SIDLIT 2026

Instructional designers constantly face challenges at their job. Given the interdisciplinary nature of the field and the considerable variances from position to position, it is vital to understand the instructional design (ID) professionals’ own experiences. This paper reports voices from novice ID professionals on the essential requirements of their ID work, and essential ID professional characteristics. From analyzing interviews with seven ID professionals from a variety of work contexts, the study reveals that the variety of key responsibilities fall onto four dimensions on contradictory ends, indicating four sets of characteristics that ID professionals need to learn to balance well. The findings present the four sets of characteristics in a spider web form with an instructional design at the center, promoting a shift to taking a holistic approach when developing competencies. This paper bears practical implications for aspiring and novice instructional designers, faculty who provide education for ID students, and employers who aim to look for the best fits for the positions, making contributions to the education of instructional designers, hiring and further professional development of ID professionals.

As generative AI becomes increasingly embedded in online and blended education, instructors face a difficult question: how can learning be supported and assessed when students can quickly generate polished answers, explanations, lesson materials, and multimedia products? Much of the current conversation focuses on academic integrity, prompt writing, tool adoption, or AI-use policies. While these issues are important, they do not fully address a deeper instructional question: what does meaningful learning look like when AI-generated output becomes part of the learning process? This work-in-progress session begins with a dialectical autoethnographic inquiry into a 24-turn interaction between the presenter and a generative AI system. Although the interaction began with a personally meaningful problem related to IRA planning, the focus of the analysis is not financial decision-making. Rather, the episode is used as a situated case for examining how learning unfolds within a human–AI–artifact system. Preliminary analysis suggests that AI-generated outputs should not be treated as final answers, neutral tools, or authoritative explanations. Instead, they function as epistemically unstable learning materials that require human verification, revision, justification, and synthesis. Building from this analysis, the session translates the emerging theoretical insight into practical strategies for online and blended teaching. The presenter will introduce assignment and assessment structures that foreground process evidence rather than only final products, including prompt archives, revision logs, delta reports, AI feedback loops, AI defense activities, peer process audits, and reflective synthesis prompts. These strategies are designed to help instructors evaluate how students define problems, examine AI-generated output, verify information, revise their thinking, justify decisions, and produce a defensible final synthesis. Participants will leave with a conceptual vocabulary for understanding generative AI-mediated learning and a set of adaptable strategies for designing assignments that make student judgment visible. The session is intended for educators, instructional technologists, online program leaders, and educational technology researchers interested in moving beyond AI-use compliance toward more rigorous, reflective, and assessable forms of AI-supported learning.

This session explores how NotebookLM can transform both studying and content delivery in higher education. Participants will see a demonstration of how NotebookLM can be used to create and manage Open Educational Resources (OER). The session will also highlight its value as a student learning tool, including features such as interactive chat, AI-generated podcasts, quizzes, slides, flashcards, infographics, study guides, and mind maps. Because NotebookLM is grounded in user-provided materials, it offers a reliable and focused AI experience for both instructors and students.

Current work in the Scholarship of Teaching and Learning (SoTL) emphasizes partnership with students as a high impact practice that can reshape curriculum design and review, especially in online and hybrid environments. Instead of treating students primarily as sources of survey data, partnership models invite them to co-formulate questions about learning, interpret evidence, and redesign assignments, policies, and syllabus language. This session introduces SoTL as systematic, context sensitive inquiry into student learning that is informed by prior scholarship and made public, then focuses on what changes when students and colleagues are invited into that inquiry as partners rather than recipients in distance learning contexts.
 
To make this concrete, the session highlights two simple online activities that instructors can adapt in their own courses. A feedback partnership map helps faculty move beyond sole reliance on end of course surveys by identifying alternative, dialogic ways to invite students into ongoing conversations about assignments, criteria, and learning experiences in virtual spaces. A mini-partnership studio shows how students can act as co-designers of an assignment or rubric in a shared digital space, suggesting revisions, surfacing bottlenecks, and helping articulate SoTL questions about the impact of the redesign on learning at a distance. Generative tools may appear as optional aids for organizing feedback or exploring alternative wording, but they are not the center of the work. The emphasis is on collaborative SoTL practices that deepen learning, enhance belonging, and build sustainable cultures of shared inquiry about teaching online.

An OER faculty stipend grant program was created in 2024 at a community college. This presentation provides an overview of the stipend program, how librarians marketed, engaged with stakeholders, and shared efforts implemented across campus to introduce faculty to the benefits of using OERs within the classroom. The current status of accepted faculty OER projects, challenges experienced in the creation of this campus initiative, and planned future improvements will be addressed.

SIGs are a networking opportunity to allow professionals to collaborate on relevant topics. These are held over the lunch hour. Hosts prepare questions and facilitate a discussion on the topic of their choice.

SIGs are a networking opportunity to allow professionals to collaborate on relevant topics. These are held over the lunch hour. Hosts prepare questions and facilitate a discussion on the topic of their choice.

During our inaugural year in partnership with the Center on Rural Innovation’s Artificial Intelligence Consortium (CORI-AI Consortium), Emporia State University (ESU) engaged in a collaborative, community-centered initiative to advance AI literacy and institutional capacity within a rural context. As part of the “Higher Ed AI Consortiums in Rural America” project, supported by Microsoft and LinkedIn, ESU partnered with Emporia Main Street and the Emporia Public Library to design and implement a scalable and sustainable framework for AI education delivery. What transpired from this partnership was the development of a flexible “template app” that supports the delivery of repeatable workshops across diverse audiences. Grounded in a train-the-trainer framework and a growing community of practice, the model enables facilitators to maintain consistency while adapting content to local needs. The resulting model offers implications for broader adoption, contributing to workforce readiness and regional economic development in increasingly AI-integrated landscapes. This presentation shares both the process and the outcomes of this first year, highlighting lessons learned at the intersection of community engagement and the push for equitable AI understanding, usage, and exploration.