learning, logistics education, supply chain management, artificial intelligence

JEL Classification

I21, I23, M11, O32

 

1. Introduction

The logistics and supply chain management (LSCM) field is constantly shifting, calling for a workforce armed with theoretical knowledge and practical skills to navigate the evolving economic. With global markets weaving tighter connections and consumer preferences branching out, the challenges in this field demand a fresh outlook on how we educate undergraduates. The usual classroom methods might not serve to prepare students holistically for the intricate realities of supply chain management. This paper proposes a pioneering blend of action research techniques and hands-on learning experiences to bridge that gap between theory and practice, moulding students to handle the dynamic demands of the LSCM industry.

Recent developments in LSCM have highlighted the significance of hands-on expertise and theoretical knowledge. Supply chain disruptions caused by unforeseen events, such as the COVID-19 pandemic, have highlighted the value of agility, adaptability, and innovative problem-solving in ensuring supply chain resilience (Christopher & Peck, 2020). As organisations increasingly rely on data-driven insights to optimise operations and enhance customer experiences, LSCM professionals need to possess robust research skills to make informed decisions (Waller et al., 2019).

The LSCM discipline is marked by continuous evolution and complexity, demanding professionals with skills beyond theoretical knowledge. The dynamic nature of the logistics and supply chain management (LSCM) industry necessitates an educational approach that actively involves students in practical problem-solving. We propose a novel educational approach that integrates action research methodology and the experiential learning pedagogy that can bridge the gap between theory and practice, where theoretical concepts are implemented in real-world scenarios (McNiff & Whitehead, 2011; Kolb, 2015).

By integrating action research and experiential learning, students immerse themselves in real-world LSCM situations and follow a structured process of inquiry and action. This paper examines the theoretical underpinnings, benefits,  and challenges of this integrated approach. The aim is to present a pragmatic framework for the effective incorporation of action research and experiential learning principles into undergraduate LSCM programs. Students acquire the technical acumen essential for supply chain management success through this novel pedagogical approach. At the same time, it fosters critical thinking, adaptability, and collaborative skills, which are essential skills for navigating the intricacies of modern business environments. This paper examines the manifold benefits stemming from this integration, emphasising its capacity to nurture advanced research abilities, proficiency in problem-solving, engagement with real-world scenarios, and comprehensive learning experiences through the lens of five case studies that showcase LSCM students applied research projects that are situations in different logistics and supply chain settings.

Additionally, we extend our study to postulate the transformative influence of artificial intelligence (AI) on teaching and learning within this context. Current literature underscores the role of AI-driven personalised learning, data-driven insights, improved collaboration, and ethical considerations in bolstering the success of this integrated educational approach. We highlight the implications of AI-enabled tools through the five exemplary case studies that were examined in this study in the latter section of the paper.

 

2. Literature Review

This section delves into the theoretical foundations of action research and experiential learning, their key components, and their applications within the context of undergraduate LSCM education.

 

2.1. Key Components of Action Research and Application in LSCM Education

Action research methodology offers a dynamic and participatory approach to learning that aligns seamlessly with the demands of the modern logistics and supply chain management (LSCM) landscape. Action research is rooted in collaboration, problem-solving, and iterative cycles. The approach empowers students to actively engage with real-world challenges and co-create meaningful solutions.

Action research traces its origins to Kurt Lewin’s work in the 1940s, which emphasised the value of democratic, participatory approaches to research. The methodology gained prominence as scholars and practitioners recognised its potential for creating change within organisations and communities (Coghlan & Brannick, 2014). Action research is particularly suited for LSCM education, where the intricate interplay of supply chain elements demands a collaborative and adaptable mindset. Action research consists of several iterative phases, each contributing to a holistic learning experience.

• Problem Identification (Industry-Student Collaboration) – students identify a relevant supply chain issue or challenge that requires attention. This selection process often involves interactions with industry partners to ensure the chosen problem is authentic and impactful.
• Action Planning – in this phase, students devise strategies and interventions to address the identified problem. Collaborative brainstorming sessions and research are integral to formulating effective solutions.
• Implementation – students put their proposed solutions into action within real-world settings. This stage provides valuable opportunities for students to experience the challenges of implementing changes in complex supply chain environments.
• Data Collection and Analysis – during and after implementation, students collect data to assess the outcomes of their interventions. This step involves qualitative and quantitative research methods, enhancing students’ research skills.
• Reflection and Adaptation – action research emphasises continuous reflection on the outcomes of interventions. Students critically evaluate their efforts, learn from successes and failures, and use this insight to adapt their strategies for future iterations.

