Tag: Learning

  • There Are No “Shy Students”, Only Poor Learning Environments – Faculty Focus

    There Are No “Shy Students”, Only Poor Learning Environments – Faculty Focus

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  • Why critical data literacy belongs in every K–12 classroom

    Why critical data literacy belongs in every K–12 classroom

    Key points:

    An unexpected group of presenters–11th graders from Whitney M. Young Magnet High School in Chicago–made a splash at this year’s ACM Conference on Fairness, Accountability, and Transparency (FAccT). These students captivated seasoned researchers and professionals with their insights on how school environments shape students’ views of AI. “I wanted our project to serve as a window into the eyes of high school students,” said Autumn Moon, one of the student researchers.

    What enabled these students to contribute meaningfully to a conference dominated by PhDs and industry veterans was their critical data literacy–the ability to understand, question, and evaluate the ethics of complex systems like AI using data. They developed these skills through their school’s Data is Power program.

    Launched last year, Data is Power is a collaboration among K-12 educators, AI ethics researchers, and the Young Data Scientists League. The program includes four pilot modules that are aligned to K-12 standards and cover underexplored but essential topics in AI ethics, including labor and environmental impacts. The goal is to teach AI ethics by focusing on community-relevant topics chosen by our educators with input from students, all while fostering critical data literacy. For example, Autumn’s class in Chicago used AI ethics as a lens to help students distinguish between evidence-based research and AI propaganda. Students in Phoenix explored how conversational AI affects different neighborhoods in their city.

    Why does the Data is Power program focus on critical data literacy? In my former role leading a diverse AI team at Amazon, I saw that technical skills alone weren’t enough. We needed people who could navigate cultural nuance, question assumptions, and collaborate across disciplines. Some of the most technically proficient candidates struggled to apply their knowledge to real-world problems. In contrast, team members trained in critical data literacy–those who understood both the math and the societal context of the models–were better equipped to build responsible, practical tools. They also knew when not to build something.

    As AI becomes more embedded in our lives, and many students feel anxious about AI supplanting their job prospects, critical data literacy is a skill that is not just future-proof–it is future-necessary. Students (and all of us) need the ability to grapple with and think critically about AI and data in their lives and careers, no matter what they choose to pursue. As Milton Johnson, a physics and engineering teacher at Bioscience High School in Phoenix, told me: “AI is going to be one of those things where, as a society, we have a responsibility to make sure everyone has access in multiple ways.”

    Critical data literacy is as much about the humanities as it is about STEM. “AI is not just for computer scientists,” said Karren Boatner, who taught Autumn in her English literature class at Whitney M. Young Magnet High School. For Karren, who hadn’t considered herself a “math person” previously, one of the most surprising parts of the program was how much she and her students enjoyed a game-based module that used middle school math to explain how AI “learns.” Connecting math and literature to culturally relevant, real-world issues helps students see both subjects in a new light.

    As AI continues to reshape our world, schools must rethink how to teach about it. Critical data literacy helps students see the relevance of what they’re learning, empowering them to ask better questions and make more informed decisions. It also helps educators connect classroom content to students’ lived experiences.

    If education leaders want to prepare students for the future–not just as workers, but as informed citizens–they must invest in critical data literacy now. As Angela Nguyen, one of our undergraduate scholars from Stanford, said in her Data is Power talk: “Data is power–especially youth and data. All of us, whether qualitative or quantitative, can be great collectors of meaningful data that helps educate our own communities.”

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  • How Credit for Prior Learning Strengthens Workforce Ties

    How Credit for Prior Learning Strengthens Workforce Ties

    In today’s rapidly evolving workforce landscape, higher education institutions face mounting pressure to demonstrate value, relevance and return on investment. Amid this challenge lies an underutilized strategy with remarkable potential: credit for prior learning.

    We’ve long recognized CPL’s benefits for students. Learners who receive CPL credits are more likely to complete their degrees (49 percent vs. 27 percent for those without) and, on average, they earn 17.6 additional credits, finish nine to 14 months sooner and save between $1,500 and $10,200 in tuition costs (CAEL). But what’s often overlooked is CPL’s power to transform relationships between educational institutions and employers—creating a win-win-win for students, institutions and industry.

