Authentic assessment is increasingly seen as essential in management education for aligning assessment tasks with the complex, collaborative, and uncertain, multi-stakeholder demands of modern workplaces. This paper argues that, despite its popularity, the impact of authentic assessment on graduate preparedness remains poorly understood. To address this, the paper builds and evaluates an integrative model relating authentic assessment design, feedback and reflection, perceptions of assessment value, professional self-efficacy, and perceived workplace outcomes among management students. Drawing on literature about authentic assessment, experiential learning, situated cognition, assessment for learning, and employability, the paper frames authentic assessment as a holistic pedagogical system. A cross-sectional survey of 412 undergraduate and postgraduate students in business and management at four universities provides the empirical basis. The instrument was honed through expert review and a pilot test, and analyses included confirmatory factor analysis, reliability and validity checks, correlations, and hierarchical regression and mediation tests. The findings show that authentic assessment design strongly correlates with workplace readiness, especially when dialogic feedback, reflection, and professional self-efficacy are present. External audience group projects, live case analysis, simulations, and portfolio-based evaluation proved effective with clear criteria and guided post-task reflection. The paper contributes a process model and actionable design principles for educators to enhance employability through meaningful assessment, advancing the discourse on management education.
Generative artificial intelligence (GenAI) amplifies four tensions in business and management education: the threat to pedagogical coherence, the literacy-to-competency gap, pervasive ethical risks, and the assessment crisis. A first wave of practice-oriented frameworks – including the Human-Centric AI-First (HCAIF) framework and the Leeds Model – offers actionable roadmaps but lacks the theoretical architecture needed to explain the systemic classroom dynamics GenAI introduces. This conceptual paper addresses that gap by developing the AI-Augmented Collaborative Learning (ACL) Model, a second-wave framework organised around three research questions: (RQ1) which theoretical lenses explain the classroom dynamics that generative AI creates in business and management education; (RQ2) how can these be synthesised into an integrated pedagogical framework whose pillars address the four systemic challenges; and (RQ3) how can human-AI collaboration be operationalised as an assessable pedagogical meta-skill. Using Socio-Technical Systems Theory, Activity Theory, Actor-Network Theory, Constructivist and Experiential Learning Theories, and the AI-TPACK framework, the ACL Model specifies four interlocking pillars – Pedagogical Intentionality, Developmental Scaffolding, Ethical Guardrails, and Authentic Assessment. The paper's primary theoretical contribution is to relocate the unit of analysis from the individual student to the student-AI network and to define collaborative intelligence as the resulting meta-competency. A six-proposition validation agenda guides testing.
Student perceptions of instructional effectiveness in technology-rich management education remain actively studied amid concerns about classroom distraction in digitally mediated environments. This study introduces IMPACT—an integrative pedagogical framework composed of Incentive, Measurement, Project-based Learning, Accountability, Critical Reflection, and Technology. It presents an exploratory, multi-course demonstration across four management courses spanning the MBA, Executive MBA (EMBA), and Executive Postgraduate Diploma in Management (EPGDM–VIL) programs, delivered in face-to-face and synchronous online modes. Implementation was examined using institutional course-evaluation data (N = 202 of 203 enrolled students), and a thematic close reading of open-ended comments informed by reflexive thematic analysis. Across all four courses, student perceptions of instructional effectiveness were uniformly high on standardized nine-item instrument (weighted averages ≥ 6.0 on a seven-point scale). Qualitative themes aligned with the framework's design intent: practical relevance, structured project workflows, visible progress indicators, and technology-mediated tools, alongside integrative configuration as a framework-level property. Findings support consistent implementation across heterogeneous settings and association with positive student perceptions, but do not support causal claims about engagement. The study contributes design-oriented vocabulary identifying integrative configuration, operational workflow, and multi-mode portability as the framework's primary contributions. Limitations include single-institution, single-instructor, construct–measurement mismatch, and the absence of comparative or pre/post designs.