Figure 1 illustrates the five stages an action researcher undertakes when conducting action research in the empirical case context.

Figure 1. Action research cycle situated within the applied research case context.

Source: the author.

The iterative nature of action research closely mirrors the cyclical dynamics of supply chains, making it an ideal fit for LSCM education. The methodology enables students to grasp the complexities of supply chain operations by engaging in problem-solving activities that simulate real-world challenges. Action research cultivates critical thinking and analytical skills and enhances students’ abilities to collaborate, communicate, and adapt — an asset in an industry characterised by constant change.

Recent studies have highlighted the efficacy of action research in enhancing students’ learning experiences in diverse contexts. For example, in a study by Stringer (2020), action research was employed to improve student engagement and learning outcomes in a business ethics course. The findings demonstrated that students who participated in action research projects exhibited higher levels of critical thinking and deeper engagement with the course content.

 

2.2. Key Components of Experiential Learning and Application in LSCM Education

In logistics and supply chain management (LSCM) education, experiential learning emerges as a pivotal approach to bridging the gap between theoretical knowledge and practical application. As the complexities of global supply chains increase, the demand for professionals equipped with theoretical insights and hands-on skills has grown significantly. This section examines the theoretical underpinnings of experiential learning, its key components, and its relevance within undergraduate LSCM programs.

Experiential learning finds its roots in the works of John Dewey, Jean Piaget, and Kurt Lewin, who emphasised learning by doing and the importance of real-world experiences in the educational process. It posits that learners actively construct knowledge through meaningful engagement with their environment. In LSCM education, experiential learning allows students to directly apply theoretical concepts to authentic supply chain scenarios, enabling a deeper and more lasting understanding of the subject matter (Kolb, 2015).

Experiential learning involves a cycle of concrete experience, reflective observation, abstract conceptualisation, and active experimentation, as articulated by Kolb’s Experiential Learning Theory, as illustrated in Figure 2.

Figure 2. Kolb’s Experiential Learning Cycle (adapted from Kolb, 2015).

• Concrete Experience – students are exposed to real-world supply chain challenges, which are the foundation for subsequent learning. This phase sparks curiosity and sets the stage for deeper exploration.
• Reflective Observation – students critically reflect on their experiences, seeking to understand the underlying dynamics and implications. This phase encourages them to consider the practical significance of theoretical concepts.
• Abstract Conceptualisation – students connect their experiences and existing theoretical knowledge in this stage. They refine their understanding of supply chain principles and develop insights for future action.
• Active Experimentation – students apply their refined understanding to new situations, testing hypotheses and refining strategies based on the lessons learned from their experiential encounters.

Recent studies emphasise the impact of experiential learning in enhancing student engagement and knowledge retention. Experiential learning holds particular relevance in the LSCM discipline due to the tangible and dynamic nature of supply chain operations. For instance, a study by Gibbons (2020) demonstrated that experiential learning activities in a supply chain management course increased student motivation, improved critical thinking, and enhanced problem-solving skills. Students develop a holistic view of how theory translates into practice by actively participating in real-world experiences. Experiential learning opportunities are conducted through site visits, simulations, case studies, and collaborative projects with industry partners. Through these experiential learning activities, students gain insight into decision-making processes, risk management, and the implications of their actions on supply chain performance. In the digital age, experiential learning can be enhanced through technology-driven simulations and virtual reality experiences, allowing students to engage with supply chain scenarios in immersive and realistic virtual environments (Dong et al., 2021).

 

3. Integrating action research and experiential learning

Integrating action research methodology and experiential learning in students’ applied research projects requires a well-structured framework that guides educators and students through the process. Recent literature emphasises the importance of structured frameworks for integrating action research and experiential learning. A study by Cunningham et al. (2021) discusses a framework for incorporating these methodologies in a business education context, highlighting the significance of clear project objectives, stakeholder engagement, and ongoing reflection. In this paper, we adapt and outline a comprehensive framework encompassing key stages and considerations for successfully implementing this integrated approach within LSCM education.

