Podcast
Friday SLO Talks
Hosted by Jarek Janio · EN
Friday SLO Talks: Rethinking Student Learning Outcomes
Welcome to Friday SLO Talks, the podcast that redefines student success in higher education by focusing on learning as skill and competency development, not just course completion or diploma attainment.
Presented by the California Outcomes Assessment Coordinators' Hub (COACHES), each episode explores effective teaching practices and assessment strategies that emphasize meaningful, measurable growth. Through in-depth conversations with educators, program leaders, and academic innovators, we bring you practical insights and tools to enhance student learning in ways that matter.
If you’re a higher education professional dedicated to cultivating real-world skills and competencies in your students, join us for inspiring discussions and a community committed to reshaping the future of student-centered education.
23episodes
Episodes
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GenAI – Your Supercharged Assessment Assistant with Dr. Gavin Henning
Mar 17, 202500:20:41Tap to summarizeHere’s a more detailed description of the episode:Podcast Episode: GenAI – Your Supercharged Assessment Assistant with Dr. Gavin HenningIn this episode of Friday SLO Talks, organized by the California Outcomes Assessment Hub (COACHES), Dr. Gavin Henning, professor of higher education at New England College, provided an in-depth look at how Generative AI (GenAI) is revolutionizing assessment in higher education. With over 25 years of experience in student learning assessment and institutional research, Dr. Henning explored the practical applications of AI in streamlining assessment processes, reducing faculty workload, and improving the quality of learning outcomes.Moderated by Dr. Jarek Janio from Santa Ana College and Enrique Jauregui from Fresno City College, the session opened with a discussion on the rapid evolution of AI, highlighting how tools such as ChatGPT, NotebookLM, and Gamma are reshaping assessment strategies. Dr. Henning acknowledged the common anxieties faculty have about AI—particularly concerns about academic integrity and student cheating—but emphasized the immense potential of AI to enhance, rather than undermine, meaningful assessment.Throughout the presentation, Dr. Henning demonstrated multiple AI-driven applications for assessment, including:Developing and Refining Learning Outcomes – AI can generate student learning outcomes based on course descriptions, revise them for clarity, and align them with different learning taxonomies such as Bloom’s Taxonomy or Fink’s Significant Learning.Rubric Creation and Evaluation – AI tools can draft assessment rubrics, refine them based on institutional needs, and help faculty evaluate the quality of their rubrics to ensure clear, measurable learning criteria.Survey and Interview Protocols – AI can assist in designing assessment instruments, such as survey questions and focus group protocols, reducing the time needed to create structured assessment tools.Qualitative and Quantitative Data Analysis – While Dr. Henning cautioned against relying too heavily on AI for statistical analyses, he demonstrated how AI can identify themes in qualitative data, synthesize feedback, and even generate reports summarizing key findings.Program Review and Accreditation Support – AI can streamline the program review process by helping faculty organize assessment data, generate accreditation reports, and compare institutional assessment strategies.Dr. Henning also showcased how AI-generated reports and summaries can be transformed into interactive learning materials, including AI-generated podcasts. He demonstrated Google’s NotebookLM, a tool that allows users to create AI-powered podcasts from assessment reports, complete with interactive question-and-answer capabilities. This innovative application of AI, he suggested, could make assessment findings more engaging and accessible to broader audiences.The discussion also touched on the ethical implications of AI in assessment, including concerns about bias, data privacy, and the environmental cost of AI technology. Dr. Henning encouraged faculty to approach AI as a tool for efficiency and equity while remaining vigilant about its limitations. He also highlighted the importance of maintaining faculty agency in assessment design, ensuring that AI complements, rather than replaces, human expertise.Dr. Henning’s message was clear: AI is moving at the speed of the Road Runner, and while it presents challenges, it also offers unprecedented opportunities to improve assessment, streamline faculty workload, and enhance student learning outcomes.