    Beyond a Student Benefit

    The traditional narrative around CPL emphasizes student advantages: increased enrollment, improved completion rates and reduced time to graduation. These metrics matter tremendously, but they tell only part of the story.

    CPL can serve as a bridge between academia and industry, creating powerful new partnerships. When colleges and universities embrace robust CPL programs, they send a clear message to employers: We value the training and development you provide. Recognizing corporate training as creditworthy learning demonstrates respect for workplace knowledge and underscores higher education’s commitment to real-world relevance.

    Employer and Workforce Gains

    For employers, CPL validates that their internal training programs have academic merit. This recognition strengthens recruitment and retention efforts, as workers see clear pathways to advance their education without duplicating learning they’ve already mastered. Companies that invest in employee development also gain educational partners who understand industry needs and value the attributes that drive employee success.

    The benefits extend further: Organizations with tuition remission or reimbursement programs can reduce costs while enhancing employee motivation and persistence.

    Deeper Collaboration Between Higher Ed and Industry

    As institutions evaluate workplace training for credit equivalency, they gain invaluable insights into industry practices and skill needs. This exchange allows colleges to refine curricula to better meet market demand, ensuring graduates possess the competencies employers seek—not just those defined within academic silos.

    The hard but necessary conversations—between faculty and corporate training leaders—help ensure CPL evaluations are rigorous and relevant. Key questions include: Why include certain topics but not others? How do we know participants can demonstrate knowledge? Does the training align with broader disciplinary or leadership needs, or is it niche? These discussions strengthen both educational and workplace outcomes.

    Reimagining CPL

    The future of higher education lies in breaking down artificial barriers between academic and workplace learning. By embracing CPL as a cornerstone strategy—not only for student success but also for employer partnerships—institutions can position themselves at the nexus of education and employment.

    This approach doesn’t diminish academic rigor; it expands our understanding of where and how meaningful learning occurs. Done well, CPL creates pathways that honor all learning, regardless of where it happens. And for learners, the message is clear: Your hard work counts.

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  • Learning to debate is an important facet of education, but too often public school students are left out 

    Learning to debate is an important facet of education, but too often public school students are left out 

    Ever since I first stepped onto the debate stage, I have been passionate about speech and debate. For the last three of my high school years, I have competed and placed nationally at major tournaments in Dallas, Los Angeles, Chicago, Atlanta and Las Vegas, among many others. Debate demands an incredible amount of research, preparation and practice, but those aren’t the biggest challenges for me.  

    I attend a public high school in California that lacks a formal debate program or coach, which has forced me to choose between quitting an activity I love and competing independently without any school support.  

    I chose the latter. And that means I prepare alone in the dark, navigate complex registration processes and, most importantly, pay hefty fees. 

    As many of us know, debate is an effective way to strengthen students’ comprehension, critical thinking and presentation skills. Debate allows students to explore ideas in a myriad of topics, from biotechnology to nuclear proliferation​​​​, and find their unique passions and interests. 

    Yet for many students, a lack of school support is a major entry barrier. It has turned debate into another private-school-dominated space, where private-school students receive access to higher quality research and on-the-spot coaching on argument structure and prose, like a football coach adjusting strategy on the sidelines. Additionally, most prestigious tournaments in the U.S. prohibit non-school-affiliated debaters like me from competing altogether.  

    Related: A lot goes on in classrooms from kindergarten to high school. Keep up with our free weekly newsletter on K-12 education.  

    These circumstances de facto prevent lower-income debaters from becoming successful in the activity. And that is why I believe that all schools should incorporate speech and debate classes into their core curriculums. Existing history and English teachers could act as debate coaches, as they do in many private schools. School districts could even combine programs across high schools to save resources while expanding access (Mountain View High School and Los Altos High School in California have pursued this strategy).  

    Over the past two decades, the debate community has engaged in efforts to democratize access to speech and debate through the creation of new formats (for example, public forum), local debate associations and urban debate leagues, among others.  