 

3.1. Project Design: Industry-Student Collaboration

Collaboration with industry partners plays a pivotal role in project design. Engage with supply chain professionals to identify real-world challenges that align with the curriculum and offer students valuable experiential learning opportunities (Stringer, 2020). These challenges range from optimising supply chain networks to sustainability initiatives and risk management strategies. The chosen projects ensure relevance and applicability to the current supply chain landscape by involving industry stakeholders.

 

3.2. Data Collection and Analysis

Incorporate various data collection methods to provide students with a comprehensive understanding of the supply chain challenges. Encourage students to interview industry experts, observe operations on-site, and analyse relevant data sets. This phase enables students to refine their research questions, identify trends, and develop insights (Coghlan & Brannick, 2014). By exposing students to firsthand data collection, they gain practical experience in data management, analysis, and interpretation – a highly sought-after skill in the LSCM industry (Waller et al., 2019).

 

3.3. Action Implementation

Students should actively collaborate with stakeholders to design and implement actionable solutions derived from their research findings (Becker et al., 2018). This phase aligns with the tenets of action research, emphasising the iterative cycle of problem-solving and solution implementation. Engaging with industry partners allows students to understand the real-world feasibility of their proposed interventions and adapt their strategies to practical constraints (Christopher & Peck, 2020).

 

3.4. Reflection and Adaptation

Regular reflection sessions are integral to the success of the integrated approach. Allocate time for students to critically assess the outcomes of their interventions and reflect on the lessons learned. This reflection encourages students to identify successes, challenges, and areas for improvement. Additionally, students should explore how the theoretical concepts they have learned intersect with real-world experiences. This meta-cognitive process enhances students’ ability to connect theory and practice (Kolb, 2015).

 

3.5. Benefits of Integration

Based on the inputs and feedback of industry partners and students immensely involved in the case studies, integrating action research methodology and experiential learning presents a transformative approach to undergraduate logistics and supply chain management (LSCM) education by combining these methodologies, students acquire theoretical knowledge and develop practical skills, critical thinking abilities, and a deeper engagement with real-world supply chain challenges. This section elucidates the multifaceted benefits of integrating action research and experiential learning within LSCM programs that we have gathered based on the reflections and feedback from students and their industry collaborators, which we have triangulated from extant literature.

1. Enhanced Research Skills – Integrating action research and experiential learning provides students a comprehensive platform to hone their research skills. Through action research cycles, students are exposed to the intricacies of designing research questions, collecting data, and analysing results within authentic supply chain contexts. These experiences equip them with invaluable data collection, interpretation, and synthesis skills. Additionally, the reflective nature of experiential learning enhances students’ ability to identify relevant information and draw meaningful conclusions (Stringer, 2020). Such competencies are vital for LSCM professionals who must analyse complex data sets to make informed decisions (Waller et al., 2019).
2. Problem-solving Proficiency – The iterative nature of action research fosters problem-solving proficiency by guiding students through a structured process of diagnosing challenges, implementing solutions, and evaluating outcomes. This approach cultivates an adaptive mindset and encourages students to approach supply chain issues creatively and resiliently. Experiential learning complements this by immersing students in scenarios that demand immediate and strategic decision-making. Integrating these methodologies prepares students to address multifaceted challenges, equipping them to contribute effectively to supply chain optimisation and crisis management (Christopher & Peck, 2020).
3. Real-world Engagement – Experiential learning connects students with real-world supply chain scenarios, facilitating engagement with industry professionals, processes, and challenges. This firsthand exposure enables students to gain insights into the intricacies of supply chain operations, fostering an authentic understanding of the field. The collaboration inherent in action research ensures that students engage with stakeholders beyond the classroom, gaining perspectives from industry partners and incorporating practical feedback into their projects. Such engagement strengthens students’ ability to navigate real-world supply chain dynamics and facilitates networking opportunities that can benefit future career endeavours (Gibbons, 2020).
4. Holistic Learning – Integrating action research and experiential learning fosters holistic learning by simultaneously addressing cognitive, affective, and behavioural domains. While action research nurtures cognitive growth through rigorous research processes, experiential learning engages students on an affective and behavioural level by evoking emotional connections with supply chain challenges. This integrated approach enhances student motivation, engagement, and self-efficacy, essential for success in the dynamic and demanding LSCM industry (Kolb, 2015).
5. Lifelong Learning Mindset – Integrating action research and experiential learning instils a lifelong learning mindset in students. By continuously engaging in problem-solving, reflection, and adaptation, students develop the capacity to learn from both successes and failures. This reflective practice encourages a growth-oriented attitude, preparing graduates to stay relevant in the ever-evolving logistics and supply chain management landscape. The skills acquired through this integrative approach become transferable to various roles and industries, enhancing graduates’ career prospects and adaptability (Cunningham et al., 2021).
6. Ethical and Social Responsibility – Incorporating action research and experiential learning nurtures ethical awareness and social responsibility in future LSCM professionals. The emphasis on collaboration, stakeholder engagement, and real-world impact encourages students to consider the ethical implications of their decisions. They learn to balance economic efficiency with social and environmental sustainability—an essential skill in supply chain management. This integrated approach equips students to contribute positively to the industry’s reputation and address ethical challenges that may arise in their careers (Stringer, 2020).
7. Bridge to Industry – The integration of action research and experiential learning provides a bridge between academia and industry. As students engage directly with supply chain challenges and collaborate with industry partners, they gain practical experience and exposure to real-world dynamics. This exposure often leads to internships, projects, and job opportunities within the supply chain field. Graduates adopting this integrative approach in their applied research project design are not only knowledgeable but also industry-ready, possessing the skills and confidence to contribute meaningfully from day one (Gibbons, 2020).
8. Contribution to Research and Practice – Integrating action research and experiential learning can contribute to both research and practice in logistics and supply chain management. Action research projects can generate practical insights and solutions that address current industry challenges. Moreover, the collected data and outcomes can provide valuable inputs for academic research, contributing to developing best practices, theories, and methodologies. This reciprocal relationship between academia and industry ensures that education remains relevant and innovative (Cunningham et al., 2021).