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Devan Walton - Tools for Program Level Assessment
Jan 3, 202500:09:19Tap to summarize1. The Evolving Role of Assessment Professionals: As AI automates routine tasks, assessment professionals must focus on higher-order skills like identifying key data, designing effective data collection strategies, and interpreting AI-generated insights. "These tools are going to allow us to collect a lot more data about students… giving us deeper insights into what’s working and what’s not in our programs."2. Agent-Based AI Models: The transition from dialogue-based tools (e.g., ChatGPT) to autonomous agent-based models introduces new considerations for task delegation and ethical use. "When we have models that we can delegate tasks to, it becomes critical to be thoughtful about what tasks are delegated."3. Thoughtful AI Adoption: Implementing AI in education requires careful consideration of student needs, data privacy, and equity to ensure ethical and effective use.Most Important IdeasAutomation of Routine Tasks: AI streamlines assessment, freeing professionals for strategic roles. For example, Walton’s tool analyzes student artifacts automatically using pre-defined rubrics.Prompt Quality Matters: The "garbage in, garbage out" principle applies. Poorly crafted prompts lead to suboptimal AI outputs. "If you give it a dumb prompt, you’ll access the dumb part of that model’s brain."Equity Concerns: Wealthier institutions investing heavily in AI may widen gaps between privileged and underserved students. "This is the single biggest equity topic…wealthier schools are throwing money at AI for their students."Human Connection is Essential: AI should complement, not replace, human tutors, allowing them to focus on personalized support and emotional needs.Communicating AI Benefits: Institutions must clearly convey the advantages of AI-powered tools to students and parents. "How are we going to package this…in a way that helps students understand the benefit?"Key QuotesDevan Walton: "We’re shifting to agent-based tools…thoughtfulness about delegated tasks is crucial."Peter Shea: "Wealthier schools are already investing heavily in AI, creating an equity gap."Anne Converse Willkomm: "We need to help students understand AI’s benefits."Ruth Slotnick: "This is a once-in-a-generation technology…bigger than the Internet."Call to ActionEngage with AI: Assessment professionals should develop a deep understanding of AI’s capabilities and limitations.Create Ethical Frameworks: Institutions must establish guidelines for responsible AI use in education.Foster Collaboration: Open dialogue between educators, students, and technology experts is essential to ensure AI serves all stakeholders effectively.AI offers transformative potential for higher education assessment, but ethical, equitable, and strategic adoption is critical to harness its benefits fully.
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Peter Shae - Trends in AI and Instructional Design
Jan 3, 202500:12:11Tap to summarizeAI and Instructional Design in Higher Education1. A New Pedagogical Model: AI offers an opportunity to transition from traditional teaching methods to "generativism," a novel approach combining evidence-based learning principles with AI technology. This shift is essential for maximizing AI's potential. "We are largely trying to use AI to drag along an older pedagogical model... rather than build an entirely new model using the unique affordances of AI."2. Institutional AI Adoption: Colleges and universities vary in their approach to AI adoption, characterized as:Ostriches: Ignoring AI.Crows: Slowly exploring policies.Falcons: Actively experimenting with AI in teaching and learning. "Falcons tend to be those schools... exploring AI for tutoring chatbots, experiential learning, and simulations."3. Transformative Instructional Design: AI revolutionizes instructional design by enhancing productivity, creating interactive learning tools, and enabling performance-based assessment. "The ability to create learning tools that observe students while they perform tasks is one of the most exciting possibilities."4. Equity and Accessibility: AI bridges equity gaps by providing consistent, high-quality assessment and feedback. It also supports continuous learning through accessible ecosystems beyond the classroom. "A well-designed AI, guided by a rubric, can generate high-quality feedback quickly. For me as a writing instructor, it's revolutionized student support."Most Important IdeasGenerativism: A pedagogical approach leveraging AI's unique capabilities to reimagine teaching and learning.Instructional Design Productivity: AI streamlines material creation, like simulations, freeing instructional designers for strategic roles.Performance-Based Assessment: AI enables real-time tracking and assessment of student performance, improving personalization and outcomes.AI-Powered Ecosystems: AI fosters engaging, continuous learning environments beyond the classroom, enhancing knowledge retention.Key TakeawaysInstitutions must embrace new models like generativism to harness AI's transformative potential.AI enhances instructional design efficiency, personalizes learning, and bridges equity gaps in feedback and assessment.Developing AI-powered ecosystems is vital for lifelong learning and extending support beyond traditional classrooms.RecommendationsAdopt Generativism: Incorporate generativism principles into instructional design.Invest in AI Tools: Focus on tools that create interactive and engaging materials.Implement Performance-Based Assessment: Integrate real-time AI-driven feedback into learning experiences.Collaborate: Build partnerships among instructional designers, faculty, and technology experts for effective AI solutions.Professional Development: Stay informed about evolving AI trends in education.AI offers transformative potential for higher education, requiring institutions to rethink pedagogy, embrace innovation, and prioritize accessibility and equity.
