Latest news with #pedagogy
Forbes
6 days ago
- General
- Forbes
Flexibility Is King: Why Rigid Education Models Shut Out Talent
Pablo Listingart is the founder of ComIT, a nonprofit providing free, tailored tech training to help people overcome employment barriers. In more than two decades of teaching (first in high school classrooms, then university lecture halls and now through the nonprofit tech‑training programs I run), I've met a lot of educators. Wonderful, passionate people. And yet, sprinkle in any discussion about how learning should happen, and the mood shifts. Suddenly, everyone's clutching their pedagogical pearls: 'Courses must be in‑person due to the social aspect of it!' 'Online is the only way to scale!' 'Eight a.m. classes build character!' Rigid certainty is oddly fashionable in education circles. It's comforting to declare one universal 'right way,' but it's also the way to keep smart, motivated people stuck on the outside looking in. The Privilege Of A Roof And The Myth Of 'Free' School I was lucky. My parents offered me a roof and food until I finished my studies at university. The deal was that everything else (weekend outings, vacation money, even some textbooks) was on me. And so that's why I started working when I was 17 years old, doing many different things. Plenty of people probably share my experience. Many others do not. Even in countries with 'free' tuition, the hidden price tag is real: transportation, food, childcare, lost wages, the cost of juggling night shifts with morning exams. Tell a single mom working one or more survival jobs that scholarships exist and see if that helps. Scholarships rarely cover diapers or bus fare, and they certainly don't solve a rigid lecture schedule. It's simple: When the choice is attending biology lab at 9 a.m. or paying the electric bill, the lab loses. Not because students lack discipline, but because Maslow organized that hierarchy for a reason. Are We Really Opening The Door? Many institutions tout diversity initiatives. Worthy efforts, but often focused on entry rather than completion. Once a student steps through the door, we stick to a fixed timetable, mandatory attendance, single‑attempt exams and 15‑week semesters. Take the single mom again. She obtains a scholarship, then misses class because her toddler spikes a fever. A zero for participation follows, and her grade slides. The scholarship renews only with a B average, and soon she's gone. We pat ourselves on the back for 'access,' never noticing the revolving door spinning behind us. What Students Actually Want Earlier this year, my nonprofit surveyed 500 learners. The results were unsurprising if you've been paying attention: • 45% prefer a hybrid format: part self‑paced, part live instruction. • 46% crave a balance of independent and collaborative work. • Only 40% believe formal degrees are the best path, though many say prestige still matters on a résumé. Translation: Students welcome structure, but not at the expense of sanity. They appreciate community, but not if it means forfeiting their paycheck. They respect credentials, but only when those credentials signal real-life skills. The Case For Flexibility (And How To Do It Without Lowering The Bar) Break courses into bite‑sized units that can be started at different moments in the year. Give evening, weekend and recorded options. Mastery, not seat time, should drive progression. Swap high‑stakes midterms for projects that mirror real work. If a student can demonstrate competency at midnight on a Tuesday, why force them into an exam hall at dawn? Pandemic Zoom fatigue taught us that slapping a webcam on a three‑hour lecture is torture. True hybrid learning mixes asynchronous micro‑lessons with short, purpose‑built live sessions for discussion, feedback or group work. Allow a limited number of 'life happens' passes per term—no doctor's note required. Missed a class because your bus broke down or your shift ran late? Use a pass, catch the recording, complete an assignment and move on. Offer micro‑certificates that build toward a larger credential. A student who finishes two modules earns something tangible even if life interrupts the third. Momentum can be a powerful antidote to dropout rates. Will The Ivory Tower Survive The Remodel? Critics worry that flexibility dilutes academic rigor. In my experience, it does the opposite. When you remove arbitrary barriers, you're left with the actual barrier: learning the material. Students no longer fail because the daycare closed; they succeed or fail on understanding algorithms, supply chain theory or Renaissance art. Exactly as it should be. And employers? They love it. Ask any CTO if she'd rather hire a graduate who perfected Java at 2 a.m. while