 

4. Methodology – Case Studies

To exemplify the practical relevance of integrating action research methodology and experiential learning in undergraduate logistics and supply chain management (LSCM) projects, we showcase five case studies that illuminate the transformative impact of this innovative pedagogical approach. These selected case studies incorporated the principles of action research and experiential learning in the students’ applied research project designs. They highlight the alignment of the project design and implementation with action research methodology and experiential learning principles, emphasising the practical application of theoretical knowledge, further substantiating the efficacy of this integration. We also gathered feedback responses and inputs from the industry partners and students involved in these cases to evaluate the prospect of the integrative action research and experiential learning framework. Here, we present the case studies of LSCM students’ applied research projects that span diverse supply chain challenges.

Case Study 1: Supply Chain Optimisation

In this instance, students collaborated with a regional distributor grappling with intricate challenges in optimising their supply chain network. By embarking on an action research journey, students explored data-driven strategies to enhance distribution efficiency, reduce lead times, and bolster inventory management. Coupled with immersive experiential learning encounters, which encompassed visits to distribution centres and hands-on interactions with supply chain professionals, students adeptly integrated theoretical insights with practical observations. Consequently, they proposed an integrated digital platform for demand forecasting, inventory replenishment, and real-time monitoring. This intervention ushered in significant reductions in excess inventory costs and expedited order fulfilment, underscoring the merging of action research and experiential learning for robust supply chain optimisation. 

Case Study 2: Sustainable Supply Chain Practices

Students pursued sustainable supply chain practices and collaborated with a global manufacturing conglomerate committed to environmental stewardship. The action research phase delved into evaluating the environmental impact of their supply chain operations, encompassing carbon emissions, waste generation, and energy consumption. Through experiential learning expeditions, students engaged with cutting-edge sustainable practices firsthand, visiting solar-powered production facilities and engaging in discussions with sustainability experts. Armed with a synthesis of action research insights and experiential learning experiences, students recommended a multifaceted sustainability framework. The multifaceted framework encompassed material sourcing from eco-friendly suppliers, lean manufacturing principles, and renewable energy adoption. The manufacturer adopted these recommendations and catalysed a substantial reduction in their carbon footprint, bolstering their reputation as an environmentally conscious industry leader.

Case Study 3: Demand Forecasting Enhancement

Students collaborated with a regional distribution centre (DC), grappling with inconsistent demand forecasting. Leveraging action research cycles, students delved into data analysis of historical sales, seasonality trends, and market dynamics. They interacted with the DC’s planning team to understand their forecasting methods and challenges. The experiential element included hands-on simulation exercises where students created demand forecasts and evaluated the forecast accuracy against actual sales. Students devised a refined demand forecasting model by merging action research and experiential learning. Their proposals included incorporating machine learning algorithms to analyse data patterns and predict demand fluctuations. Implementing these strategies led to reduced stockouts and excess inventory, optimising supply chain performance and fostering cost savings.