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Queen Mary University: Driving change through leadership development and co-creation
Nov 18, 202400:10:49Tap to summarizeDriving Change and Co-Creation in Higher EducationFriday SLO Talk: Janet De Wilde, Emily Salines, and Stephanie Fuller of Queen Mary University of London. The presentation explores the challenges and opportunities of driving change in large, legacy institutions, particularly in the context of evolving student needs, economic pressures, and technological advancements.Co-creation as a Mechanism for Change: The speakers advocate for co-creation as a collaborative approach to implementing change, involving students, staff, and various stakeholders in the process.Leadership, Scholarship, and Recognition: The presentation highlights the importance of effective leadership, scholarship, and recognition systems to support change initiatives and empower individuals within the institution.Driving Forces for Change:New Regulations and Socioeconomic Pressures: Universities face increasingly specific and challenging regulations in the UK, coupled with socioeconomic pressures impacting the sector, institutions, and students alike.Diverse Student Needs and Employability: The need to address the diverse requirements of growing student cohorts and the emphasis on employability drive efforts to meet skills gaps and prepare students for the workforce.Challenges to Change:Legacy Systems and Resistance: "People like and feel reassured and comfortable. And and that's our challenge... we need a shared understanding of the need for change."Inconsistent Understanding and Practice: "We had inconsistency of practice, and we had inconsistency of educational change. So that was our challenge is, you know, it's very spread out. And it's very different understandings."Strategies for Implementing Change:Alignment and Career Pathways: Establishing alignment between the strategy, institutional frameworks, and career pathways was crucial for effective implementation.Role-Based Leadership Programs: Specific educational leadership programs focused on role-based leadership, such as empowering module organizers to lead effectively.Focus on Scholarship and Evidence-Informed Practice: Significant investment in leadership and training helped staff develop evidence-based approaches to evaluating and implementing changes in their practices.Utilizing Co-Creation: Co-creation was embraced as a key mechanism to drive change and ensure widespread engagement and collaboration.Co-Creation in Practice:Shared Understanding and Distributed Leadership: The 2030 strategy faced challenges because many assumed it was solely the university's responsibility. To succeed, individuals needed to understand their accountability and feel empowered to act with agency.Importance of Trust and Recognition: Trust develops through effective frameworks, rewards, and recognition, which foster a sense of reliability and collaboration.Student Involvement and Recognition: Students played a key role in co-creating the University's graduate attributes, leading to the creation of the Seed Award to honor student-enhanced engagement.Key Quotes:"Strategy can drive change. But the whole thing needs scaffolding so that Staff can engage. We can't just have a strategy.""Co-creation at Queen Mary is central to our strategy. We will deliver outstanding inclusive world class education co-created with our diverse student body."