    However, many of these initiatives haven’t been successful. These newer formats, initially intended to lessen the research burden on debaters, have shifted toward emphasizing strict evidence standards and complex debate jargon. This shift has made debate less, not more, accessible, and led to more students from private schools — who were quickly able to ​​​​out-prepare those from public​​ schools — entering and dominating the competition.  

    Local debate associations and​​​​ competitive leagues for neighboring schools have provided more students with opportunities to participate. Still, debate via these organizations is limited, as they don’t provide direct coaching to member schools or rigorous opportunities for students, and prohibit certain students and programs from competing.  

    Similarly, urban debate leagues (for example, the Los Angeles Metropolitan ​​​​Debate League) have been incredibly successful in expanding debate access to lower-income and minority students; however, these programs are concentrated in major metropolitan cities, face opposition from some school districts and rely on donor funding, which can be uncertain.  

    In my debate rounds, I have analyzed pressing social problems such as global warming and economic inequality through a policymaking lens; in some rounds I defended increased wealth taxes, and in others I argued against bans on fossil fuels. Without debate, I wouldn’t be so conscious of the issues in my community. Now, as I enter college, I’m looking forward to continuing debate and leveraging my skills to fight for change.  

    Related: High school students find common ground on the debate stage 

    Speaking of college, in the competition for admission to the most selective colleges, extracurricular involvement can be a deciding factor, and debate is an excellent way to stand out, at least for those students with proper support.  

    However, when students from rural and low-income communities lack access to the same opportunities as students from more metropolitan and higher-income communities, we risk exacerbating the educational achievement gap to our collective detriment.  

    In the meantime, debate tournaments should reduce entry barriers for nontraditional debaters and for students from public schools without coaches and extra support.  

    Without these initiatives, too many rural and low-income students will be excluded from an amazing activity, one that is especially important in today’s polarizing and divisive climate.  

    Aayush Gandhi is a student at Dublin High School. He is an avid writer and nationally ranked Lincoln-Douglas debater.  

    Contact the opinion editor at [email protected].  

    This story about debate programs was produced by The Hechinger Report, a nonprofit, independent news organization focused on inequality and innovation in education. Sign up for Hechinger’s weekly newsletter.  

    The Hechinger Report provides in-depth, fact-based, unbiased reporting on education that is free to all readers. But that doesn’t mean it’s free to produce. Our work keeps educators and the public informed about pressing issues at schools and on campuses throughout the country. We tell the whole story, even when the details are inconvenient. Help us keep doing that.

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  • Are we outsourcing our thinking to AI?

    Are we outsourcing our thinking to AI?

    Key points:

    I’ll admit that I use AI. I’ve asked it to help me figure out challenging Excel formulas that otherwise would have taken me 45 minutes and a few tutorials to troubleshoot. I’ve used it to help me analyze or organize massive amounts of information. I’ve even asked it to help me devise a running training program aligning with my goals and fitting within my schedule. AI is a fantastic tool–and that’s the point. It’s a tool, not a replacement for thinking.

    As AI tools become more capable, more intuitive, and more integrated into our daily lives, I’ve found myself wondering: Are we growing too dependent on AI to do our thinking for us?

    This question isn’t just philosophical. It has real consequences, especially for students and young learners. A recent study published in the journal Societies reports that people who used AI tools consistently showed a decline in critical thinking performance. In fact, “whether someone used AI tools was a bigger predictor of a person’s thinking skills than any other factor, including educational attainment.” That’s a staggering finding because it suggests that using AI might not just be a shortcut. It could be a cognitive detour.

    The atrophy of the mind

    The term “digital dementia” has been used to describe the deterioration of cognitive abilities as a result of over-reliance on digital devices. It’s a phrase originally associated with excessive screen time and memory decline, but it’s found new relevance in the era of generative AI. When we depend on a machine to generate our thoughts, answer our questions, or write our essays, what happens to the neural pathways that govern our own critical thinking? And will the upcoming era of agentic AI expedite this decline?

    Cognitive function, like physical fitness, follows the rule of “use it or lose it.” Just as muscles weaken without regular use, the brain’s ability to evaluate, synthesize, and critique information can atrophy when not exercised. This is especially concerning in the context of education, where young learners are still building those critical neural pathways.