Case Study 4: Reverse Logistics Enhancement

Students collaborated with a multinational electronics company aiming to enhance its reverse logistics process. The project incorporates action research and experiential learning in the design. Action research was applied to analyse the company’s returns data, identify reasons for returns, and evaluate the efficiency of return handling. The experiential component included site visits to the company’s repair centres and discussions with logistics managers about their challenges. Students proposed process improvements by including better return tracking systems and streamlined repair workflows. Additionally, they suggested proactive communication with customers to prevent unnecessary returns. The company implemented these recommendations, reducing the overall processing times, improving customer satisfaction, and increasing resource efficiency in its reverse logistics operations.

Case Study 5: Supplier Relationship Enhancement

This case study involved students collaborating with a global manufacturer to strengthen its supplier relationships. Action research guided students in analysing procurement data, supplier performance metrics, and communication processes. The experiential learning aspect included engaging with the manufacturer’s procurement team, attending supplier meetings, and understanding the challenges of maintaining effective supplier relationships. Students proposed strategies such as regular performance assessments, supplier development programs, and clear communication channels by integrating action research and experiential learning. Implementing these recommendations improved supplier collaboration, reduced lead times, and enhanced overall supply chain resilience.

Overall, these case studies highlight the synergy between action research and experiential learning in addressing real-world supply chain challenges. By integrating these methodologies, students gain theoretical understanding and develop practical skills, critical thinking abilities, and a profound engagement with supply chain issues.

 

5. Findings and Discussions

 

5.1. Challenges and Considerations

While integrating action research methodology and experiential learning is promising for enhancing undergraduate logistics and supply chain management (LSCM) education, several challenges, and considerations merit attention. Acknowledging and addressing these challenges is crucial for successfully implementing this pedagogical approach.

1. Time Constraints – One notable challenge is allocating sufficient time within the academic calendar to accommodate the various phases of action research and experiential learning. Designing practical projects, conducting research, implementing solutions, and reflecting on outcomes can be time intensive. Balancing these activities with the curriculum’s content coverage requires careful planning and may necessitate adjustments to course schedules (Cunningham et al., 2021).
2. Stakeholder Involvement – Engaging industry stakeholders in the educational process can be challenging due to logistical constraints and differing priorities. Effective communication and coordination are essential to ensure that industry partners are actively involved in project design, feedback, and assessment. Maintaining consistent collaboration throughout the project duration requires ongoing effort from educators and students (Stringer, 2020).
3. Assessment Methods – Traditional assessment metrics may need to be adapted to effectively evaluate the multifaceted learning outcomes resulting from the integrated approach. Assessing students’ research skills, critical thinking abilities, and practical problem-solving competence can be challenging using conventional methods. Developing robust assessment strategies that capture the holistic impact of action research and experiential learning is crucial (Gibbons, 2020). Navigating these challenges requires proactive planning, open communication, and flexibility in curriculum design. Recent literature supports these considerations, as evidenced by a study by Cunningham et al. (2021), which emphasises the importance of stakeholder engagement and the adaptation of assessment methods when integrating action research and experiential learning in management education.
4. Faculty Training and Support – Faculty training and support are pivotal in successfully implementing the integrated approach combining action research methodology and experiential learning in undergraduate logistics and supply chain management (LSCM) programs. Educators must be equipped with the necessary knowledge and skills to guide students through the intricacies of these methodologies effectively. This section discusses the importance of faculty development and offers insights into how educators can prepare for this innovative pedagogical approach.
5. Pedagogical Training – Providing faculty members with the necessary pedagogical training on action research methodology and experiential learning pedagogies is critical. These can be conducted through workshops and seminars that familiarise educators with the principles, processes, and best practices of these methodologies. Such training empowers faculty to design projects effectively, facilitate research activities, guide students in experiential learning, and provide constructive feedback. Educational institutions should also provide faculty members with resources such as case studies, curriculum templates, assessment tools, and technological support. These resources streamline the implementation process and alleviate potential barriers educators might encounter.
6. Collaborative Learning Communities – Encouraging a grassroots approach among faculty members by creating communities of practice can be immensely beneficial. Regular meetings, discussions, and knowledge sharing enable educators to exchange experiences, challenges, and success stories related to integrating action research and experiential learning. Collaborative environments foster continuous improvement and the refinement of teaching strategies.
7. Continuous Professional Development – Given the dynamic nature of the LSCM field and educational methodologies, ongoing professional development is essential. Faculty members should be encouraged to attend conferences, participate in webinars, and research to stay current with industry trends and pedagogical advancements. Recent literature underscores the significance of faculty training in innovative teaching approaches. A study by Conway et al. (2019) emphasises the impact of faculty development on student engagement and learning outcomes. Additionally, the study by Cunningham et al. (2021) highlights the importance of providing educators with the tools and support needed to effectively integrate action research and experiential learning.