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Queen Mary University: Exploring Assessment Choice to Enhance Practice and Inclusivity in Higher Education
Nov 18, 202400:14:56Tap to summarizeExploring Assessment Choice to Enhance Practice and Inclusivity in Higher EducationFriday SLO Talks: Stephanie Marshall, Janet De Wilde, Emily Salines, and Stephanie Fuller of Queen Mary University of London's Queen Mary Academy.Main Themes:Inclusive Assessment: Queen Mary University prioritizes inclusive assessment practices, recognizing that assessment drives learning and significantly impacts student outcomes and well-being. The presentation explores how offering assessment choices can enhance inclusivity and support students from diverse backgrounds.Assessment Choice as a Driver for Change: The presentation highlights the benefits of assessment choice, such as promoting self-regulation, self-efficacy, engagement, and performance, aligning with principles of Universal Design for Learning. It showcases a small-scale research project exploring the impact of offering choice in a postgraduate academic practice program.Addressing Barriers to Change: The presentation acknowledges challenges in implementing assessment changes within a large institution, including potential resistance to moving away from traditional approaches, concerns about workload, and navigating regulatory frameworks.The Role of Educational Development: The presentation emphasizes the role of educational development units like the Queen Mary Academy in driving assessment change. It positions educational development programs as catalysts for fostering a community of innovative educators and facilitating a shift toward more inclusive practices.Burkana Institute's Two-Loop Change Model: The presentation draws inspiration from the Burkana Institute's two-loop change model, highlighting the importance of identifying and supporting pioneers of change, convening networks of innovators, and strategically phasing out outdated practices while respecting their value.Key Ideas and Facts:Queen Mary University prides itself on being an inclusive Russell Group University, committed to transforming lives and opening doors of opportunity for its diverse student body."You can survive bad teaching, but you can't survive bad assessment." This quote highlights the lasting negative impact of poor assessment practices on student learning and outcomes.A national student survey in the UK consistently reveals student dissatisfaction with assessment and feedback, underscoring the need for reform."Rethinking assessment really means rethinking long-held beliefs, and that can be difficult and painful at times." This quote acknowledges the emotional dimension of challenging ingrained assessment practices.A research project on introducing assessment choice in a postgraduate program showed that most participants found the experience positive, inclusive, and less stressful. 90% of respondents believed that offering assessment choice would be beneficial for their own students. 60% were planning to implement it in their practice.The Burkana Institute’s model encourages identifying "pioneers" of change, "convening" them into communities of practice, and utilizing "storytellers" to disseminate innovative approaches.Quotes:"Assessment drives students' learning.""[Assessment is] a key element in supporting social justice in education." Having the choice was surprisingly empowering."
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Teaching Smarter with Research-Based Learning Principles with Marie Norman
Nov 10, 202400:18:21Tap to summarizeLearning Principles and Motivation Source: Excerpts from a Friday SLO Talk webinar featuring Dr. Marie Norman, co-author of How Learning Works: Eight Research-Based Principles for Smart Teaching. Main Themes:Teaching vs. Learning: Content expertise alone doesn’t ensure effective teaching. For instance, Isaac Newton, despite his brilliance, struggled to convey his knowledge through lectures."If you know a lot about something... you are then automatically qualified to teach. But... teaching has its own very specific set of skills and knowledge."Importance of Prior Knowledge: Students bring varied knowledge, beliefs, and misconceptions to the classroom. Effective learning relies on activating, building upon, and addressing existing knowledge gaps and inaccuracies."Prior knowledge... is the single most important component in new learning." Challenges include:Inactive knowledge: Difficulty recognizing or applying prior knowledge.Gaps in knowledge: Missing foundational information.Inappropriate prior knowledge: Misapplying correct knowledge.Inaccurate prior knowledge: Holding misconceptions.Dr. Norman’s card test illustrates this: students struggled with an abstract problem but succeeded when it was framed in a familiar context (drinking age rules).Expert Blind Spot: Experienced instructors may overestimate students' understanding. For example, in a research methods course, a professor assumed students could apply statistical tests, overlooking the actual complexity for novice learners."It simply requires that students take a data set, select and apply... things which are actually quite complex."Motivation as a Key Driver of Learning: Motivation fuels student effort, with two crucial aspects:Value: Students’ perception of relevance.Expectancy: Belief in their ability to succeed and in the fairness of the environment."Students' motivation generates, directs, and sustains what they do to learn." Strategies to foster motivation include connecting content to student interests, promoting competence and autonomy, and providing clear expectations and feedback.Recommended Resources:How Learning Works by Ambrose et al.Make It Stick: The Science of Successful Learning by Brown, Roediger, & McDanielTeach Like a Champion by LemovConclusion: Dr. Norman underscores the value of understanding and applying learning principles. Addressing issues such as prior knowledge and motivation allows instructors to create more engaging and effective learning experiences.