Generative artificial intelligence has entered management education faster than many business schools have redesigned pedagogy, assessment, and employability development. This study examines how management students’ AI use can be transformed into responsible, reflective, and employable AI capabilities. Using a pre- and post-intervention design with 412 management students across two comparable course sections, the study compared a conventional AI access condition with a guided AI capability condition. The guided condition included four pedagogical modules on task alignment, evidence verification, responsible reflection, and employability translation. Data was collected through survey measures, AI use logs, reflective journals, rubric-based project assessment, and structural equation modelling. The results show that the guided group achieved substantially higher gains in task-aligned AI use, responsible reflection, AI capability, and employability confidence. Project performance data confirmed this pattern, with the largest difference in ethical awareness between the two groups. The structural model shows that AI readiness does not directly influence employability confidence. Instead, readiness influences confidence through task-aligned use, responsible reflection, and AI capability. This study contributes by shifting attention from AI adoption to AI capability and by positioning responsible reflection as the key mechanism through which AI use becomes learning.
Entrepreneurship education is often examined as a uniform educational exposure, although its associations with student development may depend on instructional mode and learner-level digital conditions. This study compares six entrepreneurship education formats and examines their associations with two self-perceived outcomes—creativity and entrepreneurial mindset—while assessing whether these relationships vary by perceived digital literacy and functional social media use. Drawing on survey data from 1181 graduating students at a multidisciplinary university in Guangdong, China, we use propensity score matching to improve comparability between participants and non-participants on observed characteristics and estimate interaction models to assess conditional relationships. The results indicate that entrepreneurship education is more consistently associated with entrepreneurial mindset than with creativity. Business plan competitions, training programs, and practical workshops generally show comparatively strong associations, particularly relative to entrepreneurship courses, although public lectures are also notably associated with entrepreneurial mindset. Perceived digital literacy displays a selective and format-dependent moderating relationship with creativity but does not consistently moderate the relationship with entrepreneurial mindset. Functional social media use shows no stable moderation in the primary binary models, while supplementary continuous-measure models reveal some operationalization-sensitive patterns. These findings indicate that entrepreneurship education is best understood as a heterogeneous set of learning experiences whose associations with student development vary across instructional modes, developmental outcomes, and learner-level digital conditions.
Existing literature on generative AI (genAI) in business education has examined students’ attitudes, motivation, and the ethics of genAI use, alongside ongoing debate about whether genAI over-reliance may diminish self-regulated learning (SRL). However, how students self-regulate their learning while working with genAI during authentic tasks remains under-explored. This study addresses this gap by examining (RQ1) how students' self-regulatory strategies manifest during genAI-assisted learning and (RQ2) how these strategies change through genAI interaction. A thematic analysis was conducted of 34 metacognitive reflections generated across two scaffolded, four-stage experiential learning activities in a Lean Startup unit. Findings inform a three-stage AI-mediated recursive loop model, comprising monitoring, strategic adoption, and limitation identification, that extends cyclical models of self-regulated learning by showing how regulation may be initiated within the task by genAI-generated suggestions. Within this structured, reflective learning context, students indicated evaluative judgement and metacognitive regulation, providing preliminary evidence that scaffolded genAI activities can elicit active rather than passive engagement. GenAI-supported cognitive deepening was task-contingent, emerging most strongly during applied refinement tasks. The model offers management educators a pedagogical process model for designing scaffolded genAI-assisted activities that elicit monitoring, selective adoption, and critical reflection.
The growing prominence of environmental, social and governance (ESG) reporting, sustainability, and ethical accountability is reshaping expectations of accounting and management graduates. While these competencies are increasingly embedded within global professional standards and competency frameworks, their translation into educational assessment remains underexplored. This study examines how ESG, sustainability, and ethics are embedded in documented assessment across global standards, professional competency frameworks, and Australian university accounting education.Using qualitative comparative document analysis, the study analyses the International Federation of Accountants’ International Education Standards, the competency frameworks of CPA Australia and Chartered Accountants Australia and New Zealand, and assessment documentation from 104 undergraduate accounting units across 26 Australian universities.The findings reveal partial and uneven alignment. Although sustainability and ethics are explicitly articulated within global and professional frameworks, they are frequently embedded implicitly within technically oriented assessment tasks rather than explicitly assessed as judgement-focused competencies. To explain this pattern, the study introduces the concept of differential assessability, which explains why some professional competencies are more readily translated into assessment than others despite comparable prominence within professional standards. By reframing ESG integration as an assessment design challenge, the study extends assessment theory and offers practical implications for responsible management and accounting education.