 

5.2. A conceptual framework for integrating action research and experiential learning

To synthesise our findings and discussions, we propose a conceptual framework for integrating action research and experiential learning in designing students’ applied research projects, as illustrated in Figure 3.

The integrative framework (shown in Figure 3) for combining action research methodology and experiential learning creates a transformative educational experience for undergraduate logistics and supply chain management students. By fostering research skills, problem-solving proficiency, real-world engagement, holistic learning, ethical awareness, industry readiness, and contributions to research and practice, this approach equips students with the multifaceted competencies demanded by the dynamic LSCM industry. As the logistics and supply chain management landscape evolves, this integrated approach stands as a cornerstone of effective and impactful education.

Figure 3. An Integrative framework combining action research and experiential learning for LSCM students applied research projects.

 

5.3. Impacts of AI on the Integrative Framework

As AI technologies become increasingly prevalent, they introduce new dimensions to teaching and learning that complement the integrated approach proposed in this paper. AI tools complement and support training and education to meet the skills needs in the evolving landscape of the logistics and supply chain management industry (Hernández et al., 2021). Hence, the integration of action research methodology and experiential learning can be further enriched by the transformative influence of Artificial Intelligence (AI). We explore the impacts of AI on LSCM education and how it enhances the integration of action research and experiential learning through the five case studies.

1. Data-Driven Insights

AI-powered analytics offer students unprecedented access to data-driven insights within supply chain contexts. Real-time data collection and analysis enable students to identify supply chain operation patterns, trends, and anomalies. These elements align seamlessly with the action research process, enhancing students’ ability to diagnose problems accurately and make informed decisions. By integrating AI-driven insights into action research cycles, students can develop robust, theoretically sound solutions rooted in empirical evidence (Waller et al., 2019).

1. Simulations and Virtual Reality

AI-driven simulations and virtual reality (VR) experiences provide immersive learning environments replicating complex supply chain scenarios. These technologies allow students to engage with real-world challenges in a controlled setting, enhancing their experiential learning journey. Dong et al. (2021) explores the impact of virtual reality and AI-driven simulations on experiential learning in operations and supply chain management. By simulating supply chain disruptions, demand fluctuations, and other dynamic scenarios, students can actively experiment and observe the outcomes of their decisions. These elements aid in developing decision-making skills and cultivating an adaptive mindset, aligning with the tenets of both action research and experiential learning.

1. Personalised Learning

Recent literature highlights the transformative role of AI in education. The study by Ellington and Earl (2020) discusses how AI-powered personalised learning enhances student engagement and critical thinking. AI-driven platforms can personalise learning experiences based on students’ strengths, weaknesses, and learning styles. Adaptive learning algorithms tailor content delivery, ensuring students receive the proper levels of challenge and support. In action research and experiential learning, personalised learning pathways can enhance students’ research skills, critical thinking abilities, and practical problem-solving competence. This individualised approach encourages deeper engagement and allows students to progress at their own pace (Ellington & Earl, 2020).

1. Continuous Feedback and Assessment

AI-enabled tools can provide real-time feedback on students’ progress and performance. This immediate feedback loop aligns with the iterative nature of action research, allowing students to refine their interventions and strategies based on AI-generated insights (Siemens & Baker, 2012). Students can benefit from experiential learning through continuous assessment, with timely input on their decision-making processes within simulations and virtual environments. Therefore, AI-enabled tools facilitate the development of reflective and adaptive learning practices (Conway et al., 2019).

As AI technologies advance, they offer exciting opportunities for enriching the integrated approach of action research methodology and experiential learning, further equipping students for success in the dynamic field of logistics and supply chain management.