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Designing Assessment to Promote Student Learning with Sam Elkington
Nov 10, 202400:23:24Tap to summarizeThis podcast explores the pressing need for a transformation in higher education assessment practices, particularly given the impact of generative AI. Professor Elkington argues that traditional, high-stakes assessments fail to prepare students adequately for modern careers, advocating instead for a learning-centered approach that values process, feedback, and evaluative skills.Key Themes and Insights:Assessment’s Evolving Role: Current assessments often impose high stakes with limited relevance to future career demands. The narrow range of formats limits student expression. Generative AI challenges traditional assessments, prompting a reassessment of academic integrity and a renewed focus on distinctly human skills.“The high-risk nature of many of our established assessment practices. We’re weighting assessments at 100, so students have a single opportunity to demonstrate their learning. That’s high-risk and high-stress.”Three Purposes of Assessment:Assessment of Learning: Summative, focused on final grades.Assessment for Learning: Formative, guiding through feedback.Assessment as Learning: Engaging students with real-world issues and metacognitive skill-building.“Assessment as learning focuses on authentic problems, issues, challenges, and projects.”Principles for Effective Assessment:Alignment with Learning Outcomes: Ensuring assessments reflect key skills.Engaging Tasks: Encouraging active, relevant learning.Timely Feedback: Providing actionable insights for immediate and future improvement.Building Evaluative Expertise: Guiding students to recognize quality work.“When it comes to assessment, you get what you model for.”Flexible Assessment at Teesside University: Teesside emphasizes inclusivity and transparency in its assessment design, offering students choice and promoting autonomy.“Flexible assessment is inclusive, learning-focused, and transparent.”Broadening the Assessment Lens: Recognizing students’ entire learning journey fosters coherence. Elkington calls for “assessment practice with an S” (processes) alongside “assessment practice with a C” (outcomes) to enable a more holistic and progressive approach.“We need to embed assessment practice with an S [processes] and assessment practice with a C [outcomes].”Assessment in an AI-Driven Era: Embracing flexible, multimodal assessment formats is crucial. Offering diverse submission options and setting negotiated criteria encourages authentic, skill-based learning for graduates in an AI-influenced world.Practical Strategies for Modern Assessment:Employer Engagement: Align assessments with authentic, industry-related tasks.Student Agency: Promote self-regulation and ownership.Collaboration: Prepare students for teamwork with collaborative projects.Adaptability: Shift towards flexible, personalized assessments.Analogies:Swiss Cheese Paradox: Layering multiple assessment types to minimize learning gaps.Mass-Produced vs. Crafted Chairs: Choosing between standardization and personalized, creative skill demonstration.
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From Compliance to Empowerment: Leveraging Transparency in Assessment Practice with Dr. Gianina Baker
Nov 7, 202400:13:14Tap to summarizeIn this episode, Dr. Gianina Baker, Associate Director of the Office of Community College Research and Leadership and Acting Director of the National Institute for Learning Outcomes Assessment (NILOA), explores how assessment practices in higher education can shift from a compliance-driven model to one focused on student empowerment and continuous improvement.Key themes include:Evolving Assessment Practices: Baker outlines how assessment began with an accreditation-driven approach but has increasingly moved towards a model that values student-centered and improvement-focused assessment.Transparency in Communication: The NILOA Transparency Framework is highlighted as a guide for institutions to effectively communicate assessment practices and learning outcomes to both internal and external stakeholders. Transparency goes beyond availability—it requires clarity and context.Using Data for Improvement: Emphasizing action over mere data collection, Baker calls for using assessment evidence to inform decisions, support improvement initiatives, and communicate the value of student learning.Equity in Assessment: Baker stresses the importance of analyzing data by student demographics to address disparities and support all learners effectively.Notable points include:The NILOA Transparency Framework: Comprised of six components, this framework supports institutions in making learning evidence clear, accessible, and actionable.Student-Centered Assessment: Moving beyond accreditation, the presentation emphasizes putting students at the heart of assessment through agency, feedback loops, and a holistic view of learning experiences.Quotes and Insights: Quotes from thought leaders like George Kuh reinforce the importance of patience and practice in assessment, with Baker noting that institutions must actively use assessment data to earn distinctions like the “Excellence in Assessment” designation.Takeaways:Apply the NILOA Transparency Framework to your institution’s assessment practices.Enhance communication around assessment data, ensuring it’s accessible to diverse audiences.Prioritize using assessment data to drive improvement and demonstrate educational value.Involve students as active participants, emphasizing their feedback and impact on assessment outcomes.This presentation provides a powerful call for institutions to rethink assessment as a tool for empowerment, transparency, and true educational impact.