caring for aging parents or someone who breezed through a lecture‑only course. Resilience, time management, grit. That's the hidden curriculum flexible programs teach. Flexibility: An Equity Issue (And A Talent Issue And A GDP Issue ... ) When education only fits the schedule of a 19‑year‑old with no dependents and plentiful cash, we waste oceans of talent. Single parents, newcomers, rural learners and neurodivergent students are not edge cases. They are the workforce we claim to need. By 2030, global shortages in tech alone could leave millions of roles unfilled. Meanwhile, capable adults shelve their potential because classes clash with paychecks. The math doesn't add up. Crowns, Thrones And The Future Which brings us back to the headline: Flexibility is king. In medieval times, the king's word was law; in modern education, flexibility should rule with similar authority. Not as a feel‑good add‑on, but as the organizing principle around which curricula, funding and policy revolve. If we fail, we'll keep graduating a narrow slice of the population and wondering why innovation stalls. If we succeed, we'll unleash minds previously sidelined by timetables and tuition receipts. Twenty years in, I've learned that teaching isn't about delivering content; it's about removing every nonessential barrier between a learner and the aha moment. Roof and food not included? Let's figure that out. Child with a fever at 10 p.m.? Record the session. Need to work the breakfast shift? Offer the lab in the afternoon or the evening. Because when our systems bend, talent doesn't break. And that, whether you're a university dean, a boot‑camp founder or a hiring manager, is the smartest investment you can make. Forbes Nonprofit Council is an invitation-only organization for chief executives in successful nonprofit organizations. Do I qualify?
Forbes
11-08-2025
- Forbes
Why Faculty Hold The Keys To Higher Ed's AI Digital Transformation
If the 20th century belonged to the textbook, the 21st belongs to the prompt. In lecture halls from Toronto to San Diego to Ho Chi Minh City, students are already co-writing their education with algorithms. Nearly 80% of undergraduates worldwide are already using generative AI, often daily. What's missing is not adoption—it's alignment. While students are busy teaching themselves AI, most universities remain frozen between prohibition and pilot. Eighty percent of students report that they have no structured AI support for teaching or learning, even as employers accelerate toward AI-mandatory job descriptions. This is more than a skills gap. It's pedagogical infrastructure debt—every semester without faculty readiness compounds the cost and complexity of catching up. We've seen similar patterns of lagging technology adoption in past waves of edtech innovation. When learning-management systems first appeared, they were largely framed as administrative upgrades. For many institutions, that framing worked: LMSs streamlined workflows, centralized compliance, and made it easier for faculty to post resources and communicate with students. Today, 99% of colleges report having an LMS, and 87% of faculty use one. But most of that use remains logistical rather than pedagogical—more about distributing syllabi and quizzes than redesigning courses around new capabilities. When MOOCs surged a decade ago, they unlocked access for millions who might never set foot on campus. That was a genuine democratization of content. But most universities launched them without fundamentally rethinking teaching models. Completion rates hovered in the single digits—typically between 3% and 15%—and many MOOCs ended up as repackaged lectures with minimal interaction. Instructors logged 100+ hours preparing courses and spent 8–10 hours a week maintaining them, yet the gains in learning outcomes were modest. Neither the LMS nor the MOOC era was a failure—they brought efficiency, visibility, and reach. But they also carried an opportunity cost. In both cases, much of the narrative, innovation, and even data ownership shifted to external platforms. That loss of control mattered less when the stakes were content delivery. With AI, the stakes are cognitive—determining how future leaders will think, decide, and solve problems. If institutions approach AI as a bolt-on feature rather than a faculty-driven transformation, they risk outsourcing not just content delivery but the very definition of academic rigor. AI could follow the same trajectory as past edtech waves—unless we change who's in the driver's As The Missing Link In The AI Workforce Pipeline In boardrooms and government offices, the conversation about AI is no longer about if but how fast. McKinsey estimates AI could add up to $23 trillion