The IMPACT model promotes the integration of AI alongside industry partnerships, mentorship, and agile curriculum design to equip students with future-ready skills, personalized career guidance, and entrepreneurial thinking. This approach not only aligns education with real-world demands but also leverages AI to enhance learning experiences, making education more adaptive, personalized, and relevant in a rapidly changing technological landscape. Additionally, platforms like Zoom can be utilized to facilitate real-time collaboration with industry experts, mentorship sessions, and virtual project-based learning. By leveraging these digital tools, the IMPACT model ensures that students can connect with professionals and peers globally, breaking down geographical barriers and providing access to a wider range of learning opportunities and perspectives.
In the rapidly evolving landscape of secondary education, the integration of AI alongside industry partnerships and mentorship programs has emerged as a transformative model for enhancing student learning. This approach is particularly powerful when aligned with the key disciplines of design, engineering, and digital technologies. AI tools can play a critical role in this integration by offering data-driven insights, personalizing learning experiences, and facilitating connections between students and professionals. By connecting students with leading professionals, entrepreneurs, and innovators, and enhancing these interactions with AI-driven platforms, schools can create dynamic learning environments that extend beyond traditional classroom boundaries. Research highlights that these partnerships, augmented by AI, not only bridge the gap between theory and practice but also empower students with the skills and insights needed to thrive in the ever-changing world of design, engineering, and digital innovation (Billett, 2011; Dede, 2014).
Additionally, secondary-age students and young adults are already leveraging highly powerful technical systems, including AI, to shape their own economic futures, shying away from formal academic pathways in favor of more direct, cost-effective routes to career development (Facer, 2011). Many are building personal brands through social media platforms, where they collaborate with influencers and specialized leads to promote their skills, products, or services. AI-driven algorithms on platforms like YouTube, Instagram, and TikTok help these young entrepreneurs optimize their content, reach targeted audiences, and even predict trends, enhancing their ability to attract sponsorships, freelance opportunities, and launch startups. Others are engaging in online communities and forums where AI-powered recommendation systems connect them with industry professionals, gaining mentorship and insights that would traditionally be acquired through years of formal study. This trend underscores the declining viability of the traditional model of spending four years in expensive study, as these students seek more seamless, AI-supported opportunities to integrate into the workforce.
Professor Ruth Bridgstock’s concept of the “key-shaped professional” is particularly relevant here, as it emphasizes the importance of students developing a deep expertise in a specific area (the stem of the key) while also cultivating broader, transferable skills (the teeth of the key) that enable them to adapt to various roles and challenges across industries (Bridgstock, 2009). Micro-credentialing plays a crucial role in this model, allowing students to earn certifications in specific skills or knowledge areas that are highly valued by industry (Gallagher, 2016). The evolving role of micro-credentialing, increasingly supported by AI-driven platforms that personalize learning paths, will create more flexible and relevant pathways that better align with the pace of industry demands. This model challenges traditional academic pathways, which often struggle to keep up with rapid technological advancements and changing workforce requirements (Collins & Halverson, 2018). As the future of schooling and academics continues to evolve, there will be a growing need for educational systems to adopt more agile, personalized, and industry-integrated approaches to remain relevant. Through real-world engagement, targeted micro-courses, and AI-enhanced learning tools, students gain valuable industry expertise, future-focused skills, and a deeper understanding of how their education directly translates into meaningful, impactful careers (Schwab, 2017; Sanders & Stappers, 2008).
Dean Ashenden’s – Unbeaching the Whale offers a critical examination of the entrenched and often outdated structures of formal education, likening the education system to a beached whale—massive, immobile, and struggling to adapt to a rapidly changing world. This metaphor is particularly relevant when considering the transformative model of secondary education that integrates industry partnerships, mentorship programs, and micro-credentialing.
Ashenden argues that the traditional educational system, with its rigid pathways and slow adaptability, is increasingly at odds with the needs of modern students and the fast-paced demands of contemporary industries. The model proposed here—where students engage directly with industry professionals, earn micro-credentials, and leverage powerful technical systems to advance their careers—embodies the kind of flexibility and relevance that Ashenden advocates for in his text.
By moving away from the traditional, one-size-fits-all academic pathway and embracing more personalized, industry-aligned learning experiences, this approach addresses the “beaching” problem that Ashenden describes. It challenges the inertia of the traditional education system, offering a more agile and responsive alternative that better prepares students for the future. With the integration of AI to personalize learning and streamline educational pathways, this model further aligns with Ashenden’s vision by enhancing the adaptability of the education system to meet the dynamic realities of the modern world, ensuring that students are equipped not just to survive, but to thrive in their chosen careers.
Proposed IMPACT Model:
Industry-Integrated Learning: Students gain direct exposure to industry trends, challenges, and innovations, ensuring their academic studies are relevant and responsive to workforce demands. This integration challenges the outdated structures critiqued by Ashenden and aligns with the need for education to bridge the gap between theory and practice, as emphasized by Billett (2011) and Dede (2014). For instance, students can collaborate with local businesses and tech companies on real-world projects, with AI-driven tools supporting their work by providing data insights or automating certain project management tasks, similar to how young people today use platforms like YouTube, Instagram and TikTok to gain practical experience and visibility.
Mastery of Future-Ready Skills: Engagement with industry professionals and micro-credentialing helps students develop critical skills like problem-solving, adaptability, and digital literacy. AI can assist in tailoring learning resources to individual student needs, ensuring that they acquire the in-demand skills necessary for the future. This approach addresses the inadequacies of traditional education in preparing students for the future, as highlighted by Ashenden and aligns with Bridgstock’s (2009) notion of the “key-shaped professional.” Young people are already demonstrating this by earning certifications through online courses and boot camps, often with AI-enhanced learning platforms.