    In short: Students need to learn how to think before they delegate that thinking to a machine.

    Can you still think critically with AI?

    Yes, but only if you’re intentional about it.

    AI doesn’t relieve you of the responsibility to think–in many cases, it demands even more critical thinking. AI produces hallucinations, falsifies claims, and can be misleading. If you blindly accept AI’s output, you’re not saving time, you’re surrendering clarity.

    Using AI effectively requires discernment. You need to know what you’re asking, evaluate what you’re given, and verify the accuracy of the result. In other words, you need to think before, during, and after using AI.

    The “source, please” problem

    One of the simplest ways to teach critical thinking is also the most annoying–just ask my teenage daughter. When she presents a fact or claim that she saw online, I respond with some version of: “What’s your source?” It drives her crazy, but it forces her to dig deeper, check assumptions, and distinguish between fact and fiction. It’s an essential habit of mind.

    But here’s the thing: AI doesn’t always give you the source. And when it does, sometimes it’s wrong, or the source isn’t reputable. Sometimes it requires a deeper dive (and a few more prompts) to find answers, especially to complicated topics. AI often provides quick, confident answers that fall apart under scrutiny.

    So why do we keep relying on it? Why are AI responses allowed to settle arguments, or serve as “truth” for students when the answers may be anything but?

    The lure of speed and simplicity

    It’s easier. It’s faster. And let’s face it: It feels like thinking. But there’s a difference between getting an answer and understanding it. AI gives us answers. It doesn’t teach us how to ask better questions or how to judge when an answer is incomplete or misleading.

    This process of cognitive offloading (where we shift mental effort to a device) can be incredibly efficient. But if we offload too much, too early, we risk weakening the mental muscles needed for sustained critical thinking.

    Implications for educators

    So, what does this mean for the classroom?

    First, educators must be discerning about how they use AI tools. These technologies aren’t going away, and banning them outright is neither realistic nor wise. But they must be introduced with guardrails. Students need explicit instruction on how to think alongside AI, not instead of it.

    Second, teachers should emphasize the importance of original thought, iterative questioning, and evidence-based reasoning. Instead of asking students to simply generate answers, ask them to critique AI-generated ones. Challenge them to fact-check, source, revise, and reflect. In doing so, we keep their cognitive skills active and growing.

    And finally, for young learners, we may need to draw a harder line. Students who haven’t yet formed the foundational skills of analysis, synthesis, and evaluation shouldn’t be skipping those steps. Just like you wouldn’t hand a calculator to a child who hasn’t yet learned to add, we shouldn’t hand over generative AI tools to students who haven’t learned how to write, question, or reason.

    A tool, not a crutch

    AI is here to stay. It’s powerful, transformative, and, when used well, can enhance our work and learning. But we must remember that it’s a tool, not a replacement for human thought. The moment we let it think for us is the moment we start to lose the capacity to think for ourselves.

    If we want the next generation to be capable, curious, and critically-minded, we must protect and nurture those skills. And that means using AI thoughtfully, sparingly, and always with a healthy dose of skepticism. AI is certainly proving it has staying power, so it’s in all our best interests to learn to adapt. However, let’s adapt with intentionality, and without sacrificing our critical thinking skills or succumbing to any form of digital dementia.

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  • Mindfulness is Gaining Traction in American Schools, But It Isn’t Clear What Students Are Learning – The 74

    Mindfulness is Gaining Traction in American Schools, But It Isn’t Clear What Students Are Learning – The 74

    In the past 20 years in the U.S., mindfulness transitioned from being a new-age curiosity to becoming a more mainstream part of American culture, as people learned more about how mindfulness can reduce their stress and improve their well-being.

    Researchers estimate that over 1 million children in the U.S. have been exposed to mindfulness in their schools, mostly at the elementary level, often taught by classroom teachers or school counselors.

    I have been researching mindfulness in K-12 American schools for 15 years. I have investigated the impact of mindfulness on students, explored the experiences of teachers who teach mindfulness in K-12 schools, and examined the challenges and benefits of implementing mindfulness in these settings.