annually to the global economy by 2040, with gains concentrated in sectors that can re-skill their workforces quickly. But here's the thing: Employers don't want graduates who don't know how to use AI. GMAC's latest survey of 1,100 employers reveals that AI fluency is rapidly becoming a hiring requirement across industries, making this educational gap not just pedagogical but economic. That capacity for AI fluency doesn't come from a few elective workshops or a tech bootcamp—it's forged in classrooms and research centers with sustained, discipline-specific learning. And the gatekeepers are faculty. If we treat AI integration as a technology problem, we get disconnected pilots and compliance documents. If we treat it as a talent pipeline problem, we invest in faculty as the designers of tomorrow's workforce capabilities. Where Faculty-Driven AI Works At the University of Toronto's Rotman School, a small teaching team decided that if students were going to use AI, it should be on the faculty's terms. They trained 'All Day TA' entirely on their own course materials—lectures, readings, problem sets—so that when students posed questions, the answers came through the same conceptual frameworks they'd be tested on. By semester's end, the assistant had fielded over 12,000 questions. Instructors weren't replaced; they were relieved of repetitive clarifications and free to focus on the discussions that require a human mind. Half a world away at British University Vietnam, the starting point was different: academic misconduct reports were rising, and administrators worried that AI use was undermining rigor. Instead of banning the tools, faculty built the AI Assessment Scale, a visible cue on every assignment indicating whether AI was prohibited, permitted, or required. Students no longer had to guess whether a chatbot was fair game. The clarity did more than curb misconduct—it lifted average attainment by nearly six percent and raised pass rates by a third. Faculty didn't lower the bar; they made sure everyone knew exactly where it was and how to clear it. And then there's UC San Diego, where leadership has moved beyond isolated experiments to an institutional commitment that puts faculty at the center. This fall, select instructors will receive AI assistants built on the university's secure TritonGPT platform. These assistants are trained on instructor-uploaded syllabi, readings, and lecture notes; tuned to each professor's voice and pedagogy. The AI engages students in Socratic dialogue, guiding them toward insights rather than serving up answers. For the faculty, it's both a teaching tool and a feedback loop. Detailed analytics show how students are engaging with the material, revealing where they struggle and where they're ready for more challenge. UCSD has extended the same philosophy to faculty's administrative burdens. One homegrown tool, Contract Reviewer, automatically applies university policy to routine agreements, cutting review time and reducing bottlenecks. The message is clear: AI is here to enhance the full scope of faculty work, from the classroom to the committee room. The Time Is Now The window for proactive AI integration is closing rapidly, and the pressure on institutional leadership is mounting. EDUCAUSE's 2025 survey of technology leaders reveals that 75% report excessive workloads while only 16% believe they have sufficient staff to meet their goals. More telling, when it comes to AI professional development, institutional priorities lean heavily toward "mitigating risks rather than supporting opportunities"—exactly the defensive posture that may leave faculty to navigate AI integration alone. If colleges fail to activate faculty now, students will continue learning AI informally—without the ethical grounding, domain rigor, or reflective habits that distinguish competent professionals from sophisticated prompt-writers. Nearly half of technology leaders (45%) now prioritize 'supporting and securing emerging technologies such as AI' as their top professional development need—yet most remain reactive, focusing on governance, ethics, and compliance. Far fewer are seizing the opportunity to help faculty apply AI in research (30%), teaching (30%), or student services (24%). The path forward isn't 'AI or integrity'—it's integrity through intentional AI, led by faculty. Universities like UC San Diego, alongside focused successes at Toronto's Rotman School and British University Vietnam, prove that comprehensive, faculty-centered AI integration isn't just possible; it's already happening. Faculty are the engine. Give them the vision, structures, and support they need, and they'll not just transform higher education—they'll secure our place in the AI-driven economy.