Table 1 summarises the impact of AI applied to the five case studies of LSCM students’ applied research projects that were examined in this study.

Impact of AI	Case Study 1: Supply Chain Optimisation	Case Study 2: Sustainable Supply Chain Practices	Case Study 3: Demand Forecasting Enhancement	Case Study 4: Reverse Logistics Enhancement	Case Study 5: Supplier Relationship Enhancement
Data-Driven Insights	AI tools enhanced timeliness in data updates and visibility	AI tools enhanced timeliness in data updates and visibility	AI tools enhanced timeliness in data updates and visibility	AI tools enhanced timeliness in data updates and visibility	AI tools enhanced timeliness in data updates and visibility
Simulations and Virtual Reality	Simulated supply chain scenario to optimise network planning	Simulated sustainable practices that incorporated multifaceted considerations	Simulated demand events to fit the best fit demand model	VR tools used for learner to mimic the return logistics process	—
Personalised Learning	Adaptive learning algorithm used in the AI platform for students to explore data-driven strategies to enhance distribution efficiency, reduce lead time	AI tools tailored content delivery for student to learning carbon emissions concepts and sustainability practices	—	—	AI tools allowed student to retrieve updated procurement data, supplier performance metrics, and simulate communication processes
Continuous Feedback and Assessment	AI tools can provide real-time feedback on students’ progress and performance	AI tools can provide real-time feedback on students’ progress and performance	AI tools can provide real-time feedback on students’ progress and performance	AI tools can provide real-time feedback on students’ progress and performance	AI tools can provide real-time feedback on students’ progress and performance

Table 1. Implications of AI on Student’s Applied Research Project and Learning.

 

6. Conclusions

Integrating action research methodology and experiential learning in undergraduate logistics and supply chain management (LSCM) programs represents a dynamic and transformative pedagogical approach. This novel integrative approach addresses the evolving demands of the LSCM industry by equipping students with a holistic skill set that combines theoretical knowledge, practical skills, critical thinking abilities, and a deep engagement with real-world challenges.

Extant literature supports the efficacy of incorporating action research and experiential learning tenets in engaging learning, internalising knowledge, and deepening skill. For instance, Cunningham et al. (2021) provide a framework for integrating action research and experiential learning in management education. Integrating action research methodology and experiential learning serves as a beacon for LSCM education. The case studies presented in this paper underscore the practical relevance and positive outcomes of integrating these methodologies. They demonstrate how students can collaborate with industry partners to address supply chain optimisation and sustainability challenges, resulting in tangible improvements and impactful contributions to the LSCM sector.

The synergistic benefits of action research and experiential learning offer a powerful educational experience for students. We found that students emerge from this approach with enhanced research skills, the ability to devise practical solutions to complex problems, a real-world understanding of supply chain dynamics, and a comprehensive learning experience encompassing cognitive, affective, and behavioural domains.

By embracing this dynamic approach, institutions can empower the next generation of supply chain professionals with the knowledge, skills, and adaptability needed to thrive in the ever-evolving logistics and supply chain management world. This study highlighted several critical elements for educators to implement this integrated approach successfully. Educational institutions must acknowledge and overcome challenges such as time constraints, stakeholder involvement, and the adaptation of assessment methods. Further, Conway et al. (2019) emphasise the importance of faculty development in improving student engagement and learning outcomes to maximise learning using such an integrative pedagogy. Hence, faculty training and support are paramount, ensuring educators are well-prepared to guide students through the intricacies of action research and experiential learning methodologies.

We also examined the impacts of artificial intelligence (AI) on teaching and learning that are expected to amplify the efficacy of this integrated approach. Students can benefit from a comprehensive and adaptable educational experience with the aid of AI-tools through personalised learning, data-driven insights, collaboration enhancement, and ethical considerations facilitated by AI. We highlight the implications of AI-enabled tools that are expected to enhance students’ learning and field experience through the five cases of LSCM applied research projects that were carried out by the students. As AI continues to shape education, its synergy with action research and experiential learning is expected to further enriches LSCM education, ensuring students are well-prepared to navigate the industry’s evolving demands.

 

About the Author

Huay Ling Tay

ORCID ID: 0000-0002-2462-3240

Singapore University of Social Sciences, Singapore

hltay@suss.edu.sg

 

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