    I have noticed that mindfulness programs vary in what particular mindfulness skills are taught and what lesson objectives are. This makes it difficult to compare across studies and draw conclusions about how mindfulness helps students in schools.

    What is mindfulness?

    Different definitions of mindfulness exist.

    Some people might think mindfulness means simply practicing breathing, for example.

    A common definition from Jon Kabat-Zinn, a mindfulness expert who helped popularize mindfulness in Western countries, says mindfulness is about “paying attention in a particular way, on purpose, nonjudgmentally, in the present moment.”

    Essentially, mindfulness is a way of being. It is a person’s approach to each moment and their orientation to both inner and outer experience, the pleasant and the unpleasant. Fundamental to mindfulness is how a person chooses to direct their attention.

    In practice, mindfulness can involve different practices, including guided meditations, mindful movement and breathing. Mindfulness programs can also help people develop a variety of skills, including openness to experiences and more focused attention.

    Practicing mindfulness at schools

    A few years ago, I decided to investigate school mindfulness programs themselves and consider what it means for children to learn mindfulness at schools. What do the programs actually teach?

    I believe that understanding this information can help educators, parents and policymakers make more informed decisions about whether mindfulness belongs in their schools.

    In 2023, my colleagues and I conducted a deep dive into 12 readily available mindfulness curricula for K-12 students to investigate what the programs contained. Across programs, we found no consistency of content, teaching practices or time commitment.

    For example, some mindfulness programs in K-12 schools incorporate a lot of movement, with some specifically teaching yoga poses. Others emphasize interpersonal skills such as practicing acts of kindness, while others focus mostly on self-oriented skills such as focused attention, which may occur by focusing on one’s breath.

    We also found that some programs have students do a lot of mindfulness practices, such as mindful movement or mindful listening, while others teach about mindfulness, such as learning how the brain functions.

    Finally, the number of lessons in a curriculum ranged from five to 44, meaning some programs occurred over just a few weeks and some required an entire school year.

    Despite indications that mindfulness has some positive impacts for school-age children, the evidence is also not consistent, as shown by other research.

    One of the largest recent studies of mindfulness in schools found in 2022 no change in students who received mindfulness instruction.

    Some experts believe, though, that the lack of results in this 2022 study on mindfulness was partially due to a curriculum that might have been too advanced for middle school-age children.

    The connection between mindfulness and education

    Since attention is critical for students’ success in school, it is not surprising that mindfulness appeals to many educators.

    Research on student engagement and executive functioning supports the claim that any student’s ability to filter out distractions and prioritize the objects of their thoughts improves their academic success.

    Mindfulness programs have been shown to improve students’ mental health and decrease students’ and teachers’ stress levels.

    Mindfulness has also been shown to help children emotionally regulate.

    Even before social media, teachers perennially struggled to get students to pay attention. Reviews of multiple studies have shown some positive effects of mindfulness on outcomes, including improvements in academic achievement and school adjustment.

    A 2023 report from the Centers for Disease Control and Prevention cites mindfulness as one of six evidence-based strategies K-12 schools should use to promote students’ mental health and well-being.

    A relatively new trend

    Knowing what is in the mindfulness curriculum, how it is taught and how long the student spends on mindfulness matters. Students may be learning very different skills with significantly different amounts of time to reinforce those skills.

    Researchers suggest, for example, that mindfulness programs most likely to improve academic or mental health outcomes of children offer activities geared toward their developmental level, such as shorter mindfulness practices and more repetition.

    In other words, mindfulness programs for children cannot just be watered down versions of adult programs.

    Mindfulness research in school settings is still relatively new, though there is encouraging data that mindfulness can sharpen skills necessary for students’ academic success and promote their mental health.

    In addition to the need for more research on the outcomes of mindfulness, it is important for educators, parents, policymakers and researchers to look closely at the curriculum to understand what the students are actually doing.

    This article is republished from The Conversation under a Creative Commons license. Read the original article.

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  • Strengthening family engagement to support the science of reading

    Strengthening family engagement to support the science of reading

    Key points:

    While most teachers are eager to implement the science of reading, many lack the time and tools to connect these practices to home-based support, according to a new national survey from Lexia, a Cambium Learning Group brand.