Management education increasingly needs ways to prepare students for AI governance, yet students have limited opportunities to practise the organisational judgement involved in deployment decisions. This paper presents “Leading in the Age of AI”, a card-based serious game in which student teams assume asymmetric C-suite roles, make AI deployment decisions under constraints, and document their reasoning in Model Cards adapted from AI documentation practice. Conceptually, the paper frames AI governance education as accountable decision-making under uncertainty: students negotiate competing priorities, allocate scarce safeguards, respond to disruption, and prepare written accounts for scrutiny. The paper contributes a reusable game design, a pedagogical adaptation of Model Cards as justification artefacts, and design patterns for management-education contexts involving accountable decisions under uncertainty. An exploratory evaluation across two undergraduate cohorts used matched pre-test/post-test data (N=67), post-session evaluations, and descriptive artefact analysis of team-produced Model Cards (n=15). Students evaluated the activity positively and reported immediate confidence gains across knowledge, ethics, and governance composites (dz=0.44 to 1.00), while quiz gains were modest and not statistically significant. Model Card analysis suggests the activity generated inspectable governance reasoning, while leaving causal learning, retention, and transfer for future research.
This study investigates the factors influencing classroom participation among Chinese undergraduate students in a UK business programme. Drawing on a mixed-methods design, focus groups first identified key barriers and motivators of engagement, which then informed a survey completed by 61 students. Exploratory factor analysis revealed four motivational dimensions, with lecturer-driven practices such as clear guidance, encouragement, and responsiveness emerging as the strongest predictors of participation. Regression analysis confirmed that guidance, positive lecturer attitude, and instructional support significantly predicted engagement. Although language barriers remained the most prominent hindrance, findings show these challenges can be moderated through inclusive pedagogical design. The results highlight that participation is shaped less by cultural background and more by the instructional environment students encounter. The study contributes evidence that lecturer agency, instructional clarity, and supportive classroom climates play central roles in fostering engagement in internationalised higher education contexts.
As universities increasingly leverage digital technologies for entrepreneurship education, understanding the mechanisms that translate learning into tangible action is crucial. This study employs a sequential explanatory mixed-methods design to investigate how digital entrepreneurship education influences university students' actual digital entrepreneurial behavior. First, a survey of 4715 university students in China was analyzed using PLS-SEM. The quantitative results indicate that digital entrepreneurship education positively affects digital entrepreneurial behavior, and this relationship is significantly mediated by entrepreneurial passion. Furthermore, family support positively moderates the crucial link between entrepreneurial passion and digital entrepreneurial behavior. Second, semi-structured interviews with 10 students were conducted to explain these statistical findings. The qualitative analysis reveals important pedagogical nuances: effective digital entrepreneurship education is practical and tool-based, providing students with tangible skills that directly ignite passion. Moreover, family support functions as a critical psychological safety net, empowering students to convert passion into risk-taking action. By integrating quantitative pathways with rich qualitative insights, this study provides a holistic understanding of digital entrepreneurship formation and offers evidence-based implications for designing effective digital learning environments that cultivate both the skills and the courage for entrepreneurship.