Forbes
18-07-2025
- Business
- Forbes
Leveraging Co-Creation As A Transformative Pedagogy In Higher Learning
Patty Patria is the CIO at Babson College. Over the last several hundred years, higher education has been fairly consistent when it comes to pedagogy. A highly educated faculty member has imparted his or her knowledge to students who are generally hungry to learn, with the goal of attaining knowledge that will help them obtain a job they're passionate about. While we've seen shifts in teaching styles over the years, from traditional to active learning to hybrid to lifelong learning, pedagogy has not changed significantly overall. Forward-thinking institutions have changed pedagogy to emphasize critical thinking, problem-solving, soft skills and collaborative learning as critical skills students need to learn while in college. However, most institutions still have an expert sharing knowledge with those who are trying to absorb that knowledge. In 2023, generative AI (GenAI) entered the learning scene, and it's starting to change how students learn and what they expect from institutions of higher education. GenAI tools like ChatGPT and Claude have made vast amounts of information readily available to anyone with an internet connection. Because many AI tools are no-cost or low-cost, it has also drastically reduced the cost of obtaining and processing this information. Additionally, many students have learned how to leverage AI at a faster rate than other employees. They leverage tools in their own business to automate sales, marketing and routine tasks. They leverage AI to develop entirely new products that were not available before. This dynamic has shifted students to become subject matter experts on AI, with knowledge they can share with others. Although many students are quickly embracing AI, many universities are struggling with how to implement AI strategically, as well as how to gain the proper AI support from faculty and administrators. According to a June 2024 research report published by Ithaka S+R, only 14% of surveyed instructors were confident when teaching with AI. This could be attributed to a lack of effective teacher training programs on AI and effective education on ethical, legal or pedagogical concerns. Universities also might not have a comprehensive institutional strategy that encompasses curriculum, student experience and administrative operations and allows them to measure the success (or failure) of these initiatives and evaluate yearly on next steps. For institutions that invest in both an AI strategy and training programs for faculty and staff and then measure effectiveness, the benefits are plentiful. For higher education to move forward when information has become a commodity, it is important for institutions to build a comprehensive AI strategy. From a curriculum perspective, one of the answers might also be a pedagogical shift to co-creation, or two-way experiential learning, where students work with faculty and outside constituents to collaboratively develop innovative solutions, particularly around AI. We recently held a daylong workshop designed to educate small business leaders on how they can leverage AI to grow their business. Erik Noyes, associate professor of entrepreneurship, and other faculty members from our interdisciplinary AI lab, The Generator, partnered with their students to show small business leaders how they can use AI in their organizations. Students demonstrated use cases ranging from AI for advertising, prototyping and visualization to agents for competitive analysis or sales lead generation. The students were very excited about the mission and purpose of this workshop, allowing them to share expertise as subject matter experts with AI while, at the same time, learning how to run a successful business from seasoned entrepreneurs. With this new model, the faculty member acted as a facilitator of learning, helping to conduct the program instead of being the subject matter expert at the head of the room. Overall, the new model was a huge success. The small business owners gave rave reviews, with one noting how it opened their eyes to new possibilities for their business, while others noted that the students demonstrated AI agents and the automation of tasks very well. Another method of co-creation in higher education is leveraging student-led projects that pair students with a business where they need to solve a pressing problem. I recently attended final presentations for a graduate course where student teams were asked to leverage AI to solve real-world business problems for both small and large businesses. The solutions the students suggested, after receiving guidance from their faculty member, were spot on. Each group offered a recommendation (which included the technology that would be required), outlined risks and mitigation strategies and even included details on training and change management. As with any massive shift in technology, pedagogy or process, co-creation's results should be measured to ensure your outcomes are achieved. This can be done through surveys assessing participant feedback, student impact and engagement surveys and leveraging feedback loops and iteration. Changes like this won't be easy, but if colleges and universities can provide a more comprehensive education to students by actively engaging them in the learning and education process, we can promote educational growth and transform lives through new learning processes. Although some institutions are still on the fence about AI, it's here to stay, and it's already changing the way students learn and faculty members teach. Could embracing co-creation with students inside and outside of the classroom be the answer for higher education? I guess we'll find out over the next few years, and I look forward to watching the journey. Forbes Technology Council is an invitation-only community for world-class CIOs, CTOs and technology executives. Do I qualify?