    The 2025 Back-to-School Teacher Survey, with input from more than 1,500 K–12 educators nationwide, points to an opportunity for district leaders to work in concert with teachers to provide families with the science of reading-based literacy resources they need to support student reading success.

    Key insights from the survey include:

    • 60 percent of teachers are either fully trained or interested in learning more about the science of reading
    • Only 15 percent currently provide parents with structured, evidence-based literacy activities
    • 79 percent of teachers cite time constraints and parents’ work schedules as top barriers to family engagement
    • Just 10 percent report that their schools offer comprehensive family literacy programs
    • Teachers overwhelmingly want in-person workshops and video tutorials to help parents support reading at home

    “Teachers know that parental involvement can accelerate literacy and they’re eager for ways to strengthen those connections,” said Lexia President Nick Gaehde. “This data highlights how districts can continue to build on momentum in this new school year by offering scalable, multilingual, and flexible family engagement strategies that align with the science of reading.”

    Teachers also called for:

    • Better technology tools for consistent school-to-home communication
    • Greater multilingual support to serve diverse communities
    • Professional learning that includes family engagement training

    Gaehde concluded, “Lexia’s survey reflects the continued national emphasis on Structured Literacy and shows that equipping families is essential to driving lasting student outcomes. At Lexia we’re committed to partnering with districts and teachers to strengthen the school-to-home connection. By giving educators practical tools and data-driven insights, we help teachers and families work together–ensuring every child has the literacy support they need to thrive.”

    The complete findings are available in a new report, From Classroom to Living Room: Exploring Parental Involvement in K–12 Literacy. District leaders can also download the accompanying infographic, “What District Leaders Need To Know: 5 Key Findings About Family Engagement and Literacy,” which highlights the most pressing data points and strategic opportunities for improving school-to-home literacy connections.

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  • Unlock High-Impact Machine Learning Projects with Source Code for MBA Project

    Unlock High-Impact Machine Learning Projects with Source Code for MBA Project

    Machine learning is the new trend which is transforming how the business world makes decisions. For MBA students, who are integrating the machine learning projects with source code into final year project work would be adding a real value and to differentiate their profile in placements or higher studies.

    Why MBA Students Should Explore Machine Learning Projects?

    Unlike computer science students, MBA students mainly focus on solving business problems. Still, machine learning opens doors to:

    • Marketing – Customer churn prediction, recommendation engines
    • Finance – Fraud detection, risk scoring, stock price forecasting
    • HR – Employee attrition prediction, talent acquisition analytics
    • Operations – Demand forecasting, supply chain optimization

    Working on machine learning projects for final year, MBA students would be bridging their gap between management and technology.

    Where to Find Machine Learning Projects with Source Code?

    1. Machine Learning Projects Kaggle

    Kaggle offers real-world datasets and pre-built models. For MBA projects, students can explore:

    • Sales forecasting
    • Retail Customer churn
    • Social media analysis and Brand sentiment.

    2. Machine Learning Projects GitHub

    GitHub repositories contain ready-to-use machine learning projects with source code. Mba Final year students can download them, customize datasets, and align them with their final year project theme.

    Best Machine Learning Project Ideas for MBA Final Year

    Marketing Analytics

    • Customer segmentation using K-Means on Fitness Centre
    • Customer Churn on local restaurant
    • Sentiment analysis of customer churn prediction in Banks

    Finance Analytics

    • Comparative study of Loan approval prediction using machine learning Methods.
    • Machine learning prediction on Stock price trend forecasting.

    HR & Operations

    • Comparative study of employee attrition prediction of an organization
    • Utilization of Machine learning in Demand and inventory forecasting.
    • Get more machine leaning titles in this link.Click here

    How MBA Students Can Use These Projects

    1. Students should choose the relevant topics (Marketing, Finance, HR, or operations).
    2. They have to Download machine learning projects with source code from Kaggle or GitHub.
    3. Modifying the datasetsas per the project context.

    Should be focussing on business insights and not just algorithms.