Value co-creation has become an influential yet conceptually fragmented construct in management education. Existing research remains dispersed across disciplines, limiting its translation into coherent educational design. This review synthesizes studies published between 2015 and 2025 to clarify how co-creation is conceptualized, enacted, and assessed in management education.Guided by service-dominant logic, stakeholder theory, and experiential learning, the review conceptualizes management education as a stakeholder learning ecosystem in which educational value is co-created through interaction rather than delivered unilaterally. Using a structured review protocol and abductive thematic analysis, five themes are identified: fragmented conceptualizations; stakeholder incentives and tensions; implementation; pedagogical strategies; and learning outcomes.Building on this synthesis, we develop a three-dimensional pedagogical framework comprising stakeholder value logic, stakeholder relational design, and stakeholder learning orchestration. The framework positions co-creation as a coordinated pedagogical approach that aligns how educational value is defined, stakeholder roles and authority are configured, and learning is governed through experiential design and assessment.Across reviewed studies, co-creation is associated with enhanced engagement, perceived relevance, and responsibility-oriented learning. However, assessment and governance remain underdeveloped. The framework addresses this by specifying minimal design conditions under which co-creation becomes educative rather than participatory, offering guidance for educators to implement co-creation systematically.
This paper documents the journey of design, development, delivery, and key learnings from a cross-functional integrated MBA-level course offered by the authors over five cycles. Drawing on film-based pedagogy, the course utilized multiple full-films, integrated readings, a cross-functional lens in delivery that involved four instructors. The focus was integration, visualization and engagement for Gen Z students using experiential and reflective learning. Addressing two instructional objectives: (1) How can an engaging film-based course be designed, developed, and integrated into conventional management education for greater effectiveness? And (2) In what ways does this innovation influence Gen Z learning and engagement? The authors tracked their experiences with the course at both individual and teaching group level along with qualitative experiences of the students. The authors situated this study within the Experiential Learning Theory (ELT), learning styles and engagement frameworks in higher education. The evidence from the course provides a useful instructional design guideline for other instructors, institutions and their leaders.
There is a growing interest in adequate entrepreneurship education and training for new venture creation. New product development depends on entrepreneurs’ expertise in product design and project management. However, there is a lack of research on integrated product design and project management training in a startup context. The purpose of this study is to investigate the contribution of a new approach to entrepreneurship education on new product development projects. We developed a workshop that combines product design and project management training, employing specialized new product development tools and techniques, as well as project management simulators. This workshop was held for the first time at a U.S. startup incubator. A cohort of twelve entrepreneurs was exposed to structured methods from ideation to project planning. We collected data through observations during the training, questionnaires, and interviews with eight entrepreneurs. We observed variations in the practices employed by the entrepreneurs during and after the training. The differences stemmed from the venture stage, knowledge gaps in understanding the voice of the customer, product requirements, and the time and cost of the project. This research contributes to entrepreneurship literature by detailing the content, methods, and impact of training. The findings offer insights into certain practices applied in a seven-day workshop that facilitates novice entrepreneurs to turn ideas into product concepts and project plans.
This study examines when class size becomes a pedagogical challenge in management education, shifting the focus from numerical thresholds to the pedagogical conditions under which difficulties arise. Drawing on a survey of 217 faculty members across disciplines in a Canadian business school, the findings show that while challenges occur in both classes perceived as too small and those perceived as too large, they are more frequently associated with large classes. No universal threshold was identified; instead, a hierarchy of challenges emerged, indicating that class size matters most when faculty aim to develop higher-order cognitive skills, implement active learning methods, and foster meaningful pedagogical relationships. The study contributes by examining student cognitive skills, teaching methods, and pedagogical relationships simultaneously, showing that class size becomes a pedagogical challenge under specific pedagogical conditions rather than at specific numerical thresholds. More broadly, it reframes the debate from “how big is too big?” to “under what pedagogical conditions does class size become a challenge?” It also invites researchers and business schools to consider the longer-term consequences of large classes for pedagogical relationships, which may erode not only student engagement but also the development of the interpersonal skills that management education seeks to cultivate.