CNA
30-05-2025
- General
- CNA
From classroom to curriculum: How one educator is rethinking teaching for today's learners
As director of the Media, Arts & Design School at Singapore Polytechnic, Mr Mark Lu believed that giving students creative freedom in their learning was the best way to impart knowledge. Interestingly, not all his classmates at the National Institute of Education, Nanyang Technological University, Singapore (NIE NTU, Singapore), saw it the same way. Two fellow students in the Master of Education (Curriculum and Teaching) programme – one from the military and the other from healthcare – shared a contrasting perspective. In their fields, strict adherence to instructions was often critical, with real consequences in life-or-death situations. This eye-opening insight into the need for different teaching approaches deepened Mr Lu's interest in education. Mr Lu had enrolled in the part-time graduate programme at NIE after a conversation with his supervisor sparked a realisation: He wanted to better understand education policy, pedagogy and curriculum, and how he could better support lecturers in their work. LEARNING FROM MANY, TEACHING FOR ALL With over 30 graduate programmes and courses designed to sharpen critical thinking, enhance professional skills and open up new career paths, NIE attracts a growing number of students from a wide range of industries and countries. Their diverse perspectives and experiences enrich classroom discussions and learning for everyone. This diversity mirrors the changing student population in polytechnics. Mr Lu observed that today's polytechnic students come from increasingly varied educational backgrounds and life stages. Many are working adults returning as full-time students or trainees, each with their own goals and life experiences. As a result, polytechnic lecturers must adopt a flexible mindset and be equipped to teach both technical and soft skills. 'They need to design meaningful classroom experiences that inspire and motivate students from all walks of life and help them work toward their aspirations,' Mr Lu explained. 'At the same time, they have to balance a rigorous curriculum that builds resilience with an awareness of students' well-being.' In such a setting, having a wide-ranging community of fellow educators is important. Mr Lu, who graduated in January this year, said that the diverse student body at NIE was his favourite part of the programme. 'I met classmates from countries like China and Vietnam, and others from fields like the military, nursing, human resources and private education. Each of them is an educator in their own way, and they brought very different yet valuable perspectives on curriculum and teaching.' Mr Lu added that his NIE chat groups remain active. One of his classmates even works in the same polytechnic, though in a different school, and they've explored opportunities to collaborate. For Mr Lu, the graduate programme at NIE offered more than just academic knowledge – it refined his understanding of the many factors and stakeholders involved in shaping curriculum decisions and education policy. 'The course on globalisation and curriculum reform gave me a broader view of Singapore's education landscape and helped me better understand why schools are structured and managed the way they are,' he shared. He especially appreciated how classroom assignments encouraged students to apply what they learned to real-world contexts. Rather than working through fixed case studies, Mr Lu and his classmates were asked to explore how key concepts played out in their own workplaces. 'This pushed me to think more critically about my work and how I can better support both lecturers and students in my school,' he said. Before taking on the role of director, Mr Lu led his school's transdisciplinary unit – a team focused on developing a curriculum that helps students build transdisciplinary skills. This approach encourages students to draw from different disciplines and integrate multiple perspectives when solving problems. With insights gained from NIE courses on curriculum development, Mr Lu and his team designed a series of transdisciplinary studio projects, where students from different creative disciplines worked together to solve social issues and industry briefs innovatively. These projects received positive feedback from industry partners, who were impressed by the students' ideas. Thanks to the research courses he took at NIE, Mr Lu was also able to collaborate with his colleagues on developing a three-year longitudinal study examining the impact of his school's transdisciplinary curriculum. The study has since been presented at both local and international academic conferences. 'Through the transdisciplinary curriculum, our students are becoming more comfortable with ambiguity and more willing to take creative risks – traits that are essential in any creative field,' Mr Lu noted. 'We're now working on developing our own instrument to measure transdisciplinary thinking.' Enrolling in NIE and becoming a student again has reshaped Mr Lu's perspective. Once focused mainly on day-to-day teaching, he now views his work through a broader, more philosophical lens. He is also keen to continue an educational journey that he finds deeply fulfilling. 'I believe continuous learning is a fundamental part of our work. We don't just teach for others to learn – we learn to teach, and we keep learning while we teach. Though I've completed my Master's programme at NIE, I am excited to learn more when I embark on my PhD in August.' Applications for the January 2026 graduate intake at NIE NTU, Singapore, are now open. Apply by Jun 19, 2025, for coursework programmes, and Jul 24, 2025, for research programmes.