    Check out this video for more indepth knowledge on Machine Learning

    Conclusion

    For MBA students, machine learning projects with source code are not about becoming data scientists—it’s about using data intelligently to make right business decisions.

    By leveraging Kaggle and GitHub, students can transform their final year project into a powerful showcase of management plus analytics skills.

    The main intent of the blog is to help students understand how to find the right mentor who can guide mba students to provide hands-on experience with ml code base.

    This content will help gain more knowledge for capstone projects,thesis work or mba project by applying customer analytics, finance strategy to complement theoretical business knowledge in machine learning and build portfolio for job interviews or internships.

    Download machine learning projects for final year pdf

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  • University of Arkansas Creates Faculty Learning Community

    University of Arkansas Creates Faculty Learning Community

    Effective teaching and learning are key elements of a student’s academic success, but ensuring professors have access to training, support and resources to employ best practices in the classroom can be a challenge for institutions.

    At the University of Arkansas at Fayetteville’s Fulbright College of Arts and Sciences, Lynn Meade created the Faculty Learning Community to tackle this issue, uniting professors across disciplines to improve student learning and achievement.

    The Faculty Learning Community, which launched this summer, strives to unite staff and faculty across campus to work toward the shared goal of student success, Meade said.

    The background: Meade has worked as a communications professor at the University of Arkansas for two decades, but in 2023, she realized there were entire student support teams and departments that she didn’t know about. The university hosted an event on high-impact practices to invite stakeholders to share and learn from one another.

    “I sat down at a table with a whole lot of student success people, and I was amazed at all the things that they were doing and how I could be on our campus for so long and [have] no idea the things that were going on behind the scenes, things students could take advantage of that they hadn’t yet,” Meade said.

    This experience prompted her to get more involved with support staff and orchestrate opportunities for other professors to learn from one another across campus. “We need to find a way to integrate faculty and student success initiatives,” Meade said. “They need to know what one another are doing, they need to shake hands, make friends, have coffee, talk—the things that really make things happen, because our students, their success depends on us cooperating.”

    Students are more likely to talk to a faculty member they trust than seek out a support office on campus, Meade said. “I think informing them not only how to teach their class well, but also how to integrate those resources, is really important.”

    The result was the Fulbright Faculty Learning Community, a community of practice and faculty development program, which Meade now leads as director.

    How it works: The program launched with four offerings for faculty: a course-building workshop, a reboot class to help with updating content, forums for sharing innovative teaching ideas and introductions to student success teams.

    One of Meade’s goals is to avoid replicating existing efforts on campus but provide a one-stop shop to unify and amplify the great work taking place. “There’s so many cool resources on our campus, but there’s no one place they all exist,” she said.

    The Fulbright Learning Community had its kickoff event this summer, engaging 14 faculty members in a three-hour workshop on course building.

    The workshop invited faculty to consider students, rather than content, at the center of their syllabus, using a communications principle of audience and purpose. “I think if our audience is students and our purpose is to teach them, maybe we shouldn’t say, ‘I’m going to cover my material,’ but, ‘I’m going to think of ways that they can learn the material,’” Meade said.

    Survey Says

    A 2024 Student Voice survey by Inside Higher Ed and Generation Lab found that 40 percent of respondents believe their academic success would improve if professors connected in-classroom learning to issues outside the classroom or students’ career goals.

    Some professors who are straight out of grad school may have only received teacher education or used material given to them by other faculty, Meade said. Others who have taught abroad but never in the U.S. may need some help adapting their materials for American students.

    The learning community also invited career center professionals to showcase ways to embed career competencies in the syllabus and attach resources to their learning management system to help address career development for students. A future session will invite professors to share how they’re using and teaching generative AI tools.

    “Faculty success equals student success,” Meade said. “The teachers are their first line [of support]; a lot of that success is what’s happening with the teacher. When we all work together on the same side, how we communicate with each other is going to make a big impact on the student retention.”

    If your student success program has a unique feature or twist, we’d like to know about it. Click here to submit.

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  • Supporting the Student Researcher: Effective Teaching, Learning, and Engagement Strategies – Faculty Focus

    Supporting the Student Researcher: Effective Teaching, Learning, and Engagement Strategies – Faculty Focus

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