This study investigates how generative AI influences students' entrepreneurial mindset development in a seven-week experiential entrepreneurship course designed with Knightian uncertainty. Adopting a constructivist grounded theory approach, we conducted a longitudinal seven-week qualitative field study involving 462 final-year undergraduate students enrolled in the module during one academic semester. Drawing on data collected from participant observation, simulation game logs, reflective essays and learning journals, longitudinal semi-structured interviews with 30 purposively selected participants, and post-course focus groups, we identify three distinct AI perception and utilization patterns: tool-instrumental, authority-decisive, and partner-collaborative. As Knightian uncertainty intensified, students recognized AI's bounded nature across four dimensions-actor ignorance, practical indeterminism, agentic novelty, and competitive recursion-leading to reduced AI dependence and strengthened entrepreneurial judgment and heuristic reasoning. The study highlights generative AI's dual role: a cognitive enhancer that reduces initial cognitive load during venture formation, yet a potential barrier to entrepreneurial mindset development when used blindly. We contribute to entrepreneurship education literature by clarifying when and how generative AI shapes entrepreneurial mindsets, introducing "productive friction" derived from Knightian uncertainty as a catalyst for cognitive growth. The research calls for educators to strategically embed greater Knightian uncertainty into entrepreneurship education, balancing AI proficiency with the cultivation of cognitive adaptability, heuristic-based decision-making, and tolerance for uncertainty, thereby preparing students for real-world entrepreneurial challenges.
Active learning strategies are widely promoted in management education, yet empirical evidence on specific assessment-based interventions remains limited. This study examines the effectiveness of student-generated questions (SGQ) as an active learning strategy in an undergraduate international business course at a Hispanic-Serving Institution. Drawing on the generation effect and retrieval practice literature, we implement a quasi-experimental design comparing students who voluntarily participated in creating multiple-choice questions with those who did not. Controlling for prior academic performance and grade point average, results indicate that participation in SGQ is positively associated with higher final exam performance. Interaction analyses do not provide evidence that this association differs across performance levels. This study contributes to management education research by demonstrating how structured student-generated assessment activities are associated with improved academic performance within a diverse classroom context.
Following major corporate scandals such as Enron and the subprime crisis, debates about the mission of business schools and their responsibility to cultivate ethical leadership tend to intensify. However, Parra et al. (2022) show that, despite extensive scholarship on the topic, institutional responses to external pressure are often superficial and fragmented, falling short of the structural reforms required for robust ethical formation. This article presents a single-case study of a Colombian private business school to examine how the alignment between institutional identity/mission and the input-process-output design of its educational system can strengthen ethical formation. The case is analytically valuable because it captures a coherent, mission-driven model operating within a competitive environment shaped by regulations, accreditations, market demands, and rankings-conditions common to many business schools yet underexplored in Latin American contexts. Methodologically, we conduct a document-based case study drawing on institutional sources (mission and vision statements, program outlines and evaluations, and accreditation reports). The study contributes to the literature on management education and ethics by, first, proposing a conceptual model that holistically links institutional policies and practices to the effectiveness of ethics education; and second, applying this model to a concrete institutional practice to illuminate how specific educational variables interact and with what implications for learners. Findings indicate that tight identity-design alignment can deepen ethical learning while remaining responsive to external pressures; however, they also reveal vulnerabilities to misalignment and potential trade-offs in faculty socialization and adaptability. We discuss implications for designing system-level strategies that move beyond isolated pedagogical initiatives.
Mathematics preparation is a key determinant of success in business and other quantitatively oriented majors, yet many students enter college underprepared and are placed into remedial coursework. This paper examines how mathematics placement shapes academic trajectories. Using administrative data from a mid-sized public university and a fuzzy regression discontinuity design, we estimate the causal impact of placement just below versus above key thresholds. Students placed into remediation are significantly less likely to enroll in gateway math courses, pursue quantitatively intensive majors, or graduate within six years. These differences emerge among students with nearly identical placement scores, suggesting that placement itself-through added time, cost, or discouragement-alters behavior. We find little evidence that remediation improves course success, indicating limited academic benefit relative to its costs. Traditional prerequisite-based remediation may therefore act as a barrier rather than a support. We conclude by discussing alternatives appropriate to business schools, including co-requisite models and integrated quantitative instruction, that may better support progression and completion.