Malay Mail
21-05-2025
- Malay Mail
Avoiding overreliance on AI in higher education — Jehana Ermy Jamaluddin
MAY 21 — Artificial Intelligence (AI) is rapidly transforming higher education, offering new tools for teaching, learning and assessment. From adaptive learning platforms to automated grading systems and AI-generated feedback, the appeal of efficiency and scalability is undeniable. However, alongside these benefits lies a growing concern: the risk of overreliance. When algorithms begin to overshadow academic judgment and interpersonal engagement, the core mission of education which is fostering critical thinking, reflection, and human connection, can be compromised. The challenge is not whether to use AI, but how to integrate it without allowing it to replace pedagogical intent. Teaching is not simply the transmission of content; it is a dynamic, relational process shaped by context, empathy, and professional intuition. Overdependence on AI tools can unintentionally narrow learning experiences. Students might begin to rely on generative tools to complete tasks without engaging with underlying concepts. Educators, in turn, may be tempted to adopt AI suggestions without exercising their own academic judgment, especially under pressure to deliver content quickly or manage large cohorts. This can result in more passive learning, reduced intellectual curiosity, and a loss of creative teaching practices. To stay grounded in pedagogy, educators must remain at the centre of instructional decisions. AI tools should be seen as support systems and not decision-makers. For example, many universities use adaptive platforms like Coursera or Moodle that recommend learning pathways based on student performance. While helpful, these systems are most effective when lecturers intervene to adjust recommendations based on their knowledge of the students and the broader learning goals. When educators actively shape the AI-enhanced experience, they ensure that learning is personal, inclusive, and meaningful. AI can also be used to enrich and not to restrict student choice. Too often, AI systems predict what students should learn next and create narrow content funnels that limit exposure to diverse topics. A student performing poorly in algorithmic thinking, for instance, might be repeatedly directed to basic exercises in data structures. Yet a thoughtful instructor might identify that the same student can engage with real-world problems like AI bias or ethical computing, thus broadening their learning journey. By stepping in, educators help students stretch beyond algorithmic assumptions, encouraging intellectual risk-taking and confidence. The ChatGPT logo is seen on the screen of a smartphone in this illustrative photo. — AFP pic One effective way to embed AI ethically is through reflective learning models. Rather than using AI to provide definitive answers, educators can frame it as a thinking partner. In a humanities class, for example, students could use a generative AI tool to draft the structure of a persuasive essay, then critically evaluate the logic and underlying assumptions. This method not only builds AI literacy but also reinforces skills in argumentation, critique, and self-awareness. Similarly, in engineering or business courses, students might be asked to compare AI-generated solutions to case studies with their own, reflecting on differences in reasoning and ethical implications. Institutions also play a critical role in shaping a balanced approach. Clear guidelines around acceptable use of AI should be developed collaboratively across departments. These frameworks can help ensure consistency while respecting the specific needs of different disciplines. Equally important is building AI literacy across the academic community. Faculty development programmes and classroom resources on how AI works; and where it falls short, empower both educators and students to engage with these tools thoughtfully and responsibly. Some universities have taken the lead by creating interdisciplinary 'Teaching with AI' task forces. These groups review emerging technologies, propose ethical standards, and help integrate AI into pedagogy without sacrificing academic integrity. Perhaps the most important strategy to avoid overreliance is the regular evaluation of learning impact. Rather than focusing solely on performance metrics generated by AI tools, institutions should review whether students are genuinely engaging with content, developing higher-order thinking, and participating actively in their own learning. This might involve classroom observations, student feedback, and peer reflection to ensure that AI is supporting and not replacing meaningful educational experiences. AI undoubtedly has a place in the future of higher education. Its ability to support personalised learning, provide rapid feedback, and assist with routine tasks can benefit both students and educators. But its value depends entirely on how we use it. If treated as a shortcut, AI can lead to shallow learning and disengagement. If used with intention and pedagogical care, it can enhance creativity, reflection, and depth. The goal is not to teach through AI, but to teach with it. That means reaffirming the role of educators as designers of learning experiences and mentors in students' intellectual journeys. It means treating AI as an assistant that extends human capabilities and not as a replacement for human connection. As institutions move forward, the guiding principle should remain clear: technology may shape the future, but it is pedagogy that defines its purpose. * The author is the Director of the Centre for Academic Advancement and Flexible Learning (CAFEL) and Senior Lecturer at the Department of Electrical and Electronics Engineering, College of Engineering, Universiti Tenaga Nasional (UNITEN). She may be reached at [email protected] ** This is the personal opinion of the writer or publication and does not necessarily represent the views of Malay Mail.