Personalized Mentorship and Career Guidance: Access to mentors and role models offers tailored advice, countering the “one-size-fits-all” approach critiqued by Ashenden, and providing clarity in educational and career pathways. AI can enhance these mentoring relationships by helping match students with the right mentors based on their career goals and learning styles. This personalization aligns with Bridgstock’s (2009) emphasis on the importance of broader, transferable skills. Students can engage with industry experts for personalized advice, similar to how emerging professionals seek mentorship from influencers and thought leaders online, sometimes facilitated by AI-powered platforms.
Agile and Innovative Curriculum Design: Embedding industry insights into the curriculum aligns education with student interests and current industry needs, challenging the rigid academic pathways that often fail to adapt, as argued by Ashenden. AI can support this agility by helping educators update curricula in real-time based on emerging trends and industry feedback. This approach also supports Collins and Halverson’s (2018) perspective on the necessity of evolving educational models. Schools can incorporate new technologies and practices into the curriculum, with AI quietly aiding in the background, reflecting the adaptability seen in young people who quickly pivot their strategies based on the latest trends and tools.
Connected Networking Opportunities: Building networks with industry leaders aids in smooth transitions from education to the workforce, bypassing the slow-moving structures critiqued by Ashenden, and ensuring that education remains relevant and impactful in a rapidly changing world, as discussed by Schwab (2017). Networking platforms can include AI-based features to suggest connections or opportunities, helping students build valuable relationships, similar to how young professionals use social media to connect with industry leaders and potential employers.
Thinking Entrepreneurially and Innovatively: Exposure to entrepreneurs inspires creativity and innovation, pushing the boundaries of traditional learning. AI tools can support entrepreneurial projects by providing market analysis, trend forecasting, and even assisting with project management. This aligns with Ashenden’s call for more dynamic educational practices and supports Sanders and Stappers’ (2008) emphasis on the importance of innovation in education. Students can be encouraged to develop their own projects or startups, leveraging digital platforms and occasionally AI-enhanced tools to innovate independently.
To implement such a model, schools could:
Partner with local businesses, tech companies, and startups to integrate real-world projects into the classroom, thus aligning with Ashenden’s vision of education that is more attuned to contemporary needs (Ashenden, 2023). This approach also reflects Bridgstock’s (2009) emphasis on the importance of equipping students with industry-relevant skills and experiences that prepare them for the evolving job market. AI can assist in matching students with projects that align with their skills and interests, enhancing the relevance and impact of these industry collaborations.
Invite industry experts to give talks, lead workshops, or mentor students, fostering a more connected and responsive educational environment (Dede, 2014). By incorporating insights from current industry professionals, schools can create a dynamic learning environment that is in line with Collins and Halverson’s (2018) call for educational models that adapt to the rapidly changing technological landscape. AI tools can be utilized to help organize and optimize these interactions, ensuring that students are paired with mentors and workshops that best suit their career goals and learning needs.
Develop micro-courses in collaboration with industry professionals, focusing on emerging technologies and innovative practices, which directly challenge the stagnation in traditional curricula critiqued by Ashenden (Ashenden, 2023). This approach also supports Billett’s (2011) argument for the need to bridge the gap between academic theory and practical application in education. AI can support the creation of these micro-courses by analyzing industry trends and helping identify the most relevant topics and skills that students should focus on.
Offer internships, job shadowing, or co-op opportunities as part of the curriculum, providing students with seamless transitions into the workforce, in contrast to the rigid, formal academic paths that may no longer serve all students effectively (Ashenden, 2023). These opportunities align with Facer’s (2011) observation of how young people are increasingly seeking direct and cost-effective pathways to career development. AI can assist in managing these opportunities by matching students with placements that best fit their skill sets and career aspirations.
Create platforms for regular interaction between students and mentors, fostering ongoing relationships that support continuous learning and development, a key element in transforming education to meet the needs of the 21st century as advocated by Ashenden (Ashenden, 2023). This is also in line with Bridgstock’s (2009) notion of the “key-shaped professional,” which emphasizes the importance of ongoing mentorship and skills development in preparing students for future challenges. AI can enhance these platforms by providing data-driven insights into student progress, helping mentors tailor their guidance more effectively.
Ashenden, D. (2022). Unbeaching the whale: Reforming the Australian education system. Monash University Publishing.
Billett, S. (2011). Workplace learning: Where it is, what it is and what it could be. Human Resource Development International, 14(1), 101-116.
Bridgstock, R. (2009). The graduate attributes we’ve overlooked: Enhancing graduate employability through career management skills. Higher Education Research & Development, 28(1), 31-44. https://doi.org/10.1080/07294360802444347
Collins, A., & Halverson, R. (2018). Rethinking Education in the Age of Technology: The Digital Revolution and Schooling in America. Teachers College Press.
Dede, C. (2014). The Role of Digital Technologies in Deeper Learning. Jobs for the Future.
Facer, K. (2011). Learning Futures: Education, Technology and Social Change. Routledge.
Gallagher, S. R. (2016). The Future of University Credentials: New Developments at the Intersection of Higher Education and Hiring. Harvard Education Press.
Sanders, E. B. N., & Stappers, P. J. (2008). Co-creation and the new landscapes of design. CoDesign, 4(1), 5-18.
Schwab, K. (2017). The Fourth Industrial Revolution. Crown Business.