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Using Artificial Intelligence to Enhance Human Intelligence, Khan Academy
Nov 7, 202400:15:11Tap to summarizeIn this episode, Kristen DiCerbo, Chief Learning Officer at Khan Academy, provides a deep dive into Khan Academy’s research-backed approach to improving student learning outcomes. From understanding the importance of usage in K-12 learning to unveiling the potential of AI-powered tools, DiCerbo shares insights on the methodologies driving Khan Academy’s commitment to educational efficacy and equity.Key themes include:Efficacy in Action: DiCerbo details how Khan Academy measures impact, emphasizing that even 30 minutes of weekly engagement can lead to significant learning gains. She explains that these benefits span across demographics, including gender, ethnicity, and socioeconomic status, though there are opportunities to enhance support for English language learners.Mastery Learning: Khan Academy champions deep learning over surface-level coverage, using the “Skills to Proficient” metric to track skill mastery, which closely correlates with external assessments. DiCerbo argues for focusing on proficiency in fewer skills rather than broad, superficial coverage to reinforce long-term retention.AI-Powered Learning with Conmigo: Khan Academy’s AI tutor, Conmigo, helps students in math, science, and writing by guiding them through problem-solving steps without giving direct answers, fostering active learning and “productive struggle.” Available in multiple languages, Conmigo also supports English language learners and includes transparency features for teachers to track student-AI interactions.Supporting Student Agency and Ethics in AI: DiCerbo discusses how AI tools can empower students to become active learners. She also emphasizes the ethical considerations of AI in education and advocates for community-driven conversations around AI literacy to responsibly integrate these technologies in learning environments.Looking ahead, Khan Academy is refining Conmigo’s design to better balance productive struggle with student frustration, ensuring learning remains both challenging and supportive. This episode highlights Khan Academy’s forward-thinking use of AI and its dedication to creating data-informed, ethical solutions for students and teachers. Join us to explore how technology is reshaping education and the future of learning.
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The Changing Landscape of Writing in the Age of AI with Christina Supe
Nov 7, 202400:16:28Tap to summarizeIn this episode, Christina Supe examines how AI is reshaping writing, literacy, and authorship. She opens by highlighting literacy’s longstanding link to power and social mobility, emphasizing that AI tools might disrupt this by enabling “cognitive outsourcing.” This trend could risk intellectual stagnation and perpetuate existing power imbalances by reducing opportunities for critical thinking.The discussion challenges traditional definitions of a "writer," exploring AI as an agent that creates text and forces us to rethink what qualifies as writing and authorship. Supe raises ethical concerns, particularly about when AI assistance is appropriate. She emphasizes the need for clear distinctions between tasks requiring authentic human input and those that may reasonably involve AI. Copyright laws are evolving to address AI’s role in content creation, with recent changes from the US Copyright Office now allowing copyright for works with minimal AI input, signaling the need for defined policies.Key quotes from Supe underline literacy as a means to access power, warning against the dangers of “outsourcing” cognitive skills to machines. She discusses the value of "reasonable reluctance" toward AI, as voiced by educators, who fear AI could undermine critical thinking and erode essential skills in close reading and analysis. AI, she argues, poses risks as a "shortcut" that may diminish learning and creativity if used inappropriately.For educational institutions, the discussion underscores the need to:Establish Clear AI Policies: Clearly outline when and how AI can be ethically used in student work to guard against plagiarism and intellectual shortcuts.Foster Critical Thinking: Encourage original thought and close engagement with materials to help students retain control over their intellectual growth.Educate on AI’s Role: Help students understand AI’s limitations and ethical considerations in writing.Reevaluate Assessments: Develop assessments that prioritize originality and deeper engagement, ensuring AI use doesn’t overshadow learning objectives.Through Supe’s insights, this episode encourages proactive strategies to balance AI’s potential with a commitment to authentic learning and intellectual development.
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